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13a2ac7b8e
It was allowing us to get away with wrong types on a few functions: `check_send_typing_notification` and `send_notification_backend` can be (and are) called with a list of `int` as `notification_to`, not just a list of `str`. The problem it was working around already had a better solution using the dummy `type` argument. Use that. Signed-off-by: Anders Kaseorg <anders@zulipchat.com>
36 lines
1.4 KiB
Python
36 lines
1.4 KiB
Python
# This mypy stubs file ensures that mypy can correctly analyze REQ.
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#
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# Note that here REQ is claimed to be a function, with a return type to match
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# that of the parameter of which it is the default value, allowing type
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# checking. However, in request.py, REQ is a class to enable the decorator to
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# scan the parameter list for REQ objects and patch the parameters as the true
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# types.
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from typing import Dict, Callable, List, TypeVar, Optional, Union, Type
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from zerver.lib.types import ViewFuncT, Validator
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from zerver.lib.exceptions import JsonableError as JsonableError
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ResultT = TypeVar('ResultT')
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class RequestConfusingParmsError(JsonableError): ...
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class RequestVariableMissingError(JsonableError): ...
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class RequestVariableConversionError(JsonableError): ...
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class _NotSpecified: ...
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NotSpecified = _NotSpecified()
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def REQ(whence: Optional[str] = None,
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*,
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type: Type[ResultT] = Type[None],
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converter: Optional[Callable[[str], ResultT]] = None,
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default: Union[_NotSpecified, ResultT, None] = NotSpecified,
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validator: Optional[Validator] = None,
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str_validator: Optional[Validator] = None,
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argument_type: Optional[str] = None,
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intentionally_undocumented: bool=False,
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documentation_pending: bool=False,
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aliases: Optional[List[str]] = None) -> ResultT: ...
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def has_request_variables(view_func: ViewFuncT) -> ViewFuncT: ...
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arguments_map = ... # type: Dict[str, List[str]]
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