Add basic stubs for some class attributes #9
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numpy/__init__.pyi
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| def newbyteoder(self, new_order:str = ...): dtype | ||
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| str: builtins.str |
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I've segregated this here so that the other strs don't need to have builtins.str here (see python/mypy#3775).
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Please add this as a comment in the code
shoyer
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shoyer
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This is a great start, thanks!
numpy/__init__.pyi
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| alignment: int | ||
| byteorder: str | ||
| char: str | ||
| descr: List[Tuple[str, str]] |
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Entries in descr can only be three element tuples, with the last item indicating a shape, e.g.,
>>> np.dtype([('x', 'f4'), ('y', np.float32), ('z', 'f4', (2,2))]).descr
[('x', '<f4'), ('y', '<f4'), ('z', '<f4', (2, 2))]
numpy/__init__.pyi
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| byteorder: str | ||
| char: str | ||
| descr: List[Tuple[str, str]] | ||
| fields: Optional[Mapping[str, Union[Tuple[dtype, int], Tuple[dtype, int, str]]]] |
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It looks like the final title field can have any type, so it should probably be keyed as Any instead of str: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.dtype.fields.html#numpy.dtype.fields
numpy/__init__.pyi
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| def newbyteoder(self, new_order:str = ...): dtype | ||
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| str: builtins.str |
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Please add this as a comment in the code
numpy/__init__.pyi
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| subdtype: Optional[Tuple[dtype, Tuple[int, ...]]] | ||
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| def newbyteoder(self, new_order:str = ...): dtype |
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please keep the space after : per pep8. This should be new_order: str = ...
numpy/__init__.pyi
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| subdtype: Optional[Tuple[dtype, Tuple[int, ...]]] | ||
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| def newbyteoder(self, new_order:str = ...): dtype |
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please keep the space after : per pep8. This should be:
new_order: str = ...
numpy/__init__.pyi
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| type: builtins.type | ||
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| @property | ||
| def base(self) -> dtype: ... |
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Is there a reason why this is a property vs. an attribute for everything else? Does mypy care about the difference?
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Properties can't be assigned to unless they have a setter. With this stub, if you had x: dtype, mypy would allow x.type = some_type but not x.base = some_dtype.
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OK, in that case we should also convert most of the other attributes into readonly properties.
numpy/__init__.pyi
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| _dtype = dtype # for ndarray type | ||
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| class flagsobj: |
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flagsobj is not exposed by NumPy's public API, so let's give it a private name (_flagsobj?)
numpy/__init__.pyi
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| def base(self) -> dtype: ... | ||
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| _dtype = dtype # for ndarray type |
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Give this a name like _dtype_class to make it a little clearer what it is?
numpy/__init__.pyi
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| data: memoryview | ||
| dtype: _dtype | ||
| flags: flagsobj | ||
| flat: Any |
| strides: Tuple[int, ...] | ||
| ctypes: _ctypes | ||
| base: Optional[ndarray] | ||
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This list is incomplete for now, so let's add def __getattr__(self, name) -> Any: ....
numpy/__init__.pyi
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| subdtype: Optional[Tuple[dtype, Tuple[int, ...]]] | ||
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| def newbyteoder(self, new_order:str = ...): dtype |
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I assume this should be newbyteorder, not newbyteoder?
* Replace tab in setup.py with spaces * Add Travis * Add flake8 config to pass tests * Use `-` instead of `_` See python/peps#568 * Add Travis badge to README * Use numpy 1.14.0
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This should be ready for another round of review! |
numpy/__init__.pyi
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| @property | ||
| def descr(self) -> List[Union[ | ||
| Tuple[str, str], | ||
| Tuple[str, str, Tuple[int, ...]]]]: ... |
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optional: it might be convenient to define an alias _Shape = Tuple[int, ...]
numpy/__init__.pyi
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| names: Optional[Tuple[str, ...]] | ||
| updateifcopy: bool | ||
| writeable: bool | ||
| writebackifcopy: bool |
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I'm not quite sure where these attributes came from -- I can't find any of updateifcopy, writeable and writebackifcopy on dtype.
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Actually, these are missing down below on flagsobj.
| def str(self) -> builtins.str: ... | ||
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| @property | ||
| def type(self) -> builtins.type: ... |
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More specifically, we could define the np.generic class and switch this to Type[generic] (but this is also fine for now -- certainly let's save defining the full NumPy scalar type hierarchy for later).
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Thanks @alanhdu ! |
| def type(self) -> builtins.type: ... | ||
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| _dtype_class = dtype # for ndarray type |
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Why does this have a duplicate name?
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Otherwise mypy gets confused when you to type the dtype ndarray attribute, e.g., def dtype(self) -> dtype refers to ndarray.dtype for the return value, not the dtype class.
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Can you fix it with an import numpy as np, and then using np.dtype?
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I don't know exactly how mypy handles circular imports, but I suspect that importing a module from itself would not work.
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