What is a function?

A function is a piece of code that takes one or more pieces of input and returns something as output or does something behind the scenes. For example:

question: |
  The word ${ color } becomes
  ${ capitalize(color) } when
  passed through the
  `capitalize()` function.
mandatory: True

Functions allow you to do a lot of different things in docassemble. This section explains the standard docassemble functions. If you know how to write Python code, you can write your own functions and include them in your interview using a modules block.

These functions are available automatically in docassemble interviews (unless you set suppress loading util). To use them in a Python module, put a line like this at the top of your .py file to indicate which functions you want to import:

from docassemble.base.util import send_email, quote_paragraphs

All of the functions described in this section are available from the docassemble.base.util module.

Functions for working with variable values

defined()

As explained in how docassemble runs your code, if your code or templates refer to a variable that is not yet defined, docassemble will stop what it is doing to ask a question or run code in an attempt to obtain a definition for that variable.

If you need to check to see if a variable has been defined yet without triggering the process of defining it, you can use defined().

The defined() function takes as its argument the name of a variable.

question: Summary
subquestion: |
  Your favorite fruit is
  ${ favorite_fruit }.

  % if defined('favorite_vegetable'):
  Your favorite vegetable
  is ${ favorite_vegetable }.
  % else:
  I do not know your favorite
  vegetable.
  % endif
mandatory: True

It is essential that you use quotation marks around the name of the variable. If you don’t, it is as if you are referring to the variable.

You should only use defined() in situations where it is absolutely necessary. Your interview logic should be based on the values of real variables, not the defined-ness of a variable. For example, suppose you have an interview like this:

question: Are you married?
yesno: married
---
question: |
  Key dates
fields:
  - "Birth date": date_of_birth
  - "Marriage date": date_of_marriage
    datatype: date
    show if:
      code: married

You might be tempted to write something like this in a DOCX template:

{% if defined(‘date_of_marriage’) %}Plaintiff is married and was married on {{ date_of_marriage }}.{% endif %}

This will work if your interview does not allow the user to go back and edit answers. But if you allow the user to edit answers, what if the user initially answered “Yes” to “Are you married?” and filled out “Marriage date,” but then went back and changed the answer to the “Are you married?” question to “No”? Now the value of date_of_marriage is obsolete, but it is still exists. Because the logic of your document is based on the defined-ness of a variable, rather than the true fact of whether the user is married, it contains an error.

The solution is to always base your logic off of actual facts:

{% if married %}Plaintiff is married and was married on {{ date_of_marriage }}.{% endif %}

By analogy, suppose that a lawyer worked on a case and wrote on a notepad: “we are still within the statute of limitations period; ok to bring tort claim.” Then, some time later, the lawyer is drafting a complaint, and wonders if he can raise a tort claim. Would he look at his notepad and see the words “ok to bring tort claim” and then conclude that he can bring a tort claim? No, he would analyze the facts as they currently stand and evaluate whether it was ok to bring a tort claim. The fact that something was once written on a notepad is not legally significant. What is legally significant is reality.

So, the defined() function is available, but using it is not advisable unless it is impossible to substitute real facts for your conditional statement.

The defined() function accepts an optional keyword argument prior. If you set prior=True, then on screens that loaded because the user pressed the Back button, defined() will look in the previous set of interview answers (the set that was deleted by pressing the Back button) to see if the variable was defined.

value()

The value() function returns the value of a variable, where the name of the variable is given as a string.

question: Summary
subquestion: |
  Your favorite fruit is
  ${ value('favorite_fruit') }.
mandatory: True

These two code blocks effectively do the exact same thing:

code: |
  answer = value('meaning_of_life')
---

---
code: |
  answer = meaning_of_life

Note that value(meaning_of_life) and value("meaning_of_life") are entirely different. The first will treat the value of the meaning_of_life variable as a variable name. So if you set meaning_of_life = 'chocolate', then value(meaning_of_life) will attempt to find the value of the variable chocolate.

The value() function accepts an optional keyword argument prior. If you set prior=True, then on screens that loaded because the user pressed the Back button, value() will look in the previous set of interview answers (the set that was deleted by pressing the Back button) for the value of the variable.

The value() function is relatively inefficient. If you can use regular Python expressions instead of value(), you should do so. value() can be particularly helpful when called from a function within a module. However, if you can rewrite your code so that the variable’s value is passed to the function, or is available as an object attribute, you should do so.

define()

The define() function defines a variable. The first argument is the name of the variable (as a string) and the second argument is the value you want the variable to have. Running define('meaning_of_life', 42) has the same effect as running meaning_of_life = 42.

code: |
  define('favorite_fruit', 'apple')
---
question: Summary
subquestion: |
  Your favorite fruit is
  ${ favorite_fruit }.
mandatory: True

Note that the second argument is the value itself. If you wanted to do the equivalent of my_favorite_fruit = your_favorite_fruit, it would be incorrect to do define('my_favorite_fruit', 'your_favorite_fruit'); you should instead do define('my_favorite_fruit', your_favorite_fruit) or define('my_favorite_fruit', value('your_favorite_fruit')).

undefine()

The undefine() function makes a variable undefined. The name of the variable must be provided as a string. If the variable is not defined to begin with, the function does not do anything.

undefine('favorite_fruit')

This effectively does the same thing as the del statement in Python.

del favorite_fruit

The difference is that when using del, the variable must first exist.

The undefine() function can be called with multiple variable names.

undefine('favorite_fruit', 'favorite_vegetable')

Calling undefine in this way is faster than calling undefine() multiple times.

invalidate()

The invalidate() function does what undefine() does, but it also remembers the previous value and offers it as a default when a question is asked again.

forget_result_of()

If you want a question with embedded blocks to be asked again, or you want a mandatory block to run again, you need to run forget_result_of() on the id of the block.

The forget_result_of() function takes one or more ids of blocks as input and causes the results of those blocks to be forgotten. If the id does not exist, or if the block has not yet been processed, no error will be raised.

This example illustrates using forget_result_of() in conjunction with del to ask a series of questions again, where some of the questions contained embedded blocks.

id: favorite_food stage 2
question: |
  Ok, are any of these your favorite food?
choices:
  - Strawberries:
      code: |
        favorite_food = 'strawberries'
  - Grapes:
      code: |
        favorite_food = 'grapes'
  - Kiwi:
      code: |
        favorite_food = 'kiwi'
  - Something else: continue
---
id: favorite_food stage 1
question: |
  What is your favorite food?
choices:
  - Apples:
      code: |
        favorite_food = 'apples'
  - Oranges:
      code: |
        favorite_food = 'oranges'
  - Something else: continue
---
event: reset_favorite_food
code: |
  del favorite_food
  forget_result_of("favorite_food stage 1", "favorite_food stage 2")

The forget_result_of() function can also be used to reset a mandatory block so that it will be run again.

mandatory: True
code: |
  favorite_fruit = "apple"
  favorite_vegetable = "turnip"
id: initialize
---
mandatory: True
code: |
  while not results_correct:
    favorites_asked
    favorites_reported
    del results_correct
    del favorites_asked
    del favorites_reported
    forget_result_of('initialize')
    re_run_logic()
  final_screen
---
question: |
  Results
subquestion: |
  You said your favorite fruit is
  ${ favorite_fruit } and
  your favorite vegetable is
  ${ favorite_vegetable }.

  Is this correct?
yesno: results_correct
---
question: |
  What are your favorites?
fields:
  - Favorite fruit: favorite_fruit
  - Favorite vegetable: favorite_vegetable
continue button field: favorites_asked
---
question: |
  Your favorites
subquestion: |
  You said your favorite fruit is
  ${ favorite_fruit } and
  your favorite vegetable is
  ${ favorite_vegetable }.

  Press Continue to reset.
field: favorites_reported
---
event: final_screen
question: |
  We are done.

Screenshot of forget-result-of-mandatory example

After resetting a mandatory block, you may want to call re_run_logic(). Otherwise, the mandatory block will not have a chance to run again until the next time the screen loads.

set_variables()

The set_variables() function is somewhat similar to define(), except that instead of setting a particular variable name, it simply updates the interview answers using a dictionary that you provide as input, where the dictionary keys represent variable names and the dictionary values represent values of those variables. For example, if trustee is an Individual, and you do:

set_variables({'plaintiff': trustee, 'favorite_fruit': 'apple'})

then this will have the same effect as doing:

plaintiff = trustee
favorite_fruit = 'apple'

set_variables() accepts an optional keyword parameter process_objects, which can be set to True or False. The default is False. If process_objects is True, then the dictionary will be transformed from docassemble’s “serializable” representation of objects (see the .as_serializable() method) into actual Python objects. For example, suppose you run the following code:

my_json = """\
{
  "user": {
    "_class": "docassemble.base.util.Individual",
    "birthdate": "2000-04-01T00:00:00-05:00",
    "favorite_fruit": "apple",
    "instanceName": "user",
    "name": {
      "_class": "docassemble.base.util.IndividualName",
      "instanceName": "user.name",
      "uses_parts": true
    }
  }
}
"""
set_variables(json.loads(my_json), process_objects=True)

This will have the effect of defining user as an Individual object, where user.name is an IndividualName object and user.birthdate is a DADateTime object.

When process_objects is True, any dictionary with a _class item is converted into a Python object of the class represented by _class, and the other items of the dictionary are converted into attributes of that object. In addition, if any string looks like a date or time (e.g. 2022-01-01, 23:15:00), an attempt will be made to convert it into a DADateTime or datetime.time object.

Note that docassemble’s “JSON representation” of objects is not a full-featured object serialization method. It cannot do everything that Python’s pickle can do. At most, process_objects=True can be used to import basic docassemble data structures.

re_run_logic()

The re_run_logic() function causes code to stop executing and causes the interview logic to be evaluated from the beginning. You might want to use this in cases when, after you make changes to variables, you want the initial and not-yet-completed mandatory blocks to be re-run in light of the changes you made.

If you use this, be careful that you do not create an infinite loop. When the blocks are re-run, the result should not be encountering the re_run_logic() function again, but should be something else, like asking the user a question.

For an example of this in action, see the code example in the forget_result_of() subsection.

reconsider()

The reconsider() function is similar to the reconsider modifier on a code block. Each argument to reconsider() needs to be a variable name, as text. E.g., reconsider('number_of_fruit', 'number_of_vegetables').

When reconsider() is run, it will undefine the given variables and then seek their definitions. However, it will only do this once in a given assembly process (i.e., once each time a screen loads). Thus, even if your code block executes multiple times in a given assembly process, each variable will only be recomputed one time.

code: |
  number_of_pets = number_of_cats + number_of_dogs
---
question: |
  You have
  ${ nice_number(number_of_pets) }
  pets.
subquestion: |
  However, I do not think
  you have been totally honest.
field: interim_report
---
question: |
  Do you want a goldfish?
yesno: wants_goldfish
---
event: final_report
question: |
  You really have
  ${ nice_number(number_of_pets) }
  pets.
subquestion: |
  % if wants_goldfish:
  You would rather have a goldfish.
  % endif
---
mandatory: True
code: |
  interim_report
  ask_dogs_again
  reconsider('number_of_pets')
  final_report

Screenshot of reconsider-function example

need()

The need() function takes one or more variables as arguments and causes docassemble to ask questions to define each of the variables if the variables are not already defined. Note that with need(), you do not put quotation marks around the variable name.

For example, this mandatory code block expresses interview logic requiring that the user first be shown a splash screen and then be asked questions necessary to get to the end of the interview.

mandatory: True
code: |
  need(user_shown_splash_screen, user_shown_final_screen)

This happens to be 100% equivalent to writing:

mandatory: True
code: |
  user_shown_splash_screen
  user_shown_final_screen

So the need() function does not “do” anything. However, writing need() functions in your code probably makes your code more readable because it helps you convey in “natural language” that your interview “needs” these variables to be defined.

force_ask()

Usually, docassemble only asks a question when it encounters a variable that is not defined. However, with the force_ask function, you can cause such a condition to happen manually, even when a variable is already defined.

In this example, we use force_ask to cause docassemble to ask a question that has already been asked.

question: |
  Are you a communist?
yesno: user_is_communist
---
mandatory: True
code: |
  if user_is_communist and user_reconsidering_communism:
    user_reconsidering_communism = False
    force_ask('user_is_communist')
---
question: |
  I suggest you reconsider your
  answer.
field: user_reconsidering_communism
---
question: |
  % if user_is_communist:
  I am referring your case to
  Mr. McCarthy.
  % else:
  I am glad you are a true
  American.
  % endif
mandatory: True

This may be useful in particular circumstances. However, force_ask() cannot be used with all types of questions. For example, it cannot be relied upon to re-ask questions that:

Use the generic object modifier (and the special variable x) or iterators (i, j, etc.);
Contain embedded blocks.

The use of force_ask() is discouraged, unless you are an expert and you know what you are doing. Usually, there is a more elegant way to craft your interview logic than by using force_ask(). If the question you want to ask is a single-variable question (field with choices, field with buttons, yesno, noyes), you can use reconsider(). If the question has fields, you can set a continue button field. You might also find it useful to use the undefine() and re_run_logic() functions.

Note that variable names given to force_ask must be in quotes. If your variable is favorite_fruit, you need to write force_ask('favorite_fruit'). If you write force_ask(favorite_fruit), docassemble will assume that, for example, apples is a variable in your interview.

force_ask() works by triggering the actions mechanism. This means that in a multi-user interview, force_ask() only changes the current question for the current user; each user has their own active action, or list of active actions.

Note also that no code that comes after force_ask() will ever be executed. Once the force_ask() function is called, the code stops running, and the question indicated by the variable name will be shown. That is why, in the example above, we set user_reconsidering_communism to False before calling force_ask(). The variable user_reconsidering_communism, which had been set to True by the “I suggest you reconsider your answer” question, is set to False before the call to force_ask so that the mandatory code block does not get stuck in an infinite loop.

A different way to reask a question is to use the built-in Python operator del. This makes the variable undefined. Instead of writing:

mandatory: True
code: |
  if user_is_communist and user_reconsidering_communism:
    user_reconsidering_communism = False
    force_ask('user_is_communist')

we could have written:

mandatory: True
code: |
  if user_is_communist and user_reconsidering_communism:
    user_reconsidering_communism = False
    del user_is_communist

This will also cause the user_is_communist question to be asked again. This is more robust than using force_ask because the user cannot get past the question simply by refeshing the screen.

The force_ask() function can also be given the names of variables that refer to event blocks. The screen will be shown, but no variable will be defined.

You can use force_ask() to ask a series of questions. Just list each variable one after another.

mandatory: True
code: |
  favorite_fruit
  favorite_vegetable
  favorite_fungus
  told_to_review
  if not all_reviewed:
    all_reviewed = True
    force_ask('favorite_fruit', 'favorite_vegetable', 'favorite_fungus')
  final_screen
---
question: |
  What is your favorite fruit?
fields:
  - Favorite fruit: favorite_fruit
---
question: |
  What is your favorite vegetable?
fields:
  - Favorite vegetable: favorite_vegetable
---
question: |
  What is your favorite fungus?
fields:
  - Favorite: favorite_fungus
---
question: |
  Please verify your answers.
subquestion: |
  I will ask each question again.
  Make any changes that you think
  are necessary.
field: told_to_review
---
event: final_screen
question: |
  Thank you.
subquestion: |
  You like
  ${ favorite_fruit },
  ${ favorite_vegetable },
  and
  ${ favorite_fungus }.
---
code: |
  all_reviewed = False

Screenshot of force-ask-multiple example

The second and subsequent arguments to force_ask() can specify actions with arguments. If an argument to force_ask() is a Python dictionary with keys action and arguments, the specified action will be run. (Internally, docassemble uses the actions mechanism to force the interview to ask these questions.)

If you give force_ask() the name of a variable that no question can define, then force_ask() will quietly ignore it. Thus you can use conditional logic within a force_ask() sequence by adding if modifiers to each question that specify under what conditions the question should be asked.

In addition to giving force_ask() variables and actions, you can give it a dictionary containing a special command.

force_ask('favorite_fruit', {'recompute': 'dessert_cost'}, 'favorite_vegetable')
force_ask('favorite_fruit', {'recompute': ['dessert_cost', 'breakfast_cost']}, 'favorite_vegetable')
force_ask('favorite_fruit', {'recompute': ['dessert_cost', 'breakfast_cost']}, 'favorite_vegetable')
force_ask('favorite_fruit', {'set': {'fruit_known': True}}, 'favorite_vegetable')
force_ask('favorite_fruit', 'favorite_vegetable', {'set': [{'fruit_known': True}, {'vegetable_known': True}]})

For more information on how these data structures work, see the subsection on customizing the display of review options.

force_ask() accepts the optional keyword parameter forget_prior. If forget_prior is set to a true value, then any pending actions will be forgotten. If forget_prior is not provided, then force_ask() will simply add one or more actions to the “stack” of pending actions.

Here is an example that demonstrates the effect of forget_prior.

mandatory: True
question: First page
subquestion: |
  [Go to second page](${ url_action('second_page') })
---
question: Second page
subquestion: |
  [Go to third page](${ url_action('third_page') })
continue button field: second_page
---
question: Third page
subquestion: |
  [Ask about food](${ url_action('food_preferences') })

  [Ask about food with forget prior](${ url_action('food_preferences_forget_prior') })
continue button field: third_page
---
#event: food_preferences
code: |
  favorite_fruit
  favorite_vegetable
  food_preferences = True
  #force_ask('favorite_fruit', 'favorite_vegetable')
---
event: food_preferences_forget_prior
code: |
  force_ask('favorite_fruit', 'favorite_vegetable', forget_prior=True)
---
question: |
  What is your favorite fruit?
fields:
  - Favorite fruit: favorite_fruit
---
question: |
  What is your favorite vegetable?
fields:
  - Favorite vegetable: favorite_vegetable

Screenshot of force-ask-forget-prior example

force_ask() accepts the optional keyword parameter evaluate. If evaluate is set to True, then the variable names given to force_ask() will be evaluated to determine their intrinsic names. For example, if you have:

objects:
  - plaintiffs: DAList.using(object_type=Individual)
  - defendants: DAList.using(object_type=Individual)
---
code: |
  if been_sued:
    user = defendants[0]
  else:
    user = plaintiffs[0]
---
mandatory: True
code: |
  user.name.first

Then if you do force_ask('user.name.first'), then docassemble will look for a question that literally defines user.name.first. However, if you actually want docassemble to look for a question that defines plaintiffs[0].name.first or defendants[0].name.first, then you can call force_ask('user.name.first', evaluate=True). Then docassemble will inspect user, then user.name, and it will find that the .instanceName of user.name is, e.g., plaintiffs[0].name, and it will look for a question that defines plaintiffs[0].name.first.

Instead of using evaluate, you could instead write force_ask(user.name.attr_name('first')). This ensures that force_ask() is called on the correct name for the attribute.

A function that is related to force_ask() is force_gather(). force_gather() cannot force the-reasking of a question to define a variable that has already been defined, but it does not have the limitations on question types that force_ask() has.

force_gather()

The force_gather() function is very similar to force_ask(), except it affects the interview logic for all users of the interview, not just the current user.

initial: True
code: |
  process_action()
---
event: gather_it
code: |
  force_gather('favorite_food')

Calling force_gather('favorite_food') means “until favorite_food is defined, keep asking questions that offer to define favorite_food, and satisfy any prerequisites that these questions require.”

Normally, you will not need to use either force_ask() or force_gather(); you can just mention the name of a variable in your questions or code blocks, as part of your interview logic, and docassemble will make sure that the variables get defined. The force_ask() and force_gather() functions are primarily useful when you are using actions to do things that are outside the normal course of the interview logic.

dispatch()

The dispatch() function provides logic so that an interview can present a menu system within a screen. For example:

mandatory: True
code: |
  dispatch('main_menu_selection')
  final_screen
---
question: |
  Main menu
field: main_menu_selection
buttons:
  - Fruit: fruit_menu
  - Vegetables: vegetable_menu
  - Rocks: rocks_page
  - Continue: Null
---
code: |
  fruit_menu = dispatch('fruit_menu_selection')
---
question: |
  Fruit menu
field: fruit_menu_selection
choices:
  - Apple: apple
  - Peach: peach
  - Back: Null
---
code: |
  vegetable_menu = dispatch('vegetable_menu_selection')
---
question: |
  Vegetable menu
field: vegetable_menu_selection
choices:
  - Turnip: turnip
  - Potato: potato
  - Back: Null
---
question: Rocks screen
field: rocks_page
---
question: Apples screen
subquestion: |
  % if likes_apples:
  You like apples.
  % endif
field: apple
---
question: |
  Do you like apples?
yesno: likes_apples
---
question: Peaches screen
subquestion: |
  You selected
  ${ main_menu_selection }
  on the main menu and
  ${ fruit_menu_selection }
  on the fruit menu.
field: peach
---
event: turnip
question: Turnip screen
subquestion: |
  You cannot go forward from
  the turnip screen.
---
question: Potato screen
field: potato
---
event: final_screen
question: |
  Done with the interview.

To make a menu, you need to add a few components to your interview:

Some code that runs dispatch() in order to launch the menu at a particular place in your interview logic.
A screen that shows the menu. This is typically a multiple-choice question in which each choice represents a screen that the user can visit.
Screens corresponding to each choice. These can be standalone screens, or they can be sub-menus.

In the example above, the main menu is a multiple-choice question that sets the variable main_menu_selection.

When the interview logic calls dispatch('main_menu_selection'), it looks for a definition of the variable main_menu_selection. It finds a multiple-choice question that offers to define main_menu_selection. This question will set the variable to one of four values:

fruit_menu
vegetable_menu
rocks_page
Null

The first three values are the names of other variables in the interview. Note that in the interview, fruit_menu and vegetable_menu are variables defined by code blocks, and rocks_page is defined by a question block. If the user selects one of these choices, the interview will look for a definition of the selected variable. This all done by the dispatch() function.

The last value, Null, is special; it ends the menu. (Note that Null or null is a special value in YAML; it becomes None in Python.) When the user selects “Continue,” the dispatch() function will end. In this sample interview, the next step after the menu is to show the final_screen. Thus, when the user selects “Continue,” the user sees the final_screen question. If you want the interview logic to be able to move past the dispatch() function, you must include a Null option.

This sample interview features two sub-menus. You can tell this because the variable fruit_menu is defined with:

fruit_menu = dispatch('fruit_menu_selection')

and the variable vegetable_menu is defined with:

vegetable_menu = dispatch('vegetable_menu_selection')

If the user selects “Fruit” from the main menu, the interview will seek a definition of fruit_menu. This in turn leads to calling the dispatch() function on 'fruit_menu_selection'. This leads to seeking a definition of the variable fruit_menu_selection. If the user selects the Null option on this menu, the user will go back to the main menu.

If the user selects “Rocks” from the main menu, the interview will seek a definition of rocks_page. In this case, the block that offers to define rocks_page is a question with a “Continue” button. When the user presses “Continue” on the “Rocks screen,” the user will return to the menu.

Note that when the interview seeks definitions of variables and displays screens, it will ask questions to satisfy prerequisites. For example, when the user selects “Apple” from the “Fruit menu,” the interview will seek the definition of apple, but in order to pose the question that defines apple, it needs the definition of likes_apples. So it will stop and ask “Do you like apples?” before proceeding to the question that defines apple.

One very important thing to know about the dispatch() function is that the variables it uses to navigate among the screens are temporary. After the call to dispatch('main_menu_selection'), the variables main_menu_selection, fruit_menu, fruit_menu_selection, apple, rocks_page, etc., will all be undefined. However, questions will be able to access these variables from within the dispatch() function. For example, the “Peaches screen” successfully accesses the values of main_menu_selection and fruit_menu_selection.

If you want to gather information about what screens your user visited or did not visit, you can use prerequisites to do so. Here is an example that uses the need specifier to run a code block when a user selects a menu item.

mandatory: True
code: |
  visited_apple = False
  visited_orange = False
---
mandatory: True
code: |
  dispatch('main_menu_selection')
  final_screen
---
question: |
  Main menu
field: main_menu_selection
buttons:
  - Apple: apple
  - Orange: orange
  - Continue: Null
---
question: Apple screen
field: apple
need: apple_tracked
---
code: |
  visited_apple = True
  apple_tracked = True
---
question: Orange screen
field: orange
need: orange_tracked
---
code: |
  visited_orange = True
  orange_tracked = True
---
event: final_screen
question: |
  All done.
subquestion: |
  % if visited_apple:
  You visited the apple menu.
  % endif

  % if visited_orange:
  You visited the orange menu.
  % endif

all_variables()

The all_variables() function returns all of the variables defined in the interview session as a simplified Python dictionary.

mandatory: True
question: |
  Interview dictionary
subquestion: |
  The variables in the dictionary are:
    
  `${ all_variables() }`

The resulting Python dictionary is suitable for conversion to JSON or other formats. Each object is converted to a Python dictionary. Each datetime or DADateTime object is converted to its isoformat(). Other objects are converted to None.

If you want the raw Python dictionary representing the variables defined in the interview session, you can call all_variables(simplify=False). The result is not suitable for conversion to JSON. This raw Python dictionary will be linked to the current interview answers, so that if you use the Python is operator to test for equivalence between objects, you will see that they are equivalent. Therefore, if you try to edit the output of all_variables(simplify=False), you may be affecting the interview variables in unwanted ways. If you want the result of all_variables(simplify=False) to be a distinct copy of the interview answers, call it using all_variables(simplify=False, make_copy=True).

docassemble keeps a dictionary called _internal in the interview variables and uses it for a variety of internal purposes. There is also an object called nav that is used for tracking which sections of an interview the user has visited. By default, _internal and nav are not included in the output of all_variables(). If you want _internal and nav to be included, set the optional keyword parameter include_internal to True.

The all_variables() function also has three special behaviors:

all_variables(special='titles') will return a Python dictionary containing information set by the metadata initial block and the set_parts() function.
all_variables(special='metadata') will return a dictionary representing the “metadata” indicated in the metadata initial blocks of the interview. (If multiple blocks exist, information is “layered” so that keys in later blocks overwrite keys in earlier blocks.) Unlike the 'titles' option, the information returned here is not updated to take into account changes made programmatically by the set_parts() function.
all_variables(special='tags') will return a Python set containing the current set of tags defined for the interview session.

Functions for special responses

message()

code: |
  message("The interview is over.", "Better luck next time!")
mandatory: True

The message() function causes docassemble to stop what it is doing and present a screen to the user that contains a given message.

By default, the user will be offered an “exit” button and a “restart” button, but these choices can be configured.

The first argument is the title of the screen the user will see (the question). The second argument, which is optional, indicates the text that will follow the title (the subquestion).

The message() function also takes keyword arguments. The following do the same thing:

message("This is the big part of the question", "This is the smaller part of the question")
message(question="This is the big part of the question", subquestion="This is the smaller part of the question")

The optional keyword arguments influence the appearance of the screen:

message("Bye!", "See ya later", show_restart=False) will show the Exit button but not the Restart button.
message("Bye!", "See ya later", show_exit=False) will show the Restart button but not the Exit button.
message("Bye!", "See ya later", url="https://www.google.com"): clicking the Exit button will take the user to Google.
message("Bye!", "See ya later", show_leave=True) will show a Leave button instead of the Exit button.
message("Bye!", "See ya later", show_leave=True, show_exit=True, show_restart=False) will show a Leave button and an Exit button.
message("Bye!", "See ya later", buttons=[{"Learn More": "exit", "url": "https://en.wikipedia.org/wiki/Spinning_wheel"}]) will show a “Learn More” button that exits to Wikipedia.

response()

The response() command allows the interview developer to use code to send a special HTTP response. Instead of seeing a new docassemble screen, the user will see raw content as an HTTP response, or be redirected to another web site. As soon as docassemble runs the response() command, it stops what it is doing and returns the response.

There are four different types of responses, which you can invoke by using one of four keyword arguments: response, binaryresponse, file, and url. There is also an optional keyword argument content_type, which determines the setting of the Content-Type header. (This is not used for url responses, though.) The response() function accepts the optional keyword parameter response_code. The default HTTP response code is 200 but you can use response_code to set it to a different value.

The four response types are:

response: This is treated as text and encoded to UTF-8. For example, if you have some data in a dictionary info and you want to return it in JSON format, you could do response(response=json.dumps(info), content_type='application/json'). If the content_type keyword argument is omitted, the Content-Type header defaults to text/plain; charset=utf-8.
binaryresponse: This is like response, except that the data provided as the binaryresponse is treated as binary bytes rather than text, and it is passed directly without any modification. You could use this to transmit images that are created using a software library like the Python Imaging Library. If the content_type keyword argument is omitted, the Content-Type header defaults to text/plain; charset=utf-8.
file: The contents of the specified file will be delivered in response to the HTTP request. You can supply one of two types of file designators: a DAFile object (e.g., an assembled document or an uploaded file), or a reference to a file in a docassemble package (e.g., 'moon_stars.jpg' for a file in the static files folder of the current package, or 'docassemble.demo:data/static/orange_picture.jpg' to refer to a file in another package).
url: If you provide a URL, the web server will redirect the user’s browser to the provided URL.

Here is an example that demonstrates response:

mandatory: True
code: |
  data = {'fruit': 'apple', 'pieces': 2}
  response(json.dumps(data), content_type="application/json")

Here is an example that demonstrates the binaryresponse:

sets: all_done
code: |
  svg_image = """\
  <?xml version="1.0" encoding="UTF-8" standalone="no"?>
  <svg
     xmlns:dc="http://purl.org/dc/elements/1.1/"
     xmlns:cc="http://creativecommons.org/ns#"
     xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
     xmlns:svg="http://www.w3.org/2000/svg"
     xmlns="http://www.w3.org/2000/svg"
     version="1.1"
     id="svg2"
     width="100"
     height="100">
    <circle
       id="circle4"
       fill="red"
       stroke-width="3"
       stroke="black"
       r="40"
       cy="50"
       cx="50" />
  </svg>
  """
  response(binaryresponse=svg_image, content_type="image/svg+xml")

The following example shows how you can make information entered into an interview available to a third-party application through a URL that returns data in JSON format.

objects:
  - user: Individual
---
mandatory: True
code: |
  multi_user = True
---
event: query_fruit
code: |
  data = {'fruit': favorite_fruit, 'pieces': number_of_pieces}
  json_response(data)
---
mandatory: True
question: |
  You currently have
  ${ nice_number(number_of_pieces) }
  ${ noun_plural('piece', number_of_pieces) }
  of
  ${ noun_singular(favorite_fruit) }.
subquestion: |
  Use
  [this link](${ interview_url_action('query_fruit') })
  to query the information from
  another application.

  You can also change the 
  [fruit](${ url_action('favorite_fruit') })
  and the
  [number of pieces](${ url_action('number_of_pieces') }).

Note the following about this interview.

We set multi_user to True in order to disable server-side encrpytion. This allows an external application to access the interview without logging in as the user.
The query_fruit event code will be run as an action when someone accesses the link created by interview_url_action().

The response() command can be used to integrate a docassemble interview with another application. For example, the other application could call docassemble with a URL that includes an interview file name (argument i) along with a number of URL arguments. The interview would process the information passed through the URLs, but would not ask any questions. It would instead return an assembled document using response().

attachment:
  name: A file
  file: test_file
  variable name: the_file
  valid formats:
    - pdf
  content: |
    Hello, ${ url_args.get('name', 'you') }!
---
mandatory: True
code: |
  response(file=the_file.pdf)

Here is a link that runs this interview. Notice how the name “Fred” is embedded in the URL. The result is an immediate PDF document.

https://demo.docassemble.org/interview?i=docassemble.base:data/questions/examples/immediate_file.yml&name=Fred

When you write code that runs in a scheduled task, you can use response() to finish the scheduled task. In this context, you can pass the optional keyword argument sleep with a number of seconds that you want to pause after the task is finished. This can be useful when your scheduled tasks would overwhelm your SQL server if executed one after another without pauses.

json_response()

Calling json_response(data) is (basically) a shorthand for response(binaryresponse=json.dumps(data).encode('utf-8'), content_type="application/json").

It takes a single positional argument and returns it as an HTTP response in JSON format.

Here is an example of how json_response() can be used in combination with the action_call() JavaScript function.

mandatory: True
question: |
  Tell me about your shipment.
fields:
  - Weight (lbs): weight
    datatype: number
  - Size: size
    choices:
      - Small box: 1
      - Medium box: 2
      - Large box: 3
  - html: |
      <button id="calcButton" class="btn btn-info float-end" type="button">Calculate</button>
      <span id="calcResults"></span>
script: |
  <script>
    $("#calcButton").on('click', function(){
      var theWeight = parseFloat(val('weight'))
      var theSize = parseInt(val('size'))
      if (theWeight && theSize){
        action_call('calc', {weight: theWeight, size: theSize}, function(data){
          $("#calcResults").html("That will cost $" + data.cost.toLocaleString('en-US') + ".");
        });
      }
    })
  </script>
---
event: calc
code: |
  json_response({'cost': 4.44 + action_argument('weight') * 5.2 + action_argument('size') * 13.1})

Screenshot of json-response-ajax example

The json_response() function accepts the optional keyword parameter response_code. The default response code is 200 but you can use response_code to set it to a different value.

Another way to get JSON output from docassemble is to use the JSON interface, which provides a JSON representation of a docassemble screen. This can be useful if you are developing your own front end to docassemble.

variables_as_json()

The variables_as_json() function acts like response() in the example above, except that is returns all of the variables in the interview session dictionary in JSON format.

mandatory: True
code: |
  multi_user = True
---
event: query_variables
code: |
  variables_as_json()
---
mandatory: True
question: |
  You currently have
  ${ nice_number(number_of_pieces) }
  ${ noun_plural('piece', number_of_pieces) }
  of
  ${ noun_singular(favorite_fruit) }.
subquestion: |
  Use
  [this link](${ interview_url_action('query_variables') })
  to query the information from
  another application.

  You can also change the 
  [fruit](${ url_action('favorite_fruit') })
  and the
  [number of pieces](${ url_action('number_of_pieces') }).

The variables_as_json() function simplifies the interview variables in the same way that the all_variables() function does. Like all_variables(), it takes an optional keyword argument include_internal, which is False by default, but when True, includes the internal variables _internal and nav in the output.

command()

mandatory: True
code: |
  command('exit', url=target_url)
---
question: |
  Where do you want to go?
field: target_url
buttons:
  - Stanford: "http://stanford.edu/"
  - Harvard: "http://www.harvard.edu/"

The command() function allows the interview developer to trigger an exit from the interview using code, rather than having the user click an exit, restart, leave or signin button.

The first argument to command() is one of the following:

'restart': deletes the user’s answers and puts them back at the start of the interview.
'new_session': starts a new session for the same interview without deleting the user’s answers.
'exit': deletes the user’s answers and redirects them to a web site
'logout': logs the user out and redirects them to a web site.
'exit_logout': deletes the user’s answers, logs the user out (if logged in) and redirects them to a web site.
'leave': redirects the user to a web site without deleting the user’s answers.
'signin': redirects the user to the sign-in screen.

The optional keyword argument url provides a URL to which the user should be redirected. The value of exitpage will be used if no url is provided.

Note that the special buttons perform a similar function to command(). See also the starting an interview from the beginning subsection for URL parameters that reset interview sessions.

One use of command() is to delete interviews after a period of inactivity. See scheduled tasks for more information. In the context of scheduled tasks, you can pass the optional keyword argument sleep with a number of seconds that you want to pause after the session is deleted. This can be useful when your scheduled tasks would overwhelm your SQL server if executed one after another without pauses.

Text transformation functions

from_b64_json()

Takes a string as input, converts the string from base-64, then parses the string as JSON, and returns the object represented by the JSON.

This is an advanced function that is used by software developers to integrate other systems with docassemble.

plain(), bold(), and italic()

The functions plain(), bold(), and italic() are useful when including variables in a template.

For example, if you write:

subquestion: |
  * Your phone number: **${ phone_number }**
  * Your fax number: **${ fax_number }**

Then the values of the two variables will have bold face markup, but if one of them is empty, you will get asterisks instead of what you presumably wanted, which was no text at all.

Your phone number: 202-555-2030

Your fax number: ****

Instead, you can write:

subquestion: |
  * Your phone number: ${ bold(phone_number) }
  * Your fax number: ${ bold(fax_number) }

This leads to:

Your phone number: 202-555-2030

Your fax number:

Alternatively, you can pass an optional keyword argument, default, if it should plug in something different when empty.

subquestion: |
  * Your phone number: ${ bold(phone_number, default='Not available') }
  * Your fax number: ${ bold(fax_number, default='Not available') }

This leads to:

Your phone number: 202-555-2030

Your fax number: Not available

Calling italic('apple') function returns _apple.

The plain() function does not supply any formatting, but it will substitute the default keyword argument.

space_to_underscore()

If user_name is John Wilkes Booth, space_to_underscore(user_name) will return John_Wilkes_Booth. This is useful if you do not want spaces in the filenames of your attachments. This function will also do basic filename sanitization to remove dangerous characters and command injection.

sets: user_done
question: Thanks!
subquestion: Here is your letter.
attachment:
  - name: A letter for ${ user_name }
    filename: Letter_for_${ space_to_underscore(user_name) }
    content file: letter.md

single_to_double_newlines()

Under the rules of Markdown, you need to insert two newlines to break a paragraph. Sometimes you have text where one newline represents a paragraph, but you want the single newlines to count as paragraph breaks. The function single_to_double_newlines() will convert the text for you.

mandatory: True
question: |
  Here is your first book.
attachment:
  name: Story of My Life
  filename: life_story
  content: |
    [BOLDCENTER] My Life Story

    ${ single_to_double_newlines(life_story) }

    [CENTER] The End.

Screenshot of single_to_double_newlines example

single_paragraph()

single_paragraph(user_supplied_text) will replace any linebreaks in user_supplied_text with spaces. This allows you to do things like:

question: Summary of your answers
subquestion: |
  When I asked you the meaning of life, you said:

  > ${ single_paragraph(meaning_of_life) }

field: ok_to_proceed

If you did not remove line breaks from the text, then if the meaning_of_life contained two consecutive line breaks, only the first paragraph of the answer would be indented.

verbatim()

If you are inserting user-supplied input into a document or onto the screen, it is possible that the text may contain characters that will result in undesired formatting changes. For example, the input may contain Markdown codes, HTML codes, or LaTeX codes. To avoid the effects of such characters, wrap the text with the verbatim() function.

question: |
  Provide some text.
subquestion: |
  Try inserting Markdown or HTML characters.
fields:
  no label: user_input
  input type: area
---
mandatory: True
question: |
  This content should be devoid
  of formatting.
subquestion: |
  ${ verbatim(user_input) }
attachment:
  content: |
    ${ verbatim(user_input) }

quote_paragraphs()

The quote_paragraphs() function adds Markdown to text so that it appears as a quotation.

mandatory: True
question: |
  Your allegations
subquestion: |
  You allege that:

  ${ quote_paragraphs(allegations) }

indent()

The indent() function adds four spaces to the beginning of each line of the given Markdown to text. This needs to be used if you are inserting a table or a paragraph of user text into the context of a Markdown bullet-point or itemized list, and you want the text to be part of an item. If you do not indent the text, the text will be treated as a new paragraph that ends the list.

mandatory: True
question: |
  Your allegations
subquestion: |
  You allege that:

  1.  The sky is blue.

  2.  You have a house.

      Your house has a roof.

      Your roof is made up of many
      shingles.

  3.  You have a car.

  ${ indent(car_allegations) }

  4.  You have at least a high
      school education.
---
template: car_allegations
content: |
  Your car is black.

  Your car's gas tank is nearly empty.

  Your car goes from 0 to 60 fast enough
  not to be rear-ended on the highway.

fix_punctuation()

The fix_punctuation() function ensures that the given text ends with a punctuation mark. It will add a . to the end of the text if no punctuation is present at the end. To use a different punctuation mark, set the optional keyword argument mark to the text you want to use.

A call to fix_punctuation(reason) will return:

I have a valid claim. if reason is I have a valid claim
I have a valid claim. if reason is I have a valid claim.
I have a valid claim! if reason is I have a valid claim!
I have a valid claim? if reason is I have a valid claim?

mandatory: true
question: |
  What to do in court.
subquestion: |
  Tell the court,
  "Please grant my petition.
  ${ fix_punctuation(rationale) }"
---
question: |
  Why is the other side wrong?
subquestion: |
  Please be brief.
fields:
  - no label: rationale
    input type: area
    hint: |
      The teapot was not broken
      and it was broken before he
      gave it to me.

redact()

The redact() function is used when preparing redacted and unredacted versions of a document. For example, instead of referring to client.ssn in a document, you can refer to redact(client.ssn). Then, in the final document, a redaction mark will be included instead of the client’s Social Security number. However, if the document is assembled with redact: False, the Social Security number will be included.

Here is an example of redact() being used when generating a PDF and RTF file from Markdown:

template: petition_text
content: |
  Dear Judge,

  My name is ${ user }.
  I have a claim against
  the defendant.  A big one.

  My SSN is ${ redact(user.ssn) }.
  My phone number is
  ${ user.phone_number }.

  My home address is:

  ${ redact(user.address) }

  I demand ${ currency(money_claimed) }.

  Thank you.

  Sincerely,

  ${ user }
---
mandatory: True
question: |
  Here is your document.
subquestion: |
  You need to print both copies
  and file them in court.

  The unredacted version goes
  to the judge, and the redacted
  version will go in the public
  record.
attachments:
  - name: Unredacted petition
    filename: petition_unredacted
    redact: False
    valid formats:
      - pdf
      - rtf
      - docx
    content: |
      ${ petition_text }
  - name: Redacted petition
    filename: petition_redacted
    valid formats:
      - pdf
      - rtf
      - docx
    content: |
      ${ petition_text }

Here is the same example, but with a docx template file named redact_demo.docx:

mandatory: True
question: |
  Here is your document.
subquestion: |
  You need to print both copies
  and file them in court.

  The unredacted version goes
  to the judge, and the redacted
  version will go in the public
  record.
attachments:
  - name: Unredacted petition
    redact: False
    filename: petition_unredacted
    docx template file: redact_demo.docx
  - name: Redacted petition
    filename: petition_redacted
    docx template file: redact_demo.docx

Here is the same example, but with a pdf template file named redact_demo.pdf:

mandatory: True
question: |
  Here is your document.
subquestion: |
  You need to print both copies
  and file them in court.

  The unredacted version goes
  to the judge, and the redacted
  version will go in the public
  record.
attachments:
  - name: Unredacted petition
    redact: False
    filename: petition_unredacted
    pdf template file: redact_demo.pdf
    field code:
      - today_date: today()
      - name: user
      - ssn: redact(user.ssn)
      - phone: user.phone_number
      - address: redact(user.address)
      - money: currency(money_claimed)
  - name: Redacted petition
    filename: petition_redacted
    pdf template file: redact_demo.pdf
    field code:
      - today_date: today()
      - name: user
      - ssn: redact(user.ssn)
      - phone: user.phone_number
      - address: redact(user.address)
      - money: currency(money_claimed)

The redact() function is intended to be called the markup of documents, as demonstrated in the various examples above. It is only in this context that the redact() function knows whether you have set redact: False or not. The redact() function can be from other contexts, but the result may not be what you want; for example, you may see redactions even though you set redact: False. If you define a variable ssn_text = redact(user.ssn), and the ssn_text variable is already defined by the time docassemble gets around to assembling a document with the redact option set to False, then your “unredacted” document will contain a redacted Social Security number.

Normally, when docassemble figures out what question to ask, it simply evaluates the interview logic: it goes through the YAML from top to bottom, and runs anything marked as initial or mandatory (skipping over mandatory blocks that have already been processed), and if it encounters an undefined variable, it seeks a definition of that undefined variable by running blocks that offer definitions of those variables.

Sometimes, however, you may want to direct docassemble to perform a specific task other than evaluating the current state of the interview logic. The mechanism for doing that is called the “actions” mechanism.

An “action” is similar to a function call in computer programming. When you call a function, you might call cancel_application() or submit_application(user, details). Running cancel_application() just runs a function called cancel_application. Running submit_application(user, details) runs a function called submit_application, and passes user and details to the function; these are referred to as the “arguments” of the function.

Here is some made-up code that illustrates how traditional functions work:

def cancel_application():
  central_authority = CentralAuth(hostname='central-authority.example.com')
  payload = {'type': 'cancel'}
  send(payload, central_authority)

def submit_application(user, details):
  central_authority = CentralAuth(hostname='central-authority.example.com')
  payload = {'type': 'submit', 'user': user, 'details': details}
  send(payload, central_authority)

In docassemble, an “action” consists of an action name and an optional dictionary of arguments. When you call the action cancel_application, docassemble will seek out a block in your YAML that offers to define cancel_application, and will run that block. To locate this block, it uses the same process that it uses when it seeks a block that defines an undefined variable.

Here is how you would implement the functions above as “actions” in your interview YAML:

event: cancel_application
code: |
  send({'type': 'cancel'}, CentralAuth(hostname='central-authority.example.com'))
---
event: submit_application
code: |
  send({'type': 'submit', 'user': action_argument('user'), 'details': action_argument('details')}, CentralAuth(hostname='central-authority.example.com'))

Writing event: cancel_application means “this block advertises that it defines cancel_application. You may have seen event used before in a context like this:

mandatory: True
code: |
  intro_screen
  favorite_fruit
  final_screen
---
event: final_screen
question: Thank you for answering my questions today.
subquestion: |
  I like ${ favorite_fruit } as well.

When a variable name is referenced, its definition will be sought if the variable is undefined, but if the variable is defined, it will continue running the Python code. The final_screen question is different, though, because it is a dead end; final_screen is a variable name that will never actually get defined.

Likewise, a code block with event: cancel_application will not actually define the variable cancel_application, but it will be executed if docassemble seeks the variable cancel_application.

“Actions” are used in a variety of contexts in docassemble, including the url_action() function, review screens, action buttons, editable tables, the force_ask() function, the url_action() JavaScript function, the action_perform() JavaScript function, the action_call() JavaScript function, the run_action_in_session() function, the POST method of /api/session/action.

Regardless of how actions are called, they are always processed by the process_action() function. The next section explains how actions work when called with the url_action() function.

url_action() and process_action()

The url_action() function allows users to interact with docassemble using hyperlinks embedded in questions.

url_action() returns a URL that, when clicked, will perform an “action” within docassemble, such as running some code or asking a question. Typically the URL will be part of a Markdown link inside of a question, in a note within a set of fields, or it might be the URL of an action_button_html().

The process_action() function processes “actions.” The process_action() function is typically called for you, behind-the-scenes, right before the interview logic is evaluated. (However, you can call it explicitly if you want to control exactly when (and if) it is called, and it is important to do so under certain circumstances.)

Here is an example of using “action” URLs in an interview:

field: lucky_information_confirmed
question: |
  Please confirm the following information.
subquestion: |
  Your lucky number is ${ lucky_number }.
  [Increase](${ url_action('set_number_event', increment=1) })
  [Decrease](${ url_action('set_number_event', increment=-1) })

  Also, your lucky color is ${ lucky_color }.
  [Edit](${ url_action('lucky_color') })
---
event: set_number_event
code: |
  lucky_number += action_argument('increment')
---
code: |
  lucky_number = 2

When the user clicks on the “Edit” link generated by url_action('lucky_color'), the interview will load as normal, much as if the user reloaded the screen. However, before initial and mandatory blocks are processed, docassemble runs the function process_action(). The process_action() function checks to see if any “actions” have been requested. If no actions have been requested, process_action() returns without doing anything. In this case, process_action() will see that the 'lucky_color' action has been requested. As a result, the process_action() function will look for a question or code block that defines lucky_color. (Internally, it calls force_ask().) Since there is a question in the interview that offers to define lucky_color, that question will be asked.

If the user refreshes the screen when the “What is your lucky color?” question is showing, the user will arrive at the “What is your lucky color?” question again. Docassemble remembers that the 'lucky_color' action was pending, and the process_action() function will continue sending the user to the “What is your lucky color?” question until the user answers it. It does this even though the interview logic (the mandatory block) does not require a definition of lucky_color. The “action” is a diversion from the interview logic. When the user answers the “What is your lucky color?” question, the action is satisfied, and is no longer considered pending. process_action() returns without forcing a question to be asked, the normal interview logic is evaluated, and the “Please confirm the following information” question is shown.

Even if the variable lucky_color is already defined, the 'lucky_color' action will always cause the “What is your lucky color?” question to be shown. This makes “actions” useful for allowing users to revisit questions they may have already answered.

When the user clicks on the link generated by url_action('set_number_event', increment=1), the process_action() function will look for a question or code block that defines set_number_event. It will find the code block that was labeled with event: set_number_event. (See Setting Variables for more information about events.) It will then run that code block. The Python code within that block uses action_argument() to retrieve the value of increment that had been specified in as a parameter to the url_action() function call.

By default, the process_action() function runs right before docassemble starts processing your initial and mandatory blocks. However, if you have a code block in your YAML that calls process_action(), docassemble will refrain from running process_action() prior to processing your initial and mandatory blocks, and will instead rely on your interview logic to call process_action(). A common reason to do this is when you have a multi-lingual interview and you have an initial block that calls set_language(); process_action() would otherwise run before the language was initialized, and as a result questions might appear in the wrong language.

mandatory: True
code: |
  multi_user = True
---
question: |
  Language/Idioma/Langue
field: user_local.language
choices:
  - English: en
  - Español: es
  - Français: fr
---
initial: True
code: |
  set_language(user_local.language)
  process_action()

Note that an initial block is just like a mandatory block except that it always runs, even if it has already run to completion in the interview session before. In this example, the mandatory block runs first, and because it runs to completion, it will not run again. The initial block will run every time the screen loads. This is a multi-user interview, and the operative language will be set to whatever language the current user speaks. (See user_local for more information about that special object.)

Calling process_action() manually in an initial block can also be useful for security purposes. You might want to ensure that actions can only be carried out if the user is logged in:

initial: True
code: |
  if user_logged_in():
    process_action()

You can pass as many named parameters as you like to an “action.” For example:

question: Hello
subquestion: |
  You can set lots of information by
  [clicking this link](${ url_action('set_stuff', fish='trout', berry='strawberry', money=65433, actor='Will Smith')}).
---
event: set_stuff
code: |
  info = action_arguments()
  user_favorite_fish = info['fish']
  user_favorite_fruit = info['berry']
  if info['money'] > 300000:
    user_is_rich = True
  actor_to_hire = info['actor']

In this example, we use action_arguments() to retrieve all of the arguments to url_action() as a Python dictionary.

You can think of “actions” as temporary diversions from the regular interview logic. When the action is over, the regular interview logic resumes. When the action is considered to be over depends on what the action refers to.

If the action refers to a variable defined by a question, the action will be over when the user answers the question. The question will be asked even if the variable is already defined.
If the action refers to the event name of a question block, the action will be over when the user clicks a continue button on the question. If the question does not have a continue button, the question will be a dead end and the action will never be over.
If the action refers to the event name of a code block, docassemble will run the code and it will consider the action to be over no matter what the code block does. From within such a code block, you can call force_ask() to cause additional actions to run.
If the action refers to a variable defined by a code block, the code will be run in a more “persistent” manner than code designated as an event. If the code stops running, for example because an undefined variable is encountered and a question needs to be asked, the process_action() function will continue to run the action the next time the screen loads. When the code runs through to completion, docassemble will continue looking backward through the YAML for other blocks that offer to define the variable, and if it finds any, it will process those blocks according to these four rules.

You can test out different types of actions in the following interview:

mandatory: True
question: Actions
subquestion: |
  Each of the links below calls a particular action. Try clicking
  these links and note that the way they work the first time they are
  clicked may be different from the way they work the next time they
  are clicked.

  [Variable defined by question](${ url_action('favorite_fruit') })

  [event question](${ url_action('fruit_info') })

  [Variable defined by code](${ url_action('vegetable_asked_about') })

  [Variable defined by code and question](${ url_action('legume_rationale') })

  [event code](${ url_action('increment_counter') })

  [event code that calls force_ask()](${ url_action('review_preferences') })

  The value of the counter is ${ counter }.
---
question: |
  What is your favorite fruit?
fields:
  - Favorite fruit: favorite_fruit
---
event: fruit_info
question: |
  Information about fruit
subquestion: |
  Fruits have seeds. Some fruits are edible.
buttons:
  - Continue: continue
---
code: |
  vegetable_intro
  favorite_vegetable
  log("The favorite vegetable question has been asked.", "success")
  vegetable_asked_about = True
---
question: |
  Introduction to vegetables
subquestion: |
  Note that the `code` block action we are in right now will not be
  over unless `vegetable_intro` and `favorite_vegetable` are defined.
  You can refresh the screen now and this screen will appear again.
  Note that `code` blocks with `event` do not behave this way.
continue button field: vegetable_intro
---
question: |
  What is your favorite vegetable?
fields:
  - Favorite vegetable: favorite_vegetable
---
question: |
  What is your favorite legume?
fields:
  - Legume: favorite_legume
---
question: |
  Why do you like ${ favorite_legume }?
subquestion: |
  Note that `legume_rationale` has already been defined by a
  `code` block during this action, but this `question` is
  being asked anyway.

  An `action` will continue past a `code` block that defines a
  variable and will seek a `question` that defines the same
  variable, if such a `question` exists.
fields:
  - label: |
      Reason liking ${ favorite_legume }
    field: legume_rationale
    label above field: True
    input type: area
---
code: |
  favorite_legume
  legume_rationale = "because legumes are good"
---
event: increment_counter
code: |
  counter += 1
---
code: |
  counter = 0
---
event: review_preferences
code: |
  force_ask('favorite_fruit', 'favorite_vegetable')

Actions are “stackable.” If an action is launched while another action is still active, then when the second action is complete, the user will be returned to the first action.

You can test this out in the following interview:

mandatory: True
question: First page
subquestion: |
  [Go to second page](${ url_action('second_page') })
---
question: Second page
subquestion: |
  [Go to third page](${ url_action('third_page') })
continue button field: second_page
---
question: Third page
subquestion: |
  [Go to fourth page](${ url_action('fourth_page') })

  [Go to fourth page with forget prior](${ url_action('fourth_page', _forget_prior=True) })
continue button field: third_page
---
question: Fourth page
continue button field: fourth_page

Note that when you press a Continue button in this interview, you are taken back to where you were when you clicked on the action link; you complete the current action and “fall back” to the previous incomplete action.

The url_action() function accepts an optional keyword parameter _forget_prior. If set to True, then when the action is run, any actions that were already pending are “forgotten.” The above example interview demonstrates this; note that when you click the “Go to fourth page with forget prior” link, you go to the fourth page, but then when you click Continue, you go back to the first page of the interview; launching the action to go to the fourth page wipes out all of the prior actions.

Using _forget_prior=True is useful when you have an action that serves a navigation-related purpose. If the user clicks links to navigate through screens, the “stacking” aspect of actions is not what the user expects.

Note that the “current action” or the current “stack” of actions is specific to the user. In a multi-user interview, if one user has a pending action, other users will not see that pending action, even though the normal interview logic may take both users to the same screen. The action “stack” that is effective for a user is based on access credentials stored in a cookie in the browser. If a user is not logged in, these credentials are tied to the user’s session in their browser.

See interview_url_action() and scheduled tasks for information about triggering actions externally.

action_menu_item()

One way to let the user trigger “actions” is to provide a selection in the menu of the web app. You can do this by setting the menu_items list. See special variables section for more information about setting menu items.

mandatory: True
code: |
  menu_items = [ action_menu_item('Review Answers', 'review_answers') ]

In this example, a menu item labeled “Review Answers” is added, which when run triggers the action “review_answers.”

The action_menu_item(a, b) function returns a Python dictionary with keys label and url, where label is set to the value of a and url is set to the value of url_action(b).

If you want to pass arguments to the action, you can include the arguments as keyword parameters to action_menu_item().

mandatory: True
code: |
  menu_items = [ action_menu_item('Get more', 'change_count', increment=1),
                 action_menu_item('Get less', 'change_count', increment=-1) ]

One keyword parameter has special meaning. If you set _screen_size to 'small', then the menu item will only appear on small screens. If you set it to 'large', it will only appear on large screens. A “large” screen is Bootstrap md size or above.

interview_url()

The interview_url() function returns a URL to the interview that provides a direct link to the interview and the current variable store. This is used in multi-user interviews to invite additional users to participate.

mandatory: True
code: |
  multi_user = True
---
question: |
  Ready to proceed?
subquestion: |
  To invite someone else to complete
  this interview, ask them to go to
  [this URL](${ interview_url() }).

  To proceed with the interview,
  click "Yes."
yesno: ready_to_proceed

People who click on the link (other than the current user) will not be able to access the interview answers unless multi_user is set to True. This is because interviews are encrypted on the server by default. Setting multi_user to True disables this encryption. Note that the communication between docassemble and the browser will always be encrypted if the site is configured to use HTTPS. The server-side encryption merely protects against the scenario in which the server running docassemble is compromised.

You can include keyword arguments to interview_url(). These will be included as additional URL parameters. When the user visits the URL, docassemble will store the names and values in the url_args dictionary of the interview, and the interview logic of the interview can access the names and values by inspecting url_args.

The keyword argument i is special: you can set this to the name of an interview (e.g., docassemble.demo:data/questions/questions.yml) and this interview will be used instead of the current interview. In this case, the session parameter is omitted and the URL functions as a referral to a different interview, with a fresh variable store. Interview filenames relative to the current package are valid (e.g., questions.yml).

The keyword argument session is also special: you can set this to the known session ID of an interview (e.g., obtained from interview_list()), and also set i to the filename of the interview corresponding with the session. Then the link will point not to the current session, but to the session indicated by the session ID.

If you want the URL to always starts a new session when the user clicks on it, include the keyword argument new_session and set it to 1. For more information about how this works, see the documentation for the new_session URL parameter.

If you want the URL to restart any existing sessions that the user already is running in the interview, set reset=1. For more information about how this works, see the documentation for the reset URL parameter.

The keyword argument local is also special: set this to True if you want the URL to be relative (i.e., it will start with ?). Note that for purposes of the “copy link” feature of web browsers, this does not matter; the web browser will provide a full URL even if the underlying URL is relative. However, docassemble treats URLs differently if they begin with http:/https: or ?: links that begin with http will open in another tab.

The keyword argument style is also special: set this to 'short' if you want the URL to begin with /run instead of /interview. This will use /run/shortcutname format if the interview is listed in dispatch, and otherwise will use /run/packagename/filename format. In the absence of a style argument, the URL returned by interview_url() in the context of the web application will use the style of the URL that is in the location bar of the web browser. If the URL in the location bar is /run/packagename/filename, the URL returned by interview_url() will be /run/packagename/filename. However, if interview_url() is called by a background process or a call to the API, interview_url() will return /interview?i=docassemble.packagename:data/questions/filename.yml by default, unless a style is specified.

There are security risks with URLs created using interview_url(). The URLs contain a session key, and if multi_user is True, anyone with that session key can access the interview session. If you e-mail the result of interview_url(), the session key may be stored permanently in the person’s e-mail account, where a third party may see it.

One way around this potential security risk is to set the keyword argument temporary. Then a special URL will be returned, which will contain a code that will expire after a certain number of hours. For example, if you add temporary=48 to the keyword arguments, the link will expire after 48 hours. When the user clicks visits the link, the user will be redirected to the location that interview_url() would return if temporary was not set. By using a temporary URL, you will avoid sharing the actual session ID, and you will protect against any unauthorized access that would take place after 48 hours have expired.

mandatory: True
code: |
  multi_user = True
---
question: |
  Ready to proceed?
subquestion: |
  To invite someone else to complete
  this interview, ask them to go to
  [this URL](${ interview_url(temporary=1) })
  within the next hour.

  To proceed with the interview,
  click "Yes."
yesno: ready_to_proceed

Screenshot of interview-url-temp example

If you set temporary to 0 or to a non-number, the expiration period will default to 24 hours.

You can add additional security by using the keyword argument once_temporary instead of the keyword argument temporary. This works the same way as temporary, except the link will also expire immediately after it is used for the first time.

interview_url_as_qr()

interview_url_as_qr() is like interview_url(), except it inserts into the markup a QR code linking to the interview. The resulting QR code can be used to pass control from a web browser or a paper handout to a mobile device.

interview_url_action()

interview_url_action() is like interview_url(), except that it also has the effect of running url_action(). You will want to use this instead of url_action() if you want the user to be able to share the URL with other people, or run it unattended.

objects:
  - user: Individual
---
mandatory: True
code: |
  multi_user = True
  status = 'normal'
---
initial: True
code: |
  process_action()
---
event: check_update_status
code: |
  if 'status' in action_arguments():
    status = action_argument('status')
---
mandatory: True
question: |
  The current status is ${ status }.
subquestion: |
  Anyone can use the following links
  to change the current status:

  * Change to [normal](${ interview_url_action('check_update_status', status='normal') })
  * Change to [danger](${ interview_url_action('check_update_status', status='danger') })
  * Change to [critical](${ interview_url_action('check_update_status', status='critical') })

Screenshot of interview_url_action example

Note that in this example, multi_user is set to True. This disables server-side encryption of answers. This is necessary because the encryption uses an decryption key, and a decryption key should not be embedded in a URL.

The first argument to interview_url_action() is the name of the action. The keyword arguments are the arguments of the action. In this respect, interview_url_action() is similar to url_action(). However, the following keyword arguments have special meaning:

i - if you set an i parameter, interview_url_action() will form a URL for an interview other than the current interview. The current session ID will not be included by default in the URL.
session: if you set a session parameter, the value of session will be used as the session ID. This will allow the user of the URL to resume an existing interview session other than the current interview session. By default, if i is not set, the session ID of the current session is included in the URL, which allows the user of the URL to resume the current interview session
local: if you set the local parameter to a true value, then a relative URL will be returned. By default, interview_url_action() returns a complete URL.
new_session: if you set the new_session parameter to a true value, then new_session=1 will be included in the URL. Set this if you are providing an i parameter and you want to make sure that the user of the URL starts a new session rather than resuming an existing one.
reset: if you set the reset parameter to a true value, then reset=1 will be included in the URL. Set this if you are providing an i parameter and you want the user of the URL to restart any existing session they may be using in the interview indicated by i.
_forget_prior: if you set the _forget_prior parameter to a true value, then the action, when run, will cause any prior pending actions to be forgotten, and the only pending action will be the one indicated by interview_url_action(). For more information about the meaning of _forget_prior, see the documentation for the url_action() function.

interview_url_action_as_qr()

interview_url_action_as_qr() is like interview_url_action(), except it inserts into the markup a QR code linking to the interview, with the specified actions.

Note that there is a limit to the number of characters a QR code can hold, and you might run up against this limit if you try to add too many arguments to the URL. Using the temporary keyword parameter is one way around this limitation.

action_arguments()

The action_arguments() function returns a dictionary with any arguments that were passed when the user clicked on a link generated by url_action() or interview_url_action().

When a check in action takes place, action_arguments() returns the fields on the screen. Although the special arguments _initial and _changed can be read with action_argument(), the action_arguments() function does not return these values.

action_argument()

The action_argument() function is like action_arguments(), except that it returns the value of a given argument.

For example, if you formed a URL with:

question: |
  The total amount of your bill is ${ currency(bill + tip) }.
subquestion: |
  [Tip your waiter $10](${ url_action('tip', amount=10)}).

  [Tip your waiter $20](${ url_action('tip', amount=20)}).

Then you could retrieve the value of amount by doing:

event: tip
code: |
  tip = action_argument('amount')

If you are writing an initial block that calls process_action() and you want to know the name of the action itself before you call process_action(), you can retrieve the name of the action by calling action_argument() without an argument. This will return the name of the action itself. If the result is None, then no action was called for the current request (and process_action() will not do anything).

You can only retrieve the action name with action_argument() before you call process_action(). During the processing of the action, and after process_action() returns, action_argument() will always return None.

url_of()

This function returns a URL to a file within a docassemble package’s static folder.

For example, you might have PDF files associated with your interview. You would keep these in the data/static directory of your package, and you would refer to them by writing something like:

mandatory: True
question: You are done.
subquestion: |
  To learn more about this topic, read
  [this brochure](${ url_of('docassemble.mycompany:data/static/brochure.pdf') }).

You can also refer to files in the current package by leaving off the package part of the file name:

mandatory: True
question: You are done.
subquestion: |
  To learn more about this topic, read
  [this brochure](${ url_of('brochure.pdf') }).

If you do not specify a package, docassemble will look for the file in the static folder of the package in which the current question or current code block resides.

Special uses

The url_of() function also has a few special uses.

If applied to a DAFile object, it will return a URL to the file.
url_of('help') returns a URL that causes the help tab to be shown, if there is a help tab.
url_of('login') returns a URL to the sign-in page. It takes an optional keyword parameter next, which you can set to a URL if you want the user to be directed to a particular URL after they log in.
url_of('signin') does the same thing as url_of('login').
url_of('restart') returns a URL that will delete the current session and restart it with the same URL parameters.
url_of('new_session') returns a URL that starts a new session of the current interview, preserving the existing session.
url_of('exit') returns a URL that deletes the interview session and redirects to the exitpage.
url_of('interview') returns a URL to the interview page. This should be used with an i parameter. If your i parameter does not begin with a package name, the current package will be substituted. (See also interview_url(), which does something similar but with more features.)
url_of('logout') returns a URL that logs the user out. It accepts a next parameter.
url_of('exit_logout') returns a URL that deletes the interview session, logs the user out (if the user is logged in), and redirects to the exitpage.
url_of('leave') redirects to the exitpage. It does not log the user out or delete the interview session.
url_of('register') returns a URL to the user registration page. It accepts a next parameter.
url_of('profile') returns a URL to the logged-in user’s profile page.
url_of('change_password') returns a URL to a page where a logged-in user can change his or her password.
url_of('interviews') returns a URL to the page listing the on-going interviews of a signed-in user.
url_of('dispatch') returns a URL to the page listing the interviews defined in the dispatch directive of the Configuration.
url_of('manage') returns a URL to a page where the user can delete his or her account data.
url_of('config') returns a URL to the Configuration page.
url_of('playground') returns a URL to the Playground.
url_of('playgroundtemplate') returns a URL to the Templates folder of the Playground.
url_of('playgroundstatic') returns a URL to the Static folder of the Playground.
url_of('playgroundsources') returns a URL to the Sources folder of the Playground.
url_of('playgroundmodules') returns a URL to the Modules folder of the Playground.
url_of('playgroundpackages') returns a URL to the Packages folder of the Playground.
url_of('configuration') returns a URL to the Configuration page.
url_of('root') returns the root URL of your server.
url_of('temp_url', url=some_url) returns a URL that redirects to some_url. This special feature is explained below.
url_of('login_url', username='[email protected]', password='abc123', i='docassemble.foo:data/questions/bar.yml') returns a URL that a user can click on to be automatically logged in This special feature is explained below.

By default, url_of() returns relative URLs, which begin with /. However, if you want a full URL, you can call, e.g., url_of('root', _external=True).

You can set _attachment=True if you want the user to download the file. This only works when url_of() refers to a file.

The url_of() function can also be used to format URLs with parameters. For example, url_of('https://example.com', query="Hello, world!") becomes https://example.com?query=Hello%2C+world%21.

You can also use this feature to format mailto: URLs:

question: |
  What e-mail would you like to send?
fields:
  - To: addressee
    datatype: email
  - Subject: subject
  - Body: body
    input type: area
---
mandatory: True
question: |
  Draft e-mail
subquestion: |
  [Your draft e-mail](${ url_of('mailto:' + addressee, subject=subject, body=body) })
  is ready.

url_of('redirect', url=some_url) acts like a URL shortener; it returns a URL to the /goto endpoint of the docassemble server with a URL parameter c set to a 32-character code. When this URL is visited, the server responds with a redirect to the URL indicated by the url parameter. The /goto URL expires after 90 days or another time period you indicate.

mandatory: True
question: |
  All done
subquestion: |
  [Click here within 60 seconds](${ url_of('redirect', url='https://google.com', expire=60) })

The temp_url variant of url_of() returns a URL that redirects to another URL. It uses four keyword parameters:

url (required): the URL to which the user should be redirected.
expire (optional): this indicates the number of seconds until the temporary URL should no longer funtion. The default is 7,776,000 sends (90 days).
local (optional): if local is true, the /goto URL returned by temporary_url() will be a relative URL (e.g., /goto). If local is false (which is the default), the URL will be complete (e.g., https://yourserver.com/goto).
one_time (optional): if one_time is true, then the redirect link can only be used once. If the /goto URL is visited once, the temporary URL immediately expires. This has security advantages. If the /goto link is visited by a bot (for example, if Slack tries to visit the link in order to fetch its metatag information and show “preview” information) then /goto responds with a blank page; this helps protect against the link expiring prematurely when one_time is used. By default, redirect links can be used more than once.

If the URL that you want to shorten is a URL created with interview_url(), you do not need to use url_of('temp_url'); the temporary and once_temporary keyword parameters to interview_url() do the same thing.

The login_url variant of url_of() provides a URL containing a special code that logs the user in and directs them to an interview session or another destination. It uses the following keyword parameters:

username: the user name of the user.
password: the password of the user.
i (optional): the filename of an interview to which the user will be redirected after they log in. E.g., docassemble.demo:data/questions/questions.yml.
session (optional): the session ID for the interview session (if i is also provided). Providing this here rather than in the url_args prevents sending the session ID to the user’s browser.
resume_existing (optional): set this to 1 if you do not know the session code but you are providing an i filename and you want the user to resume an existing session in that interview, if they have one.
expire (optional): the number of seconds after which the URL will expire. The default is 15 seconds.
url_args (optional): a dictionary containing additional URL arguments that should be included in the URL to which the user is directed after they log in.
next (optional): if the user should be directed after login to a page that is not an interview, you can omit i and instead set this parameter to a value like playground (for the Playground) or config (for the Configuration page). For a list of all possible values, see above (these are the “special uses” of url_of()). If url_args are supplied, these will be included in the resulting URL.

In addition to expiring after expire seconds, the URL expires immediately after first use. The best way to use a login_url link is by creating the URL and then immediately redirecting the user to the URL. If you share the URL with the user directly, there is a chance that the URL could expire before the user has a chance to click on it. Some software visits URL for purposes of rendering a URL preview box, and if the software visits the URL before the user does, the software will invalidate the URL.

An API version of the login_url feature is available at /api/login_url.

url_ask()

The url_ask() function is like url_action(), except instead of accepting a single action name and optional arguments, it accepts a single data structure, which is treated like the fields specifier inside an item of a review block. It returns a URL that will result in the asking of certain questions when the user visits it.

url_ask('favorite_fruit') - Ask the question that defines favorite_fruit.
url_ask(['favorite_fruit', 'favorite_vegetable']) - Ask the question that defines favorite_fruit, then ask the question that defines favorite_vegetable.
url_ask(['favorite_fruit', {'follow up': ['favorite_apple']}, 'favorite_vegetable']) - Ask the question that defines favorite_fruit; then ask the question that defines favorite_apple, if such a question can be found; then ask the question that defines favorite_vegetable.
url_ask(['favorite_fruit', {'recompute': ['fruit_to_offer']}, 'favorite_vegetable']) - Ask the question that defines favorite_fruit; then undefine the variable fruit_to_offer if it is defined; then compute the value of fruit_to_offer; then ask the question that defines favorite_vegetable.
url_ask(['favorite_fruit', {'set': [{'fruit_to_offer': 'apple'}]}, 'favorite_vegetable']) - Ask the question that defines favorite_fruit; then set fruit_to_offer to 'apple'; then ask the question that defines favorite_vegetable.
url_ask([{'action': 'increment_counter', 'arguments': {'amount': 2}}, 'follow_up_screen']) - Run the action increment_counter with the argument amount set to 2, and when that is done, ask the question that defines follow_up_screen.

For more information on how these data structures work, see the subsection on customizing the display of review options.

action_button_html()

The action_button_html() function returns the HTML of a Bootstrap-formatted button (an <a> tag styled as a button) that visits a given URL. It is often given the output of url_ask() or url_action(), but you can give it any URL.

mandatory: True
question: |
  Need more information?
subquestion: |
  ${ action_button_html("https://docassemble.org", label="Visit our web site", color="primary", size="md") }

Screenshot of action-button-html example

It accepts the following optional keyword arguments:

icon - this is the name of the Font Awesome icon to use at the start of the button. It can take a value like 'pencil-alt'. By default, the icon is assumed to be in the “solid” collection (fas). To use a different collection, specify a name such as fab-fa-windows for the windows icon in the “brand” collection. If you do not want any icon, set icon to None. The default is None.
color - this is the Bootstrap color of the button. The options are primary, secondary, success, danger, warning, info, light, link, and dark. The default is 'dark'. The actual colors depend on the Bootstrap theme.
size - this is the Bootstrap size of the button. The options are 'sm', 'md', and 'lg'. The default is 'sm'.
block - if set to True, the button will fill the width of the question area.
label - this is the text on the button. It passes through the word() function, so you can use the translation system to handle different languages.
classname - set this to one or more class names (separated by a space) if you want to add additional CSS classes to the button.
new_window - By default, internal links open in the same tab, except for links to files, which open in a new tab. If you want to force the link to open in the same window, set new_window=False. If you want to force the link to open in a new tab, set new_window=True. If you use a value other than True or False, it will be used as the target of the hyperlink. If your link runs an action that responds with a command() or a response(), setting new_window to True, False, or a manual target is helpful for its side effect, which is that the action will be submitted to the server as a synchronous GET request from the browser, rather than an asynchronous POST request using Ajax. This will ensure that the response is handled appropriately.
id_tag - if you want your button to have an id so that you can manipulate it with JavaScript, set id_tag to the id you want to use. For example, if you don’t want the button to actually visit a link, you can do action_button_html('#', label="Click me", id_tag="mybutton") and then write JavaScript code that does something like $("#mybutton").click(function(e){e.preventDefault(); console.log("Hello"); return false;}).

QR code functions

qr_code()

The qr_code() function allows you to include the [QR ...] markup statement using Python.

It has two optional parameters: width and alt_text.

question: |
  Read the news on your mobile
  phone
subquestion: |
  If you have a QR code reader on
  your phone, point it here:

  ${ qr_code('https://news.google.com') }
mandatory: True

These two questions are equivalent:

question: |
  Here is a QR code.
subquestion: |
  Go to Google:

  ${ qr_code('http://google.com', width='200px') }

  Or go to Yahoo:

  ${ qr_code('http://yahoo.com') }

question: |
  Here is a QR code.
subquestion: |
  Go to Google:

  [QR http://google.com, 200px]

  Or go to Yahoo:

  [QR http://yahoo.com]

For more information about what the [QR ...] markup statement does, see the QR markup documentation.

Since this function returns [QR ...] markup, if you want to use it within a docx template file, you will need to use the markdown filter:

{{p qr_code(url) | markdown }}

Note that if you want to include a QR code that points to an interview or an interview action, there are shorthand functions for that. See interview_url_as_qr() and interview_url_action_as_qr().

read_qr()

This function reads QR codes from one or more image files and returns a Python list with the encoded text string or strings.

question: |
  Please upload a file (or files) with
  a QR code.
fields:
  - File: user_upload
    datatype: files
---
question: |
  Codes found
subquestion: |
  The following codes were found:

  % for code in read_qr(user_upload):
  * ${ code }
  % endfor
mandatory: True

The first argument must be a DAFile or DAFileList object. If the argument is a DAFileList with more than one file, all files (and all pages within all files) will be scanned for QR codes.

The function accepts image files (JPEG, PNG, etc.) as well as PDF files. If you provide PDF files, the following optional parameters customize the reading of the PDF files (they are passed directly to pdftoppm).

f indicates the first page of the PDF file to read. By default, all pages are read.
l indicates the last page of the PDF file to read. By default, all pages are read.
x: for cropping PDF pages. Indicates the x-coordinate of the crop area’s top left corner, in pixels. (By default, PDF files are converted at 300 dpi unless another value is given by the ocr dpi configuration directive.)
y: for cropping PDF pages. Indicates the y-coordinate of the crop area’s top left corner, in pixels.
W: for cropping PDF pages. Indicates the width of the crop area in pixels (default is 0).
H: for cropping PDF pages. Indicates the height of the crop area in pixels (default is 0).

The function returns a Python list with the codes found, in the order in which they were found.

E-mail functions

send_email()

The send_email() function sends an e-mail.

objects:
  - recipient: Individual
---
mandatory: true
question: |
  E-mail test
subquestion: |
  % if intro_provided and email_sent_ok:
  The e-mail was sent successfully.
  % else:
  There was a problem sending the e-mail.
  % endif
---
question: |
  E-mail test
subquestion: |
  This interview will send you an e-mail.
field: intro_provided
---
question: |
  What is your name?
fields:
  - First Name: recipient.name.first
  - Last Name: recipient.name.last
---
question: |
  What is your e-mail address?
fields:
  - E-mail: recipient.email
    datatype: email
---
code: |
  email_sent_ok = send_email(to=recipient, template=notification)
---
template: notification
subject: |
  Greetings, ${ recipient }!
content: |
  This is an e-mail sent from a
  **docassemble** interview.

  Have a nice day!

All of the arguments to send_email() are keyword arguments:

to expects a list of Individuals, or Persons, DAEmailRecipients, or plain e-mail addresses. It also accepts a single item of any of these.
sender expects a single Individual. If not set, the default_sender information from the configuration is used.
reply_to expects a single Individual, or None. This sets the (optional) Reply-To header of the e-mail, which determines the e-mail address to which replies are directed.
cc expects a list of Individuals, or None.
bcc expects a list of Individuals, or None.
body expects text, or None. Will set the plain text content of the e-mail.
html expects text, or None. Will set the (optional) HTML content of the e-mail.
subject expects text, or None. Will set the subject of the e-mail. The default is "".
template expects a template object, or None. These templates can be created in an interview file using the template specifier. If this keyword argument is supplied, both the plain text and HTML contents of the e-mail will be set by converting the Markdown text of the template into HTML and by converting the HTML to plain text (using html2text). In addition, the subject of the e-mail will be set to the subject of the template. You can override any of these behaviors by manually specifying body, html, or subject.
task expects the name of a task. If this argument is provided, and if sending the e-mail is successful, the task will be marked as having been performed (i.e., mark_task_as_performed() will be called). Alternatively, you can handle this in your own code, but you might find it convenient to let the send_email() function handle it for you.
task_persistent: if you set a task, you can optionally set the “persistence” of the task by setting this to True or a value like 'user'. For more information, see the documentation for the task-related functions.
attachments expects a list of DAFile, DAFileList, or DAFileCollection objects. You can include:
- Images generated by signature blocks (objects of class DAFile);
- File uploads generated by including fields of datatype: file or datatype: files in a question (objects of class DAFileList);
- Documents generated by attachments to a question for which a variable was provided (objects of class DAFileCollection).
mailgun_variables expects a dictionary of user variables that should be passed to the Mailgun API. This is only applicable if you are using the Mailgun API for e-mail sending.
dry_run can be set to True if you want to do a “dry run” of the e-mail sending process. You would use this if you wanted to make sure that all of the variables send_email() needs are defined before you actually send the e-mail. The default is False.
config can be set to the name of an e-mail configuration if you are using multiple e-mail configurations in your Configuration. This allows you to contol which e-mail server or provider is used to send the e-mail. Alternatively, you can set a default e-mail configuration for the interview using email config in the metadata, in which case any call to send_email() within the interview will use that e-mail configuration.

If you use Individual objects as recipients, send_email() will use the name and email attributes of the listed Individuals to form e-mail addresses.

send_email() returns False if an error prevented the e-mail from being delivered to the mail server; otherwise it returns True. Note that this function might return True even though no e-mail is actually delivered to the recipient; the return value indicates only whether there was a problem sending the e-mail with Flask-Mail.

See configuration for information about how to configure the mail server that send_email() will use.

Here is an example of sending an attachment via e-mail:

question: |
  Please fill in the following information.
fields:
  - Your First Name: user.name.first
  - Your Last Name: user.name.last
  - Your E-mail: user.email
    datatype: email
  - A Picture: the_file
    datatype: file
---
code: |
  success_sending_email = send_email(to=[user], template=hello_email, attachments=[the_file])

Screenshot of send-email-with-attachment example

Sending e-mail can be slow. If you call send_email() from within your interview logic, the user might have to look at a spinner. In order to provide a better experience to users, you may wish to call send_email() from within a background process.

interview_email()

The interview_email() function returns an e-mail address that the user can use to send a message to the interview. For more information about how users can send e-mails to interview sessions, see the documentation for the e-mail to interview feature.

If the incoming mail domain directive in your configuration is help.example.com, then interview_email() will return something like [email protected].

The address returned by interview_email() is a unique random sequence of six lowercase letters. If any e-mails are received at this e-mail address, docassemble will associate them with the user’s session and the e-mails can be retrieved with get_emails().

The result returned by interview_email() will be unique to the session. Every time your interview calls interview_email(), the same e-mail address will be returned.

You can also associate more than one e-mail address with the session, if you wish. For example, in a litigation application, you may want to have one e-mail address for receiving evidence from the client and another address for corresponding with opposing counsel. You can obtain these different e-mail addresses using the optional keyword argument key. For example, interview_email(key='evidence') and interview_email(key='opposing counsel') will return different unique addresses.

If you are using a key to get an e-mail address, you can also set the optional keyword argument index to an integer. For example, if there are multiple opposing counsel and you want a separate e-mail address for each one, you can use interview_email(key='opposing counsel', index=1), interview_email(key='opposing counsel', index=2), etc.

get_emails()

The get_emails() function returns a list of objects representing e-mail addresses generated with interview_email(). For more information about how users can send e-mails to interview sessions, see the documentation for the e-mail to interview feature.

Each object in the list returned by get_emails() has the following attributes:

address: the part of the e-mail address before the @.
emails: a list of DAEmail objects representing e-mails that have been sent to the e-mail address.
key: the key associated with the e-mail address, which is None if you did not supply a key to interview_email()
index: the index associated with the e-mail address, which is None if you did not supply an index to interview_email().

If you used key with interview_email(), you can use the optional key and index keyword arguments to get_emails() in order to filter the results. For example, get_emails(key='evidence') will only return information about e-mail addresses created with interview_email(key='evidence'). Calling get_emails(key='evidence', index=2) will limit the list even further to the e-mail address created by interview_email(key='evidence', index=2).

Fax functions

send_fax()

The send_fax() function sends a PDF document as a fax. This function requires you to create an account with a fax provider.

send_fax() takes two arguments, a destination and a file.

objects:
  - user: Individual
---
question: |
  What is your fax number?
fields:
  - Fax: user.fax_number
---
question: |
  What file would you like
  me to fax?
fields:
  - File: document
    datatype: file
---
code: |
  fax_result = send_fax(user, document)
---
mandatory: True
question: |
  % if fax_result.received():
  The fax was received.
  % else:
  The status of the fax is
  ${ fax_result.status() }.
  % endif
reload: True

The destination can be a Person or a fax number. If it is a Person, the fax number will be obtained from the fax_number attribute of the object. The send_fax() function will convert the fax number to E.164 format. To do so, it will need to determine the appropriate country calling code for the phone number. This country code will be based on the country attribute of the object, or the address.country attribute, but if neither of these attributes is already defined, the value of get_country() will be used. If you want to use a specific country, you can call send_fax() with the optional keyword parameter country. The format of the country attribute and the keyword parameter is expected to be ISO 3166-1 alpha-2 format.

The second argument, the file, must be a file object such as a DAFile, DAFileList, DAFileCollection, or DAStaticFile object.

The send_fax() function returns an object that represents the status of the fax sending. The object has the following methods:

.status() - this will represent the status of the sending of the fax. The available values depend on your fax provider. If there is a configuration error, it will be 'not-configured', and if no result is available, it will be 'no-information'.
.info() - this will be a dictionary containing information about the fax. The format depends on which fax provider you are using.
.received() - this will be True or False depending on whether the fax has been received yet. It will be None if no result is available.
.pages() - if the fax is successfully delivered, this will return the number of pages sent.

Immediately after send_fax() is called, the result will likely be unavailable, because the fax provider will not have had time to start processing the request.

In addition, the result will expire 24 hours after the last time the fax provider reported a change in the status of the fax sending. Thus, if you want to ensure that the outcome of a fax sending gets recorded in the interview session dictionary, you should launch a background_action() that polls the status, or set up a scheduled task that checks in hourly.

Geographic functions

map_of()

The map_of() function inserts a Google Map into question text. (It does not work within documents.) The arguments are expected to be docassemble objects. Different objects are mapped differently:

Address objects: if an Address object is provided as an argument to map_of(), a map marker will be placed at the geocoded coordinates of the address. The description of the address will be the address itself.
- Technical details: if the object is called address, the marker will be placed at the coordinates address.location.latitude and address.location.longitude. (The attribute address.location is a LatitudeLongitude object.) The description of the marker will be set to address.location.description. These fields are set automatically during the geocoding process, which will take place the first time docassemble runs map_of(), if it has not taken place already. The marker icon can be customized by setting address.icon.
Organization objects: map markers will be placed at the locations of each of the organization’s offices. For example, if the object name is company, markers will be placed on the map for each address in company.office (which is a list of Addresses). The icon for the ith office will be company.office[i].icon, or, if that is not defined, it will be company.icon if that is defined. The description of each marker will be the organization’s name (company.name.full()) followed by company.office[i].location.description.
Person objects: a map marker will be placed at the person’s address. The description will be the person’s name, followed by the address. The marker icon can be customized by setting person.icon (for a Person object called person). If the Person object is the user, the default icon is a blue circle.

objects:
  - user: Individual
  - enemy: Individual
---
initial: True
code: |
  set_info(user=user, role='user')
  track_location = user.location.status()
---
mandatory: True
code: |
  need(welcome_screen, user.address.address, enemy.name.first, enemy.address.address, map_shown)
---
event: map_shown
question: Map of you and your enemy
subquestion: |
  ${ map_of(user, enemy) }

In order for maps to appear, you will need to configure a Google API key. From the google section of the configuration, the google maps api key will be used if it exists. If a google maps api key is not present, the api key will be used.

location_known()

Returns True or False depending on whether docassemble was able to learn the user’s GPS location through the web browser.

See track_location and LatitudeLongitude for more information about how docassemble collects information about the user’s location.

location_returned()

Returns True or False depending on whether an attempt has yet been made to transmit the user’s GPS location from the browser to docassemble. Will return true even if the attempt was not successful or the user refused to consent to the transfer.

See track_location and LatitudeLongitude for more information about how docassemble collects information about the user’s location.

user_lat_lon()

Returns the user’s latitude and longitude as a tuple.

See track_location and LatitudeLongitude for more information about how docassemble collects information about the user’s location.

iso_country()

The iso_country() function takes a country name or abbreviation as input and returns a two-character ISO 3166-1 alpha-2 code or other ISO 3166-1 information about a country.

question: |
  In what country do you live?
fields:
  - Country: country
validation code: |
  try:
    country = iso_country(country)
  except:
    validation_error("That country does not exist.  Please try again.")
---
mandatory: True
question: |
  You live in ${ country_name(country) }.

By default, it returns the ISO 3166-1 alpha-2 country code, but it can return other things depending on the optional keyword parameter part, which can be set to one of the following values:

'alpha_2' (the default): returns the two-letter country code (e.g., US).
'alpha_3': Returns the three-letter country code (e.g., 'USA').
'name': Returns the name of the country (e.g., 'United States').
'numeric': Returns the three-digit country code, as text (e.g., '840').
'official_name': Returns a long-form name of the country (e.g., 'United States of America').

countries_list() and country_name()

The countries_list() function returns a list of dictionaries, where each dictionary contains a single key-value pair mapping a two-letter, capitalized country abbreviation to the name of the country (in English). This function is primarily useful when asking a user to specify his or her country.

The country_name() function returns the name of a country (in English) based on the two-letter, capitalized country abbreviation.

question: |
  Where do you live?
fields:
  - Country: user_country
    code: countries_list()
    default: US
---
mandatory: True
question: |
  You live in
  ${ country_name(user_country) },
  which is abbreviated
  ${ user_country }.

When working with countries, it is a good idea to store country names in this two-letter, capitalized format (ISO 3166-1 alpha-2 format). The country code is used by the send_sms() function to determine the appropriate universal formatting of phone numbers.

The data come from the pycountry package.

states_list() and state_name()

The states_list() function returns a dictionary that maps state abbreviations to state names. This function is primarily useful when asking a user to specify his or her state.

The function takes an optional keyword argument country_code, which is expected to be a country abbreviation (ISO 3166-1 alpha-2, e.g., 'SE' for Sweden). If the country_code is not provided, it is assumed to be the default country (the value returned by get_country()). For countries other than the United States, the geographic areas returned are the first-level subdivisions within the country. The name of these subdivisions varies. The subdivision_type() function can be used to find the name of the major subdivision, and also to find if the country has any subdivisions at all.

The states_list() function also takes an optional keyword argument abbreviate. The default value is False. If it is set to True, then the labels and values will both be the abbreviated version of the state name.

The state_name() function returns the name of a state based on the state abbreviation provided.

question: |
  Where do you live?
fields:
  - State: user_state
    code: states_list()
---
mandatory: True
question: |
  You live in
  ${ state_name(user_state) },
  which is abbreviated
  ${ user_state }.

Like states_list(), state_name() accepts an optional keyword parameter country_code that determines which country is used to find the state name.

When working with states, it is a good idea to store state names in this abbreviated format.

The data come from the pycountry package.

subdivision_type()

Given a country code (ISO 3166-1 alpha-2), subdivision_type() returns the name of the primary subdivision within that country.

mandatory: True
question: |
  Geography lesson
subquestion: |
  % for country in ['BG', 'SE', 'TN', 'VN', 'LV', 'US']:
  In ${ country_name(country) },
  you live in a
  ${ subdivision_type(country) }.
  
  % endfor

Note that some countries have no subdivisions at all. In that case, this function will return None.

The data come from the pycountry package.

For more information about the progress bar, see the documentation for the progress bar initial block and the progress modifier.

For more information about the navigation bar, see the documentation for the navigation bar feature and how to work with sections.

get_progress()

You can retrieve the current numeric value of the progress bar by calling get_progress().

set_progress()

You can set the numeric value of the progress bar by calling, e.g., set_progress(20). If you run set_progress(None), the progress meter will be hidden. You can also use the progress modifier on a question to set the progress meter to a particular value.

nav.get_section()

The navigation bar is controlled by a special variable called nav. This is a special Python object of type DANav. Access to the navigation bar is achieved by methods that act upon this object.

sections:
  - Introduction
  - About you:
    - Contact info
    - Demographics
  - Preferences
  - Conclusion
---
features:
  navigation: True
  progress bar: True
---
mandatory: True
code: |
  menu_items = [ action_menu_item('Roadmap', 'road_map') ]
---
initial: True
code: |
  if returning_user(minutes=0.5):
    welcome_back
---
mandatory: True
question: |
  Welcome to the interview
subquestion: |
  If you are not on a
  smartphone-sized device,
  you should see a navigation
  bar to the left.
field: sees_nav_bar
---
mandatory: True
question: |
  I am going to ask you some
  questions about yourself.
field: intro_to_about_you
section: About you
---
mandatory: True
question: |
  What is your name?
fields:
  - First Name: first_name
  - Last Name: last_name
section: Contact info
---
mandatory: True
question: |
  What is your e-mail address?
fields:
  - E-mail: email_address
    datatype: email
---
mandatory: True
question: |
  What is your gender?
field: gender
choices:
  - Male
  - Female
  - Something else
section: Demographics
---
mandatory: True
question: |
  What kind of belly button
  do you have?
subquestion: |
  To see what a user would
  see after returning to
  the interview after a period
  of absence, try waiting
  thirty seconds, then
  [click into the
  interview](${ interview_url(local=True) }).

  In addition, there is a similar
  screen available on the Menu in the
  upper-right, under "Roadmap."
field: belly_button
choices:
  - Innie
  - Outie
---
mandatory: True
question: |
  What is your favorite fruit?
fields:
  - Favorite fruit: favorite_fruit
section: Preferences
---
mandatory: True
question: |
  What is your favorite vegetable?
fields:
  - Favorite vegetable: favorite_vegetable
---
progress: 100
mandatory: True
question: Thank you.
subquestion: |
  ${ first_name },

  Your answers mean a lot to me.
  
  I am going to go eat some
  ${ favorite_vegetable }
  now.
section: Conclusion
---
event: welcome_back
question: |
  Welcome back!
subquestion: |
  You are currently in the
  **${ nav.get_section(display=True) }**
  section.

  ${ nav }

  Press "Continue" to pick up
  where you left off.
buttons:
  Continue: continue
---
event: road_map
question: |
  Roadmap
subquestion: |
  You are currently in the
  **${ nav.get_section(display=True) }**
  section.

  ${ nav }

  Press "Continue" to resume the
  interview.
buttons:
  Continue: continue

You can retrieve the current section by calling nav.get_section(). This will return the keyword corresponding to the current section. To get the displayed name of the section, call it using nav.get_section(display=True). When you call it with display=True, you can also use the optional keyword parameter language to indicate a language to use, if you want the display name for a language other than the current language.

nav.set_section()

You can change the current section by calling nav.set_section() with the keyword of the section you want to be the current section.

sections:
  - intro: Introduction
  - about: About you
    subsections:
      - contact: Contact info
      - demographic: Demographics
  - prefs: Preferences
  - conclusion: Conclusion
---
features:
  navigation: True
---
mandatory: True
code: |
  sees_nav_bar
  nav.set_section('about')
  intro_to_about_you
  nav.set_section('contact')
  first_name
  email_address
  nav.set_section('demographic')
  gender
  belly_button
  nav.set_section('prefs')
  favorite_fruit
  favorite_vegetable
  nav.set_section('conclusion')
  final_screen
---
question: |
  Welcome to the interview
subquestion: |
  If you are not on a
  smartphone-sized device,
  you should see a navigation
  bar to the left.
field: sees_nav_bar
---
question: |
  I am going to ask you some
  questions about yourself.
field: intro_to_about_you
---
question: |
  What is your name?
fields:
  - First Name: first_name
  - Last Name: last_name
---
question: |
  What is your e-mail address?
fields:
  - E-mail: email_address
    datatype: email
---
question: |
  What is your gender?
field: gender
choices:
  - Male
  - Female
  - Something else
---
question: |
  What kind of belly button
  do you have?
field: belly_button
choices:
  - Innie
  - Outie
---
question: |
  What is your favorite fruit?
fields:
  - Favorite fruit: favorite_fruit
---
question: |
  What is your favorite vegetable?
fields:
  - Favorite vegetable: favorite_vegetable
---
event: final_screen
question: Thank you.
subquestion: |
  ${ first_name },

  Your answers mean a lot to me.
  
  I am going to go eat some
  ${ favorite_vegetable }
  now.

Screenshot of sections-keywords-code example

nav.get_sections()

Calling nav.get_sections() returns a Python list with the sections defined using the sections initial block or the nav.set_sections() method.

sections:
  - intro: Introduction
  - about: About you
    subsections:
      - contact: Contact info
      - demographic: Demographics
  - prefs: Preferences
  - conclusion: Conclusion
---
features:
  navigation: True
---
mandatory: True
question: |
  Welcome to the interview
subquestion: |
  The sections of this interview,
  as a Python list, are:

  `${ nav.get_sections() }`
field: sees_nav_bar
---
mandatory: True
question: |
  I am going to ask you some
  questions about yourself.
field: intro_to_about_you
section: about
---
mandatory: True
question: |
  What is your name?
fields:
  - First Name: first_name
  - Last Name: last_name
section: contact
---
mandatory: True
question: |
  What is your e-mail address?
fields:
  - E-mail: email_address
    datatype: email
---
mandatory: True
question: |
  What is your gender?
field: gender
choices:
  - Male
  - Female
  - Something else
section: demographic
---
mandatory: True
question: |
  What kind of belly button
  do you have?
field: belly_button
choices:
  - Innie
  - Outie
---
mandatory: True
question: |
  What is your favorite fruit?
fields:
  - Favorite fruit: favorite_fruit
section: prefs
---
mandatory: True
question: |
  What is your favorite vegetable?
fields:
  - Favorite vegetable: favorite_vegetable
---
mandatory: True
question: Thank you.
subquestion: |
  ${ first_name },

  Your answers mean a lot to me.
  
  I am going to go eat some
  ${ favorite_vegetable }
  now.
section: conclusion

Screenshot of sections-keywords-get-sections example

nav.set_sections()

You can programmatically set the list of sections using nav.set_sections(). It takes one argument, the Python list containing the sections defintion. The list should have the same structure as a sections definition using the sections initial block (except it should be a Python data structure rather than YAML text). This method takes an optional keyword argument language that you can specify if you want to define the section names for a language other than the current language.

sections:
  - intro: Introduction
  - about: About you
    subsections:
      - contact: Contact info
      - demographic: Demographics
  - prefs: Preferences
---
features:
  navigation: True
---
question: |
  What additional section
  would you like to add to
  this interview?
fields:
  - Name: new_name
  - Keyword: new_keyword
    help: |
      Use only letters and
      underscores.
---
mandatory: True
code: |
  new_section = {}
  new_section[new_keyword] = new_name
  the_sections = nav.get_sections()
  the_sections.append(new_section)
  nav.set_sections(the_sections)
---
mandatory: True
code: |
  sees_nav_bar
  nav.set_section('about')
  intro_to_about_you
  nav.set_section('contact')
  first_name
  email_address
  nav.set_section('demographic')
  gender
  belly_button
  nav.set_section('prefs')
  favorite_fruit
  favorite_vegetable
  nav.set_section(new_keyword)
  final_screen

Screenshot of sections-keywords-set-sections example

nav.show_sections()

To display the section list to the user in the body of a question, you can include the nav variable in a Mako template like so: ${ nav }. This has the effect of doing ${ nav.show_sections(style='inline') }. This method takes the optional keyword arguments style, the options for which are None or 'inline', and show_links, which you can set to True if you want users to be able to click on section names.

nav.hide()

If you want to hide the main navigation bar, run nav.hide(). The sections system will still work, and you can still insert nav into the body of a question, but the main navigation bar will not be shown on the screen. The navigation bar is shown by default if sections are defined.

nav.unhide()

Calling nav.unhide() will undo the effect of nav.hide().

nav.visible()

The result of nav.visible() will be False if the navigation bar has been hidden with nav.hide(), and it will return False if no sections have been defined. nav.visible() takes an optional keyword argument language, and when determining whether no sections have been defined, it will look to that language. If sections are defined and the navigation bar has not been hidden with nav.hide(), nav.visible() will return True.

nav.disable()

If your navigation bar has clickable links, but you want to make the links inoperable, run nav.disable().

nav.enable()

Calling nav.enable() will undo the effect of calling nav.disable().

nav.enabled()

To test whether clickable links in the navigation bar are currently enabled or disabled, call nav.enabled(). True will be returned unless the navigation bar had been disabled with nav.disable().

Functions for managing global variables

If you try writing your own functions, you will learn that functions do not have access to all of the variables in your interview. Functions only know the variables you pass to them.

If your functions need to know background information about the interview, but you do not want to have to pass a lot of variables to every function you call, you can use “global” variables.

You set “global” variables in docassemble by calling set_info() and you retrieve them by calling get_info(). Note that docassemble will forget the values of these variables every time the screen loads, so you will have to make sure they are set by setting them in initial code, which runs every time the screen loads.

set_info()

This function is used to store information for later retrieval by get_info(). You pass it one or more keyword arguments:

---
initial: True
code: |
  set_info(interview_type='standard')
---

Some of the functions and methods will behave differently depending on who the interviewee is and what the interviewee’s role is. For example, if trustee is an object of the class Individual, and you call trustee.do_question('have'), the result will be “do you have” if if the interviewee is the trustee, but otherwise the result will be “does Fred Jones have” (or whatever the trustee’s name is).

In order for docassemble to know this background information, you need to include an initial code block (or a default role block containing code) that:

Defines user as an object of the class Individual;
Defines role as a text value (e.g., 'advocate'); and
Calls set_info(user=user, role=role).

For example, this is how basic-questions.yml does it:

---
objects:
  - client: Individual
  - advocate: Individual
  # etc.
---
default role: client
code: |
  if user_logged_in() and user_has_privilege('advocate'):
    user = advocate
    role = 'advocate'
  else:
    user = client
    role = 'client'
  set_info(user=user, role=role)
---

(See initial blocks for an explanation of objects and default role. See the roles section for an explanation of how user roles work in docassemble.)

get_info()

This function is used to retrieve information passed to set_info().

For example, if you passed interview_type as a keyword argument to set_info(), you can retrieve the value in your Python module by doing:

from docassemble.base.util import *

class Recipe(DAObject):
    def difficulty_level(self):
        if get_info('interview_type') == 'standard':
            #etc.

If the item was never set, get_info() will return None.

interface()

The interface() function returns 'web' if the user is accessing the interview through a web browser and 'sms' if the user is using SMS. If the web interface is used, but &json=1 is added to the URL, then interface() will return 'json'. If the API is being used, interface() will return 'api'.

question: |
  You are using the ${ interface() }
  interface.
mandatory: True

Sometimes interviews are accessed by background processes. interface() will return 'cron' if the interview is being accessed by a scheduled task, and will return 'worker' if it is being accessed by a background process.

You might want to use this function to provide special instructions to users depending on the way they access the interview. For example, the following will show a special instruction screen to users who are accessing the interview through SMS.

---
mandatory: True
code: |
  if interface() == 'sms':
    sms_instructions
---
question: |
  Instructions
subquestion: |
  To leave the interview, type exit.
field: sms_instructions
---

You can also use interface() to distinguish between actual user requests and requests that originate from background processes.

---
code: |
  request_counter = 0
---
initial: True
code: |
  if interface() in ['sms', 'web']:
    request_counter += 1
---

user_logged_in()

The user_logged_in() function returns True if the user is logged in, and otherwise returns False.

You can use this function to ensure that the user is logged in before the user can finish your interview:

mandatory: True
code: |
  favorite_fruit
  ok_to_finish
  final_screen
---
question: |
  What is your favorite fruit?
fields:
  - Fruit: favorite_fruit
---
code: |
  if not user_logged_in():
    require_login_screen
  ok_to_finish = True
---
event: require_login_screen
question: |
  You need to log in to finish this interview.
buttons:
  - Log in: leave
    url: ${ url_of('login', next=interview_url()) }

This function uses the url_of() function and the interview_url() function. The next parameter is set to a URL for the session. The URL returned by interview_url() takes the user back to the original session.

user_privileges()

The user_privileges() function returns the user’s privileges as a list. If the user is not logged in, the result is ['user']. If the user is a “user” as well as a “customer,” the result is ['user', 'customer']. If the interview is running a scheduled task, the result is ['cron'].

user_has_privilege()

The user_has_privilege() function returns True if the user has any of the given privileges, and False otherwise. For example, if the user has the privilege of “customer,” user_has_privilege('customer') will return True. A list can also be provided, in which case True will be returned if the user has any of the given privileges. For example, if the user has the privilege of “developer”, user_has_privilege(['developer', 'admin']) will return True.

current_context()

The current_context() function will return an object with the following attributes describing information about the context in which Python code is executing:

session the session ID of the current interview session
filename the filename of the current interview session
package the package of the current filename
question_id the id of the current question, or None if there is no current question or the question does not have an id.
current_filename the filename of the currently executing block
current_package the package of the filename of the currently executing block
variable the name of the last variable to be sought, or None if there was no variable being sought.
current_section the name of the current section, as determined by the section modifier of the latest question docassemble tried to process. In most situations, you will want to use nav.get_section() instead. The current_section is useful if your Python code needs to know the section modifier of the question that docassemble is currently trying to display (which might not be the same question that ultimately is displayed).
inside_of the document assembly context, if any. The possible values are 'standard', 'docx', 'pdf', 'pandoc', 'raw', 'md', and 'html'. The default context is 'standard'; the other contexts are in effect if code is executing to assemble a file using the docx template file, pdf template file, Pandoc document assembly system, raw text file assembly, creation of a Markdown file, or creation of an HTML version of a Markdown file (typically used with the Pandoc document assembly system as an HTML preview of the output).

user_info()

The user_info() function will return an object with the following attributes describing the current user:

id the integer ID of the user, which is used in the API and appears in the URLs of Playground files.
first_name
last_name
email
country (will be an official ISO 3166-1 alpha-2 country code like US)
subdivision_first (e.g., state)
subdivision_second (e.g., county)
subdivision_third (e.g., municipality)
organization (e.g., company or non-profit organization)
language the user’s language, if set (an ISO-639-1 or ISO-639-3 code)
timezone the user’s time zone, in a format like America/New_York

All of these attributes are set by the user on the Profile page. They can also be set by the set_user_info() function.

For example:

---
question: |
  Your e-mail address is ${ user_info().email }. Is that
  the best way to reach you?
yesno: email_is_best
---

If the user is not logged in, the first name will be 'Anonymous', the last name will be 'User', and the other attributes will be None.

set_save_status()

The set_save_status() function is useful in code that replies to actions. By default, running an action will create a new step in the interview history (which the user can undo by clicking the Back button). However, sometimes this can be a source of confusion. When the user undoes something, the user will expect to see something different; but if you are using actions, undoing an action might not change anything visibly on the screen. You can use set_save_status() to tell the interview to save the result of the action, but not create a new step. Or, if you want to run a “read only” action that does not change the interview answers at all, you can use set_save_status() for that. This can be useful for actions that return a JSON response.

The function takes one of three parameters:

set_save_status('new') - the changes made during the processing of the interview logic are saved, and a new step is created in the interview history. This is the default.
set_save_status('overwrite') - the changes made during the processing of the interview logic are saved, but the current step is overwritten.
set_save_status('ignore') - the changes made during the processing of the interview logic are not saved.

set_parts()

The set_parts() function allows you to configure text on various parts of the screen, which is displayed in the “My Interviews” list and in the navigation bar. It is also used to set certain interview-level default values.

It accepts any of the following optional keyword arguments:

title - this is the main title of the interview. It should be plain text. It is displayed in the navigation bar if there is no logo.
logo - this can be used for raw HTML that you want to go into the navigation bar in place of the plain text title of the interview. If you include an image, you should size it to be about 20 pixels in height.
short_logo - If you include a logo that is much wider than 100 pixels, you should also specify a short logo that is not as wide, so your navigation bar will look good on small screens.
short - for the mobile-friendly version of the interview title, which is displayed in the navigation bar when the screen is small.
short_title does the same thing as short.
subtitle - for the subtitle of the interview, which is displayed in the “Interviews” list. The subtitle is not visible on the screen of the interview itself.
tab - for the HTML title of the web page. This is typically displayed in the browser tab.
tab_title does the same thing as tab.
exit_link - can be set to 'exit' or 'leave' in order to control the behavior of the “Exit” menu option, which is displayed when show login is False. If set to 'exit', then clicking “Exit” will delete the user’s answers. If set to 'leave', the user’s answers will not be deleted. The default behavior is 'exit'.
exit_label - can be used to change the appearance of the “Exit” menu option.
pre - can be set to HTML that will be inserted before the question part of a screen.
submit - can be set to HTML that will be inserted before the buttons.
continue_button_label - will change the text in the Continue button.
resume_button_label - will change the text in the Resume button on review screens.
back button label - will change the text of the back button that appears inside
help_label - will change the default label of the help tab and the help button
under - can be set to HTML that will be inserted after the buttons.
right - can be set to HTML that will be inserted to the right of the question, or below the under content on small screens.
post - can be set to HTML that will be inserted at the bottom of the screen, after the buttons.
date format - this can be set to a default date format string used by the format_date() function and the .format_date() method of the DADateTime object (which is called when a DADateTime object is reduced to text).
datetime format - this can be set to a default date/time format string used by the format_datetime() function and the .format_datetime() method of the DADateTime object.
time format - this can be set to a default time format string used by the format_time() function and the .format_time() method of the DADateTime object.

In the following interview, note that the screen parts that were initially set by metadata are overridden when set_parts() is run.

metadata:
  title: Set the interview title
  short title: Title
  tab title: The Title
  subtitle: The subtitle
  pre: The pre text
  submit: The submit text
  post: The post text
---
question: |
  What is your favorite fruit?
subquestion: |
  Note the interview titles.
fields:
  Fruit: favorite_fruit
---
mandatory: True
code: |
  favorite_fruit = noun_plural(favorite_fruit)
  favorite_fruit = capitalize(favorite_fruit)
---
mandatory: True
code: |
  set_parts(
    title=favorite_fruit + " rule",
    short="I'm Tiny!",
    tab="TabTab",
    subtitle="a fruit interview",
    pre="This is about fruit",
    submit="Get ready for some buttons",
    post=DAStaticFile(filename="endmatter.html").slurp())

The following example shows how you can use a DAStaticFile to display a logo from your “static” folder in the navigation bar.

objects:
  - company_logo: DAStaticFile.using(filename='example-inc.svg')
---
mandatory: True
code: |
  set_parts(title='Example Inc.', logo='<img src="' + company_logo.url_for() + '" style="height: 20px; width: 157px;">')

For information about other ways to set defaults for different parts of the screens during interviews, see the screen parts section.

session_tags()

Every interview and interview session can be “tagged” with “tags.” If you include a tags specifier in your interview’s metadata, and the tags specifier is a list, then you will define the tags for the interview itself. These tags can be seen on the list of available interviews that can be started (/list) and on the list of saved interviews that can be resumed (/interviews).

The tags associated with an interview session can be edited using Python code. The function session_tags() returns a Python set representing the tags. It isn’t technically a Python set, but it works just like one, and it allows you to read and write the tags associated with the interview session.

metadata:
  tags:
    - apples
    - oranges
---
mandatory: True
question: Tags
subquestion: |
  The tags are:

  % for tag in session_tags():
  * ${ tag }
  % endfor

  Check your
  [interview list](${ url_of('interviews') })
  to see these tags.
field: first_screen_done
---
mandatory: True
code: |
  session_tags().add('grapes')
---
mandatory: True
question: Tags
subquestion: |
  The tags are:

  % for tag in session_tags():
  * ${ tag }
  % endfor

  Check your
  [interview list](${ url_of('interviews') })
  to see how these tags
  have changed.

set_status()

The set_status() function allows you to configure global settings for the interview session. You give it keyword arguments for one or more settings, and it will save the values for the session.

Currently, there is only one setting available, variable_access, which turns off the get_interview_variables() feature on a production server. By default, the get_interview_variables() function can be called from JavaScript and all of the variables in the interview answers will be returned in JSON format. While this function is useful for many applications, it also poses a risk of revealing confidential information, particularly in multi-user interviews where users should not be able to find out other users’ answers. Setting variable_access to False with set_status() will disable this feature.

mandatory: True
code: |
  set_status(variable_access=False)

However, if your server is a development server (the debug directive in the Configuration is set to True), then this has no effect.

get_status()

If you set a value using set_status(), you can retrieve the value using get_status(). For example:

field: variable_access_shown
question: |
  % if get_status('variable_access') is False:
  The `get_interview_variables()` function is
  disabled.
  % else:
  The `get_interview_variables()` function is
  enabled.
  % endif

If a setting has not been set, the function returns None.

update_terms()

The update_terms() function allows you to define or override interview-wide terms or auto terms using Python code.

terms:
  - creeper: |
      A tall green creature that explodes if
      you get too close.
  - zombie pigman: |
      A harmless creature who carries a gold
      sword.
---
mandatory: True
code: |
  update_terms({'zombie pigman': 'A nether dweller', 'nether': 'The underworld'})

update_terms() has one required parameter, a Python dictionary that maps terms to definitions. It also accepts two optional keyword parameters:

auto: whether to update auto terms or terms. Set to True for auto terms. The default behavior of update_terms() is to update the interview-wide terms, not the interview-wide auto terms.
language: the language to update. For example, to update the French translations of terms, set language to fr. If you leave language unset, the terms you will update are the terms associated with the default language *. If your interview uses a default language initial block or uses the language modifier, you should set a specific language when you call update_terms().

Functions for determining information about the browser

language_from_browser()

The language_from_browser() function returns a language code representing the preferred language of the user. Most browsers allow users to select one or more preferred languages. These languages are transmitted to web sites using the Accept-Language header. The language_from_browser() function reads this header and extracts the language from it.

The code will be in ISO-639-1, ISO-639-2, or ISO-639-3 format and will be in lower case. If multiple languages are listed in the Accept-Language header, the first recogized language will be returned.

question: |
  I think your language code is
  `${ language_from_browser() }`.
mandatory: True

Screenshot of language_from_browser example

That this function will return None if the interface() is sms, if the Accept-Language header is missing, or if no valid ISO-639-1, ISO-639-2, or ISO-639-3 code can be found in the Accept-Language header.

Optionally, you can call language_from_browser() with arguments, where the arguments are valid languages. The first valid language will be returned. If none of the languages in the Accept-Language header is in the list, None will be returned.

question: |
  % if language_from_browser('es', 'fr') is None:
  I guess you do not speak
  Spanish or French.
  % else:
  Great!  Your language code is
  `${ language_from_browser('es', 'fr') }`.
  % endif
mandatory: True

Screenshot of language_from_browser_restricted example

device()

The device() function returns an object containing information about the user’s browser, derived from the User-Agent header.

question: |
  % if device().is_mobile:
  You are on a phone.
  % elif device().is_tablet:
  You are on a tablet.
  % elif device().is_pc:
  You are on a PC.
  % elif device().is_bot:
  You are a bot.
  % else:
  Your device is: ${ device() }.
  % endif
subquestion: |
  % if device().is_touch_capable:
  You are using a touchscreen device.
  % else:
  You are not using a touchscreen device.
  % endif
mandatory: True

For more information about the properties of this object, see the documentation for the user-agents library.

If docassemble cannot determine information about the user’s browser, this function will return None.

You can also use this function to obtain the user’s IP address. If you call the function using device(ip=True), the IP address is returned:

question: |
  Your IP address is
  ${ device(ip=True) }.
mandatory: True

Language and locale functions()

These functions access and change the active language and locale. See language support for more information about these features.

get_language()

If the language is set to English, get_language() returns en.

set_language()

This sets the language that will be used in the web application and in language-specific functions of docassemble. It does not change the active Python locale. See update_locale() for information on changing the Python locale.

If you need to set the language to something other than the language set in the configuration, you need to call set_language() within initial code. For example:

initial: True
code: |
  set_language(user_language)
---
question: |
  What language do you speak? (¿Qué idioma habla?)
field: user_language
choices:
  - English: en
  - Español: es
---

The value given to set_language() must be a lowercase ISO-639-1 or ISO-639-3 code. For example in ISO-639-1, Spanish is es, French is fr, and Arabic is ar.

Using the optional dialect and voice keyword arguments, you can also set the dialect and/or voice of the language that should be used for the text-to-speech engine. For example:

---
initial: True
code: |
  set_language('en', dialect='au', voice='Zoe')
---

This will set the language to English, and will instruct the text-to-speech engine to use an Australian dialect with the voice of “Zoe.” (The dialect is relevant only for the text-to-speech engine, which is controlled by the special variable speak_text.) The default values are controlled by the VoiceRSS Configuration.

For more information about languages in docassemble, see language support.

If your interview uses actions, and your actions need to know what language to use, you will need to manually include process_action() in an initial block, as follows:

initial: True
code: |
  set_language(user_language)
  process_action()

By default, process_action() is called automatically, prior to the execution of any mandatory or initial blocks. However, in cases where your actions have a prerequisite, you need to indicate exactly where in the interview logic actions should be executed.

Note that in the above example, actions will not be able to be run until user_language is defined, so if your interview uses actions very early on in the interview, you may need to set a default value for user_language before asking the user what user_language should be.

language_name()

Given a ISO-639-1 or ISO-639-3 language code, such as 'en', 'de', 'eng', or 'deu', language_name() returns the name of the language, such as 'English' or 'German'. The database of languages comes from the pycountry package.

The language name is passed through the word() function, so that you can use the words system to provide translations from English representations of a language name into other languages. Language names are not listed by default in the system phrase translation file because there are 7,847 of them, so you will need to add them manually.

If the language cannot be found, the language code is returned, also passed through word().

get_dialect()

Returns the current dialect, as set by the dialect keyword argument to the set_language() function.

get_country()

Returns the current country as a two-digit ISO 3166-1 alpha-2 country code. The default country is 'US', unless a different default is set using the country configuration setting.

set_country()

Sets the current country. Expects a two-digit, uppercase country code (ISO 3166-1 alpha-2 format) such as 'US', 'GB', or 'DE'.

set_locale()

If you run set_locale('FR.utf8'), then get_locale() will return FR.utf8. The only effect is to remember the value; there are no side effects.

The actual Python locale will not change unless you run update_locale(), which will use the value you set with set_locale('FR.utf8').

The information you set with set_locale(), like the language you set with set_language(), is only remembered for the duration of a page load. Thus, you can use set_locale() and get_locale(), without update_locale(), for your own purposes, as a way of passing a locale identifier to custom functions and methods without having to pass the locale identifier as an argument or setting an object attribute.

A second use of set_locale() is to set a default currency symbol for use in an interview session, if the default currency symbol associated with the locale is not appropriate. To indicate what currency symbol should be used, you can call set_locale() with a currency_symbol keyword parameter. You need to call this in an initial block, in much the same way as you use set_language() to indicate what language to use.

---
initial: True
code: |
  if user.address.country == 'US':
    set_locale(currency_symbol='$')
  else:
    set_locale(currency_symbol='€')

It is important that an initial code block is used, because the code needs to run every time the screen loads.

If you want to undo the effect of set_locale() with a currency_symbol, call set_locale(currency_symbol=None) and the default behavior will be used instead.

Other locale conventions can be overridden by passing keyword parameters to set_locale(). The conventions that docassemble uses are currency_symbol, n_cs_precedes, p_cs_precedes, n_sep_by_space, p_sep_by_space, thousands_sep, mon_thousands_sep, decimal_point, and mon_decimal_point. Any locale convention you set with set_locale() can be retrieved with get_locale(). Note that these overrides do not affect the behavior of the locale Python package.

Another way to change the currency symbol that users see is to set the currency symbol field specifier on the datatype: currency fields you use to collect currency values. You can also provide a symbol keyword parameter to the currency() function.

get_locale()

If the locale is set to US.utf8, get_locale() returns US.utf8.

Given an argument, get_locale() returns a characteristic of the current locale To obtain the currency symbol, call get_locale('currency_symbol'). This will return None if there is no currency symbol set.

update_locale()

Running update_locale will change the Python locale based on the current language and locale settings.

For example, if you run:

import docassemble.base.util
docassemble.base.util.set_language('fr')
docassemble.base.util.set_locale('FR.utf8')
docassemble.base.util.update_locale()

then the Python locale will be changed to fr_FR.utf8.

Running update_locale() is necessary in order to affect the behavior of functions like currency() and currency_symbol().

Note that changes to the locale are not thread-safe. This means that there is a risk that between the time docassemble runs update_locale() and the time it runs currency_symbol(), another user on the same server may cause docassemble to run update_locale() and change it to the wrong setting.

If you want to host different interviews that use different locale settings on the same server (e.g., to format a numbers as 1,000,000 in one interview, but 1.000.000 in another), you will need to make sure you run the docassemble web server in a multi-process, single-thread configuration. (See installation for instructions on how to do that.) Then you would need to begin each interview with initial code such as:

---
initial: True
code: |
  import docassemble.base.util
  docassemble.base.util.set_language('fr')
  docassemble.base.util.set_locale('FR.utf8')
  docassemble.base.util.update_locale()
---

Access time functions

Internally, docassemble keeps track of the last time the interview session was accessed. The following functions retrieve information about access times. These functions are particularly useful in scheduled tasks.

start_time()

start_time() returns a DADateTime object representing the time the interview session was started.

The time is expressed in the UTC time zone. If you would like to localize the time to a particular time zone, you can set the optional keyword parameter timezone (e.g., to 'America/New_York').

last_access_time()

last_access_time() returns a DADateTime object containing the last time the interview session was accessed by a user other than the special cron user.

The time is expressed in the UTC time zone. (Note: before version 0.2.27, the object returned was a UTC datetime without a time zone; as of 0.2.27, the object returned is UTC with a time zone). If you would like to localize the time to a particular time zone, you can set the optional keyword parameter timezone (e.g., to 'America/New_York').

Optionally, a privilege name or a list of privilege names can be provided. In this case, the function will return the latest access time by any user holding one of the privileges.

last_access_time('client'): returns the last time a user with the privilege of client accessed the interview session.
last_access_time('advocate'): returns the last time a user with the privilege of advocate accessed the interview session.
last_access_time(['advocate', 'admin']): returns the last time a user with the privilege of advocate or admin accessed the interview session.

The first argument can also be written as a keyword parameter include_privileges:

last_access_time(include_privileges='client'): same as last_access_time('client').

By default, last_access_time() will ignore session access by the cron user. However, if you do not wish to ignore access by the cron user, you can call last_access_time() with the optional keyword argument include_cron equal to True:

last_access_time(include_cron=True): returns the last time any user, including the cron user if applicable, accessed the session.

You can also provide a list of privileges you want the method to ignore, using the exclude_privileges keyword parameter. This can be useful because users can have multiple privileges.

last_access_time(include_privileges='advocate', exclude_privileges=['developer']): returns the last time a user who is an advocate but not a developer accessed the interview.

The last_access_time() function takes an optional keyword argument timezone. If timezone is provided (e.g., timezone='America/New_York'), the DADateTime object will be expressed in the given time zone.

last_access_days()

The function last_access_days() works just like last_access_time(), except that it returns the number of days (including fractional days) between the current time and the last access time.

last_access_hours()

Like last_access_days(), except returns hours.

last_access_minutes()

Like last_access_days(), except returns minutes.

last_access_delta()

The function last_access_delta() works just like last_access_time(), except that it returns a datetime.timedelta object giving the difference between the current time and the last access time.

returning_user()

The function returning_user() returns True if the user has not accessed the interview session in at least six hours, and otherwise returns False. To use a different time limit, you can set one of the optional keyword arguments.

returning_user(minutes=5)
returning_user(hours=1)
returning_user(days=30)

Functions for working with dates and times

month_of(), day_of(), year_of(), and dow_of()

These functions read a date and provide the parts of the date.

mandatory: True
question: |
  The date ${ some_date }, explained.
subquestion: |
  The year is ${ year_of(some_date) }.

  The month is ${ month_of(some_date) }.

  The month as a word is
  ${ month_of(some_date, as_word=True) }.

  The day of month is
  ${ day_of(some_date) }.

  The day of week is
  ${ dow_of(some_date) }.

  The day of week as a word is
  ${ dow_of(some_date, as_word=True) }.

The month_of() and dow_of() functions have an optional setting: if called with the optional parameter as_word=True, they will return the result as a word (according to the current language and locale) rather than as a number.

format_date()

The format_date() function takes as input a date and returns the date formatted appropriately for the current language. It can be given a piece of text containing a time, a DADateTime object, a datetime.datetime object, or a datetime.time object.

For example:

format_date(today()) returns the current date, formatted like January 1, 2018.
format_date("10/31/2016") returns October 31, 2016.
format_date("2016-04-01") returns April 1, 2016.
format_date('April 5, 2014') returns April 5, 2014.
format_date('April 5, 2014', format='long') returns April 5, 2014.
format_date('April 5, 2014', format='full') returns Saturday, April 5, 2014.
format_date('April 5, 2014', format='EEEE') returns Saturday.
format_date('April 5, 2014', format='yyyy') returns 2014.
format_date('April 5, 2014', format='yy') returns 14.
format_date('April 5, 2014', format='MMMM') returns April.
format_date('April 5, 2014', format='MMM') returns Apr.
format_date('April 5, 2014', format='d') returns 5.
format_date('April 5, 2014', format='dd') returns 05.
format_date('April 5, 2014', format='E') returns Sat.
format_date('April 5, 2014', format='e') returns 6 (numbers range from 1 to 7).
format_date('April 5, 2014', format='EEEE, MMMM d, yyyy') returns Saturday, April 5, 2014.
format_date('April 5, 2014', format='short') returns 4/5/14.
format_date('April 5, 2014', format='M/d/yyyy') returns 4/5/2014.
format_date('April 5, 2014', format='MM/dd/yyyy') returns 04/05/2014.
format_date('April 5, 2014', format='yyyy-MM-dd') returns 2014-04-05.

The date formatting is provided by the babel.dates package, which has good support for language and locale variation. The format argument, is passed directly to the babel.dates.format_date() function.

The patterns used in date formatting by babel.dates.format_date() are based on Unicode Technical Standard #35.

If you do not provide a format argument, the default date format will be used. This default can be set in the interview metadata or overridden using set_parts(). If no default is set, 'long' is used.

The date formatting will be different depending on the current language. For example, if you run set_language('es'), then format_date('4/5/2014') returns 5 de abril de 2014. If you run set_language('fr'), then format_date('4/5/2014') returns 5 avril 2014.

format_time()

The format_time() function works just like format_date(), except it returns a time, rather than a date. It can be given a piece of text containing a time, a DADateTime object, a datetime.datetime object, or a datetime.time object.

For example:

format_time(current_datetime()) returns the current time, formatted like 12:00 AM.
format_time("04:01:23") returns 4:00 AM.
format_time("04:01:23", format='h') returns 4.
format_time("04:01:23", format='hh') returns 04.
format_time("04:01:23", format='m') returns 1.
format_time("04:01:23", format='mm') returns 01.
format_time("04:01:23", format='ss') returns 23.
format_time("04:01:23", format='a') returns AM.
format_time("04:01:23", format='z') returns EST, or whatever the current time zone is.
format_time("04:01:23", format='zzzz') returns Eastern Standard time, or whatever the current time zone is.
format_time("04:01:23", format='h:mm a') returns 4:01 AM.

The time formatting is provided by the babel.dates package.

The format argument is passed directly to the babel.dates.format_time() function. The patterns used in time formatting are based on Unicode Technical Standard #35.

If you do not provide a format argument, the default time format will be used. This default can be set in the interview metadata or overridden using set_parts(). If no default is set, 'short' is used.

format_datetime()

The format_datetime() function works like a combination of format_date() and format_time(). It is different only in that it allows date and time to be joined in the same output.

format_datetime('4/5/2014 07:30') returns April 5, 2014 at 07:30:00 AM EST.
format_datetime('4/5/2014 07:30', 'h:mm in MMMM') returns '7:30 in April'.

If you do not provide a format argument, the default datetime format will be used. This default can be set in the interview metadata or overridden using set_parts(). If no default is set, 'long' is used.

today()

question: |
  Today's date is ${ today() }.
mandatory: True

Returns a DADateTime object representing today’s date at midnight. It takes an optional keyword argument timezone, which refers to one of the time zone names in timezone_list() (e.g., 'America/New_York'). If the timezone is not supplied, the default time zone will be used.

Since the result is a DADateTime object, if today() is included in a Mako template, the result will be equivalent to calling format_date() on the object.

So this:

Today's date is ${ today() }.

becomes, for example:

Today’s date is August 1, 2018.

The fact that the object is a DADateTime object means you can use methods on it. For example, you can write things like Your term paper is due in a week, so make sure you give it to me by ${ today().plus(weeks=1) }!

The today() function also takes an optional keyword parameter format. If a format is provided, then today() returns text, not an object. So this:

Today's date is ${ today(format='M/d/YYYY') }.

becomes, for example:

Today’s date is 8/1/2018.

timezone_list()

question: |
  What is your time zone?
fields:
  - Time zone: user_timezone
    default: "America/New_York"
    code: |
      timezone_list()

The timezone_list() function returns a list of time zones that the other date-related functions in docassemble understand. The list is generated from the pytz module. The primary purpose of this function is to include in a multiple choice question.

Note that the items in this list are strings, like America/New_York.

get_default_timezone()

question: |
  The default time zone is
  ${ get_default_timezone() }.
mandatory: True

The get_default_timezone() function returns the default timezone (e.g., 'America/New_York'). This is the time zone of the server, unless the default timezone is set using the timezone configuration.

as_datetime()

question: |
  The Delorean will go back in time to 
  ${ as_datetime('11/5/1955').year }.
mandatory: True

The as_datetime() function expresses a date as a DADateTime object with a time zone. It takes an optional keyword argument, timezone, which will override the default time zone.

as_datetime('12/25/2018') returns midnight on Christmas.
as_datetime('12/25/2018 07:30 AM') returns 7:30 a.m. on Christmas.
as_datetime('07:30 AM') returns 7:30 a.m. on the current day.
as_datetime('07:30 AM', timezone='America/New_York') returns 7:30 a.m. on the east coast.

In combination with the .time() method of DADateTime, this function can be used to create objects of type datetime.time.

as_datetime('07:30 AM').time() returns a datetime.time object representing 7:30 a.m.

current_datetime()

question: |
  % if current_datetime() < as_datetime('October 14, 1066'):
  The Normans have not yet invaded
  England.
  % else:
  Unfortunately, the Normans have
  already invaded England.
  % endif
mandatory: True

The current_datetime() function returns the current date and time as a DADateTime object. It takes an optional keyword argument, timezone (e.g., 'America/New_York'), which will override the default time zone.

date_difference()

code: |
  birthday = as_datetime('5/17/2016')
  christmas = as_datetime('12/25/2016')
  interval = date_difference(starting=birthday, ending=christmas)
---
question: |
  The length of time between my
  birthday and Christmas can be
  described several ways.
subquestion: |
  * ${ interval.weeks } weeks
  * ${ interval.days } days
  * ${ interval.hours } hours
  * ${ interval.minutes } minutes
  * ${ interval.seconds } seconds
mandatory: True

The date_difference() function returns the difference between two dates as an object with attributes that express the difference using different units. The function takes two keyword arguments: starting and ending. If either is omitted, the current_datetime() is used in its place.

If you do date_difference(starting=a, ending=b), then if date a comes before date b, the resulting values will be positive. But if date b comes before date a, the values will be negative.

For example, if you set z = date_difference(starting='1/1/2025', ending='1/3/2025'), then:

z.years returns 0.005475814013977016.
z.weeks returns 0.2857142857142857.
z.days returns 2.0.
z.hours returns 48.0.
z.minutes returns 2880.0.
z.seconds returns 172800.
z.delta returns a datetime.timedelta object representing the difference between the times.

Dates without time zones are localized into the default time zone before the calculation takes place. You can supply the optional keyword argument timezone (e.g., 'America/New_York') to use a different time zone.

The object returned by date_difference() has a method .describe(). If you set z = date_difference(starting='1/1/2024', ending='4/3/2025'), then:

z.describe() returns one year, three months, and two days.
z.describe(capitalize=True) returns One year, three months, and two days.
z.describe(specificity='year') returns one year.
z.describe(specificity='month') returns one year and three months.
z.describe(nice=False) returns 1 year, 3 months, and 2 days

If you set z = date_difference(starting='1/1/2022 23:22:35', ending='4/3/2023 21:45:22'), then:

z.describe() returns one year, three months, and one day.
z.describe(specificity='second') returns one year, three months, one day, 22 hours, and 47 seconds.

If you set z = date_difference(starting='4/3/2025 20:45:22', ending='4/3/2025 23:22:35'), then:

z.describe() returns two hours
z.describe(specificity='minute') returns two hours and 37 minutes

If you set z = date_difference(starting='4/3/2025 21:45:22', ending='4/3/2025 23:22:35'), then:

z.describe() returns one hour and 37 minutes
z.describe(specificity='hour') returns one hour

If you set z = date_difference(starting='4/3/2025 22:45:22', ending='4/3/2025 23:22:35'), then:

z.describe() returns 37 minutes

If you set z = date_difference(starting='4/3/2025 23:22:22', ending='4/3/2025 23:22:35'), then:

z.describe() returns 13 seconds

If you reduce the result of date_difference() to text, this has the effect of running .describe() on the object.

date_interval()

question: |
  In three days, it will be
  ${ format_date( current_datetime() + date_interval(days=3) ) }.
mandatory: True

The date_interval() function can be used to perform calculations on a date. For example,

current_datetime() + date_interval(days=1) represents 24 hours in the future.
current_datetime() - date_interval(years=1) represents one year in the past.

The available keyword arguments are:

years
months
days
weeks
hours
minutes
seconds
microseconds

This function is a direct wrapper around dateutil.relativedelta.relativedelta.

Functions for working with phone numbers

The following functions help with mangaging phone numbers. They rely on the phonenumbers package in Python.

phone_number_in_e164()

The phone_number_in_e164() function takes a phone number and formats it into E.164 format. It takes an optional keyword argument country, which is expected to be a country abbreviation (ISO 3166-1 alpha-2 format, e.g., 'SE' for Sweden). (See the pycountry package for the list of codes.) The country code is used to determine the country code for the phone number. If country is not provided, the get_country() function is used to determine the applicable country.

phone_number_formatted()

The phone_number_formatted() function is use to rewrite a number in a standard phone number format according to national conventions. It works like phone_number_in_e164(), except that it returns the format in the national format for the country, rather than E.164.

phone_number_is_valid()

The phone_number_is_valid() function takes a phone number and returns True or False depending on whether the phone number is valid. It takes an optional keyword argument country that is used to determine the country whose phone number standards should be used to determine the validity of the phone number. The country must be expressed in ISO 3166-1 alpha-2 format. If country is not provided, the get_country() function is used to determine the applicable country.

phone_number_part()

The phone_number_part() function is use to extract individual parts of a phone number.

phone_number_part("555-212-5623", 0) returns '555'.
phone_number_part("555-212-5623", 1) returns '212'.
phone_number_part("555-212-5623", 2) returns '5623'.

The function takes an optional keyword argument country, a ISO 3166-1 alpha-2 country code, that is used to format the phone number according to the national conventions. If country is not provided, the get_country() function is used to determine the applicable country.

Functions for tracking tasks

These are helpful functions for keeping track of whether certain tasks have been performed. For example, if your interview logic sends an e-mail to the user about something, but you want to avoid sending the e-mail more than once, you can give the “task” a name and use these functions in your code to make sure your interview logic only sends the e-mail if it has never been successfuly sent before.

Instead of using these functions, you could use your own variables to keep track of whether tasks have been carried out or not. These functions do not do anything besides keep track of information. A good reason to use these functions is to increase the readability of your code.

task_performed()

The task_performed() function returns True if the task has been performed at least once, otherwise False.

For example, task_performed('application_for_assistance') will return False until mark_task_as_performed('application_for_assistance') is called.

task_not_yet_performed()

The task_not_yet_performed() function returns True if the task has never been performed, otherwise False. It is simply the opposite of task_performed().

mark_task_as_performed()

The mark_task_as_performed() function increases by 1 the number of times the task has been performed.

For example, if task_performed('send_reminder') is False, and then you call mark_task_as_performed('remind_user'), then task_performed('send_reminder') will now return True, and times_task_performed('remind_user') will return 1.

If you call mark_task_as_performed('remind_user') again, task_performed('send_reminder') will still return True, and times_task_performed('remind_user') will now return 2.

times_task_performed()

The times_task_performed() function returns the number of times the task has been performed (i.e., the number of times mark_task_as_performed() is called). If the task has never been performed, 0 is returned.

set_task_counter()

The set_task_counter() function allows you to manually set the number of times the task has been performed. set_task_counter('remind_user', 0) sets the counter of the remind_user task to zero, which means that task_performed('remind_user') would subsequently return False.

Persistent task results

The above functions for tracking “tasks” store data in the interview answers. When the user presses the “Back” button to undo the results of answering questions, the record of a task being completed will also be undone. Thus, if the user goes back and changes a variable on which the task depends, the task will be re-run. If you do not want a task to be re-run, you can set the optional keyword parameter persistent on your functions.

The example below demonstrates how this works; after the user answers the favorite_fruit question, the task is marked as completed, but if the user clicks the “Back” button, the fact that the the task was completed will “persist.” Without persistent=True, the memory of the task completion would be forgotten along with the value of favorite_fruit.

default screen parts:
  under: |
    % if task_performed('fruit_gathered', persistent=True):
    The task has been performed.
    % else:
    The task has not been performed.
    % endif
---
mandatory: True
code: |
  favorite_fruit
  mark_task_as_performed('fruit_gathered', persistent=True)
  final_screen
---
question: |
  What is your favorite fruit?
subquestion: |
  Note whether the task has been 
  performed yet.
fields:
  - Fruit: favorite_fruit
---
event: final_screen
question: |
  You like ${ favorite_fruit }
subquestion: |
  Press the Back button and 
  then notice whether the task 
  has been performed.

When persistent is true, the task functions use a DAStore instead of the interview answers to store information about whether tasks have been completed. Specifically, the functions use a DAStore with a base of 'session' within that DAStore, they use a value called tasks. If you set persistent to something other than True, the DAStore will use this value as the base. Thus, if you call mark_task_as_performed('fruit_gathered', persistent='interview'), then the result of task completion will apply across all sessions in the same interview. If you set persistent to 'user', the results will apply across all sessions of the user. If you set persistent to 'global', the results will apply across all sessions of the server.

Tracking reasoning

It may be important that the logic of your interview be explainable. There are many ways to write your interviews in such a way you can explain to the user the reasoning you are applying, and there is no one right way to do this; nor is there a way that this process can be feasibly automated.

The functions in this subsection may be of use for explaining reasoning. They allow you to write “comment”-like phrases in your code that are saved into a list as the user goes through the interview. Then you can present the user with the list of phrases.

Here is an illustrative example:

modules:
  - .somefuncs
---
mandatory: True
code: |
  clear_explanations()
  if favorite_fruit in ('apple', 'orange'):
    explain("You said your favorite fruit was " + favorite_fruit + ".")
    if wrong_vegetable(favorite_vegetable):
      explain("Because your favorite vegetable is disgusting, you are not eligible for the space program.")
      eligible = False
    else:
      explain("Since you like apple or orange, and turnips are not your favorite, you are mentally fit to go to the moon.")
      eligible = True
  else:
    explain("Since you do not like apple or orange, you are not eligible for the space program.")
    eligible = False
  final_screen
---
event: final_screen
question: |
  % if eligible:
  You will be joining the Apollo mission.
  % else:
  You are not allowed to enter the space program.
  % endif
subquestion: |
  Reasoning:

  % for reason in logic_explanation():
  * ${ reason }
  % endfor

The contents of the referenced module, somefuncs.py, are:

from docassemble.base.util import explain

__all__ = ['wrong_vegetable']

def wrong_vegetable(vegetable):
    if vegetable == 'turnip':
        explain("You also said your favorite vegetable was turnip.")
        return True
    else:
        explain("You also said your favorite vegetable was " + vegetable + ".")
        return False

Note that even though the call to explain takes place in a module, and even though it references no variables in your interview answers, the phrase is tracked in the list of explanations.

explain()

The explain() function stores a phrase in the list of explanations. If the same phrase, verbatim, already exists in the list, the phrase is not added.

The explain() function takes an optional keyword argument, category. This allows you to keep track of more than one list of explanations. By default, the category is 'default'. The two category names that are reserved are 'default' and 'all'.

clear_explanations()

The clear_explanations() function resets the explanation list. It takes an optional keyword argument category, which resets the given list. If you set category to 'all', every list is reset.

It is a good idea to call clear_explanations() every time the screen loads. If your users can edit their answers, then reasoning that has been made obsolete by changes to the variables may persist in the explanations list. Clearing the history and running through all of the logic every time the screen loads will help make sure that the explanations are corrected.

logic_explanation()

The logic_explanation() function returns the explanation list as a Python list. If the list does not exist, an empty list is returned. This function takes an optional keyword argument category, which indicates the category of explanation list you would like to be returned.

Simple translation of words

word()

word() is a general-purpose translation function that is used in the code of the web application to ensure that the text the user sees is translated into the user’s language. It is also available for use inside interviews. It is not the only mechanism for translating your interviews into different languages, but it is one of the essential components of language support in docassemble.

Suppose the following words directive appears in the Configuration.

words:
  - docassemble.missouri:data/sources/words.yml

Suppose that the words.yml file contains the following:

es:
  "fish": "pez"
  "cow": "vaca"

Suppose further that your interview has an initialcode block that sets the language to 'en' or 'es':

initial: True
code: |
  set_language(user_language)
---
question: |
  Please select your language.
field: user_language
choices:
  - English: en
  - Español: es

Finally, suppose that the user selected “Español” as their language.

Thereafter, if code in your interview runs word("cow"), the returned value will be 'vaca'. However, if the user had selected “English” as their language, the returned value would have been 'cow'.

When you call word("cow"), the word() function looks through all the data in the YAML files listed under words and checks to see if there is an entry for the phrase cow under the current language (which is controlled by set_language() and get_language()). If, among the key/value pairs listed under the language in question, there is a key matching the word 'cow', the corresponding value is returned.

In addition to using the words directive in the Configuration, you can a Python module to change the translations. The function docassemble.base.util.update_word_collection() takes a language and a Python dictionary as parameters and updates the translation tables, which are kept in memory.

import docassemble.base.util
definitions = {'Continue': 'Continuar', 'Help': 'Ayuda'}
docassemble.base.util.update_word_collection('es', definitions)

Since this function is not thread-safe, you should only run it from code that runs when the module loads.

Language-specific functions

These functions behave differently according to the language and locale. You can write functions for different languages, or reprogram the default functions, by using import docassemble.base.util and then running docassemble.base.util.update_language_function().

For example, suppose you had a Spanish linguistic package that you wanted to use for writing possessives. You could include the following in a Python module that you include in your interview:

import docassemble.base.util
from special.spanish.package import spanish_possessify

def possessify_es(a, b, **kwargs):
    return spanish_possessify(a, b)

docassemble.base.util.update_language_function('es', 'possessify', possessify_es)

This means that whenever the current language is Spanish, the function possessify_es should be substituted for the default function. The first argument is the name of the language, the second argument is the name of the standard language function, and the third argument is a reference to your function.

If you want to override the default function, use '*' as the language. This will be used if no language-specific function exists.

If you want to create a new language function that does not already exist in docassemble, you can use the language_function_constructor() function from docassemble.base.util.

import docassemble.base.util

__all__ = ['closing']

closing = docassemble.base.util.language_function_constructor('closing')

def closing_default(indiv, **kwargs):
    return "Goodbye, " + indiv.name.first + "!"

def closing_fr(indiv, **kwargs):
    return "Au revoir, " + indiv.name.first + "."

docassemble.base.util.update_language_function('*', 'closing', closing_default)
docassemble.base.util.update_language_function('fr', 'closing', closing_fr)

When writing a language function, do not use named keyword parameters. Instead, using **kwargs so that the function accepts any combination of keyword parameters. This is necessary because language functions can be called with an optional parameter language, which forces the use of a language other than the default language. It is also helpful so that other developers can extend your language function. For example, suppose someone wants to add a Japanese version of closing(), but in Japanese there are formal and informal ways of saying goodbye. In interviews, the developer will want to write things like closing(client, formal=False) or closing(judge, formal=True) to use these different forms. The developer would create a module that imports your module. Then they would write a function called closing_ja and call docassemble.base.util.update_language_function('ja', 'closing', closing_ja). Unless **kwargs is used, the keyword parameter formal would trigger an error when used outside of a Japanese context.

Note that updates to language functions are not thread-safe; they have a server-wide effect. update_language_function() needs to be called in main body of a module so that it has an effect on all threads. The code needs to run when the server starts and loads modules. Module files are only loaded when the server starts if 1) they contain a class definition; 2) they contain the literal text docassemble.base.util.update somewhere; or 3) they contain a line that starts with # pre-load. Therefore, if your module runs from docassemble.base.util import update_language_function, then you need to include a line that starts with # pre-load.

Listed below are some of the existing language functions that can be customized.

capitalize()

question: |
  ${ capitalize(color) } is your
  favorite color, but ${ color } is
  not your favorite color of eggs.
sets: all_done

If favorite_food is defined as “spaghetti marinara,” then capitalize(favorite_food) will return Spaghetti marinara. This is often used when a variable value begins a sentence. For example:

question: |
  ${ capitalize(favorite_food) } is being served for dinner. Will you
  eat it?
yesno: user_will_eat_dinner

There is also the title_case() function, which is described below.

comma_and_list()

If things is a Python list with the elements ['lions', 'tigers', 'bears'], then:

comma_and_list(things) returns lions, tigers, and bears.
comma_and_list(things, oxford=False) returns lions, tigers and bears.
comma_and_list('fish', 'toads', 'frogs') returns fish, toads, and frogs.
comma_and_list('fish', 'toads') returns fish and toads
comma_and_list('fish') returns fish.
comma_and_list('fish', 'toads', 'frogs', and_string='or') returns fish, toads, or frogs.
comma_and_list('fish', 'toads', 'frogs', comma_string='; ') returns fish; toads; and frogs.
comma_and_list('fish', 'toads', 'frogs', before_and='---') returns fish; toads;---and frogs.
comma_and_list('fish', 'toads', 'frogs', after_and=' (last but not least) ') returns fish, toads, and (last but not least) frogs.

comma_list()

If things is a Python list with the elements ['lions', 'tigers', 'bears'], then:

comma_list(things) returns lions, tigers, bears.
comma_list(things, comma_string='; ') returns lions; tigers; bears.
comma_list('fish', 'toads', 'frogs') returns fish, toads, and frogs.
comma_list('fish') returns fish.

add_separators()

The add_separators() functions takes a list as input and returns a list in which each item is reduced to text, a period is appended to the last item, ; and is appended to the penultimate item, and ; is appended to all other items.

mandatory: True
question: |
  Fruits
subquestion: |
  You like:
    
  % for item in add_separators(fruit):
  * ${ item }
  % endfor
attachment:
  docx template file: add-separators.docx
buttons:
  - Try another: restart

add_separators() takes three optional keyword parameters:

separator: default is ';'
last_separator: default is '; and'
end_mark: default is '.'

The function is also available as a Jinja2 filter called add_separators. In the above example, the add-separators.docx file contains:

You like:
{%p for item in fruit | add_separators %}
1. {{ item }}
{%p endfor %}

currency()

If the locale is US.utf8, currency(45.2) returns $45.20.

question: |
  If you sold ${ number } fish for
  a dollar each, you would get
  ${ currency(number) }.
mandatory: True

currency(45) returns $45.00, but currency(45, decimals=False) returns $45.

With decimals unset or equal to True, this function uses the locale module to express the currency. However, currency(x, decimals=False) will simply return currency_symbol() followed by x formatted as an integer, which might not be correct in your locale. This is due to a limitation in the locale module. If the currency function does not meet your currency formatting needs, you may want to define your own.

If you defined a currency symbol in an initial block by calling set_locale() with a currency_symbol keyword parameter, then the locale-specific currency formatting function is not used.

The currency() function accepts an optional keyword parameter symbol. If this is set, then the locale-specific currency formatter function is not used, and instead the provided symbol is used.

question: |
  How much is your house worth?
fields:
  - Value: house_value
    datatype: currency
    min: 0
    currency symbol: €
---
question: Your home value
subquestion: |
  Your house is worth
  ${ currency(house_value, symbol=u'€') }.
mandatory: True

If the optional keyword argument symbol_precedes is set to true, then the symbol will come before the number. If symbol_precedes is set to false, the symbol will come after the number. If it is unset, the position of the symbol will be determined by the current locale.

currency_symbol()

If the locale is US.utf8, currency_symbol() returns $.

The locale can be set in the configuration or through the set_locale() and update_locale() functions.

If you set currency symbol in the configuration, then currency_symbol() returns the symbol specified there, and does not use the locale to determine the symbol.

indefinite_article()

question: |
  Would you prefer to have
  ${ indefinite_article(fruit) }
  as opposed to
  ${ indefinite_article(vegetable) }?
yesno: prefer_fruit

The English language version of this function uses the article() function of pattern.en.

indefinite_article('bean') returns a bean and indefinite_article('apple') returns an apple.

nice_number()

question: |
  There are ${ nice_number(toads) }
  toads and ${ nice_number(frogs) }
  frogs in the pond.
buttons:
  - Restart: restart
sets: all_done

nice_number(4) returns four
nice_number(10) returns ten
nice_number(10, capitalize=True) returns Ten
nice_number(10, language='es') returns diez
nice_number(11) returns 11
nice_number(5.0) returns five
nice_number(23423) returns 23,423 (this depends on the locale)
nice_number(12873818.27774) returns 12,873,818.28 (this depends on the locale)
nice_number(501) returns 501
nice_number(501, use_word=True) returns five hundred and one
nice_number(5.1) returns 5.1
nice_number(5.1, use_word=True) returns five point one
nice_number(-1) returns -1
nice_number(-1, use_word=True) returns minus one

This function uses the num2words package, which supports several languages by default, but not all languages.

This function can be customized by calling docassemble.base.util.update_nice_numbers() with a language as the first parameter and a dictionary as the second parameter, where the dictionary maps numbers to their textual representation. Since docassemble.base.util.update_nice_numbers() is not thread-safe, you should only run it from a Python module in code that runs when the module loads.

noun_plural()

question: |
  There
  % if the_number > 1:
  are
  ${ nice_number(the_number) }
  ${ noun_plural(the_noun) }
  % else:
  is one ${ the_noun }
  % endif
  in the pond.
fields:
  - Singular noun: the_noun
sets: all_done

The English language version of this function passes all arguments through to the pluralize() function of pattern.en.

noun_plural('friend') returns friends
noun_plural('fish') returns fish
noun_plural('moose') returns mooses

You can also pass a number as a second argument to the function. If the number is 1, the first argument will be returned as a singular noun; otherwise, the pluralized version of the first argument will be returned.

noun_plural('friend', number_friends) returns friend if number_friends is 1, otherwise it returns friends.

Instead of a number, you can pass a list, dictionary, or set as the second argument to the function. If the number of items in the group is 1, the singular will be used. Otherwise, the plural will be used.

The noun_plural() function can accept a noun that is either singular or plural. For example, noun_plural('barrel') and noun_plural('barrels') both return 'barrels'. The function handles this by passing the first argument through noun_singular(), and then using the pluralize() function of pattern.en on the result. In some circumstances, this can lead to an incorrect word being returned. If you know that the noun you are providing is singular, you can call noun_plural('barrel', noun_is_singular=True) and noun_plural() will not call noun_singular() on the noun.

quantity_noun()

mandatory: True
question: |
  You have ${ quantity_noun(4, "apple") }.

This function combines nice_number() and noun_plural() into a single function. It will round the number to the nearest integer unless you add the optional keyword argument as_integer=False.

quantity_noun(2, "apple") returns two apples.
quantity_noun(1, "apple") returns one apple.
quantity_noun(144, "apple") returns 144 apples.
quantity_noun(1.5, "apple") returns 2 apples.
quantity_noun(1.5, "apple", as_integer=False) returns 1.5 apples.

noun_singular()

The English language version of this function passes all arguments through to the singularize() function of pattern.en.

noun_singular('friends') returns friend
noun_singular('fishes') returns fish
noun_singular('mooses') returns moose

You can also pass a number as a second argument to the function. If the number is 1, the singularized version of the first argument will be returned. Otherwise, the first argument will be returned, untouched.

noun_singular('friends', number_friends) return friend if number_friends is 1, otherwise it returns friends.

ordinal_number()

ordinal_number(8) returns eighth.
ordinal_number(8, capitalize=True) returns Eighth.
ordinal_number(8, use_word=False) returns 8th.
ordinal_number(10) returns tenth.
ordinal_number(11) returns 11th.
ordinal_number(11, use_word=True) returns eleventh.
ordinal_number(523, use_word=True) returns five hundred and twenty-third.

question: |
  The ${ ordinal_number(toads) }
  toad is here to see you.
buttons:
  - Restart: restart
sets: all_done

By default, the num2words package is used to produce the word supports several languages by default, but not all languages.

ordinal_number() can be customized with docassemble.base.util.update_ordinal_numbers() and docassemble.base.util.update_ordinal_function().

import docassemble.base.util

es_ordinal_nums = {
  '0': 'zeroth',
  '1': 'primero',
  '2': 'segundo',
  '3': 'tercero',
  '4': 'cuarto',
  '5': 'quinto',
  '6': 'sexto',
  '7': 'séptimo',
  '8': 'octavo',
  '9': 'noveno',
  '10': 'décimo'
}

docassemble.base.util.update_ordinal_numbers('es', es_ordinal_nums)
docassemble.base.util.update_ordinal_function()

Since update_ordinal_numbers() and update_ordinal_function() are not thread-safe, you should only run them from a Python module in code that runs when the module loads.

ordinal()

ordinal(x) returns ordinal_number(x + 1). This is useful when working with indexes that start at zero.

alpha()

alpha(x) returns x + 1 as an alphabetical character. This is intended to be used with indexes that start at zero.

alpha(0) returns A.
alpha(25) returns Z.
alpha(26) returns AA.
alpha(26) returns AB.
alpha(0, case='lower') returns a.

roman()

roman(x) returns x + 1 as a Roman numeral. This is intended to be used with indexes that start at zero.

roman(0) returns I.
roman(65) returns LXVI.
roman(65, case='lower') returns lxvi.

item_label()

item_label(x) returns x + 1 as a label for a list item. This is intended to be used with indexes that start at zero. It takes an optional second argument indicating a level between 0 and 6. It takes an optional keyword argument punctuation indicating whether punctuation should be provided or not.

item_label(0) returns I..
item_label(1) returns II..
item_label(0, 0) returns I..
item_label(0, 1) returns A..
item_label(0, 2) returns 1..
item_label(0, 3) returns a).
item_label(0, 4) returns (1).
item_label(0, 5) returns (a).
item_label(0, 6) returns i).
item_label(0, 6, punctuation=False) returns i.

period_list()

period_list returns a list within a list:

[[12, "Per Month"], [1, "Per Year"], [52, "Per Week"],
[24, "Twice Per Month"], [26, "Every Two Weeks"]]

This is useful for using in code associated with periodic currency amounts.

question: |
  What is your income?
fields:
  - Income: user_income_amount
    datatype: currency
  - Period: user_income_period
    datatype: number
    code: |
      period_list()

The text in the default period_list() function can be translated to different languages using the docassemble.base.util.update_word_collection() function. If you want to customizes the choices available, you can override the default function by including something like the following in your Python module:

def my_period_list():
  return [[365, word("Per Day")], [52, word("Per Week")]]

docassemble.base.util.update_language_function('*', 'period_list', my_period_list)

name_suffix()

Like period_list(), except it represents common suffixes of individual names.

Returns the following list:

['Jr', 'Sr', 'II', 'III', 'IV', 'V', 'VI']

Here is a question that asks for the user’s name with an optional suffix:

question: |
  What is your name?
fields:
  - First Name: user.name.first
  - Middle Name: user.name.middle
    required: False
  - Last Name: user.name.last
  - Suffix: user.name.suffix
    required: False
    code: |
      name_suffix()
---

title_case()

question: |
  Title of your book
subquestion: |
  If your book is about
  ${ subject },
  its title should be
  "${ title_case(subject) }."
sets: all_done

title_case("the importance of being ernest") returns The Importance of Being Ernest.

The default version of this function passes through all arguments to the titlecase() function of the titlecase module.

There is also the capitalize() function, which is described above.

verb_past()

question: |
  I ${ verb_past(the_verb) }
  the apple.
fields:
  - Present tense verb: the_verb
sets: all_done

The English-language version of this function passes all arguments through to the conjugate() function of pattern.en.

verb_past('help', '3gp') returns helped (third person past tense).
verb_past('help', 'ppl') returns helped (plural past tense).

verb_present()

The English-language version of this function passes through all arguments to the conjugate() function of the pattern.en.

verb_present('helped', '3sg') returns helps (third person singular).
verb_present('helps', '1sg') returns help (first person singular).
verb_present('helps', 'pl') returns help (plural).

Simple language functions

The following simple language functions all have the property that if the optional argument capitalize=True is added, the resulting phrase will be capitalized.

her('turtle') returns her turtle.
her('turtle', capitalize=True) returns Her turtle.
his('turtle') returns his turtle.
a_in_the_b('cat', 'hat') returns cat in the hat.
do_you('smoke') returns do you smoke.
does_a_b('Fred', 'smoke') returns does Fred smoke.
in_the('house') returns in the house.
of_the('world') returns of the world.
possessify('Fred', 'cat') returns Fred's cat.
possessify_long('Fred', 'cat') returns the cat of Fred.
the('apple') returns the apple.

Note that unlike other functions, these functions are not available for use within interviews.

These functions are intended to be used from within Python modules, where you can import them by doing:

from docassemble.base.util import his, her

Note that doing from docassemble.base.util import * will not work, because these functions are not automatically exported by docassemble.base.util.

You can customize the functions for different languages:

def her_fr(word, capitalize=False):
  if capitalize:
    return 'Sa ' + word
  else:
    return 'sa ' + word
docassemble.base.util.update_language_function('fr', 'her', her_fr)

Or, you can accomplish the same result with a handy function generator from docassemble.base.util:

docassemble.base.util.update_language_function('fr', 'her', docassemble.base.util.prefix_constructor('sa '))

Helper functions for form filling

yesno()

The yesno() function returns 'Yes' or 'No' depending on the truth value of the argument. This is useful for filling in checkboxes in PDF templates. It takes an optional keyword argument invert, which, if set to true, returns 'No' in place of 'Yes' and vice-versa.

noyes()

The noyes() function does the opposite of yesno(), or the same thing as yesno(some_fact, invert=True).

split()

The split() function splits a phrase into parts that are a certain number of characters long. It splits on word breaks when it can. This is useful for filling in PDF templates when a single phrase must be typed into more than one field.

The first argument is the phrase. The second argument is a list of maximum character lengths of each part. If there are two numbers, there will be at most three parts. The third argument is the index of the part you want. The first index is 0.

In this example, the first part should be no more than 12 characters and the second part should be no more than 20 characters.

split("The quick brown fox jumped over the lazy dog", [12, 20], 0) returns 'The quick'.
split("The quick brown fox jumped over the lazy dog", [12, 20], 1) returns 'brown fox jumped over'.
split("The quick brown fox jumped over the lazy dog", [12, 20], 2) returns 'the lazy dog'.

If you only want to split in two parts, and you do not wish to limit the length of the second part, you can pass a single number instead of a list of numbers as the second argument.

split("The quick brown fox jumped over the lazy dog", 12, 0) returns 'The quick'.
split("The quick brown fox jumped over the lazy dog", 12, 1) returns 'brown fox jumped over the lazy dog'.

If you refer to an index for a part that does not exist because the phrase was too short, empty text ('') is returned.

To figure out what character lengths you should use, one method is to test the PDF file to see how many letter Ms you can fit into a field. If you can fit 10 Ms into the first field and 22 Ms in into the second field, the second argument to split() would be [10, 22].

showif()

The showif() function returns the value of variable if the given condition is true, and otherwise returns empty text ('').

showif('favorite_fruit', likes_fruit) returns the value of the variable favorite_fruit, but only if the variable likes_fruit is true.

Note that the first argument must be a variable name in quotes. This ensures that a definition of the variable will not be sought unless the condition is true.

If you want the function to return something other than the empty string (''), supply a third argument:

showif('favorite_fruit', likes_fruit, 'no fruit') returns the value of the variable favorite_fruit if the variable likes_fruit is true, and otherwise returns the text no fruit.

showifdef()

The showifdef() function is like showif(), except that the value of the variable is only returned if the variable is defined.

showifdef('favorite_fruit') returns the value of the variable favorite_fruit if the variable favorite_fruit is defined, and otherwise returns empty text.
showifdef('favorite_fruit', 'no fruit') returns the value of the variable favorite_fruit if the variable favorite_fruit is defined, and otherwise returns the text no fruit.

The showifdef() function accepts an optional keyword argument prior. If you set prior=True, then on screens that loaded because the user pressed the Back button, showifdef() will look in the previous set of interview answers (the set that was deleted by pressing the Back button) to see if the variable was defined.

Administrative functions

interview_list()

If the current user is logged in, interview_list() returns a list of dictionaries indicating information about the user’s interview sessions. This function provides a programmatic version of the screen available at /interviews.

interview_list() takes the following optional keyword parameters:

exclude_invalid - if True, do not return any sessions where the interview could not be found or the interview_answers (the dict) could not be unencrypted. The default is True.
action - if set to 'delete_all', then interview_list() will delete the sessions and return the number of sessions deleted. This can be limited by specifying filename, session, user_id, or query. The action parameter can also be set to 'delete', in which case a filename and a session must be specified, and that single session will be deleted.
filename - if set, interview_list() will only act on sessions with this interview filename (e.g., docassemble.demo:data/questions/questions.yml).
session - if set, interview_list() will only act on sessions with this session ID.
user_id - if not set, interview_list() will only act on interviews owned by the current user. If set to an integer, interview_list() will only act on sessions that the user with the given user ID is a user of. If set to 'all', the sessions will not be limited to the interviews of a particular user; you can then use query to narrow the list. Only users with admin privileges (or users with a custom privilege with the access_sessions permission) can access sessions of other users.
query - this can be set to a query expression if you want to do a complex query. The syntax is explained below.
include_dict - if True, then interview_list() will return the interview answers in the response. If you are not going to use the interview answers, it is best to set this to False. The default is True.
delete_shared - this can be set to True if you set action to 'delete_all' or 'delete', in which case all of the interview answers of the deleted sessions will be deleted even if the user is one of several users in the session. The default is False.
next_id - this is used for pagination (more on that later).

When action is set to 'delete_all' or 'delete', interview_list() returns an integer indicating the number of sessions deleted. Otherwise, interview_list() returns a list of sessions.

Since the list of sessions may be very long, interview_list() uses pagination. When you first call interview_list(), up to 100 records are returned in the first item in the tuple. The number of records returned is configurable using the pagination limit Configuration directive. If additional records exist, the second item in the tuple will be a code. To obtain the next page of records, call interview_list() again, this time with the next_id optional keyword parameter set to the second item in the tuple. By making multiple calls to interview_list(), you can obtain the complete list of user records. For example:

from docassemble.base.util import interview_list

sessions_list = []
next_id = None
while True:
    (items, next_id) = interview_list(next_id=next_id)
    sessions_list.extend(items)
    if not next_id:
        break

The first item in the tuple (items in this example) is a Python list of Python dictionaries, where the items in each dictionary are:

dict: the interview session dictionary for the session (not present if include_dict is False).
encrypted: whether the interview session dictionary is encrypted (not present if include_dict is False).
email: the e-mail address of the logged-in user associated with the session, if any.
user_id: the user ID of the logged-in user associated with the session, if any.
temp_user_id: the temporary user ID of the anonymous user associated with the session, if the user was not logged in. (Note that these IDs do not correspond in any way with the IDs of logged-in users.)
filename: the filename of the interview, e.g., docassemble.demo:data/questions/questions.yml
metadata: the metadata of the interview as a dictionary.
modtime: the modification time of the session, in text format, formatted to the user’s time zone.
session: the ID of the session.
starttime: the start time of the session, in text format, formatted to the user’s time zone.
title: the title of the session.
subtitle: the subtitle of the session.
utc_modtime: the modification time of the session, in UTC.
utc_starttime: the start time of the session, in UTC.
valid: whether the interview session can be resumed. This will be False if there is an error with the interview that prevents it from being resumed, or the interview session dictionary is not able to be decrypted.

Sometimes you might not need to use pagination. For example, the following question will display a list of the titles of each session associated with the current user (at most the first 100):

question: Sessions
subquestion: |
  % for info in interview_list()[0]:
  * ${ info['title'] }
  % endfor

To limit the results to sessions involving specific interviews, you can provide the optional keyword argument filename:

question: Session start times
subquestion: |
  % for info in interview_list(filename='docassemble.demo:data/questions/questions.yml')[0]:
  * ${ info['starttime'] }
  % endfor

If the current user has admin privileges or a custom privilege with the access_sessions permission, the optional keyword argument user_id can be used to retrieve a list of sessions belonging to another user:

question: Sessions John has started
subquestion: |
  % for info in interview_list(user_id=22)[0]:
  * ${ info['title'] }
  % endfor

To list sessions belonging to any user, set user_id to 'all'.

question: Who has what session
subquestion: |
  % for info in interview_list(filename='docassemble.demo:data/questions/questions.yml', user_id='all')[0]:
  * ${ info['email'] } started at ${ info['starttime'] }.
  % endfor

Since the information about each session could include the interview session dictionary, to avoid storing all of this information in your own dictionary, it is a good idea to avoid keeping interview information around when you are done using it. For example, this interview runs del to ensure that the variable info is not left over when the for loop completes its work:

code: |
  users = set()
  for info in interview_list()[0]:
    users.add(info['email'])
    del info

You can also refrain from obtaining the interview session dictionary by setting the optional keyword parameter include_dict to False.

The interview_list() function takes an optional keyword argument exclude_invalid. If this is set to False, a session will be included even if there is an error that would prevent the session from being resumed. By default, exclude_invalid is True, meaning that sessions will only be included if they can be resumed. You can check whether a session can be resumed by checking the value of the valid key. The most common reason for a session not to be valid is that the current user does not have an encryption key that decrypts the interview answers; so a session belonging to someone else might be not valid for you, but it would be valid for the user who started that session.

The interview_list() function can be useful in interviews that replace the standard list of sessions. See the session list interview configuration directive for more information.

Note that more than one user can be associated with any given session. Unless server-side encryption prevents it, any user who has the session ID of a session can join that interview by visiting a URL with the i and session parameters set. This will associate the user with the session. Thus, if a session has been joined by more than one user, it will show up multiple times in the list returned by interview_list(user_id='all').

You can use interview_list() to delete sessions. If you set the optional keyword parameter action to 'delete_all', all of the user’s sessions will be deleted. Or, if you want to delete all of the sessions belonging to any user, you can set user_id to 'all' and set action to 'delete_all'. You can delete a particular session by setting action to 'delete', with optional keyword parameter filename set to the filename of the session’s interview, and optional keyword parameter session set to the ID of the session. By default, the underlying session data associated with a particular user will not be deleted if it is shared by another user. For example, if there was an interview with multi_user set to True, and two users accessed a session of this interview, and then one user deletes the session, the other user will still be able to access the session and all of its data. However, if you set the optional keyword parameter delete_shared to True, then the session and its data will be deleted regardless of whether it is shared by one or more other users.

If you want to filter the results by attributes other than filename, session, and user_id, or you want to filter with a boolean query, you can set the keyword parameter query to an expression such as the following:

DA.Sessions.modtime < '4/5/2022'
DA.Sessions.user_id.In(1, 41)
DA.Sessions.email == '[email protected]'
DA.Sessions.email.Like('%@abc.com') & DA.Sessions.modtime < '4/5/2022'
DA.Sessions.first_name == 'Joseph' | DA.Sessions.first_name == 'Joe'
DA.Sessions.first_name == 'Joseph' | (DA.Sessions.first_name == 'Joe' & DA.Sessions.last_name == 'Smith')

The available fields are:

DA.Sessions.indexno - the integer number of the latest step in the interview answers of the session. This is the integer that is used for next_id.
DA.Sessions.modtime - the timestamp of the latest step in the interview answers.
DA.Sessions.filename - the filename of the interview.
DA.Sessions.session - the session ID of the session.
DA.Sessions.encrypted - a boolean value representing whether the latest step in the interview answers of the session is encrypted.

The following fields are available for sessions that are tied to a logged-in user. They come from the user profile.

DA.Sessions.user_id - the user_id of the user.
DA.Sessions.email - the e-mail address of the user.
DA.Sessions.first_name - the user’s first name.
DA.Sessions.last_name - the user’s last name.
DA.Sessions.country - the user’s country.
DA.Sessions.subdivisionfirst - the user’s first geographical subdivision.
DA.Sessions.subdivisionsecond - the user’s second geographical subdivision.
DA.Sessions.subdivisionthird - the user’s third geographical subdivision.
DA.Sessions.organization - the user’s organization name.
DA.Sessions.timezone - the user’s time zone.
DA.Sessions.language - the user’s language code.
DA.Sessions.last_login - the timestamp of the user’s last login.

When writing query expressions, you can indicate “and” and “or” in two different ways.

DA.Sessions.modtime >= '4/1/2022' & DA.Sessions.modtime < '5/1/2022'
DA.And(DA.Sessions.modtime >= '4/1/2022', DA.Sessions.modtime < '5/1/2022')

Likewise, the following are equivalent:

DA.Sessions.first_name == 'Joseph' | DA.Sessions.first_name == 'Joe'
DA.Or(DA.Sessions.first_name == 'Joseph', DA.Sessions.first_name == 'Joe')

The operators ==, !=, >=, >, <=, and < are available. In addition, the ~ operator can be used to negate conditions. For example, to exclude sessions owned by users named Joseph, you would write something like:

~DA.Or(DA.Sessions.first_name == 'Joseph', DA.Sessions.first_name == 'Joe')
~DA.Sessions.first_name.like('Jo%')
~(DA.Sessions.first_name == 'Joseph')

There are two methods available, Like and In:

DA.Sessions.email.Like('%@abc.com')
DA.Sessions.last_name.In('Smith', 'Jones')

For API versions of this function, see /api/interviews, /api/user/interviews, and /api/user/<user_id>/interviews.

interview_menu()

The interview_menu() function returns a list of dictionaries indicating information about interviews available on the web site. See the dispatch configuration directive for information about setting up this menu. This function provides a programmatic version of the screen available at /list.

The keys in each dictionary are:

title: the title of the interview
subtitle: the subtitle of the interview
filename: e.g., docassemble.demo:data/questions/questions.yml
link: a hyperlink to the interview on your server
metadata: a dictionary representing the metadata of the interview (minus the tags, which are provided separately).
package: the package in which the interview is located, e.g., docassemble.demo
status_class: this is set to dainterviewhaserror if there is a problem with the interview.
subtitle_class: this is set to invisible if there is a problem with the interview.
tags: a list of tags specified in the interview metadata.

The interview_menu() function takes three optional keyword arguments, absolute_urls, start_new, and tag.

If absolute_urls is set to True, then the URLs will be absolute rather than relative, so that the HTML can be used from a web site on another server.

If start_new is set to True, then the URLs will have &reset=1 at the end. Thus, even if the user has already started an interview, clicking the link will start the interview at the beginning again.

If tag is set to 'estates' (for example), then interview_menu() will only return interviews that have 'estates' defined as a tag in the interview metadata.

This function can be useful in interviews that replace the standard list of available interviews. See the dispatch interview configuration directive for more information.

For an API version of this function, see /api/list.

create_user()

The create_user() function creates a new user account on the system.

new_user_id = create_user('[email protected]', 'xxxsecretxxx')

This will create an account with the e-mail address [email protected] and the password xxxsecretxxx. The variable new_user_id will be set to the user ID of the newly-created account.

Only users with privileges of admin or users with a custom privilege with the create_user permission can use this function.

The create_user() function also accepts an optional keyword parameter privileges, which can be set to the name of a privilege (e.g., 'advocate') or a list of privileges (e.g., ['advocate', 'trainer']). Non-admin users do not have the power to confer privileges of admin, developer, or advocate.

The function also accepts an optional keyword parameter info, which is expected to be a dictionary containing information about the new user. The info dictionary can contain any of the following keys:

country: user’s country code (ISO 3166-1 alpha-2 format).
first_name: user’s first name.
language: user’s language code.
last_name: user’s last name.
organization: user’s organization
subdivisionfirst: user’s state.
subdivisionsecond: user’s county.
subdivisionthird: user’s municipality.
language the user’s language (an ISO-639-1 or ISO-639-3 code).
timezone: user’s time zone (e.g. 'America/New_York').

To set this information after the user account is created, use set_user_info().

For an API version of this function, see /api/user/new.

invite_user()

The invite_user() function allows an administrator to create an invitation for a user with a given email address to create an account on the server.

Creating the invitation does not create an account; it generates a token that can be transmitted to the user. The user can use that token when registering. The administrator can indicate that the user should be given a specific privilege upon registering.

url = invite_user('[email protected]', privilege='advocate', send=False)

This will return a URL that can be shared with a user. The URL is the URL of the registration screen of the server with a token parameter. When the user visits the URL, they will go to the registration page and they will be able to register there even if allow registration is false.

When the user chooses a password and submits the registration form, a new user account will be created. If a privilege was indicated, the user will have that privilege. Only one privilege may be defined through the invitation process.

If send is set to True, which is the default, the invite_user() function will email the URL to the email address and None will be returned. If send is False, the registration URL is returned.

Only users with privileges of admin or users with a custom privilege with the create_user permission can use this function.

For an API version of this function, see /api/user_invite.

get_user_list()

The get_user_list() function returns a list of registered users on the server. If the optional keyword parameter include_inactive is set to True, then any inactive users are included in the results; otherwise they are excluded.

In order to use this function, the user must have privileges of admin, advocate, or a custom privilege with the access_user_info permission.

The function returns a two-item tuple. The first item in the tuple is a Python list of Python dictionaries, where each dictionary has the following keys:

active: whether the user is active. This is only included if the include_inactive parameter is set.
country: user’s country code (ISO 3166-1 alpha-2 format).
email: user’s e-mail address.
first_name: user’s first name.
id: the integer ID of the user.
language: user’s language code.
last_name: user’s last name.
organization: user’s organization
privileges: a Python list of the user’s privileges (e.g., 'admin', 'developer').
subdivisionfirst: user’s state.
subdivisionsecond: user’s county.
subdivisionthird: user’s municipality.
language the user’s language (an ISO-639-1 or ISO-639-3 code).
timezone: user’s time zone (e.g. 'America/New_York').

The second item in the tuple is a code that is used for pagination. Since the list of users may be very long, get_user_list() uses pagination. When you first call get_user_list(), up to 100 records are returned in the first item in the tuple (configurable using the pagination limit Configuration directive). If additional records exist, the second item in the tuple will be a code. To obtain the next page of records, call get_user_list() again, this time with the next_id optional keyword parameter set to the second item in the tuple. By making multiple calls to get_user_list(), you can obtain the complete list of user records. For example:

from docassemble.base.util import get_user_list

user_list = []
next_id = None
while True:
    (items, next_id) = get_user_list(next_id=next_id)
    user_list.extend(items)
    if not next_id:
        break

For an API version of this function, see /api/user_list.

get_user_info()

The get_user_info() function is like get_user_list(), except it only returns information about one user at a time. If called without arguments, it returns a Python dictionary of information about the current user. The function can also take a user ID as an argument (e.g., get_user_info(user_id=22)), or an e-mail address as an argument (e.g., get_user_info(email='[email protected]'), in which case it returns information about the user with that user ID or e-mail address. If no user is found, None is returned.

This function will only work if the user running the interview that calls the function is logged in. If the user is not logged in, None will be returned.

In order to see information about other users, the user must have privileges of admin, advocate, or a custom privilege with the access_user_info permissions.

For API versions of this function, see /api/user and /api/user/<user_id>. (Searching by e-mail address is not supported in the API.)

set_user_info()

The set_user_info() function writes information to user profiles.

It accepts the following keyword parameters, all of which are optional:

country: user’s country code (ISO 3166-1 alpha-2 format).
first_name: user’s first name.
last_name: user’s last name.
language the user’s language (an ISO-639-1 or ISO-639-3 code).
organization: user’s organization
subdivisionfirst: user’s state.
subdivisionsecond: user’s county.
subdivisionthird: user’s municipality.
timezone: user’s time zone (e.g. 'America/New_York').
password: user’s new password.
old_password: user’s old password. If this is supplied when password is supplied, the user’s encrypted information will be converted from the old encryption key to the new encryption key.
account_type: the type of login the user used. This is local for the username/password system, auth0 for Auth0, google for Google, etc.

The current user’s profile will be updated with the values of the parameters. Note that the user_id and email attributes cannot be changed using this function; these attributes are used only for selecting the user whose information is going to be changed.

This function will only work if the user running the interview that calls the function is logged in.

In order to change information about other users, the user must have privileges of admin or a custom privilege with the following permissions, depending on what information they try to change:

edit_user_info for editing any information about other users;
edit_user_password for editing passwords;
edit_user_active_status for making a user inactive or active;
edit_user_privileges for editing a user’s privileges.

Only users with the admin privilege can edit the information of users with admin, developer, or advocate privileges.

Here is an example of a code block that updates the name of the user:

mandatory: True
code: |
  set_user_info(first_name=user.name.first, last_name=user.name.last)

If the user running the interview that calls the function has appropriate privileges, then the function can be used to change the profiles of other users. A user account can be indicated by the inclusion of an additional keyword parameter, user_id or email, that identifies the user whose profile should be changed.

For example, the following Python code, when run by a user with sufficient privileges, will change the “organization” setting of the user [email protected]:

set_user_info(email='[email protected]', organization='Example, Inc.')

Users with admin privileges or the edit_user_active_status permission can disable user accounts by setting the active keyword parameter to False (or enable a disabled account by setting active to True).

In addition, users with admin privileges or the edit_user_privileges permission can change the privileges of a user by setting the privileges keyword parameter to the list of privilege names that the user should have.

set_user_info(user_id=22, privileges=['user', 'trainer'])

For an API version of this function, see the POST method of /api/user/<user_id>, the DELETE method of /api/user/<user_id>, the POST method of /api/user/<user_id>/privileges, and the DELETE method of /api/user/<user_id>/privileges (Changing accounts by e-mail address is not supported in the API.)

get_user_secret()

The get_user_secret() function takes an e-mail address and a password as arguments and returns a decryption key if the e-mail address/password combination is valid. You will need this decryption key in order to use get_session_variables() and set_session_variables() with interview answers that are encrypted.

secret = get_user_secret('[email protected]', 'xx_Secr3t_xx')

Note that you need to keep decryption keys secret, or else you defeat the purpose of server-side encryption. The idea behind server-side encryption is that if a system’s security is breached, and all the data on the server is revealed, the information would still be protected because it is encrypted. But if the decryption key is stored on the server in an accessible place, then the information would no longer be protected, since someone who found the decryption key could decrypt the data. Thus, you would not want to store the result of get_user_secret() in the interview session dictionary of an interview that sets multi_user to True. Also, even if your interview answers are encrypted, it is still a good idea to avoid storing passwords or decryption keys in an interview session dictionary.

For an API version of this function, see /api/secret.

get_session_variables()

The get_session_variables() function retrieves the dictionary for an interview session. It has two required arguments: an interview filename (e.g., 'docassemble.demo:data/questions/questions.yml'), a session ID (e.g., 'iSqmBovRpMeTcUBqBvPkyaKGiARLswDv'). In addition, it can take a third argument, an encryption key for decrypting the interview answers. If the interview answers are encrypted, the third argument is required.

If the third argument is omitted, but the interview answers are encrypted, the current user’s decryption key will be tried. To obtain an encryption key for a different user, you can use get_user_secret().

To get the interview filename for the current interview, and the session ID for the current interview session, you can use the user_info() function.

However, note that if you want to get the dictionary for the current interview session, you can simply use the all_variables() function.

Like the all_variables() function, get_session_variables() simplifies the dictionary (converting objects to dictionaries, for example), so that it is safe to convert the result to a format like JSON. If you want the raw Python dictionary, you can call get_session_variables() with the optional keyword parameter simplify set to False.

vars = get_session_variables(filename, session_id, secret, simplify=False)

For an API version of this function, see the GET method of /api/session.

create_session()

The create_session() function allows you to initiate a session in an interview.

yaml_filename = 'docassemble.demo:data/questions/questions.yml'
secret = get_user_secret(username, password)
session_id = create_session(yaml_filename, secret=secret, url_args={'foo': 'bar'})

The session_id that is returned can then be passed to functions like set_session_variables().

The first and only required parameter is the file name of the YAML interview for which you want to create a session.

create_session() supports two optional keyword parameters:

secret
url_args

The parameter secret can be set to the output of get_user_secret(). If the target interview does not use server-side encryption (multi_user is set to True), then the secret parameter is not important. If you do not provide a secret parameter and the target interview uses server-side encryption, then the current user’s decryption key will be used, and only the current user will be able to access the session.

The optional keyword parameter url_args can be set to a Python dictionary representing the url_args you want to be present in the session when it starts.

After setting the url_args (if any), create_session() will evaluate the interview logic in the session and save the interview answers for the session. Thus, if mandatory or initial blocks in the interview cause side effects, these side effects will be triggered by the call to create_session(). Also, note that when this code executes, the user for purposes of this code execution will be the same as the user who ran create_session().

set_session_variables()

The set_session_variables() function allows you to write changes to any interview session dictionary (except the current interview session). It has three required parameters: an interview filename (e.g., 'docassemble.demo:data/questions/questions.yml'), a session ID (e.g., 'iSqmBovRpMeTcUBqBvPkyaKGiARLswDv'), and a Python dictionary containing the variables you want to set.

If you run this:

vars = {"defense['latches']": False, "client.phone_number": "202-555-3434"}
set_session_variables(filename, session_id, vars)

Then the following statements will be executed in the interview session dictionary:

defense['laches'] = False
client.phone_number = '202-555-3434'

Note that if you pass DAFile, DAFileList, or DAFileCollection objects from one interview session to another, the other interview will not be able to read the files unless the .set_attributes() method has been used to either change the session and filename to match the destination interview session, or the private attribute has been set to False. Note that if the session and filename are changed, then the first interview session will no longer be able to access the file. Note also that if private is set to False, then the file will be accessible on the internet from a URL.

set_session_variables() supports the following optional keyword parameters:

question_name
secret
overwrite
process_objects
delete

If you set question_name to the ID of a question in the interview, the question will be marked as answered. You can obtain the ID of a question from the questionName attribute in the question data using get_question_data() or the /api/session/question API method. It is only necessary to specify a question_name when you are setting a variable for purposes of answering a mandatory question. You can tell if a question is mandatory by checking for the presence of the attribute mandatory in the question data.

The keyword parameter secret can be an encryption key for decrypting the interview answers. If no secret is provided, the encryption key of the current user is used.

The parameter overwrite can be set to True if you do not want to create a new step in the interview when the function runs.

The parameter process_objects can be set to True if you want the Python dictionary that you pass to set_session_variables() to be treated as a “serializable” representation of docassemble objects. For more information about how this works, see the documentation for the set_variables() function, which also accepts a process_objects keyword parameter. By default, set_session_variables() does not process the variables as docassemble objects.

The parameter delete can be set to a list of variables in the interview answers of the other session that you want to undefine.

set_session_variables(filename, session_id, {}, delete=["defense['estoppel']", "client.paid"])

For an API version of this function, see the POST method of /api/session.

run_action_in_session()

The run_action_in_session() function runs an action in a different session. It requires three positional parameters: the YAML filename of the interview, the session ID of the session in that interview, and the action to run.

For example, this code block runs the action do_the_thing in the session of the interview docassemble.demo:data/questions/questions.yml with the session ID 45BrppwmAxQRRhdCYCs4rVJ4iYtfleDm.

code: |
  run_action_in_session('docassemble.demo:data/questions/questions.yml',
                        '45BrppwmAxQRRhdCYCs4rVJ4iYtfleDm',
                        'do_the_thing')
  action_has_been_run = True

run_action_in_session() accepts the following optional keyword parameters:

arguments: if the action takes arguments, set arguments to a dictionary containing the arguments.
secret: the encryption key to use with the interview, if the interview uses server-side encryption. (See get_user_secret().) If no secret is provided, the encryption key of the current user is used.
persistent: set this to True if you intend the action to show a question, as opposed to merely execute some code. The default behavior is for the action to run in a non-persistent fashion.
overwrite: if set to True, then when the interview answers are saved, they will overwrite the previous interview answers instead of creating a new step in the session. The default behavior is to create a new step in the session.

Here is an example interview that uses run_action_in_session(), among other functions for manipulating other sessions.

code: |
  interview_filename = 'docassemble.demo:data/questions/examples/secondary-interview.yml'
---
mandatory: True
question: |
  Press Continue to start a new session in
  `${ interview_filename }`.
continue button field: first_screen
---
code: |
  session_id = create_session(interview_filename)
---
mandatory: True
question: |
  The session ID of the other session is
  `${ session_id }`.
subquestion: |
  `number_of_fruit` in the other session is
  currently
  `${ get_session_variables(interview_filename, session_id)['number_of_fruit'] }`.

  `favorite_fruit` in the other session is
  currently
  `${ get_session_variables(interview_filename, session_id)['favorite_fruit'] }`.

  Press Continue to set the variable
  `favorite_fruit` in the other session
  to `'apple'`.
continue button field: second_screen
---
mandatory: True
code: |
  set_session_variables(interview_filename,
                        session_id,
                        {'favorite_fruit': 'apple'})
---
mandatory: True
question: |
  The favorite fruit in the other session is now
  `${ get_session_variables(interview_filename, session_id)['favorite_fruit'] }`.
subquestion: |
  Press Continue to run the action
  `add_to_fruit_count` in the other session
  with action argument `number` set to `2`.
continue button field: third_screen
---
mandatory: True
code: |
  run_action_in_session(interview_filename,
                        session_id,
                        'add_to_fruit_count',
                        arguments={'number': 2})
---
mandatory: True
question: |
  `number_of_fruit` in the other session
  is now
  `${ get_session_variables(interview_filename, session_id)['number_of_fruit'] }`.
subquestion: |
  Note: if you press the Back button
  and press Continue again, you will see
  number increase again, since the other
  session is not affected by the Back
  button in this session.

  ${ action_button_html(interview_url(i=interview_filename, session=session_id), label='Visit other session', new_window=True) }

For an API version of this function, see the POST method of /api/session/action.

get_question_data()

The get_question_data() function returns data about the current question of an interview session. It has two required parameters: an interview filename (e.g., 'docassemble.demo:data/questions/questions.yml') and a session ID (e.g., 'iSqmBovRpMeTcUBqBvPkyaKGiARLswDv'). If the interview session is encrypted, you must supply a third parameter (or the keyword parameter secret) containing the encryption key for decrypting the interview answers.

code: |
  data = get_question_data('docassemble.demo:data/questions/questions.yml',
                           'iSqmBovRpMeTcUBqBvPkyaKGiARLswDv',
                           secret=secret_of_other_user)

The function returns a Python dictionary containing information about the question. The format of the dictionary varies by question type.

You can only use this function to access the question data for an interview other than the current interview.

For an API version of this function, see the /api/session/question.

go_back_in_session()

The go_back_in_session() function has the effect of clicking the Back button in another interview session. It has two required parameters: the interview filename and the session ID of the other session. It also accepts an optional keyword parameter secret, which is the encryption key to use to decrypt the interview session dictionary, if it is encrypted.

go_back_in_session(filename, session_id, secret=secret)

For an API version of this function, see the POST method of /api/session/back.

manage_privileges()

The manage_privileges() function allows a user with admin privileges or a custom privilege with appropriate permissions to list, add, remove, or see additional information about privilege types from the list of existing privileges.

manage_privileges('list') returns the list of existing privilege types as an alphabetically sorted list. If the user does not have admin privileges, the user must have a privilege with the access_privileges permission.
manage_privileges('add', 'supervisor') adds a privilege called supervisor to the list of existing privilege types. If the user does not have admin privileges, the user must have a privilege with the access_privileges and edit_privileges permissions in order to use the 'add' feature.
manage_privileges('remove', 'supervisor') removes the privilege called supervisor from the list of existing privilege types. Moreover, if any users have the privilege, the privilege is taken away from the users. If the user does not have admin privileges, the user must have a privilege with the access_privileges and edit_privileges permissions in order to use the 'remove' feature.
manage_privileges('inspect', 'supervisor') returns the permissions of the custom privilege supervisor.

For an API version of this function, see /api/privileges.

Miscellaneous functions

validation_error()

The validation_error() function takes an error message as a parameter and raises a DAValidationError exception with that error message. This means that any code that follows the call to validation_error() will not be executed.

This is primarily useful inside validate code and validation code when you want to indicate that the validation did not succeed. The validation_error() function requires a single argument, which is the error message the user should see.

For more information, see the documentation for validate and validation code.

The validation_error() function can be used to raise an error message from inside a lambda function that is used as the argument for validate:

question: Repeat after me.
subquestion: |
  To continue, type "I solemnly swear
  that I am up to no good."
fields:
  - no label: oath
    validate: |
      lambda y: validation_error("No, you typed it wrong.") if y != 'I solemnly swear that I am up to no good.' else True
---
mandatory: True
need: oath
question: |
  You are now allowed to use
  the Marauder's Map.

However, note that lambda functions can be confusing to people who don’t have a good knowledge of Python, so you might want to keep them out of your interview files.

validation_error() accepts an optional keyword argument field, which should refer to a variable name on the screen. If you call validation_error() from validation code and reference a field, the error message will be placed next to the indicated field.

server_capabilities()

The server_capabilities() function returns a dictionary indicating whether the server has particular features enabled.

mandatory: True
question: |
  Server capabilities
subquestion: |
  % for feature, enabled in server_capabilities().items():
  * **${ feature }**: ${ 'enabled' if enabled else 'disabled' }
  % endfor

Screenshot of server-capabilities example

The keys are:

sms - whether SMS messaging is available. See the twilio configuration.
fax - whether fax sending is available. See the twilio configuration.
google_login - whether logging in with Google is available. See the oauth configuration.
facebook_login - whether logging in with Facebook is available. See the oauth configuration.
twitter_login - whether logging in with Twitter is available. See the oauth configuration.
phone_login - whether logging in with an SMS security code is available. See the phone login configuration.
voicerss - whether the text-to-speech feature is available. See the voicerss configuration.
s3 - whether Amazon S3 is enabled. See the s3 configuration.
azure - whether Azure blob storage is enabled. See the azure configuration.
googledrive - whether Google Drive synchronization is available. See the googledrive configuration.
github - whether developers have the option of integrating their Playgrounds with GitHub. See the github configuration.
pypi - whether developers have the option of integrating their Playgrounds with PyPI. See the pypi configuration.
google_maps - whether the Google Maps API (used in the map_of() function and the geocode() method) is available. See the google configuration.

referring_url()

Returns the URL that the user was visiting when the user clicked on a link to go to the interview (if that click initiated the interview).

Under some circumstances, this URL (which comes from the referer header) cannot be obtained. For example, if the user started the interview by typing a URL directly into the location bar of the browser, or if the user has a browser setting that blocks the referer header, then the URL will not be available.

If the URL cannot be obtained, then the URL indicated by the optional keyword parameter default will be returned. If no default URL is provided, or default is None, then the value of the configuration directive exitpage will be used.

This function is useful when you want to bring the user back to where they started at the end of the interview.

question: |
  We are on a quest.
subquestion: |
  This quest is exciting!
field: continue_with_quest
---
question: |
  We have finished our quest.
buttons:
  - Return: exit
    url: |
      ${ referring_url() }
need:
  - continue_with_quest
mandatory: True

If you just want to find out the referring URL, make sure to set the default parameter to something you can test. For example, the following blocks will set the variable how_user_heard_of_us either by obtaining the referring URL or, if the URL is not available, by asking the user “How did you hear about us?”

question: |
  How did you hear about us?
fields:
  no label: how_user_heard_of_us
---
code: |
  if referring_url(default=False) is not False:
    how_user_heard_of_us = referring_url()

If you set the optional keyword parameter current to True, it will return the Referer of the current request, if available.

static_image()

mandatory: True
question: |
  An image created by code
subquestion: |
  This is the "${ image_name }" image.

  ${ static_image(image_name + '.svg') }

Returns appropriate markup to include a static image. If you know the image path, you can just use the [FILE ...] markup statement. The static_image() function is primarily useful when you want to assemble the image path using code.

The function takes an optional keyword argument “width” that will affect the width of the image on the screen or page:

static_image('docassemble.demo:crawling.png', width='2in'))

get_config()

Returns a value from the docassemble configuration file. If the value is not defined, returns None.

See the explanation of this function in the configuration section for more information.

prevent_going_back()

docassemble’s back button helps users when they make a mistake and want to go back and correct it. But sometimes, we want to prevent users from going back. For example, if the interview code causes an e-mail to be sent, or data to be written to a database, allowing the user to go back and do the process again would create confusion.

You can call prevent_going_back() to instruct the web application to prevent the user from going back past that point. See also the modifier of the same name.

code: |
  app_submitted = True
  prevent_going_back()

selections()

This is used in multiple choice questions in fields lists where the datatype is object, object_radio, or object_list and the list of selections is created by embedded code. The function takes one or more arguments and outputs an appropriately formatted list of objects. If any of the arguments is a list, the list is unpacked and its elements are added to the list of selections.

objects_from_file()

objects_from_file() imports data from a YAML or JSON file, including objects.

The import acts like a standard YAML import, except that when an associative array (dictionary) is encountered that has the keys object and items, then the associative array is converted into a list of objects (specifically, a DAList). In addition, if an associative array is encountered that has the keys object and item, then the associative array is converted into a single object.

code: |
  people = objects_from_file("contacts.yml", use_objects=True)
---
mandatory: true
question: |
  How to contact us
subquestion: |
  % for person in people:
  You can e-mail ${ person } at
  ${ person.email }.
  
  % endfor

In the above example, contacts.yml is a file in the data/sources folder of the package, and it has the following contents:

object: Individual
module: docassemble.base.util
items:
  - name:
      object: IndividualName
      item:
        first: Fred
        last: Smith
    email: [email protected]
    allergies:
      - peanuts
      - subway tokens
  - name:
      object: IndividualName
      item:
        first: Larry
        last: Jones
    email: [email protected]
    skills:
      - stapling
      - making coffee

This example uses two standard docassemble objects, Individual and IndividualName.

A JSON file can also be used.

code: |
  people = objects_from_file("contacts.json")
---
mandatory: true
question: |
  How to contact us
subquestion: |
  % for person in people:
  You can e-mail ${ person } at
  ${ person.email }.
  
  % endfor

Screenshot of objects-from-file-json example

In the above example, the file contacts.json file has the following contents:

{
    "object": "Individual",
    "module": "docassemble.base.util",
    "items": [
        {
            "name": {
                "object": "IndividualName",
                "module": "docassemble.base.util",
                "item": {
                    "first": "Fred",
                    "last": "Smith"
                }
            },
            "email": "[email protected]",
            "allergies": [
                "peanuts",
                "subway tokens"
            ]
        },
        {
            "name": {
                "object": "IndividualName",
                "module": "docassemble.base.util",
                "item": {
                    "first": "Larry",
                    "last": "Jönes"
                }
            },
            "email": "[email protected]",
            "skills": [
                "stapling",
                "making coffee"
            ]
        }
    ]
}

What gets returned

The objects_from_file() function will return a DAList object if:

There is more than one YAML “document” (separated by ---).
There is one YAML “document” and it is an associative array with the keys object and items.

If there is one YAML “document” and it is an associative array with the keys object and item, then the object itself will be returned.

If there is one YAML “document” and it is something other than an associative array with the keys object and items or object and item, then the data structure will be returned.

There is an optional keyword argument name that will be used to set the .instanceName attribute of the resulting object. If you do not pass a name parameter, the object/data structure returned by objects_from_file() will still be readable, but it will not be writable by docassemble questions.

There is also an optional keyword argument use_objects, which, if True, will cause lists to become gathered DALists, and dictionaries to become gathered DADicts.

Note that there is an initial block called objects from file that can be used as a shorthand way of calling objects_from_file(). Instead of writing:

---
mandatory: True
code: |
  claims = objects_from_file('claim_list.yml', name='claims')
---

you can instead write:

---
objects from file:
  - claims: claim_list.yml
---

Using your own object types

If you want to import objects that are not standard docassemble objects, you need to specify a module that defines the object’s class so that docassemble knows where to get the class definition.

For example, suppose you defined some classes with a Python module called fish.py:

from docassemble.base.util import DAObject

class Halibut(DAObject):
    pass

class Food(DAObject):
    pass

Suppose you want to import some objects of type Halibut. You can create a YAML file called fishes.yml with the following contents:

object: Halibut
module: .fish
items:
  - name: Fred Halibut
    scales: 500
    food:
      object: Food
      module: .fish
      items:
        - name: plankton
          calories: 5
  - name: Larry Halibut
    scales: 600
    food:
      object: Food
      module: .fish
      items:
        - name: seaweed
          calories: 2

Note the inclusion of module: .fish along with each object specifier. This indicates that the Halibut and Food classes are defined in the module .fish.

The following interview will import these two Halibut objects into the interview:

code: |
  fishes = objects_from_file("fishes.yml")
---
mandatory: true
question: |
  Fish summary
subquestion: |
  % for fish in fishes:
  ${ fish } has
  ${ fish.scales } scales.
  
  % endfor

Note that the . in front of the module name (.fish) is standard Python notation for indicating that the module is part of the current package. In this example, the interview lives in the docassemble.demo package, so we could have written the full module name, docassemble.demo.fish, instead of .fish.

To see how these separate files are able to find one another, check out the docassemble.demo package on GitHub and look for the following files:

The interview file, data/questions/examples/fish-example.yml
The Python module, fish.py
The YAML data file, data/sources/fishes.yml

How YAML files are located

When the interview calls objects_from_file('fishes.yml'), the objects_from_file() function looks for the file fishes.yml in the data/sources folder of the current package (or the sources folder if your interview is running in the Playground).

The objects_from_file() function can also be given explicit references. For example, calling objects_from_file('docassemble.demo:data/sources/fishes.yml') would have the same effect.

Preventing recursive object conversion

By default, objects_from_file() will comb through the data structure looking for objects to convert. If you only want it to convert objects that are specified in an associative array at the very top level, you can set the keyword parameter recursive to False.

code: |
  raw_data = objects_from_file("raw_data.yml", recursive=False)
---
mandatory: true
question: |
  The imported data
subquestion: |
  % for item in raw_data:
  The `inventory` of
  "${ item.title }" is:
  
  > `${ item.inventory }`
  
  % endfor

How objects are created

The objects_from_file() creates objects by passing keyword arguments to the object constructor. In the “fishes” example above, the first object was effectively created by calling:

Halibut(name='Fred Halibut', scales=500, food=[Food(name='plankton', calories=5)])

The second object was effectively created by calling:

Halibut(name='Larry Halibut', scales=600, food=[Food(name='seaweed', calories=2)])

Therefore, object attributes will only be initialized if the object supports initialization of attributes through keyword arguments passed to the constructor. All objects that are instances of the DAObject class have this property.

However, if you are using objects that are not DAObjects, but you want to make them compatible with objects_from_file(), you can include an __init__() method in your class that does the following:

class SwordFish:
    def __init__(self, **kwargs):
        for key, value in kwargs.iteritems():
            setattr(self, key, value)

You could also write your own custom code in __init__() that initiates the object attributes in special ways in response to keyword parameters.

You can use objects_from_file() to import other kinds of objects that allow initialization through keyword parameters. For example, datetime.datetime objects can be created by doing:

datetime.datetime(year=2017, month=4, day=1)

Thus, you could import a datetime.datetime object with the following YAML:

object: datetime
module: datetime
item:
  year: 2017
  month: 4
  day: 1

Importing group objects

To import a DAList, DADict, or DASet objects that contain items, set the elements attribute to a YAML list (in the case of a DAList or DASet or a YAML dictionary (in the case of a DADict).

Here is a sample YAML file that defines a DADict:

object: DADict
item:
  elements:
    apple: 4
    peach: 5
    orange: 10

Here is an interview that imports this file:

code: |
  fruitseeds = objects_from_file("fruitseeds.yml")
---
mandatory: True
question: |
  Summary of
  ${ fruitseeds.number_as_word() }
  fruit
subquestion: |
  % for fruit in fruitseeds:
  The seeds of ${ fruit } are
  ${ fruitseeds[fruit] }
  in number.
  
  % endfor

Screenshot of objects-from-file-dadict example

By default, any groups that are populated by importing will be marked as gathered. If you want docassemble to ask the user if more elements should be added, you can set the optional keyword argument gathered to False:

code: |
  fruitseeds = objects_from_file("fruitseeds.yml", gathered=False, name='fruitseeds')
---
question: |
  The fruits so far are ${ fruitseeds }.
  Are there more?
yesno: fruitseeds.there_is_another
---
question: |
  What fruit would you like to add?
fields:
  - Fruit: fruitseeds.new_item_name
  - Seeds: fruitseeds.new_item_value
---
mandatory: True
question: |
  Summary of
  ${ fruitseeds.number_as_word() }
  fruit
subquestion: |
  % for fruit in fruitseeds:
  The seeds of ${ fruit } are
  ${ fruitseeds[fruit] }
  in number.
  
  % endfor

Screenshot of objects-from-file-gather example

Avoiding problems with whitespace

If you include text in your YAML file and you wish to use this text within documents, you should understand a few rules about YAML.

This in YAML:

claim: |
  The landlord is not entitled
  to collect back rent.

becomes this in Python:

{'claim': 'The landlord is not entitled\nto collect back rent.\n'}

Note that the newline after the word “entitled” was treated literally (\n), and a newline was added at the end. This is not a problem when your text is treated as Markdown, because Markdown treats single newlines as though they were spaces and only breaks a line when it sees two newlines together. However, if you are inserting text into a docx template file, the newlines will cause paragraph breaks, which may be what you want, or it may not be what you want.

Here are some YAML tips that can help you out in situations like this.

This in YAML:

claim: |-
  The landlord is not entitled
  to collect back rent.

becomes this in Python:

{'claim': 'The landlord is not entitled\nto collect back rent.'}

Changing the quote mark from | to |- gets rid of the newline at the end, but not the one in the middle.

This in YAML:

claim: >
  The landlord is not entitled
  to collect back rent.

becomes this in Python:

{'claim': 'The landlord is not entitled to collect back rent.\n'}

The > treats newlines as spaces, but adds a newline at the end.

claim: >-
  The landlord is not entitled
  to collect back rent.

becomes this in Python:

{'claim': 'The landlord is not entitled to collect back rent.'}

The >- quote mark treats newlines as spaces and refrains from adding a newline at the end.

This in YAML:

claim: The landlord is not entitled to collect back rent.

becomes this in Python:

{'claim': 'The landlord is not entitled to collect back rent.'}

Similarly, this in YAML:

claim: "The landlord is not entitled to collect back rent."

also becomes:

{'claim': 'The landlord is not entitled to collect back rent.'}

The quotation marks do not change the text in this case. Quotation marks can still be useful, however, if your text contains any punctuation marks that have special meaning in YAML.

If you want literal quotation marks, you could use quotes within quotes:

This in YAML:

quotation: '"It was the best of times, it was the worst of times."'

becomes this in Python:

{'quotation': '"It was the best of times, it was the worst of times."'}

Similarly, this in YAML:

quotation: >-
  "It was the best of times, it was the worst of times."

also becomes:

{'quotation': '"It was the best of times, it was the worst of times."'}

For more information, see The YAML Format.

ocr_file()

Given a PDF file, ocr_file() uses optical character recognition (OCR) to read the text of the file. In the text returned, pages are separated by the form feed character.

mandatory: True
question: |
  Here is the text of the file
subquestion: |
  ${ ocr_file(the_file) }
---
question: |
  Please upload a file
fields:
  - File: the_file
    datatype: files

The first argument must be a DAFile or DAFileList object. If the argument is a DAFileList with more than one file, all files will be OCRed, and the text of all the pages will be returned.

The following optional keyword arguments affect the way OCR is performed.

language indicates the language of the document. If not specified, the language returned by get_language() is used. The language must be a lowercase ISO-639-1/ISO-639-3 code or a language code that Tesseract uses.
psm indicates the Tesseract page segmentation mode. The default is 6 (“assume a uniform block of text”). The choices are:
- 0: Orientation and script detection (OSD) only.
- 1: Automatic page segmentation with OSD.
- 2: Automatic page segmentation, but no OSD, or OCR.
- 3: Fully automatic page segmentation, but no OSD.
- 4: Assume a single column of text of variable sizes.
- 5: Assume a single uniform block of vertically aligned text.
- 6: Assume a single uniform block of text. (Default)
- 7: Treat the image as a single text line.
- 8: Treat the image as a single word.
- 9: Treat the image as a single word in a circle.
- 10: Treat the image as a single character.

In addition, the following optional parameters, which are passed to pdftoppm, customize the conversion of PDF files:

f indicates the first page of the PDF file to read. By default, all pages are read.
l indicates the last page of the PDF file to read. By default, all pages are read.
x: for cropping PDF pages. Indicates the x-coordinate of the crop area’s top left corner, in pixels. (By default, PDF files are converted at 300 dpi unless another value is given by the ocr dpi configuration directive.)
y: for cropping PDF pages. Indicates the y-coordinate of the crop area’s top left corner, in pixels.
W: for cropping PDF pages. Indicates the width of the crop area in pixels (default is 0).
H: for cropping PDF pages. Indicates the height of the crop area in pixels (default is 0).

If you want a PDF with embedded OCRed text, see the make_ocr_pdf() method of DAFile.

By default, the ocr_file() function uses Tesseract to do optical character recognition. Optionally, you can use Google Cloud Vision instead. To do so, call ocr_file() with the keyword parameter use_google=True.

ocr_file(the_file, use_google=True)

To get the raw output of the Google Cloud Vision API, set raw_result to True:

ocr_file(the_file, use_google=True, raw_result=True)

The output will then be a Python list of data structures returned from the Google Cloud Vision API. The format will be different depending on whether a PDF or other image was provided. Consult the Google Cloud Vision API to figure out what the data structures represent.

When use_google=True is used, none of the other keyword arguments (language, psm, f, l, etc.) are applicable. Those arguments are specific to the default Tesseract engine.

In order to use use_google=True, you need to follow the setup instructions for DAGoogleAPI. In addition, in your app in Google Cloud Console, under “APIs & Services,” you need to enable the APIs for Google Cloud Vision and Google Cloud Storage. In addition, you need to provide the name of a bucket in Google Cloud Storage that ocr_file() can use to do its work.

google:
  work bucket: some-unique-name-a28b3d97d

The ocr_file() will create this bucket in your Google Cloud Storage if it does not already exist. It needs this bucket in order to temporarily store files for use by the Google Cloud Vision API. Unless something goes wrong, it will delete the files it writes to the bucket.

Note that Google Cloud Vision is not necessarily faster than the Tesseract OCR engine, so you may need to use ocr_file_in_background() (which also accepts the use_google=True keyword parameter`).

ocr_file_in_background()

Note that the OCR process usually takes a long time; it takes a lot of computational power to recognize characters from a graphical image. Unless the document is only one page long, the user will have to wait, looking at a spinner, for what may be an inconvenient period of time. The user may think that the application has crashed.

The best practice is to run OCR tasks in the background, using the ocr_file_in_background() function. This function is a cross between ocr_file() and background_action().

To control the details of the OCR process, you can set optional keyword parameters language, psm, x, y, W, and H. (See ocr_file() for information about what these do.)

Like background_action(), it immediately returns an object representing a background task. You can call .ready() on this object to see if the task is still running in the background, and you can call .get() to obtain the result of the OCR task. (See background_action() for more information about these methods.)

Here is an example of how ocr_file_in_background() can be used.

mandatory: true
code: |
  the_task
  final_screen
---
code: |
  the_task = ocr_file_in_background(the_file)
---
question: |
  Please upload one or more files.
fields:
  - File: the_file
    datatype: files
---
question: |
  What is your nickname?
fields:
  - Nickname: nickname
---
event: final_screen
question: |
  Here is the text of the uploaded
  file, ${ nickname }.
subquestion: |
  % if the_task.ready():
  The text is: ${ the_task.get() }
  % else:
  Still processing.  Please press Refresh
  after a few seconds to see if the task
  is done.
  % endif
buttons:
  - Refresh: refresh

This example demonstrates a technique for avoiding making the user wait. First, the user uploads a document. Then, ocr_file_in_background() is called on the uploaded file, which starts the OCR process in the background. Then, the user is asked a question (“What is your nickname?”). Then is the user sent to a screen that displays the text obtained through OCR. Hopefully, the question about the nickname took enough time that the results of the OCR are ready by the time this screen appears in the interview. Just in case there wasn’t enough time, the interview question calls .ready() to check to see if the task is done. If it is not done, the user is asked to wait, and to press “Refresh.” If the process has completed by then, .ready() will be True, and the user can see the text obtained through OCR.

It is safe to call .get() without first ensuring that .ready() is True. The .get() method will cause the system to wait until the OCR text is available. The user will see a spinner in the meantime.

Other questions could be asked, in addition to the nickname question, in order to give the computer more time to finish the OCR process.

If you do not want to stall for time by asking questions, but you want to give the user a user-friendly screen to look at while they wait and you don’t want to make the user press a Refresh button, you can use the optional second argument to the ocr_file_in_background() function. This second argument acts like the second argument to background_action(). In this example, we set it to refresh:

mandatory: true
code: |
  the_files
  if the_task.ready():
    final_screen
  else:
    waiting_screen
---
code: |
  the_task = ocr_file_in_background(the_files, 'refresh')
---
event: waiting_screen
question: |
  Please wait.
subquestion: |
  Your document is being processed.
  This may take several minutes.

  The text of your document will be
  shown on the screen when the
  processing is finished.
---
event: final_screen
question: |
  Here is the text of the uploaded
  file.
subquestion: |
  ${ the_task.get() }
---
question: |
  Please upload one or more files.
fields:
  - File: the_files
    datatype: files

Be careful about combining the use of refresh with the method of asking questions of the user to pass the time. If any of the questions call for the user to type something in, the user will be very annoyed if the screen refreshes while they are typing; they will lose what they have typed. However, if you are only asking questions that require buttons to be pressed, then the user will not notice if the screen refreshes.

You can also use other notification methods, such as:

ocr_file_in_background(the_file, 'javascript', message='all done')
ocr_file_in_background(the_file, 'flash', message='All done')

These notification methods show a Javascript alert or a message “flashed” at the top of the screen when the background task is complete. The message is “OCR succeeded” unless you override the message using the optional keyword argument message.

See the documentation of background_action() for more information about notification methods.

The value returned by .get() is an object, not a piece of text. If the attribute .ok is True, the text can be found in the .content attribute of this object. If the attribute .ok is False, then there was an error during the OCR process, and the error message can be found in the attribute .error_message. When you put the output of .get() inside of a ${ ... } Mako tag, the object is forced to be text, in which case either .content or .error_message is used, depending on the success of the OCR process.

By default, ocr_file_in_background() uses Tesseract as the OCR engine. Optionally, you can use Google Cloud Vision as an OCR engine by passing use_google=True as a keyword parameter to ocr_file_in_background(). For more information about setting this up, see the documentation about use_google=True in ocr_file().

If you want a PDF with embedded OCRed text, see the make_ocr_pdf_in_background() method of DAFile.

Advantages of `ocr_file_in_background()` over `ocr_file()`

Note that it is also possible to use ocr_file() within background_action():

mandatory: True
code: |
  the_file
  the_task
  user_testimonial
  if not the_task.ready():
    waiting_screen
---
question: |
  Please upload a file
fields:
  - File: the_file
    datatype: files
---
code: |
  the_task = background_action('ocr_start', None)
---
event: ocr_start
code: |
  the_text = ocr_file(the_file)
  background_response_action('ocr_finish', text=the_text)
---
event: ocr_finish
code: |
  text_of_the_file = action_argument('text')
  background_response()
---
question: |
  How do you describe what happened?
fields:
  - no label: user_testimonial
    input type: area
---
event: waiting_screen
reload: 5
question: |
  Please wait.
---
mandatory: True
question: |
  All done
subquestion: |
  You claim that:

  ${ quote_paragraphs(user_testimonial) }

  The document states:

  ${ quote_paragraphs(text_of_the_file) }

However, the advantage of ocr_file_in_background() is that it can be a lot faster if there is more than one page image. The ocr_file() function OCRs one page at a time, using a single CPU core. The ocr_file_in_background() function, by constrast, assigns each page image to a separate background task, and these tasks are then distributed across all the CPU cores in your system. If your docassemble installation has two application servers, each with four CPU cores, the system will process the OCR job eight pages at a time rather than one page at a time. For a large document, ocr_file_in_background() will get the whole job done much faster.

Running OCR with languages other than English

Tesseract supports the following languages.

Code	Language
`afr`	Afrikaans
`ara`	Arabic
`aze`	Azerbaijani
`bel`	Belarusian
`ben`	Bengali
`bul`	Bulgarian
`cat`	Catalan
`ces`	Czech
`chi-sim`	Simplified Chinese
`chi-tra`	Traditional Chinese
`chr`	Cherokee
`dan`	Danish
`deu`	German
`deu-frak`	German Fraktur
`ell`	Greek
`eng`	English
`enm`	Middle English
`epo`	Esperanto
`est`	Estonian
`eus`	Basque
`fin`	Finnish
`fra`	French
`frk`	Frankish
`frm`	Middle French
`glg`	Galician
`grc`	ancient Greek
`heb`	Hebrew
`hin`	Hindi
`hrv`	Croatian
`hun`	Hungarian
`ind`	Indonesian
`isl`	Icelandic
`ita`	Italian
`ita-old`	Old Italian
`jpn`	Japanese
`kan`	Kannada
`kor`	Korean
`lav`	Latvian
`lit`	Lithuanian
`mal`	Malayalam
`mkd`	Macedonian
`mlt`	Maltese
`msa`	Malay
`nld`	Dutch
`nor`	Norwegian
`pol`	Polish
`por`	Portuguese
`ron`	Romanain
`rus`	Russian
`slk`	Slovak
`slk-frak`	Slovak Fractur
`slv`	Slovenian
`spa`	Spanish
`spa-old`	Old Spanish
`sqi`	Albanian
`srp`	Serbian
`swa`	Swahili
`swe`	Swedish
`tam`	Tamil
`tel`	Telugu
`tgl`	Tagalog
`tha`	Thai
`tur`	Turkish
`ukr`	Ukranian
`vie`	Vietnamese

The language parameter is flexible; you can set it to a language code that Tesseract supports (e.g., eng, chi-sim, chi-tra, slk-frak), or you can give it a two-character ISO-639-1 code, in which case docassemble will convert it to the corresponding Tesseract code. If Tesseract does not support the language, English will be used. If the language parameter is not supplied, docassemble will use the default language (the result of get_language()).

For some languages, there is more than one variant. For example, if you specify Chinese, zh, docassemble will use chi-tra (traditional Chinese). If this is not what you want, you can specify an explicit language parameter, such as chi-sim (simplified Chinese). Alternatively, you can override the mapping between ISO-639-1 codes and Tesseract codes by editing the ocr languages directive in the configuration. For example, if you wanted all Chinese to be interpreted as Simplified Chinese, and all Uzbek to be interpreted as the Cyrillic form, you could set the following:

ocr languages:
  zh: chi-sim
  uz: uzb-cyrl

path_and_mimetype()

The path_and_mimetype() function returns a tuple consisting of a file path and MIME type for a given reference to a file.

The function works with a variety of file references, including:

A DAFile object;
A file number (see DAFile);
A reference to a file in the current package (e.g., data/sources/training-data.json);
A reference to a file in a particular package (e.g., docassemble.demo:data/static/crown.png); or
A URL to a file on the Internet.

If the reference is to a file on the Internet, the file will be downloaded to a temporary file.

code: |
  (filename_a, mimetype_a) = path_and_mimetype('data/static/hello.pdf')
  (filename_b, mimetype_b) = path_and_mimetype('docassemble.demo:data/static/house.png')
  (filename_c, mimetype_c) = path_and_mimetype('https://docassemble.org/img/docassemble-logo.jpg')
---
mandatory: True
question: |
  File locations and MIME types
subquestion: |
  #### `data/static/hello.pdf`

  Path **${ filename_a }** has
  MIME type **${ mimetype_a }**.

  #### `docassemble.demo:data/static/house.png`

  Path **${ filename_b }** has
  MIME type **${ mimetype_b }**.

  #### `https://docassemble.org/img/docassemble-logo.jpg`

  Path **${ filename_c }** has
  MIME type **${ mimetype_c }**.

Paths retrieved through path_and_mimetype() can be used by Python functions right away.

Note, however, that paths obtained from DAFile objects, file numbers, and URLs, will not necessarily be stable from request to request. If you save a path to a variable at one time, and expect to use it later in a subsequent question, you may find that the path does not exist. This is because temporary files can be deleted, and subsequent user screens may be handled by different servers.

If you want a file that persists from request to request, you should store its contents to a DAFile object. When a DAFile object is assigned to a variable, you can reliably obtain the file path by calling the .path() method on the variable.

The path_and_mimetype() function can be used along with the .set_mimetype() and .copy_into() methods of the DAFile class in order to save files to DAFile objects.

The following interview retrieves an image from the Internet and saves it to a variable logo, which is a DAFile object.

mandatory: True
objects:
  - logo: DAFile
---
code: |
  url = 'https://docassemble.org/img/docassemble-logo.jpg'
  (filename, mimetype) = path_and_mimetype(url)
  logo.set_mimetype(mimetype)
  logo.copy_into(filename)
---
field: initial_screen
question: |
  Obtained file
subquestion: |
  The URL [${ url }](${ url })
  has been saved to a file.

  It has a MIME type of
  ${ mimetype }.

  Click "Continue" to see it.
---
mandatory: True
need: initial_screen
question: |
  Here is the file.
subquestion: |
  ${ logo }

run_python_module()

The run_python_module() runs a Python module as though it were being run from the command line, and returns the output of the command (standard output as well as standard error) along with the return code from running the command.

The first argument, which is required, is the name of the module. This can be expressed in a few ways. If it is the name of a file ending in .py, it is assumed to be a module in the same package as the interview file. Or, if you are using the Playground, it is assumed to be a file in the modules folder. The module file is executed as you would execute a module file by using python modulename.py from the command line. If the first argument is the name of a module, that module will be run, much as you would execute a module by using python -m modulename from the command line.

The function returns a tuple of two variables: the output of the command (text) and the return value (an integer). If the command was successful, the return value will be zero.

The following three example interviews refer to a very simple Python module file, hello.py. The contents of this file are:

print "Hello, world!"

The interviews and the hello.py module are all in the docassemble.demo package.

The first example refers to the .py file:

code: |
  output, return_code = run_python_module('hello.py')
---
mandatory: True
question: |
  ${ output }

The second example refers to the same Python module, but by its full module name:

code: |
  output, return_code = run_python_module('docassemble.demo.hello')
---
mandatory: True
question: |
  ${ output }

The third example refers to the same Python module, but using a relative module name instead of a full module name:

code: |
  output, return_code = run_python_module('.hello')
---
mandatory: True
question: |
  ${ output }

Note that the first example and the third example only work because the interviews and the module are in the same package.

When calling run_python_module(), you can also include an optional second argument, which must be a list of command line arguments to be passed to the module.

The following example demonstrates how you can use run_python_module() to run unit tests using the standard unittest framework. The interview, the tests.py file it refers to, and the my_name_suffix module that is being tested in tests.py, are all in docassemble.demo package.

The command line argument -v results in “verbose” output.

code: |
  output, return_code = run_python_module('tests.py', ['-v'])
---
mandatory: True
question: |
  Result of unit tests
subquestion: |
  % if return_code == 0:
  Command succeeded.
  % else:
  Command failed!
  % endif
  
  ${ indent(output) }

Screenshot of run-python-module-tests example

The indent() function is used here because it indents each line in the output by four spaces. In Markdown, this causes the text to be displayed in a monospace font.

pdf_concatenate()

The pdf_concatenate() function accepts one or more file objects (DAFile, DAStaticFile, DAFileList, or DAFileCollection) as input (raw file paths are also accepted) and returns a DAFile containing the files concatenated into a single PDF file. Image files and word processing files (.doc, .docx, .rtf, and .odt) will be converted to PDF. If any of the arguments is a list, it will be unpacked.

objects:
  - static_file: DAStaticFile.using(filename='star.pdf')
---
attachment:
  variable name: assembled_file
  filename: assembled_file
  content: |
    Hello world!
---
question: |
  Upload a file
fields:
  - File: uploaded_file
    datatype: file
---
mandatory: True
code: |
  output_file = pdf_concatenate(uploaded_file, assembled_file, static_file, filename="result.pdf")
---
mandatory: True
question: |
  Here is your concatenated file.
subquestion: |
  ${ output_file }

pdf_concatenate() supports the following optional keyword parameters:

filename: if provided, this will be the name of the resulting file. If not provided, the file will be named file.pdf.
pdfa: if True, the PDF file will be converted to PDF/A format. The default is False.
password: if provided, the PDF file will be protected. If password is a string, the password will be a “user password.” To supply an “owner password,” you can set password=[owner_pw, user_pw] or password={'owner': owner_pw, 'user': user_pw}.
output_to: if this refers to a DAFile object, the output of pdf_concatenate() will be saved to this DAFile. By default, pdf_concatenate() returns a new DAFile with a random instance name.

docx_concatenate()

The docx_concatenate() function accepts one or more file objects (DAFile, DAStaticFile, DAFileList, or DAFileCollection) as input (raw file paths are also accepted) and returns a DAFile containing the files concatenated into a single DOCX file. Only word processing files (.doc, .docx, .rtf, and .odt) are accepted. If any of the arguments is a list, it will be unpacked.

docx_concatenate() takes an optional keyword parameter filename, which, if provided, will be used as the name of the resulting file. If no filename is provided, the file will be named file.docx.

docx_concatenate() takes an optional keyword parameter output_to, which, if provided, will be used as the DAFile object to which the output of docx_concatenate() will be stored. By default, docx_concatenate() returns a new DAFile with a random instance name.

overlay_pdf()

The overlay_pdf() function overlays a single page from a PDF file on top of the pages of another PDF file.

It has two mandatory parameters: a main document, and an overlay document. The parameters can be DAFileCollection, DAFileList, or DAFile objects. They can also be file paths for files on the file system.

The function returns a DAFile containing a PDF file where the first page of the overlay document has been superimposed on top of the main document.

question: |
  What is your favorite fruit?
fields:
  - Fruit: favorite_fruit
---
question: |
  What is your favorite vegetable?
fields:
  - Vegetable: favorite_vegetable
---
question: |
  Upload your company logo.
fields:
  - Logo: logo_image
    datatype: file
---
attachment:
  variable name: logo_page
  docx template file: logo_template.docx
---
attachment:
  variable name: the_document
  docx template file: food_template.docx
---
mandatory: True
question: |
  Here is your document.
subquestion: |
  ${ overlay_pdf(the_document, logo_page) }

The overlay_pdf() function accepts several optional keyword parameters. If you only want to overlay on top of some of the pages of the main document, you can indicate a first_page and/or a last_page, which will instruct overlay_pdf() to start at a given page number and/or end at a given page number. By default, overlay_pdf() starts on the first page and ends on the last page. If you only want to overlay over even-numbered pages, set only to 'even'. If you only want to overlay over odd-numbered pages, set only to 'odd'.

If your document containing the logo has more than one page, you can specify which page to use by setting logo_page to the page number of the page you want to use.

The optional keyword parameter multi is used when you want to overlay two PDF files with the same number of pages on top of one another. (That is, page 1 of document A will be overlayed with page 1 of document B, page 2 of document a will be overlayed with page 2 of document B, etc.)

question: |
  Upload a PDF file.
subquestion: |
  Page numbers will be overlayed on your PDF.
fields:
  - File: the_doc
    datatype: file
---
attachment:
  variable name: overlay_doc
  docx template file: numbering_template.docx
---
mandatory: True
question: |
  Here is your document.
subquestion: |
  ${ overlay_pdf(the_doc, overlay_doc.pdf, multi=True) }

When multi=True is used, the first_page, last_page, only, and logo_page parameters are disregarded.

overlay_pdf() takes an optional keyword parameter output_to, which, if provided, will be used as the DAFile object to which the output of overlay_pdf() will be stored. By default, overlay_pdf() returns a new DAFile with a random instance name.

zip_file()

The zip_file() function is like the pdf_concatenate() function, except it returns a ZIP file archive of the files.

zip_file() has two optional keyword parameters:

filename: if provided, this will be the name of the resulting file. If not provided, the file will be named file.zip.
output_to: if this refers to a DAFile object, the output of zip_file() will be saved to this DAFile. By default, zip_file() returns a new DAFile with a random instance name.

If you want your zip file to include file structure, you can pass a Python dictionary as a parameter, and they keys of the dictionary will be folder names.

The following example results in a ZIP file called “Image files.zip” that contains an uploaded file and a folder called assets that contains two files from the “static” folder of the interview’s package.

objects:
  - coins_picture: DAStaticFile.using(filename='coins36.png')
---
question: |
  Please upload a picture of yourself.
fields:
  - Picture: user_picture
    datatype: file
---
mandatory: True
question: |
  Here is your ZIP file.
subquestion: |
  ${ zip_file(user_picture, {'assets': [coins_picture, 'cow.jpg'] }, filename="Image files.zip") }

log()

The log() function allows you to log a message to the server log, to the browser console, or to the user’s screen.

The first parameter is the message you want to send. The second parameter, which is optional, is the “priority” of the message. The default priority is 'log'.

mandatory: True
code: |
  log("Hello, user!", "info")
  log("Lookout, user!", "danger")
---
mandatory: True
decoration: coins
question: |
  The interview is complete.

The options for the priority are:

'log' - a message is immediately logged to the server logs.
'console' - when the next screen loads in the user’s browser, the message will appear in the browser log. (This uses the console.log JavaScript function.)
'javascript' - like 'console', except that the contents of the “message” will be passed to the eval JavaScript function instead of the console.log JavaScript function. This allows you to log a message in the front end in your own custom fashion. It can also be used for tasks other than logging messages.
'success' - when the next screen loads in the user’s browser, a popup message (a Bootstrap alert) will appear at the top of the page, using the Bootstrap color associated with “success” (typically green). The message will disappear after a few seconds.
'info' - like 'success', except it uses the “info” Bootstrap color. The message will not disappear.
Other Bootstrap color names besides 'info' and 'success'.

The Bootstrap color names are as follows:

primary

secondary

success

danger

warning

info

light

dark

You can also use the JavaScript function flash() to display notifications like this.

encode_name()

In the HTML of the web interface, input elements for variables are base64-encoded versions of the Python variable names.

The encode_name() function converts a variable name to base64 encoding.

>>> encode_name('favorite_fruit')
'ZmF2b3JpdGVfZnJ1aXQ'

For more information about the relationship between HTML and the setting of variables, see the discussion in the section on custom front ends.

decode_name()

The decode_name() function does the opposite of encode_name(): it converts a variable name from base64 encoding to plain text.

>>> decode_name('ZmF2b3JpdGVfZnJ1aXQ')
'favorite_fruit'

mmdc()

Using the mmdc() function, you can use the mermaid diagram-drawing system to produce a DAFile containing a completed diagram.

The mmdc() function is defined in the docassemble.base.mermaid package. To use it, you will need to include the docassemble.base.mermaid module in your interview:

modules:
  - docassemble.base.mermaid

Then you can call the mmdc() function on a text string or a template object.

modules:
  - docassemble.base.mermaid
---
template: diagram
content: |
  graph TD;
      ${ a }-->${ b };
      ${ a }-->${ c };
      ${ b }-->${ d };
      ${ c }-->${ d };
---
question: Give me some names.
fields:
  - A: a
    default: A
  - B: b
    default: B
  - C: c
    default: C
  - D: d
    default: D
---
mandatory: True
question: |
  Here is your diagram.
subquestion: |
  ${ mmdc(diagram, file_format='png') }

If you installed docassemble with the standard Docker installation, then the mermaid executable (mmdc) should be available on the standard system path. You can set a precise location by setting the mmdc path directive in the Configuration.

mmdc path: /var/www/node_modules/.bin/mmdc

transform_json_variables()

transform_json_variables() is a function that is used by set_session_variables() when process_objects is enabled.

It recursively traverses the data structure it is given, transforming dictionaries of the form generated by .as_serializable() into DAObject instances, and strings that look like dates/times in into datetime objects.

Functions for working with SMS messages

send_sms()

The send_sms() function is similar to send_email(), except it sends a text message (also known as an SMS message). This requires a Twilio account.

All of its arguments are keyword arguments, the defaults of which are:

send_sms(to=None, body=None, template=None, task=None, attachments=None, config='default')

to expects a list of recipients. The list can consist of Individuals (or any other Persons), objects of type phonenumbers.PhoneNumber, or a simple string containing a phone number. If the number begins with whatsapp:, then WhatsApp will be used to send the message. If the recipient is a Person, then the sms_number() method will be used to obtain the person’s number.
body expects text, or None. If provided, it will be the content of the message. Markdown will be converted to plain text.
template expects a template object, or None. These templates can be created in an interview file using the template specifier. The “subject” of the template, if provided, will be the first line of the message.
task expects the name of a task. If this argument is provided, and if sending the text message is successful, the task will be marked as having been performed (i.e., mark_task_as_performed() will be called). Alternatively, you can handle this in your own code, but you might find it convenient to let the send_email() function handle it for you.
task_persistent: if you set a task, you can optionally set the “persistence” of the task by setting this to True or a value like 'user'. For more information, see the documentation for the task-related functions.
attachments expects a list of DAFile objects, DAFileList objects, DAFileCollection objects, or ordinary URLs. If provided, the message will be an MMS message containing the attached files. No more than 10 attachments may be added. You can include:
- Images generated by signature blocks (objects of class DAFile);
- File uploads generated by including fields of datatype: file or datatype: files in a question (objects of class DAFileList);
- Documents generated by attachments to a question for which a variable was provided (objects of class DAFileCollection).
config indicates the section of the twilio configuration that should be used when sending the text message. If you only have one Twilio phone number, you do not need to set this parameter. This will determine which Twilio phone number will be used to send the text.
dry_run can be set to True if you want to do a “dry run” of the SMS sending process. You would use this if you wanted to make sure that all of the variables send_sms() needs are defined before you actually send the SMS message. The default is False.

When the recipients are Individuals or Persons, the mobile_number attribute will be used, but only if it already exists. Otherwise, the phone_number attribute will be used, and sought if it is not already defined.

Note that Twilio expects the phone number to be expressed in E.164 format, which includes the country calling code (e.g., 1 for the United States). However, users do not typically write phone numbers in such a way. Therefore, the phonenumbers package is used to convert phone numbers to E.164 based on the applicable country. If an Individual or Person is the recipient, the country attribute, if it exists, will be used to determine the country. Otherwise, the get_country() function is used to determine the applicable country. Your interview can use set_country() in initial code to set a default country, or you can set a default on a server level by setting the country configuration directive. The country must be specified as a two-letter, capitalized abbreviation (ISO 3166-1 alpha-2 format).

send_sms() returns False if an error prevented the message from being sent; otherwise it returns True.

See the twilio configuration directive for information about how to configure that send_sms() will use.

get_sms_session()

When someone sends a text message to one of your Twilio numbers, the SMS interface is invoked. The interview session is tracked based on the user’s phone number and the Twilio number with which the user interacts.

The function get_sms_session() retrieves session information and returns it in the form of a Python dictionary with the following keys:

yaml_filename - the name of the interview; e.g., docassemble.demo:data/questions/questions.yml.
uid - the session ID
secret - the encryption key for decrypting the interview answers
encrypted - a True or False value indicating whether the interview answers are encrypted.
email - the e-mail address of the user. If the user is not authenticated, this is None. Note that authentication of SMS users is only possible if the interview session is started with initiate_sms_session().

The get_sms_session() functions takes an optional keyword argument config, which indicates a section of the twilio configuration that should be used. A single SMS user can have multiple sessions with the SMS interface if there is more than one twilio configuration directive.

initiate_sms_session()

The initiate_sms_session() function is used to bring someone into an interview using the SMS interface.

In its simplest form, initiate_sms_session("202-555-1212") will send an SMS message to 202-555-1212, where the body of the message is the current question in the interview.

The following optional keyword arguments alter the way the function works:

yaml_filename - this controls which interview the SMS user will be placed into. If yaml_filename is not specified, the current interview will be used.
email - this controls the identity of the SMS user in user login system, which may affect the interview questions that the SMS user sees. If email is not specified, the SMS user will have the same identity as the user who was using the interview when the call to initiate_sms_session() was made.
new - this controls whether the SMS user will join an ongoing interview session or start a fresh session. Set this to True if you want the SMS user to start a fresh session. If new is not specified, the SMS user will join the session that was ongoing when the call to initiate_sms_session() was made.
send - this controls whether the invitation message should be sent or not. If send is not specified, the message will be sent. Set this to False to suppress sending the message. If send is False, the SMS session will still be created. The fact that the session is created means that if an SMS message is received from the given phone number, the SMS user will receive a response as if the interview session had already been started. The user’s initial message will not be interpreted as a choice of an interview from the dispatch section of the twilio configuration.
config - this controls which Twilio phone number is used for communication. You would only need to use this if you have more than more than one twilio configuration directive set up in your configuration.

If you are not using new=True, note that there may be a delay between the time the message is sent to the SMS user and the time the SMS user sees the message and responds. The SMS user will join the interview at whatever state the interview session is in at the time the SMS user responds. docassemble does not make a copy of the interview state when the call to initiate_sms_session() is made.

Here is an example interview that solicits input through SMS.

mandatory: True
code: |
  if interface() == 'sms':
    how_many_apples
    all_done_sms
  if ok_to_initiate and session_initiated:
    all_done_web
---
question: |
  How many apples are there?
fields:
  - no label: how_many_apples
    datatype: integer
---
sets: all_done_sms
question: |
  Thank you!
---
question: |
  What phone number should be used?
fields:
  Phone Number: phone_number
---
question: |
  Ready to send a message to
  ${ phone_number }.
field: ok_to_initiate
---
code: |
  initiate_sms_session(phone_number)
  session_initiated = True
---
sets: all_done_web
question: |
  All done.
subquestion: |
  % if defined('how_many_apples'):
  Visitor said there are ${ how_many_apples } apples.
  % else:
  We have not heard from the visitor yet.
  % endif
buttons:
  - Check: refresh

terminate_sms_session()

The terminate_sms_session() function will terminate the current session, if any, for a given phone number.

terminate_sms_session("202-555-1212")

After the above code executes, then if a message is received from 202-555-1212, it will be treated as a selection of an interview from the dispatch section of the twilio configuration. If the SMS user had been in the middle of an interview session, the user will not be able to get back to that session again.

Storing data

With Redis

If you do not know what a Redis server is, skip this section!

The background processes feature of docassemble depends on a Redis server being available. The server is also used to facilitate live chat.

Interview developers may want to make use of the Redis server for purposes of storing information across users of a particular interview, keeping usage statistics, or other purposes.

objects:
  r: DARedis
---
mandatory: True
code: |
  key = r.key('my_variable')
  r.set(key, 'hello world')
---
mandatory: True
question: |
  Value has been retrieved from
  the redis server.
subquestion: |
  The key is `${ key }`.
  
  The value is "${ r.get(key).decode() }".

To use the Redis server, use an objects section to create an object of type DARedis. This object can now be used to communicate with the redis server, much as though it had been created by calling redis.StrictRedis().

With SQL

Since Redis is an in-memory database, it is not appropriate for long-term storage or for the storage of large amounts of data.

An alternative is to store data in SQL. docassemble provides an object called DAStore that is similar to DARedis, except it uses SQL instead of Redis, and it supports encryption.

objects:
  - userdata: DAStore
  - preferences: DAObject
---
code: |
  if userdata.defined("prefs"):
    preferences = userdata.get("prefs")
---
question: |
  What is your favorite fruit?
fields:
  - Fruit: preferences.favorite_fruit
---
mandatory: True
code: |
  preferences.favorite_fruit
  if not userdata.defined("prefs"):
    userdata.set("prefs", preferences)
---
mandatory: True
code: |
  final_screen
---
event: final_screen
question: All done
subquestion: |
  Your favorite fruit is
  ${ userdata.get("prefs").favorite_fruit }.

In the above example, the user’s preferences are stored in the database using a key that is specific to the user. The first time the user uses the interview, the user is asked for their favorite fruit. If the user restarts the interview (which permanently erases the interview answers), the user’s favorite fruit will be retrieved from the DAStore, and it will not need to be asked of the user. The object stored in the database is a DAObject, and the favorite fruit is an attribute of that object. In the database, the object is stored under key called prefs. This key is specific to the user, so that each user will have their own personal prefs entry in the database.

For more information, see the DAStore documentation.

write_record(), read_records(), and delete_record()

There are also three functions, write_record(), read_records(), and delete_record(), for managing data in SQL. These functions are useful when you want to store a list of one or more “records” under a single “key.” Encryption is not used.

mandatory: True
code: |
  write_record('fruit', favorite_fruit)
---
reconsider: True
code: |
  fruit_summary = ''
  records = read_records('fruit')
  for id in records:
    fruit_summary += "* " + str(records[id]) + "\n"
---
mandatory: True
question: |
  Contents of database
subquestion: |
  The following fruits have
  been reported:
  
  ${ fruit_summary }

When you call write_record(key, data), the variable data is stored in a SQL database. The function returns the integer unique ID for the record. The data variable can be any type of data, such as a number, some text, an object, a Python dictionary, or something else. The only limitation is that the information in the variable needs to be able to be pickled.

When you call read_records(key), you will retrieve all of the records that had been stored using that key. The function returns a Python dictionary where the keys are integers representing the unique ID of the record.

You can delete records by calling delete_record(key, id) where key is the key under which the record was saved and id is the unique ID integer of the record.

Note that all interviews on the server will have access to the data stored with write_record(), and the data are not encrypted on the server. It is important to choose your key names wisely because if you use a simple name like mydata, another interview developer might have chosen the same key, and then your data will become intermingled. It is a good idea to include your interview package name in the key names you choose.

docassemble will attempt to sanitize data you pass to write_record() by converting any item that cannot be pickled to None.

Example of using stored objects with write_record()

Suppose you have an interview that your user might complete several times for different situations, but you do not want the user to have to re-enter the same information more than once. You can use read_records() and write_record() to accomplish this.

Here is an example:

metadata:
  title: Side of the bed
---
code: |
  user_key = 'workers_comp_user:' + user_info().email
---
objects:
  - user: Individual
---
code: |
  saved_records = read_records(user_key)
  for id in saved_records:
    user = saved_records[id]
---
mandatory: True
code: |
  if not user_logged_in():
    command('leave', url=url_of('login', next=interview_url()))
  first_part_finished
  user_info_saved
  interview_finished
---
question: |
  Thanks for all that information!
subquestion: |
  We now know that your name is
  ${ user },
  your favorite fruit is
  ${ user.favorite_fruit },
  and you woke up on the
  ${ side_of_bed }
  side of the bed this morning.
field: first_part_finished
---
question: |
  What is your name?
fields:
  - First name: user.name.first
  - Last name: user.name.last
---
question: |
  What is your favorite fruit?
fields:
  - Fruit: user.favorite_fruit
---
question: |
  On which side of the bed did you
  wake up this morning, ${ user }?
field: side_of_bed
choices:
  Right side: right
  Wrong side: wrong
---
event: interview_finished
question: |
  Ok, go eat some
  ${ user.favorite_fruit },
  ${ user }.
subquestion: |
  Perhaps you will wake up on
  the ${ side_of_bed } side of
  the bed tomorrow, too.
buttons:
  - Exit: leave
    url: ${ url_of('dispatch') }
---
code: |
  for id in read_records(user_key):
    delete_record(user_key, id)
  write_record(user_key, user)
  set_parts(title=capitalize(side_of_bed) + " side of the bed")
  session_tags().add(side_of_bed)
  user_info_saved = True

The first time the user goes through the interview, the interview will ask for the user’s name and favorite fruit. The second time the user goes through the interview, the interview does not ask for the name and favorite fruit, because it already knows the information – even though the user’s second interview is a separate session with a separate, isolated set of interview answers.

The interview accomplishes this using write_record() and read_records().

When the interview is done asking questions, it calls write_record() to store the object user to SQL. It records this information using a unique “key” that is based on the e-mail address of the user (e.g., workers_comp_user:[email protected]). To get the e-mail address of the user, the interview requires the user to log in, and uses user_info().email to get the e-mail address.

Whenever the interview starts, the interview first checks to see if anything has been stored under the unique “key.” If there is something stored, then the user object is retrieved from storage. If there is nothing stored, user is initialized as an object of type Individual.

Note that the timing of when user is stored is important. The write_record() function will store a “snapshot” of the object, so if user is stored before the necessary information (name and favorite fruit) have been gathered, then the interview will not work as intended.

Here is the code that initializes the user object:

objects:
  - user: Individual
---
code: |
  saved_records = read_records(user_key)
  for id in saved_records:
    user = saved_records[id]

Note that neither of these blocks is mandatory; when the interview needs to know the definition of user, it will try the code block first (because it is later in the YAML). If user is still undefined, the interview will “fall back” to trying the objects block, which will initialize a fresh object of class Individual.

The read_records() function always returns a Python dictionary, because you can store more than one record under a single key. But in this interview, we are only storing one record under the key user_key.

The interview logic starts with forcing the user to log in:

mandatory: True
code: |
  if not user_logged_in():
    command('leave', url=url_of('login', next=interview_url()))
  first_part_finished
  user_info_saved
  interview_finished

The command() line redirects the user to the sign-in page, but tells the sign-in page that when the user logs in, the user should be directed back to the same interview.

The reference to user_info_saved before interview_finished ensures that before the user sees the last screen of the interview, some code is run that saves the user object to storage.

The code block that defines user_info_saved looks like this:

code: |
  for id in read_records(user_key):
    delete_record(user_key, id)
  write_record(user_key, user)
  set_parts(title=capitalize(side_of_bed) + " side of the bed")
  session_tags().add(side_of_bed)
  user_info_saved = True

First, the code deletes any existing records under user_key, and then stores the user object. This means that even if the interview session started off by retrieving user from storage, it will save a new copy of the user object to storage. Thus, the interview can make changes to the user object if necessary, and those changes will be saved.

This interview also uses set_parts() and session_tags() to change the title and tags of the interview, so that when the user goes to “My Interviews,” the user will see a different title and different tags based on their interview answers. Using a technique like this might help your users in case your users want to resume their interview session.

Now, suppose you have a variety of interviews, all of which relate to the same topic (e.g., workers compensation). If any one of these interviews is the first interview that the user uses, you want the basic questions (name, favorite fruit) to be asked. And if the user launches another interview, you don’t want to re-ask those basic questions.

You can do this using interviews like the above, but each interview would need to contain the same blocks that force the user to log in, retrieves user from storage, saves user to storage at the end, etc. It is inconvenient to maintain the same code in several different files.

You can avoid this problem by using include. You can create a “common” YAML file called wc_common.yml, which contains the following:

objects:
  - user: Individual
---
code: |
  user_key = 'workers_comp_user:' + user_info().email
---
code: |
  saved_records = read_records(user_key)
  for id in saved_records:
    user = saved_records[id]
---
initial: True
code: |
  if not user_logged_in():
    command('leave', url=url_of('login', next=interview_url()))
---
question: |
  What is your name?
fields:
  - First name: user.name.first
  - Last name: user.name.last
---
question: |
  What is your favorite fruit?
fields:
  - Fruit: user.favorite_fruit
---
code: |
  for id in read_records(user_key):
    delete_record(user_key, id)
  write_record(user_key, user)
  user_info_saved = True

Then your actual interview file will just incorporate this by reference. For example, you could have a file called wc_side_of_bed.yml, which looks like this:

metadata:
  title: Side of the bed
---
include:
  - wc_common.yml
---
mandatory: True
code: |
  first_part_finished
  user_info_saved
  interview_tagged
  interview_finished
---
question: |
  Thanks for all that information!
subquestion: |
  We now know that your name is
  ${ user },
  your favorite fruit is
  ${ user.favorite_fruit },
  and you woke up on the
  ${ side_of_bed }
  side of the bed this morning.
field: first_part_finished
---
question: |
  On which side of the bed did you
  wake up this morning, ${ user }?
field: side_of_bed
choices:
  Right side: right
  Wrong side: wrong
---
event: interview_finished
question: |
  Ok, go eat some
  ${ user.favorite_fruit },
  ${ user }.
subquestion: |
  Perhaps you will wake up on
  the ${ side_of_bed } side of
  the bed tomorrow, too.
buttons:
  - Exit: leave
    url: ${ url_of('dispatch') }
---
code: |
  set_parts(title=capitalize(side_of_bed) + " side of the bed")
  session_tags().add(side_of_bed)
  interview_tagged = True

You could then create other YAML files that follow the same pattern, all of which include the wc_common.yml file. Any time you wanted to change a “common” question, you would only need to make the change in one place.

Storing interview answer snapshots in unencrypted JSON format in SQL

If you want to “run reports” on the interview answers of multiple sessions, you can use store_variables_snapshot() in your interview logic to save an unencrypted copy of the interview answers in JSON format to a SQL table. If you use PostgreSQL, you can conveniently run SQL queries on the contents of interview answers. Using PostgreSQL syntax for working with JSON data, you can extract, filter, and order by specific variables embedded in the interview answers of sessions.

Here is an example of an interview that asks the user a question and then saves the interview answers in JSON format to a SQL table. Then, using a function analyze() that was defined in the read_snapshot.py module, the final question of the interview reads the interview answers of all sessions that have been completed on this interview on the server and summarizes the results.

modules:
  - .read_snapshot
---
mandatory: True
code: |
  favorite_fruit
  store_variables_snapshot()
  final_screen
---
question: |
  What is your favorite fruit?
fields:
  - Fruit: favorite_fruit
---
event: final_screen
question: |
  Your favorite fruit is
  ${ favorite_fruit }.
subquestion: |
  Here is a summary of fruits
  and how many people like them.

  % for fruit, count in sorted(analyze().items(), key=lambda y: y[1], reverse=True):
  * **${ fruit }**:
    % if count == 1:
    1 person
    % else:
    ${ count } people
    % endif
  % endfor

The contents of the read_snapshot.py module are as follows.

from docassemble.base.util import variables_snapshot_connection, user_info

__all__ = ['analyze']

def analyze():
  conn = variables_snapshot_connection()
  cur = conn.cursor()
  cur.execute("select data->>'favorite_fruit' from jsonstorage where filename='" + user_info().filename + "'")
  counts = dict()
  for record in cur.fetchall():
    fruit = record[0].lower()
    if fruit not in counts:
      counts[fruit] = 0
    counts[fruit] += 1
  conn.close()
  return counts

The analyze() function imports the variables_snapshot_connection() function from docassemble.base.util and calls it in order to get a SQL connection object. If your database is PostgreSQL, this will be a psycopg2 connection object. Note that variables_snapshot_connection() is not available for use inside interview YAML the way store_variables_snapshot() is. If you tried to call variables_snapshot_connection() from inside of a code block, you would get an error. Always call variables_snapshot_connection() from a function or method defined in a Python module.

When using PostgreSQL, the data type used for the JSON data is JSONB. This allows for the use of the special PostgreSQL operators -> and ->> to efficiently probe inside the data structure. For more information on how these operators work, see the documentation for the JSONB data type.

Note that the JSON snapshots created by store_variables_snapshot() are tied to the underlying interview session. When the session is deleted, the snapshot is deleted. (However, see the discussion of persistent below.)

If you call store_variables_snapshot() multiple times, each time you will overwrite the stored JSON snapshot of the interview answers. (However, see the discussion of key below.)

Note that the snapshot is a copy of the interview answers, not the interview answers themselves. The JSON snapshot does not automatically synchronize with the current state of the interview answers. In docassemble, the interview answers are stored in a Python-specific object format, not JSON; it is not possible for JSON to serve as the format for docassemble interview answers because docassemble allows interview answers to contain complex data structures containing Python objects and object references. The conversion from Python objects to JSON is one-way, and is a simplification; Python objects cannot be recreated from JSON.

Because of this, the store_variables_snapshot() is not as useful as other data storage options for many applications. You should use store_variables_snapshot() if you want to run SQL queries on multiple sessions belonging to different users. You should use other methods, such as DAStore, for storing reusable global data.

The store_variables_snapshot() accepts the optional keyword parameters, key, persistent, include_internal, and data.

If you want to save multiple snapshots during the course of the interview, you can set key when you call store_variables_snapshot(). For example, you might want to save a snapshot after the user completes an initial section of an interview, and save another snapshot after the user completes the entire interview. You could write:

mandatory: True
code: |
  intro_section_completed
  store_variables_snapshot(key='intro')
---
mandatory: True
code: |
  final_section_completed
  store_variables_snapshot(key='final')

This will allow you to run queries on two populations of users: a large population of users who started but may not have finished, and a smaller population of users who finished. The key is similar to a key in Redis; it uniquely identifies a snapshot within the interview session.

If you do not want the interview snapshot (or snapshots) to be deleted when the session is deleted, call store_variables_snapshot(persistent=True). Note that this means that if a user restarts an interview session, the user may have multiple sessions in JSON data table.

By default, store_variables_snapshot() does not save the “internal” portion of the interview answers; this is a data structure under the _internal key that docassemble uses internally. (The data structure is not documented and the design may change at any time, but you are welcome to use it at your own risk.) store_variables_snapshot() also does not store the nav variable, which stores information about which sections have been visited. If you want to include the _internal data and the nav varialbe in the JSON snapshot, call store_variables_snapshot() with include_internal=True.

store_variables_snapshot() can store something other than the interview answers if you set the optional keyword parameter data. You can set data to any Python data structure, and it will be serialized to JSON and stored in place of the data structure representing the interview answers.

While the example above shows how the JSON data table can be queried from within an interview, you will probably find that it is easiest to query the data tables from outside of docassemble. You can set up your server’s db configuration to use an external SQL database, and then query the jsonstorage table in that database using the credentials for the docassemble SQL database. However, there are many other tables in this database, and it may be preferable to use a separate database for JSON snapshots. If you define a variables snapshot db in your Configuration, a jsonstorage table will be created in the referenced database, and store_variables_snapshot() and variables_snapshot_connection() will use this database instead of the default docassemble database.

The columns in the jsonstorage table are as follows.

id - a unique integer ID for the row
filename - the YAML filename of the interview
key - the session ID of the session
data - the JSON data
tags - the value of the key you passed to store_variables_snapshot() (not to be confused with the column key)
modtime - the last time the row was modified
persistent - whether the row should be preserved when the session is deleted.

Note that there is no API for querying the JSON data. The best way to access the data is by using a PostgreSQL client because it provides an extremely powerful and flexible query language.

Note that unlike DAStore, store_variables_snapshot() cannot use server-side encryption. If the interview itself uses server-side encryption, calling store_variables_snapshot() will effectively defeat the purpose of server-side encryption by storing user data in a way that would allow anyone with shell access on the server to read the data.

Advanced SQL storage

Though the data are stored on a SQL server, you cannot use SQL queries to retrieve data stored by write_record(); you can only use read_records() to retrieve data.

If you want to use the full power of SQL in your interviews, you can write a module that does something like this:

from docassemble.base.util import get_config
import psycopg2

def get_conn():
    dbconfig = get_config('db')
    return psycopg2.connect(database=dbconfig.get('name'),
                            user=dbconfig.get('user'),
                            password=dbconfig.get('password'),
                            host=dbconfig.get('host'),
                            port=dbconfig.get('port'))
def some_function(id, thing):
    conn = get_conn()
    cur = conn.cursor()
    cur.execute("update foo set bar=%s where id=%s", (thing, id))
    conn.commit()
    cur.close()

This assumes the db configuration refers to a PostgreSQL database. If you connect to the database with the credentials from db, you have the power to create and drop tables.

Temporarily stashing encrypted data

The stash_data() and retrieve_stashed_data() functions can be used to store encrypted data in Redis for a period of time.

The stash_data() function stores a Python dictionary. The dictionary given to stash_data() can contain any pickle-able Python objects in any structure. In this example, the user object is stored.

(key, secret) = stash_data({'user': user}, expire=300)

The key and secret are needed to retrieve and decrypt the data later. The optional keyword parameter expire indicates that the data should disappear after five minutes (300 seconds). If expire is not provided, the default period is 90 days.

The retrieve_stashed_data() function takes the key and secret as input and returns the Python dictionary that was stored.

stored_data = retrieve_stashed_data(key, secret)
if stored_data is not None:
  set_variables(stored_data)

If the data cannot be retrieved, retrieve_stashed_data() returns None. This example uses the set_variables() function to set the variable user in the interview answers.

retrieve_stashed_data() accepts the optional keyword parameter delete, which indicates whether the data should be deleted after being retrieved. The default is False. It is generally a good idea to use delete=True whenever possible because it frees up space in Redis.

retrieve_stashed_data() accepts the optional keyword parameter refresh, which can be set to True or an integer number of seconds. If refresh is True, then after the information is accessed, the expiration date of the data stash will be reset to 90 days from the current time. If refresh is set to an integer number of seconds, then the expiration time is set to that number of seconds.

For API versions of these functions, see /api/stash_data and /api/retrieve_stashed_data.

Functions for working with DOCX templates

include_docx_template()

The include_docx_template() function can be called from within a DOCX template file in order to include the contents of another DOCX file within the template being assembled.

mandatory: True
question: |
  Here is your document.
attachment:
  name: A document
  filename: final_document
  docx template file: main_document.docx

The file main_document.docx looks like this:

include_docx_template

The file sub_document.docx looks like this:

include_docx_template_sub

Note that it is important to use the p form of Jinja2 markup, or else the contents of the included document will not be visible. The template text must also be by itself on a line, and the include_docx_template() function must be by itself within a Jinja2 p tag, and not combined with the + operator with any other text.

The filename that you give to include_docx_template() must be a file that exists in the templates folder of the current package. You can also refer to templates in other packages using a full package filename reference, such as docassemble.demo:data/templates/sub_document.docx. You can also give the function a DAFile, a DAFileList, a DAFileCollection, or a DAStaticFile object.

The include_docx_template() function also accepts optional keyword parameters. These values become variables that you can use in Jinja2 inside the DOCX file you are including. This can be useful if you have a “sub-document” that you want to include multiple times, but you want to use different variable values each time you include the “sub-document.”

Here is an example:

mandatory: True
question: |
  Here is your document.
attachment:
  name: A document
  filename: final_document
  docx template file: main_doc_params.docx

The file main_doc_params.docx looks like this:

include_docx_template_param

The file sub_doc_params.docx looks like this:

include_docx_template_param_sub

In this example, the variables grantor, grantee, and stuff are set by the keyword parameters of the include_docx_template() function. Note that in your sub-document you can still refer to ordinary interview variables in addition to variables created by keyword parameters; in this example, the sub-document references the variable planet, which is set by the interview.

The effect of including keyword parameters is to insert Jinja2 set commands at the start of the included document. For example, the first call to include_docx_template() might result in the following:

{%p set grantor = father %}
{%p set grantee = mother %}
{%p set stuff = 'toadstools' %}

Nobody ever actually sees these set statements; they are inserted and evaluated behind the scenes.

Note that if the values of any of your keyword arguments are objects other than DAObjects, they will be converted to their repr() representation before being included. This means that there may be some objects that you cannot pass through to your sub-documents.

When a docx template file document contains a call to include_docx_template(), the document is assembled in multiple “passes.” On the first pass, all of the Jinja2 is evaluated. The effect of include_docx_template() is to insert any set statements based on keyword parameters, along the verbatim contents of the file. Then, on the second pass, any remaining Jinja2 code is evaluated; this would be any Jinja2 code contained in sub-documents, as well as the set statements included by include_docx_template(). If any of the sub-documents contain calls to include_docx_template(), a third pass will be done, and so on, until the document is fully assembled. (The number of passes is limited to 10 in order to protect against accidentally creating an infinite loop of document inclusion.)

There is a special keyword parameter change_numbering that when set to False will refrain from fixing up the numbering of lists in the included documents. You should set change_numbering=False when your included document only contains list items, and you want the list items to merge into a list in the main document.

As discussed above, include_docx_template() needs to be used with {{p … }} because it returns the paragraphs from the included document. If you would like to include “inline” text from a secondary DOCX file, you can do so by setting the _inline keyword parameter. You can create a DOCX file called (for example) statement.docx that only contains one paragraph, and then include something like the following in your main document:

I state the following: {{r include_docx_template(‘statement.docx’, _inline=True) }}`

Note the use of {{r; this is necessary because when include_docx_template() is called with _inline=True, it returns character-level content. (Similarly, when you use the inline_markdown filter, you need to use {{r.) When you use _inline=True, only the first paragraph of the included document matters; other paragraphs will be ignored.

raw()

This function is only used in the context of an attachments block that uses a docx template file and values are passed to the DOCX template using the code or field code methods.

Normally, all values that you transfer to a DOCX template with code or field code are converted so that they display appropriately in your DOCX file. For example, if the value is a DAFile graphics image, it will be displayed in the DOCX file as an image. Or, if the value contains document markup codes that indicate line breaks, these will display as actual line breaks in the DOCX file, rather than as codes like [BR].

However, if your DOCX file uses advanced template features, such as for loops, this conversion might cause problems for you. By passing a value val as raw(val), you will ensure that the template sees the original value of val, not a converted value.

For example, suppose you have a variable fruit_list that is defined as a DAList with items ['apples', 'oranges'], and you pass it to a DOCX template as follows.

event: document_shown
question: |
  Here is the document.
attachment:
  docx template file: letter_template.docx
  field code:
    list_of_fruit: fruit_list

This will work as intended if your template uses list_of_fruit in a context like:

make sure to bring {{ list_of_fruit }} to the party

This will result in:

make sure to bring apples and oranges to the party

When the DAList is converted to text, the .comma_and_list() method is automatically applied to make the data structure “presentable.”

However, suppose you wanted to write:

{%p for fruit in list_of_fruit: %}
Don't forget to bring {{ fruit }}!
{%p endfor %}

In this case, the variable list_of_fruit is a literal piece of text, apples and oranges. The for loop will loop over each character, and you will get:

Don’t forget to bring a! Don’t forget to bring p! Don’t forget to bring p! Don’t forget to bring l!

and so on. That is certainly not what you want!

You can prevent the conversion of fruit_list into text by wrapping it in the raw() function, as follows:

event: document_shown
question: |
  Here is the document.
attachment:
  docx template file: letter_template.docx
  field code:
    list_of_fruit: raw(fruit_list)

Now, the resulting DOCX file will contain:

Don’t forget to bring apples! Don’t forget to bring oranges!

Note that another way to pass “raw” values to a DOCX template is to use a list of raw field variables.

Moreover, the easiest way to pass “raw” values is to omit field, field code, field variables, code, and raw field variables entirely, so that your DOCX file is assembled using your full set of interview variables.

assemble_docx()

The assemble_docx() function does what an attachment does, except it is triggered by Python code and it does not create a DAFile in the document storage.

This is an advanced function, so in the vast majority of circumstances, you should instead use an attachments block.

The assemble_docx() takes a single positional parameter, which needs to be a file. The format is flexible; it can be a DAFile or related object, or a template reference like 'data/templates/mytemplate.docx'.

The function returns a path to a temporary file in DOCX format, representing the assembled document. This file needs to be processed right away, because it is not guaranteed to persist across HTTP requests.

It also takes the following optional keyword parameters:

fields: this can be set to a Python dictionary in which the keys are variable names and the values are the values of those variables. This allows you to superimpose particular variables on top of the interview answers for purposes of document assembly. The values are not saved in the interview answers. The keys can only be simple Python variable names (favorite_fruit, type_of_document), not indices (fruits[0], favorite['fruit']) or attributes (favorite_vegetable.color, apple.seeds).
output_path: if you want the function to save a file to a particular path instead of returning a path to a temporary file, set output_path to the path to which you want assemble_docx to write.
output_format: if you want the assembled document to be converted to PDF, set output_format to 'pdf'. If you want it assembled to Markdown, set output_format to 'md'.
pdf_options: if you are setting output_format to 'pdf', you can also set options for the way the PDF conversion is conducted by setting pdf_options to a Python dictionary with one or more of the following keys: pdfa (boolean for whether PDF/A should be created, password (a password for securing the PDF), update_refs (if you want references to be updated in the DOCX file before conversion), tagged (if you want LibreOffice to produce a tagged PDF). For more information about these options, see the Documents section.
return_content: if you want the contents of the file to be returned, instead of a file path, set return_content to True.

Here is an example of an interview that uses assemble_docx() in a contract assembly interview. All of the clauses of the contract are in the contract.docx DOCX template file, but they are written in such a way that they can be extracted from the DOCX file using assemble_docx() and converted into Markdown. Extracting clauses in Markdown format is useful because:

It allows you to manage your contract clauses as a list of paragraphs, separated from the logic about whether the clauses should be included in the contract or not.
It allows you to draft your contract clauses in a DOCX file, which is the ideal format for writing, especially when formatting is used.
It allows you to show the text of the contract clauses in the web browser, without needing to maintain the content for the contract clauses in more than one place.
It allows you to give the user an opportunity to edit contract clauses during the interview and then insert the clauses into the DOCX file with formatting preserved (at least as far as the formatting translates to and from Markdown).

objects:
  - markdown_clause: DADict
  - edited_clause: DADict
---
code: |
  markdown_clause[i] = assemble_docx('data/templates/contract.docx', fields={'clause': i}, output_format='md', return_content=True)
---
code: |
  # This variable is set to None 
  # so that the .docx file does 
  # not assemble a single clause
  # when it is assembled at the
  # end.
  clause = None
---
question: |
  A contract
subquestion: |
  You are agreeing to a contract 
  with me.  Please continue.
continue button field: welcome_screen
---
question: The clauses
subquestion: |
  The firstborn clause is:
  
  ${ quote_paragraphs(markdown_clause['firstborn']) }

  The counterparts clause is:
  
  ${ quote_paragraphs(markdown_clause['counterparts']) }
continue button field: clauses_shown
---
question: |
  Make any necessary changes to the ${ i } clause.
fields:
  - no label: edited_clause[i]
    default: ${ markdown_clause[i] }
    input type: area
---
event: final_screen
question: |
  Here is the contract.
attachment:
  name: Contract
  docx template file: contract.docx

The contract.docx DOCX template is used for two very different purposes:

Assembling a document containing a single clause.
Assembling the contract itself.

The template uses the variable clause to determine which clause to assemble, or whether to assemble the contract itself. In the interview answers, clause is set to None, but the fields parameter passed to assemble_docx() will override that value for purposes of assembling a single clause.

The DOCX file uses the macro feature of Jinja2. The DOCX template could be written without the use of macro definitions, but they are useful so that if you want, you can insert clauses into the contract without converting them to Markdown and back again.

Writing your own functions

There are two ways that you can write your own functions in docassemble.

The first way is to use the <%def></%def> feature of Mako in order to use “functions” in your templates. These are not true Python functions because they are based around Mako templates, but they are similar to Python functions. The <%def></%def> feature is documented on the Mako web site. docassemble’s def block makes it easy to re-use def blocks in your interviews.

The second way, which is usually more elegant, is to write a Python module containing a definition of a Python function, and then include that module in your interview using the modules block. This allows you to use your function both in Mako templates and in code blocks.

Here is a brief tutorial on how to write a function plus_one() that takes a number and returns the number plus one. For example, plus_one(3) should return 4.

First, go to the Playground. (This requires that you have a developer account on the server.)

Then, go to the modules folder of the Playground.

modules folder

Then, type the following Python code into the text box:

def plus_one(number):
  return number + 1

The screen should look like this:

sample function

Then, press the “Save” button at the bottom of the screen. This will create a Python module called test. (The text file is called test.py in the modules folder because files containing Python code have the extension .py in their file names. Within Python, you refer to modules using the file name without the file extension.)

Then click the “Back to Playground” button to leave the “Modules” folder.

Now, you can use the plus_one() function in your interviews by doing something like:

modules:
  - .test
---
mandatory: True
question: |
  The number after 3 is
  ${ plus_one(3) }.

The . in front of the module name is Python’s way of referring to modules that are in the current package. If you put your module within a package called docassemble.simplemath, then you could write, instead:

---
modules:
  - docassemble.simplemath.test
---

Note that the modules block has the same effect as:

from docassemble.simplemath.test import *

This means that every name defined in the module file will be imported into the interview answers. It is recommended that you always define __all__ in your modules in order to limit what gets imported. You should only import the names you actually need to use in your interview YAML, such as the names of functions or classes.

__all__ = ['plus_one']

def plus_one(number):
  return number + 1

When docassemble pickles the interview answers, it will screen out top-level names that refer to modules, functions, classes, and other standard objects that are not able to be pickled. However, custom objects like database connection objects will not be screened out, so you may encounter pickle-related errors if you import too much into your interview answers. Defining __all__ in every module you write will protect against this.

Using a module is a good way to avoid pickling errors. Objects that cannot be pickled can live in the namespace of the module (in which case you should make sure you have an __all__ variable and make sure it does not include the names of those objects). Objects that cannot be pickled can also live in the namespace of a function. You can call those functions from Python code in your YAML, but if so, make sure that you do not save the result of the function call in a variable in your interview answers, or else you will encounter a pickling problem. Also note that if you define a class in your module file and you want to keep instances of that class in your interview answers, all of the attributes of the object instance need to be pickleable. For example, you should not define a database connection object as an attribute of an object, because in order to save the object instance to the SQL database, docassemble would have to pickle the database connection object, which is not possible.

A caveat regarding functions called from docx templates

If you write your own functions and they are called from markup inside docx template file functions, beware that Jinja2 will send your functions objects in place of arguments when the arguments are undefined. For example, consider a a template that contains:

{%p if claiming_damages %}
You owe me {{ currency(compute_damages(amount_owed, demand_interest)) }}.
{% endif %}

If demand_interest is undefined, and claiming_damages is true, docassemble should seek out a block that defines amount_owed. However, when Jinja2 sees that demand_interest is undefined, it creates an object amount_owed of the class jinja2.runtime.Undefined. If the only way compute_damages() acts upon demand_interest is by evaluating the conditional expression demand_interest is True, the expression will evaluate to False, even though your interview has not actually defined demand_interest.

This is different to how Python normally works. Normally, if the code is compute_damages(amount_owed, demand_interest) and demand_interest is undefined, a NameError is raised before compute_damages() is even called.

The behavior of Jinja2 might not be a problem if your function does arithmetic with the variable, calls unicode() on the variable or does other things with the variable that access its “value”; in those situations, an exception will be raised and docassemble will seek out a definition of the undefined variable. However, if your function uses try/except on the operations, this exception may not be passed on to docassemble.

To get around this problem, you can include the following in your module file:

from docassemble.base.util import ensure_definition

Then at the start of every function that might be called from Jinja2, run the function’s parameters through ensure_definition:

def compute_damages(amount_owed, demand_interest):
    ensure_definition(amount_owed, demand_interest)
    ...

The ensure_definition() function checks to see if each of its arguments (both positional and named) are Undefined, and if so, it raises an exception that will cause docassemble to seek out the appropriate definition.

Example module: using Google Sheets

This section explains an example of something you might do with a module: integrate with Google Sheets.

In order for your site to communicate with Google Sheets, you will need to create an account on the Google Developers Console and create an “app.” Within this app, you will need to create a “service account.” (More information is available on the internet about what a “service account” is and how you create one.) When you create the service account, you will be provided with “credentials.” Download the JSON (not p12) credential file for the service account. Also make a note of the e-mail address of the service account.

Within the Google Developers Console, enable the Google Drive API and the Google Sheets API.

Go to Google Sheets, pick a spreadsheet that you want to use, and share it with the e-mail address of the service account, just like you were sharing it with a real person. (When you share the spreadsheet with this e-mail address, you will get an e-mail notification from Google about an undeliverable e-mail. This is because Google will try to e-mail the service account, but the service account does not actually have an e-mail account. To avoid getting this e-mail, click the “Advanced” link on the sharing screen and uncheck “Notify people.”)

Go to the Configuration and set the service account credentials subdirective under the google directive. Set it to the contents of the JSON file you downloaded. The directive will look something like this:

google:
  service account credentials: |
    {
      "type": "service_account",
      "project_id": "redacted",
      "private_key_id": "redacted",
      "private_key": "-----BEGIN PRIVATE KEY-----REDACTED-----END PRIVATE KEY-----\n",
      "client_email": "[email protected]",
      "client_id": "redacted",
      "auth_uri": "https://accounts.google.com/o/oauth2/auth",
      "token_uri": "https://accounts.google.com/o/oauth2/token",
      "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
      "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/googledocs%40redacted.iam.gserviceaccount.com"
    }

Next, go to the modules folder of the Playground and add a new module called google_sheets.py. Set the contents to:

import gspread
import json
from docassemble.base.util import get_config
from oauth2client.service_account import ServiceAccountCredentials
credential_info = json.loads(get_config('google').get('service account credentials'), strict=False)
scope = ['https://spreadsheets.google.com/feeds',
         'https://www.googleapis.com/auth/drive']
__all__ = ['read_sheet']

def read_sheet(sheet_name, worksheet_index):
  creds = ServiceAccountCredentials.from_json_keyfile_dict(credential_info, scope)
  client = gspread.authorize(creds)
  sheet = client.open(sheet_name).get_worksheet(worksheet_index)
  return sheet.get_all_records()

You might need to change the reference to 'google' and 'service account credentials' to something else if you used a different name for the JSON crededials in your Configuration.

Go to the Playground and create an interview that references the google_sheets module and the read_sheet function.

modules:
  - .google_sheets
---
mandatory: True
question: |
  List of countries
subquestion: |
  % for row in read_sheet("Country Data", 0):
  * ${ row['name'] } is at ${ row['longitude'] } longitude.
  % endfor

In this example, a Google Sheet called “Country Data” has been shared with the “service account” that owns the credentials in the service account credentials subdirective under the google directive. The first worksheet in the spreadsheet (index 0) contains a table with headings for name and longitude, among other columns. The read_sheet function returns a list of dictionaries representing the contents of the table.

For more information on using Google Sheets from Python, see the documentation for the gspread module.

Example module: storing data in a Google Sheet

The following example interview extends the system developed in the previous section by adding functionality for writing data to the worksheet. This interview asks the interviewee some questions and then stores the results in a Google Sheet, much like Google Forms would.

modules:
  - .google_sheets
---
mandatory: True
code: |
  data_stored_in_google_sheet
  final_screen_shown
---
code: |
  append_to_sheet('Fruits and veggies', [user_name, favorite_fruit, favorite_vegetable])
  data_stored_in_google_sheet = True
---
event: final_screen_shown
question: |
  Thank you for your input!
subquestion: |
  % if favorite_vegetable in ('turnips', 'brussel sprouts'):
  Although I disagree with your
  vegetable preferences!
  % endif
---
question: |
  What is your first name?
subquestion: |
  Note: This interview will store
  your answers in a public Google
  Sheet.
fields:
  - Name: user_name
---
question: |
  What is your favorite fruit?
fields:
  - Fruit: favorite_fruit
---
question: |
  What is your favorite vegetable?
fields:
  - Vegetable: favorite_vegetable

This interview uses a Google Sheet called Fruits and veggies (you can view it at that link), which has been shared with the “service account” referenced in the service account credentials subdirective under the google directive in the Configuration on the demo.docassemble.org server.

You can try out this interview and then look at the Fruits and veggies spreadsheet to see your answers along with the answers of other people who have tested the interview.

There is a single mandatory block in this interview: a code block that first requires a definition of data_stored_in_google_sheet, and then seeks a definition of final_screen_shown.

The variable data_stored_in_google_sheet is defined by a code block that calls append_to_sheet(), which is a function defined in the google_sheets module. This module is in the same Python package as the interview (docassemble.demo). (The google_sheets module is based on the Python module described in the previous section.)

The append_to_sheet() function is very similar to the read_sheet() function described in the previous section.

def append_to_sheet(sheet_name, vals, worksheet_index=0):
    creds = ServiceAccountCredentials.from_json_keyfile_dict(credential_info, scope)
    client = gspread.authorize(creds)
    sheet = client.open(sheet_name).get_worksheet(worksheet_index)
    sheet.append_row(vals)

There is a handy method in gspread called append_row(), which adds a row to the end of a spreadsheet. If you use a method like this yourself, please note in Google Sheets, spreadsheets by default have several hundred rows, so if you append data to them, you might not see the data that you have appended unless you scroll all the way down. It is recommended that you delete all of these extraneous rows before you use gspread’s append_row() method to write to a spreadsheet.

Javascript functions

If you know how to program in JavaScript, you can include browser-side code in your interviews using script, html, and css elements within a fields block, or you can put JavaScript and CSS static files in your packages and bring them into your interview using the javascript and css specifiers within a features block.

The following JavaScript functions are available for your use in your JavaScript code.

flash() JavaScript function

The flash() function displays a notification at the top of the screen, using the standard Bootstrap notification style.

mandatory: True
decoration: coins
question: |
  The interview is complete.
script: |
  <script>
    flash("Hello, user!")
    flash("Lookout, user!", "danger")
  </script>

The first parameter is the message itself, the second parameter is the optional priority, and the third parameter is an optional true/false value indicating whether the existing messages should be removed before the new message is displayed.

The available priorities are:

primary

secondary

success

danger

warning

info

light

dark

If no priority is supplied, 'info' is used.

The success message is special because it automatically disappears after three seconds.

If you only want to clear the messages, you can run flash(null, null, true).

You can also access this function under the name da_flash(), which can be useful if you are embedding docassemble and there is a name conflict.

val() JavaScript function

If you need the value of one of the HTML inputs on the screen, you can call val(), passing as the sole parameter the variable name of the field as a string. The variable name must be written exactly as it appears in the underlying question.

question: |
  What do you want for
  dessert<span id="the_dessert"></span>?
fields:
  - Dessert: dessert
  - html: |
      <a href="#" id="show_me" class="btn btn-primary">Eat it</a>
script: |
  <script>
    $("#show_me").click(function(){
      $("#the_dessert").html(" besides " + val('dessert'));
      return false;
    });
  </script>

This function is essential for using the js show if feature.

Note that val() only works with fields that exist on the screen; the JavaScript environment is not aware of the Python environment. If you want to pass variable values from Python to JavaScript, see the recipe on the topic.

If you have a datatype: checkboxes field where the variable name is favorite_fruits and the choices are apple, orange, and peach, then:

val("favorite_fruits['apple']") will return true or false depending on whether the checkbox is checked.
val("favorite_fruits") will return an Array where the items are the strings "apple", "orange", etc., depending on which items were selected.
val("favorite_fruits[nota]") will return true or false depending on whether the “None of the above” checkbox is checked.
val("favorite_fruits[aota]") will return true or false depending on whether the “All of the above” checkbox is checked.

If you call val() on a field with a datatype of yesno, noyes, yesnoradio, or noyesradio, the function will return null (if no selection has been made), true, false.

If you call val() on a field with a datatype of yesnomaybe or noyesmaybe, the result is the same except that if the “I don’t know” choice is selected, the function will return "None".

The val() function returns null if the field for the given variable is disabled or non-existent.

You can also access this function under the name da_val(), which can be useful if you are embedding docassemble and there is a name conflict.

getField() JavaScript function

The getField() function is similar to val(), except that instead of returning the value of the input element, it returns the element itself.

question: |
  What do you want for
  dessert<span id="the_dessert"></span>?
fields:
  - Dessert: dessert
  - html: |
      <a href="#" id="show_me" class="btn btn-primary">Eat it</a>
script: |
  <script>
    $("#show_me").click(function(){
      $("#the_dessert").html(" besides " + getField('dessert').value);
      return false;
    });
  </script>

If a field consists of multiple radio buttons or checkboxes, getField() returns the <fieldset> element that contains the input elements.

The getField() function returns null if the field for the given variable is disabled.

You can also access this function under the name daGetField(), which can be useful if you are embedding docassemble and there is a name conflict.

setField() JavaScript function

The setField() function sets the value of a field. The first parameter is the the variable name of the field, as a string. The second parameter is the value that the variable should have. The variable name must be written exactly as it appears in the underlying question.

question: |
  What groceries should we buy for
  tomorrow's breakfast?
subquestion: |
  <a id="decide" href="#" class="btn btn-sm btn-primary">Decide for me</a>
fields:
  - Cold cereal: cold_cereal
    choices:
      - Lucky Charms
      - Cheerios
      - Froot Loops
      - Corn Flakes
  - Hot cereal: hot_cereal
    input type: radio
    choices:
      - Oatmeal
      - Cream of wheat
      - Bran
  - Juice: juice_varieties
    datatype: checkboxes
    choices:
      - Apple
      - Orange
      - Grapefruit
  - Other: other_groceries
script: |
  <script>
    $("#decide").click(function(){
      setField("cold_cereal", "Lucky Charms");
      setField("hot_cereal", "Cream of wheat");
      setField("juice_varieties['Apple']", true);
      setField("juice_varieties['Orange']", true);
      setField("juice_varieties['Grapefruit']", false);
      setField("other_groceries", "Bread and jam");
      return false;
    });
  </script>

If you have a datatype: checkboxes field where the variable name is favorite_fruits and the choices are apple, orange, and peach, then:

setField("favorite_fruits['apple']", true) will check the apple checkbox.
setField("favorite_fruits", ['apple', 'orange']) will check the apple and orange checkboxes.
setField("favorite_fruits[nota]", true) will check the “None of the above” checkbox.
setField("favorite_fruits[aota]", true) will check the “All of the above” checkbox.

You can also access this function under the name daSetField(), which can be useful if you are embedding docassemble and there is a name conflict.

getFields() JavaScript function

The getFields() function returns an array of names of the fields on the screen that can be used with val(), getField(), and setField().

question: |
  Tell me about your musical tastes.
fields:
  - Best band ever: best_band
  - Best singer ever: best_singer
  - Best composer ever: best_composer
  - Best songwriter ever: best_songwriter
  - html: |
      <a href="#" id="decide_for_me" class="btn btn-success">Decide for me</a>
script: |
  <script>
    $("#decide_for_me").click(function(){
      var fields = getFields();
      for (var i = 0; i < fields.length; ++i){
        setField(fields[i], 'Carly Simon');
      }
      return false;
    });
  </script>
---
mandatory: True
question: |
  You like ${ comma_and_list(set([best_band, best_singer, best_composer, best_songwriter])) }.

If you have a datatype: checkboxes field where the variable name is favorite_fruits and the choices are apple, orange, and peach, then getFields() will return favorite_fruits, favorite_fruits["apple"], favorite_fruits["orange"], etc., but it will not return favorite_fruits[nota] or favorite_fruits[aota].

You can also access this function under the name daGetFields(), which can be useful if you are embedding docassemble and there is a name conflict.

url_action() JavaScript function

The url_action() function, like its Python namesake, returns a URL that will run a particular action in the interview. The first parameter is the action to run, and the second parameter is an object containing the arguments to provide to the action (to be read with action_argument()), and the third (optional) parameter is a boolean value representing whether the action should cause any pending actions to be terminated (the default is false).

mandatory: True
code: |
  dessert = "cod liver oil"
---
mandatory: True
question: |
  Your dessert is ${ dessert }.
subquestion: |
  If you want, you can
  <a id="choose">choose something tastier</a>.
script: |
  <script>
    $("#choose").attr('href', url_action('myaction', {fruit: 'apple'}));
  </script>
---
event: myaction
code: |
  fruit = action_argument('fruit')
  dessert = fruit + " pie"

You can also access this function under the name da_url_action(), which can be useful if you are embedding docassemble and there is a name conflict.

action_perform() JavaScript function

The action_perform() function is like url_action(), except that instead of returning a URL that would run the action if accessed, it actually causes the user’s web browser to run the action.

The JavaScript function takes three arguments:

The action to take. This corresponds with the name of an event in your interview.
An object containing arguments to pass to the action. In your interview, you can use the action_argument() function to read these values.
(optional) A boolean value representing whether the action should cause any pending actions to be terminated. The default is false.

You can also access this function under the name da_action_perform(), which can be useful if you are embedding docassemble and there is a name conflict.

action_call() JavaScript function

The action_call() function is like url_action(), except it makes an Ajax call to the URL and runs a callback function when the server responds to the request. In combination with json_response(), this can allow you to write JavaScript code that interacts with “APIs” within your interview.

The JavaScript function takes three arguments:

The action to take. This corresponds with the name of an event in your interview.
An object containing arguments to pass to the action. In your interview, you can use the action_argument() function to read these values.
A callback function that will be run when the Ajax call returns. This function takes a single argument (data in this example), which is the return value of json_response().
(optional) A boolean value representing whether the action should cause any pending actions to be terminated. The default is false.

mandatory: True
question: |
  The pie
subquestion: |
  <button id="run" class="btn btn-primary">Run</button>

  <span id="resultsArea"></span>
script: |
  <script>
    $("#run").click(function(){
      action_call('myaction', {fruit: 'apple'}, function(data){
        $("#resultsArea").html("The pie is called " + data.pie + ".")
      });
    });
  </script>
---
event: myaction
code: |
  fruit = action_argument('fruit')
  dessert = fruit + " pie"
  json_response(dict(pie=dessert))

This example takes advantage of the CSS classes btn and btn-primary that are available in Bootstrap. See the Bootstrap documentation for more information about using these classes.

Note that Ajax interactions with the interview are possible without writing any JavaScript code; see the check in feature.

You can also access this function under the name da_action_call(), which can be useful if you are embedding docassemble and there is a name conflict.

get_interview_variables() JavaScript function

If you would like to work with all of the variables in the interview in your JavaScript code, you can do so with the get_interview_variables() function, which sends an Ajax call to the server to retrieve the contents of the interview session dictionary.

The function takes a single argument, which is the callback function. The callback function is given one parameter, which is an object having the following attributes:

success: this will be True if the call succeeds, False otherwise.
variables: this will be an object containing the interview variables in the format produced by all_variables().
i: the current interview YAML file.
uid: the current session ID.
encrypted: whether the interview session dictionary is encrypted.
steps: the number of steps taken so far in the interview.

var the_vars;
get_interview_variables(function(data){
  if (data.success){
    the_vars = data.variables;
    console.log("The current role is " + the_vars['role']);
  }
});

You can also access this function under the name da_get_interview_variables(), which can be useful if you are embedding docassemble and there is a name conflict.

Running Javascript at page load time

If you have JavaScript code in a .js file that you load with the javascript feature, but you need that code to run when a screen loads, it is necessary to wrap the code in a daPageLoad trigger.

$(document).on('daPageLoad', function(){
  console.log("The screen is loaded");
});

This is because the docassemble front end is a “single page application.” When the user navigates from screen to screen, the whole page is not reloaded; rather, an Ajax request is sent and the DOM is redrawn. Thus, the javascript file will only executed on the first page load, or when the user presses the refresh button. The daPageLoad event is triggered whenever the user arrives at a new screen.

Note that you should only attach a daPageLoad listener from a javascript file, not from a script

Functions

What is a function?

Functions for working with variable values

defined()

value()

define()

undefine()

invalidate()

forget_result_of()

set_variables()

re_run_logic()

reconsider()

need()

force_ask()

force_gather()

dispatch()

all_variables()

Functions for special responses

message()

response()

json_response()

variables_as_json()

command()

Text transformation functions

from_b64_json()

plain(), bold(), and italic()

space_to_underscore()

single_to_double_newlines()

single_paragraph()

verbatim()

quote_paragraphs()

indent()

fix_punctuation()

redact()

Functions related to actions

url_action() and process_action()

action_menu_item()

interview_url()

interview_url_as_qr()

interview_url_action()

interview_url_action_as_qr()

action_arguments()

action_argument()

url_of()

Special uses

url_ask()

action_button_html()

QR code functions

qr_code()

read_qr()

E-mail functions

send_email()

interview_email()

get_emails()

Fax functions

send_fax()

Geographic functions

map_of()

location_known()

location_returned()

user_lat_lon()

iso_country()

countries_list() and country_name()

states_list() and state_name()

subdivision_type()

Navigation and progress bar functions

get_progress()

set_progress()

nav.get_section()

nav.set_section()

nav.get_sections()

nav.set_sections()

nav.show_sections()

nav.hide()

nav.unhide()

nav.visible()

nav.disable()

nav.enable()

nav.enabled()

Functions for managing global variables