mirror of https://github.com/zulip/zulip.git
f4caf9dd79
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.
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| __init__.py | ||
| custom_check.py | ||
| exclude.py | ||