Vinta Django Questionnaires

A reusable Django application for building data-driven questionnaires.

Supports Python 3.10, 3.11, 3.12, 3.13, 3.14 and Django 5.2, 6.0.

Installation

pip install vinta-django-questionnaires

Then add the app to INSTALLED_APPS:

INSTALLED_APPS = [
    ...,
    "vinta_django_questionnaires",
]

Trying it

There is a runnable project under example/ with a seeded questionnaire -- four pages, conditions, a skippable page, a nested sub-questionnaire, a model-backed value set and a couple of project-specific validators:

uv run python -m example.manage migrate
uv run python -m example.manage seed_example
uv run python -m example.manage demo_response   # narrates a whole response
uv run python -m example.manage runserver       # admin at /admin/, API at /api/questionnaires/

And a React front end for it under demo/ -- TanStack Start, Vite and the vinta-schedule-design-system, rendering and validating entirely from the plan the server sends:

npm --prefix demo install
npm --prefix demo run dev   # http://localhost:5273, with Django on 8000

Usage

Defining a questionnaire

A questionnaire is a key with versions; everything else hangs off a version.

from vinta_django_questionnaires.models import (
    Page,
    Question,
    Questionnaire,
    QuestionnaireVersion,
    Section,
)
from vinta_django_questionnaires.question_types import QuestionType

intake = Questionnaire.objects.create(key="intake")
version = QuestionnaireVersion.objects.create(questionnaire=intake, version=1, title="Intake form")
page = Page.objects.create(questionnaire_version=version, key="about", title="About you")
section = Section.objects.create(page=page, key="basics", title="Basics")
question = Question.objects.create(
    section=section,
    key="email",
    title="Email",
    question_type=QuestionType.FREE_TEXT,
)

Every model runs full_clean() on save, so a question can never reference a widget that cannot render it, carry props its widget rejects, or name a validator nobody registered. Pass save(validate=False) from data migrations.

Pages, sections and questions each take a condition: a JMESPath expression evaluated against the answers. version.iter_applicable_questions(answers) yields the questions that should actually be validated and saved.

Changing a questionnaire that is already in use

Every page, section and question belongs to exactly one version. Nothing is shared between versions, so a version that has been answered can never change underneath those answers by accident.

The ordinary way to change a live questionnaire is therefore to fork it:

from vinta_django_questionnaires.versioning import new_version_from

draft = new_version_from(version)  # a deep copy, as a new draft
draft.pages.get(key="about").sections.get(key="basics").questions.get(key="colour").delete()
draft.publish()

The copy carries everything -- window size ranges, the columns each layer sets, pages, sections, questions, choices, validators -- and keeps question keys, so answers stay comparable from one version to the next. What a question points at, like a widget or a value set, is shared: those are their own records.

Editing in place is still allowed, because sometimes a typo is just a typo. But once a version has responses, an edit to a page, section, question, choice or validator changes what those responses mean, so it has to be acknowledged, and the acknowledgement is kept:

from vinta_django_questionnaires.editing import acknowledged_edit

with acknowledged_edit(user=request.user, reason="The old wording was ambiguous"):
    question.title = "What is your company's name?"
    question.save()

Without that, the save raises UnacknowledgedEdit. With it, an AcknowledgedEdit row records who, when, why, what changed field by field, and how many responses were already in when they did it.

The line is the first response: before that there is nothing to reinterpret, so authors correct a live version freely. Override requires_acknowledgement() to draw it elsewhere -- at publication, say.

What is gated is the models a respondent reads or is measured against: pages, sections, questions, their choices and their validators. The responsive grid is not -- LayerColumns and QuestionMinimumColumns are their own models, and narrowing a question on a phone does not change what its answer meant. A question's order is gated, because it is a field of the question.

The admin puts that in front of someone as a checkbox; see below. AcknowledgedEditAdminMixin does the same for an admin of your own:

@admin.register(Question)
class QuestionAdmin(AcknowledgedEditAdminMixin, admin.ModelAdmin):
    pass

Telling whether a question is still the same question

Because versions copy rather than share, "is this the same question as in v1?" needs an answer. Keys give identity; fingerprints give sameness:

from vinta_django_questionnaires.fingerprints import compare_versions

comparison = compare_versions(version_1, version_3)
comparison.unchanged  # question keys that ask exactly the same thing
comparison.changed  # ... and those that do not
comparison.can_pool("email")  # whether answers to it are comparable

A fingerprint covers what a respondent reads or is measured against -- title, description, type, choices, validators, condition -- and ignores presentation, so reordering a form or swapping a widget leaves it alone.

Validating answers

Validators are configured per question, in order, and each one receives a context carrying what the earlier ones found.

from vinta_django_questionnaires.models import QuestionValidator

QuestionValidator.objects.create(
    question=question,
    validator="required",
    order=0,
)
QuestionValidator.objects.create(
    question=question,
    validator="email",
    order=1,
    message_overrides={"invalid_email": "We need a working address."},
)

context = question.run_validators("not-an-email")
[issue.error_key for issue in context.issues]  # ["invalid_email"]

Other apps add their own from a questionnaire_validators module, which the app config autodiscovers:

from vinta_django_questionnaires.validators import BaseValidator, ClientSpec, register_validator


@register_validator
class IsCompanyDomainValidator(BaseValidator):
    key = "is_company_domain"
    error_messages = {"foreign_domain": "Use your {domain} address."}
    params_schema = {
        "type": "object",
        "properties": {"domain": {"type": "string"}},
        "required": ["domain"],
        "additionalProperties": False,
    }
    client = ClientSpec.custom()  # or ClientSpec.server_only()

    def validate(self, value, context):
        if not value.endswith(f"@{self.params['domain']}"):
            self.fail("foreign_domain", domain=self.params["domain"])

Filling in a response

A response is filled a page at a time. Each page pushed becomes a PageResponse, so which pages exist -- and the order they are in -- is what says where the respondent got to.

from vinta_django_questionnaires.submissions import skip_page, start_response, submit_page

response = start_response(version, respondent=request.user)
response.current_page  # the first page still pending
submit_page(response, page, {"email": "hugo@vinta.com.br"})
response.progress()  # completed / skipped / pending / current / isComplete

submit_page validates the page on its own and writes nothing if it does not hold up, raising PageValidationError with the issues keyed by question. What the page is asking is decided against the answers as they will be once the page lands, so a question whose condition depends on an answer in the same payload is handled.

A page marked is_skippable can be left for later:

skip_page(response, page)  # recorded as skipped, reason "manual_action"

A page whose condition does not hold is recorded too, with the reason false_condition, so every page of a response has an account of itself. The difference matters: a manual skip is still pending -- skipping means later, not never -- while a page ruled out by its condition is not, and does not hold up completion.

Conditions depend on answers, and answers change. sync_condition_skips runs after every submission and keeps those records honest: a page ruled out after being filled becomes false_condition and its answers stop counting, and if the condition holds again the page comes back with its answers intact.

What a version still accepts

Each version decides for itself whether a recorded answer can be changed, and until when:

from datetime import datetime, timezone as tz

version.edit_policy = EditPolicy.ALWAYS  # never / until_completed / always
# After this, no page can be answered:
version.responses_due_at = datetime(2026, 9, 30, 23, 59, tzinfo=tz.utc)
# After this, no answer can be changed:
version.edits_due_at = datetime(2026, 10, 15, 23, 59, tzinfo=tz.utc)
version.save()

Answering and editing are different acts with their own deadline. Writing a page that has nothing recorded yet is answering, governed by responses_due_at. Writing one that already has answers is editing, governed by edit_policy and edits_due_at. The two are independent, so a version can stop taking new answers on Friday while letting the answers it has be corrected until Sunday -- or the other way around.

edit_policy is a choice rather than a flag because "editable" means two different things:

Editing a completed response can make it incomplete again -- a changed answer can bring a conditional page back into play -- so the status follows what is recorded, and the response reopens on its own.

start_response, submit_page and skip_page enforce all of this, raising RespondingClosed, EditingClosed or EditingNotAllowed.

The response API

Include the views where you want them:

urlpatterns = [
    path("api/questionnaires/", include("vinta_django_questionnaires.urls")),
]

A page that does not validate comes back as 422, with the issues keyed by question:

{"errors": {"email": [{"validator": "email", "errorKey": "invalid_email", "message": "..."}]}}

A page refused because the deadline passed or the version does not allow the change comes back as 409 with a detail. Every response payload carries a policy block -- editPolicy, canRespond, canEdit, responsesDueAt, editsDueAt -- so the client can put the form in read-only rather than let someone type into a page that will be refused.

Who may open a response, and who may see one, are methods on ResponseAccessMixin rather than settings. The defaults are the careful ones: authenticated users, each seeing only their own. Override check_access, get_respondent or get_response_queryset for anonymous or externally identified respondents.

The admin

The package ships its own admin and registers it when the app is installed, so there is nothing to write:

INSTALLED_APPS = ["vinta_django_questionnaires", ...]

It is arranged around what someone actually does rather than around the model graph, because the graph is four deep and following it means five page loads and four saves to fix a typo.

• A questionnaire lists its versions, each with a link straight to its structure, its settings and its responses, and a button that starts the next version by copying the latest.
• A version's change form holds only what belongs to the version: title, status, the two deadlines, the breakpoints, the grid. Everything in it is one click away.
• The structure editor is the point. Every page, section, question, choice and validator of a version is on one form and saves together, so a change that touches six of them is one save. Rows carry the key, title and type; everything else is behind a disclosure, and each list reorders by dragging or with the arrow keys. The validator dropdown is the registry, so a validator another app registered is there without this package knowing about it.
• The responses have a table view with a column per question, a picker grouped by page, and a CSV export that takes exactly the columns on screen -- the same reporting module the API and the React demo use, so the three cannot drift. Each response also shows what it wrote into your own models and what it set off, with a link to the record.

Editing a version that has responses asks for the acknowledgement once, for the whole page, and records it against every change the save makes.

One thing to set. The structure editor posts a whole questionnaire in one form, which for a dozen questions is a couple of thousand inputs, and Django's DATA_UPLOAD_MAX_NUMBER_FIELDS defaults to 1000:

DATA_UPLOAD_MAX_NUMBER_FIELDS = 5000

Without it the editor says so, with the number it needs, rather than failing with a traceback.

Registering it yourself

Registering is opt-out, because a project may already have an admin for one of these models, or may want a different base class under all of them:

QUESTIONNAIRES_REGISTER_ADMIN = False

Then call register() from your own admin.py. It skips anything already registered, so adding one admin of your own needs nothing else:

from vinta_django_questionnaires.admin import register, unregister

register()  # everything not already registered
register(my_site)  # against a site of your own
register(force=True)  # replacing what is there
unregister()  # take it all back off

With a themed admin

A themed admin styles a form through the base class it is built on, so register() takes the bases to put underneath -- inlines included, since those are declared inside the admin classes. For django-unfold, that is the whole of it:

from unfold.admin import ModelAdmin, TabularInline
from vinta_django_questionnaires.admin import register

register(model_admin_base=ModelAdmin, inline_base=TabularInline)

The structure editor and the response table are pages of ours rather than the admin's, so they are styled from static/vinta_django_questionnaires/admin.css. Every colour there is a --vqa- token mapped onto the Django admin's own, and each mapping falls back to a value mixed out of currentColor -- so a theme that defines none of Django's properties (Unfold defines not one of them) gets borders and shading that read against whatever background it uses, rather than the silent collapse an unguarded var() would cause.

Both are checked: the editor measures zero WCAG AA failures under Django's light and dark themes and under Unfold's, and the whole flow -- editing across three levels, the acknowledgement gate, saving -- was exercised under Unfold.

The authoring API and the React editor

Questionnaires are edited in the Django admin, or from the React editor the client package ships. The editor needs two things the response API does not have -- a version as an editable document, and a catalog of what can be picked -- so those live behind their own URLs:

urlpatterns = [
    path("api/authoring/", include("vinta_django_questionnaires.editor_urls")),
]

Who may author is AuthoringAccessMixin.check_access, and the default is staff only.

The document is not the validation plan. The plan is resolved and flattened for rendering; the document keeps every field as its author set it -- a column count each layer declares rather than the one it resolves to, an empty widget where the author left the type's default -- because that is what has to go back.

from vinta_django_questionnaires.definition import apply_definition, definition_document

document = definition_document(version)
document["pages"][0]["title"] = "About you"
apply_definition(version, document)

Keys are identity. A page, section, question or choice is matched to what is stored by its key, so changing a key is a delete and a create rather than a rename -- answers are keyed by question key, and pretending otherwise would quietly reattach them to a different question. The editor says so before you save.

A document that does not hold up is refused whole, with one entry per node that would not go, addressed the way the editor addresses its own state:

{"issues": [{"path": "pages.0.sections.0.questions.2", "errors": {"key": ["..."]}}]}

One bad question does not hide the other nine: every node is checked, and nothing at all is written unless all of it was. Editing a version that already has responses goes through the same acknowledgement gate as any other in-place edit -- PUT takes {"document": ..., "acknowledgement": {"understood": true, "reason": "..."}}, and without it the save is refused.

For the editor itself, see client/README.md.

Reading the responses

The same authoring URLs serve the responses as a table. What the columns are is not something a client can know in advance, so they come back with the rows -- one per question the version asks, in the order it asks them, plus the handful of things about a response anyone reading a table wants.

Both take questionnaire, version, status, search and columns; the listing adds page and pageSize. Filtering by questionnaire is what makes answer columns available at all -- a table across every questionnaire has only the metadata ones, because different questionnaires ask different things.

from vinta_django_questionnaires.reporting import columns_for, csv_rows, response_queryset

columns = columns_for(version)
rows = csv_rows(response_queryset(questionnaire="intake"), columns)

The export is streamed, and the listing costs one query for the answers of the whole page rather than one per row -- a table is exactly where that matters. An answer with no flat form, a matrix or a list of files, goes into a CSV cell as the JSON it already is.

Turning a response into something else

Two things a project almost always wants once a response is in: put the answers into its own models, and tell another system about them. Both are configured rather than coded, and both read the answers the way conditions do -- JMESPath, one expression per field.

A mapping names its target through the content type framework, so this package never has to know about the model it writes to:

mapping = ResponseMapping.objects.create(
    key="onboarding-lead",
    name="Onboarding to Lead",
    questionnaire=questionnaire,
    content_type=ContentType.objects.get_for_model(Lead),
    operation=MappingOperation.UPSERT,
    defaults={"source": "client-onboarding"},
)
MappingField.objects.create(
    mapping=mapping,
    role=FieldRole.LOOKUP,
    target_field="email",
    expression="answers.email",
    is_required=True,
)
MappingField.objects.create(
    mapping=mapping,
    target_field="company",
    expression="answers.company_name",
)

insert creates; update writes to whatever the lookup fields find, and does nothing when they find nothing; upsert does one or the other. defaults are written when a record is created, and a mapped field with a value of its own wins over them. A lookup that resolves to nothing is skipped rather than matching every row, an unanswered optional field is left out rather than nulling what is there, and a required one that resolves to nothing abandons the whole mapping.

A webhook is three templates over the same document -- the URL, the headers and the body:

ResponseWebhook.objects.create(
    key="onboarding-crm",
    questionnaire=questionnaire,
    method="POST",
    url_template="https://crm.example.com/companies/{company}/leads/",
    url_params={"company": "answers.company_name"},
    headers={"X-Response": {"$jmespath": "id"}},
    body={"email": {"$jmespath": "answers.email"}, "source": "questionnaire"},
)

Anywhere in the headers or the body, {"$jmespath": "..."} is replaced by what that expression resolves to; everything else is a literal. A {placeholder} in the URL needs an expression in url_params, which is checked on save rather than discovered at delivery.

Both run when the response completes, or on every page if trigger says so, and both carry a condition of their own. Neither can break a submission: they run after the transaction commits, each outcome is written down as a MappingRun or a WebhookDelivery, and the respondent never sees a failure. The document they read is the answers, flat and under answers, plus the response's own metadata:

{
    "email": "...",
    "answers": {"email": "..."},
    "id": "...",
    "status": "completed",
    "questionnaire": "intake",
    "version": 2,
    "context": {},
    "respondent": {...},
}

Delivery goes through the standard library, so there is no new dependency. Point QUESTIONNAIRES_WEBHOOK_SENDER at a send(request) of your own to use something else, and set QUESTIONNAIRES_RUN_INTEGRATIONS = False to stop the submission layer running them inline and call run_integrations() from a task queue instead.

The API, written down

openapi.yml describes both URL modules -- every path, method, parameter and payload. The test suite checks it against the URLconf, so an endpoint added without a matching entry fails CI rather than going unnoticed.

The same rules in the browser

vinta_django_questionnaires.plan emits a JSON validation plan -- base type, checks in order, resolved messages -- that the TypeScript client turns into a Zod schema. See client/README.md.

from vinta_django_questionnaires.plan import questionnaire_plan

return JsonResponse(questionnaire_plan(version))

Both sides replay shared/conformance-cases.json, so a rule that behaves differently in the browser than on the server fails CI.

Development

The project uses uv for dependency management and tox to run the suite across the support matrix.

uv sync --all-groups
uv run pre-commit install --install-hooks --hook-type commit-msg
uv run pytest

Useful commands:

Both shared/ artifacts are checked into the repository and asserted to be current by the test suite: adding or changing a validator means regenerating them in the same commit.

Releasing

Two packages come out of this repository and they version independently, so the tag says which one is going: vX.Y.Z is the Django app, client-vX.Y.Z is the npm package. Each workflow ignores the other's tags.

The Django app, to PyPI:

1. Bump the version in pyproject.toml and move the Unreleased section of CHANGELOG.md under the new number.
2. Tag the commit as vX.Y.Z and publish a GitHub release.
3. publish.yml builds, verifies that the tag matches the version, uploads through trusted publishing, and attaches Sigstore signatures.

To rehearse, run that workflow manually with the testpypi target.

The client, to npm:

1. Bump the version in client/package.json.
2. Tag the commit as client-vX.Y.Z and publish a GitHub release.
3. publish-client.yml type checks, tests, builds, checks that the tag matches the version and that the version is not already on npm, then publishes through trusted publishing.

To rehearse, run that workflow manually and leave Dry run ticked: it does everything up to and including npm pack, uploads the tarball as an artifact, and stops.

Neither workflow stores a token. Both mint a short-lived one from GitHub's OIDC, which is why each has its own deployment environment -- pypi, testpypi and npm -- named in the trusted publisher on the other side. npm's provenance attestation is generated automatically from the same exchange, and is why client/package.json carries a repository field pointing at this repository and the client directory inside it.

Staying up to date with the template

This project was generated from vinta-django-package. To pull in later improvements to the tooling:

uvx copier update --trust

License

MIT. See LICENSE.