FM / brain

/opt/imh-python/lib/python3.9/site-packages/astroid/brain/

/opt/imh-python/lib/python3.9/site-packages/astroid/brain

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
brain_argparse.py	1813	0644	edit dl rm
brain_attrs.py	3352	0644	edit dl rm
brain_boto3.py	1072	0644	edit dl rm
brain_builtin_inference.py	37433	0644	edit dl rm
brain_collections.py	4787	0644	edit dl rm
brain_crypt.py	915	0644	edit dl rm
brain_ctypes.py	2720	0644	edit dl rm
brain_curses.py	3529	0644	edit dl rm
brain_dataclasses.py	22363	0644	edit dl rm
brain_datetime.py	771	0644	edit dl rm
brain_dateutil.py	819	0644	edit dl rm
brain_functools.py	6390	0644	edit dl rm
brain_gi.py	7598	0644	edit dl rm
brain_hashlib.py	2757	0644	edit dl rm
brain_http.py	10687	0644	edit dl rm
brain_hypothesis.py	1800	0644	edit dl rm
brain_io.py	1589	0644	edit dl rm
brain_mechanize.py	2698	0644	edit dl rm
brain_multiprocessing.py	3260	0644	edit dl rm
brain_namedtuple_enum.py	23912	0644	edit dl rm
brain_nose.py	2402	0644	edit dl rm
brain_numpy_core_einsumfunc.py	885	0644	edit dl rm
brain_numpy_core_fromnumeric.py	792	0644	edit dl rm
brain_numpy_core_function_base.py	1408	0644	edit dl rm
brain_numpy_core_multiarray.py	4400	0644	edit dl rm
brain_numpy_core_numeric.py	1740	0644	edit dl rm
brain_numpy_core_numerictypes.py	8606	0644	edit dl rm
brain_numpy_core_umath.py	4939	0644	edit dl rm
brain_numpy_ma.py	948	0644	edit dl rm
brain_numpy_ndarray.py	9066	0644	edit dl rm
brain_numpy_random_mtrand.py	3496	0644	edit dl rm
brain_numpy_utils.py	2553	0644	edit dl rm
brain_pathlib.py	1705	0644	edit dl rm
brain_pkg_resources.py	2252	0644	edit dl rm
brain_pytest.py	2270	0644	edit dl rm
brain_qt.py	2874	0644	edit dl rm
brain_random.py	3170	0644	edit dl rm
brain_re.py	2966	0644	edit dl rm
brain_regex.py	3433	0644	edit dl rm
brain_responses.py	1920	0644	edit dl rm
brain_scipy_signal.py	2328	0644	edit dl rm
brain_signal.py	3932	0644	edit dl rm
brain_six.py	7666	0644	edit dl rm
brain_sqlalchemy.py	1061	0644	edit dl rm
brain_ssl.py	6716	0644	edit dl rm
brain_subprocess.py	2971	0644	edit dl rm
brain_threading.py	922	0644	edit dl rm
brain_type.py	2481	0644	edit dl rm
brain_typing.py	16717	0644	edit dl rm
brain_unittest.py	1136	0644	edit dl rm
brain_uuid.py	727	0644	edit dl rm
helpers.py	4303	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /opt/imh-python/lib/python3.9/site-packages/astroid/brain/brain_numpy_core_multiarray.py (4400B)

# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
# For details: https://github.com/pylint-dev/astroid/blob/main/LICENSE
# Copyright (c) https://github.com/pylint-dev/astroid/blob/main/CONTRIBUTORS.txt

"""Astroid hooks for numpy.core.multiarray module."""

import functools

from astroid.brain.brain_numpy_utils import (
    attribute_looks_like_numpy_member,
    infer_numpy_member,
    name_looks_like_numpy_member,
)
from astroid.brain.helpers import register_module_extender
from astroid.builder import parse
from astroid.inference_tip import inference_tip
from astroid.manager import AstroidManager
from astroid.nodes.node_classes import Attribute, Name

def numpy_core_multiarray_transform():
    return parse(
        """
    # different functions defined in multiarray.py
    def inner(a, b):
        return numpy.ndarray([0, 0])

def vdot(a, b):
        return numpy.ndarray([0, 0])
        """
    )

METHODS_TO_BE_INFERRED = {
    "array": """def array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0):
            return numpy.ndarray([0, 0])""",
    "dot": """def dot(a, b, out=None):
            return numpy.ndarray([0, 0])""",
    "empty_like": """def empty_like(a, dtype=None, order='K', subok=True):
            return numpy.ndarray((0, 0))""",
    "concatenate": """def concatenate(arrays, axis=None, out=None):
            return numpy.ndarray((0, 0))""",
    "where": """def where(condition, x=None, y=None):
            return numpy.ndarray([0, 0])""",
    "empty": """def empty(shape, dtype=float, order='C'):
            return numpy.ndarray([0, 0])""",
    "bincount": """def bincount(x, weights=None, minlength=0):
            return numpy.ndarray([0, 0])""",
    "busday_count": """def busday_count(
        begindates, enddates, weekmask='1111100', holidays=[], busdaycal=None, out=None
    ):
        return numpy.ndarray([0, 0])""",
    "busday_offset": """def busday_offset(
        dates, offsets, roll='raise', weekmask='1111100', holidays=None,
        busdaycal=None, out=None
    ):
        return numpy.ndarray([0, 0])""",
    "can_cast": """def can_cast(from_, to, casting='safe'):
            return True""",
    "copyto": """def copyto(dst, src, casting='same_kind', where=True):
            return None""",
    "datetime_as_string": """def datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind'):
            return numpy.ndarray([0, 0])""",
    "is_busday": """def is_busday(dates, weekmask='1111100', holidays=None, busdaycal=None, out=None):
            return numpy.ndarray([0, 0])""",
    "lexsort": """def lexsort(keys, axis=-1):
            return numpy.ndarray([0, 0])""",
    "may_share_memory": """def may_share_memory(a, b, max_work=None):
            return True""",
    # Not yet available because dtype is not yet present in those brains
    #     "min_scalar_type": """def min_scalar_type(a):
    #             return numpy.dtype('int16')""",
    "packbits": """def packbits(a, axis=None, bitorder='big'):
            return numpy.ndarray([0, 0])""",
    # Not yet available because dtype is not yet present in those brains
    #     "result_type": """def result_type(*arrays_and_dtypes):
    #             return numpy.dtype('int16')""",
    "shares_memory": """def shares_memory(a, b, max_work=None):
            return True""",
    "unpackbits": """def unpackbits(a, axis=None, count=None, bitorder='big'):
            return numpy.ndarray([0, 0])""",
    "unravel_index": """def unravel_index(indices, shape, order='C'):
            return (numpy.ndarray([0, 0]),)""",
    "zeros": """def zeros(shape, dtype=float, order='C'):
            return numpy.ndarray([0, 0])""",
}

def register(manager: AstroidManager) -> None:
    register_module_extender(
        manager, "numpy.core.multiarray", numpy_core_multiarray_transform
    )

for method_name, function_src in METHODS_TO_BE_INFERRED.items():
        inference_function = functools.partial(infer_numpy_member, function_src)
        manager.register_transform(
            Attribute,
            inference_tip(inference_function),
            functools.partial(attribute_looks_like_numpy_member, method_name),
        )
        manager.register_transform(
            Name,
            inference_tip(inference_function),
            functools.partial(name_looks_like_numpy_member, method_name),
        )

cmd: