The goal of typed_endpoint is to replicate most features supported by
has_request_variables, and to improve on top of it. There are some
unresolved issues that we don't plan to work on currently. For example,
typed_endpoint does not support ignored_parameters_supported for 400
responses, and it does not run validators on path-only arguments.
Unlike has_request_variables, typed_endpoint supports error handling by
processing validation errors from Pydantic.
Most features supported by has_request_variables are supported by
typed_endpoint in various ways.
To define a function, use a syntax like this with Annotated if there is
any metadata you want to associate with a parameter, do note that
parameters that are not keyword-only are ignored from the request:
```
@typed_endpoint
def view(
request: HttpRequest,
user_profile: UserProfile,
*,
foo: Annotated[int, ApiParamConfig(path_only=True)],
bar: Json[int],
other: Annotated[
Json[int],
ApiParamConfig(
whence="lorem",
documentation_status=NTENTIONALLY_UNDOCUMENTED
)
] = 10,
) -> HttpResponse:
....
```
There are also some shorthands for the commonly used annotated types,
which are encouraged when applicable for better readability and less
typing:
```
WebhookPayload = Annotated[Json[T], ApiParamConfig(argument_type_is_body=True)]
PathOnly = Annotated[T, ApiParamConfig(path_only=True)]
```
Then the view function above can be rewritten as:
```
@typed_endpoint
def view(
request: HttpRequest,
user_profile: UserProfile,
*,
foo: PathOnly[int],
bar: Json[int],
other: Annotated[
Json[int],
ApiParamConfig(
whence="lorem",
documentation_status=INTENTIONALLY_UNDOCUMENTED
)
] = 10,
) -> HttpResponse:
....
```
There are some intentional restrictions:
- A single parameter cannot have more than one ApiParamConfig
- Path-only parameters cannot have default values
- argument_type_is_body is incompatible with whence
- Arguments of name "request", "user_profile", "args", and "kwargs" and
etc. are ignored by typed_endpoint.
- positional-only arguments are not supported by typed_endpoint. Only
keyword-only parameters are expected to be parsed from the request.
- Pydantic's strict mode is always enabled, because we don't want to
coerce input parsed from JSON into other types unnecessarily.
- Using strict mode all the time also means that we should always use
Json[int] instead of int, because it is only possible for the request
to have data of type str, and a type annotation of int will always
reject such data.
typed_endpoint's handling of ignored_parameters_unsupported is mostly
identical to that of has_request_variables.
Translators benefit from the extra information in the field names, and
need the reordering freedom that isn’t available with multiple
positional fields.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
Black 23 enforces some slightly more specific rules about empty line
counts and redundant parenthesis removal, but the result is still
compatible with Black 22.
(This does not actually upgrade our Python environment to Black 23
yet.)
Signed-off-by: Anders Kaseorg <anders@zulip.com>
This error message is for a very precise situation -- the pattern not
having the desired format. We should say that, rather than a generic
"Malformed".
Currently an user can create multiple options with same text/label in
the select/"list of options" custom profile field type.
Fix this issue by extending the validator to throw an error if there
are duplicate choices in the "list of options" in custom profile
field.
Tweaked by tabbott to use a simpler check.
Fixes: #21880
For aliases that will no longer be listed, see the third column of
grep '^L ' zulip-py3-venv/lib/python3.*/site-packages/pytz/zoneinfo/tzdata.zi
Time zones previously set to an alias will be canonicalized on demand.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
This reverts commit cd93d0967f.
This check_or is redundant with check_union; it gives a misleading
error message for the non-matching case; and it has no type safety.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
This commit moves check_settings_values to user_settings.py
from validator.py such that we can import the functions at
the top without any issue of cyclic imports.
We extract the checks for default_language, notification_sound,
and email_notifications_batching_period_seconds setting values
in json_change_settings to a new function check_settings_values.
Tuples cannot be deserialized from JSON.
While we do use these validators for other things, like event
dictionaries, we have migrated the API away from using those. The
last use was removed in 4f3d5f2d87
Signed-off-by: Anders Kaseorg <anders@zulip.com>
We create a class called ZulipRequestNotes as a new home to all the
additional attributes that we add to the Django HttpRequest object.
This allows mypy to do the typecheck and also enforces type safety.
Most of the attributes are added in the middleware, and thus it is
generally safe to assert that they are not None in a code path that
goes through the middleware. The caller is obligated to do manual
the type check otherwise.
This also resolves some cyclic dependencies that zerver.lib.request
have with zerver.lib.rate_limiter and zerver.tornado.handlers.
django.utils.translation.ugettext is a deprecated alias of
django.utils.translation.gettext as of Django 3.0, and will be removed
in Django 4.0.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
Note that I don't actually convert the
checker from check_dict to check_dict_only,
because that would be a user-facing change,
but I think we can sweep a lot of things
like this after the next release.
We now have our muted topics use tuples internally,
which allows us to tighten up the annotation
for get_topic_mutes, as well as our schema
checking.
We want to deprecate sub_validator=None
for check_list, so we also introduce
check_tuple here. Now we also want to deprecate
check_tuple, but it's at least isolated now.
We will use this for data structures that are tuples,
but which are sent as lists over the wire. Fortunately,
we don't have too many of those.
The plan is to convert tuples to dictionaries,
but backward compatibility may be tricky in some
places.
We only use this in a few places, but they're really important places
for understanding the types in the codebase, and so it's worth having
a bit of expository documentation explaining how we use it.
(And I expect we'll add more with time).
Old: a validator returns None on success and returns an error string
on error.
New: a validator returns the validated value on success and raises
ValidationError on error.
This allows mypy to catch mismatches between the annotated type of a
REQ parameter and the type that the validator actually validates.
Signed-off-by: Anders Kaseorg <anders@zulip.com>
Anders Kaseorg
Zixuan James Li
Alex Vandiver
Josh Klar
yogesh sirsat
NerdyLucifer
seiwailai
Sahil Batra
PIG208
Steve Howell
Vishnu KS
tushar912
Tim Abbott