Bug pylint 2721

ChangeLog

@@ -6,6 +6,25 @@ What's New in astroid 2.3.0?
 ============================
 Release Date: TBA
 
+* Numpy brain support is improved.
+
+  Numpy's fundamental type ``numpy.ndarray`` has its own brain : ``brain_numpy_ndarray`` and 
+  each numpy module that necessitates brain action has now its own numpy brain :
+
+    - ``numpy.core.numeric`` 
+    - ``numpy.core.function_base`` 
+    - ``numpy.core.multiarray`` 
+    - ``numpy.core.numeric`` 
+    - ``numpy.core.numerictypes`` 
+    - ``numpy.core.umath`` 
+    - ``numpy.random.mtrand``
+
+  Close PyCQA/pylint#2865
+  Close PyCQA/pylint#2747
+  Close PyCQA/pylint#2721
+  Close PyCQA/pylint#2326
+  Close PyCQA/pylint#2021
+
 * Add support for Python 3.8's `NamedExpr` nodes, which is part of assignment expressions.
 
   Close #674

astroid/brain/brain_numpy_core_fromnumeric.py

@@ -0,0 +1,23 @@
+# Copyright (c) 2018-2019 hippo91 <guillaume.peillex@gmail.com>
+
+# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
+# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER
+
+
+"""Astroid hooks for numpy.core.fromnumeric module."""
+
+import astroid
+
+
+def numpy_core_fromnumeric_transform():
+    return astroid.parse(
+        """
+    def sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None):
+        return numpy.ndarray([0, 0])
+    """
+    )
+
+
+astroid.register_module_extender(
+    astroid.MANAGER, "numpy.core.fromnumeric", numpy_core_fromnumeric_transform
+)

astroid/brain/brain_numpy_core_function_base.py

@@ -0,0 +1,29 @@
+# Copyright (c) 2018-2019 hippo91 <guillaume.peillex@gmail.com>
+
+# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
+# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER
+
+
+"""Astroid hooks for numpy.core.function_base module."""
+
+import functools
+import astroid
+from brain_numpy_utils import looks_like_numpy_member, infer_numpy_member
+
+
+METHODS_TO_BE_INFERRED = {
+    "linspace": """def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0):
+            return numpy.ndarray([0, 0])""",
+    "logspace": """def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0):
+            return numpy.ndarray([0, 0])""",
+    "geomspace": """def geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0):
+            return numpy.ndarray([0, 0])""",
+}
+
+for func_name, func_src in METHODS_TO_BE_INFERRED.items():
+    inference_function = functools.partial(infer_numpy_member, func_src)
+    astroid.MANAGER.register_transform(
+        astroid.Attribute,
+        astroid.inference_tip(inference_function),
+        functools.partial(looks_like_numpy_member, func_name),
+    )

astroid/brain/brain_numpy_core_multiarray.py

@@ -0,0 +1,55 @@
+# Copyright (c) 2018-2019 hippo91 <guillaume.peillex@gmail.com>
+
+# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
+# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER
+
+
+"""Astroid hooks for numpy.core.multiarray module."""
+
+import functools
+import astroid
+from brain_numpy_utils import looks_like_numpy_member, infer_numpy_member
+
+
+def numpy_core_multiarray_transform():
+    return astroid.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])
+        """
+    )
+
+
+astroid.register_module_extender(
+    astroid.MANAGER, "numpy.core.multiarray", numpy_core_multiarray_transform
+)
+
+
+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])""",
+    "zeros": """def zeros(shape, dtype=float, order='C'):
+            return numpy.ndarray([0, 0])""",
+}
+
+for method_name, function_src in METHODS_TO_BE_INFERRED.items():
+    inference_function = functools.partial(infer_numpy_member, function_src)
+    astroid.MANAGER.register_transform(
+        astroid.Attribute,
+        astroid.inference_tip(inference_function),
+        functools.partial(looks_like_numpy_member, method_name),
+    )

astroid/brain/brain_numpy_core_numeric.py

@@ -0,0 +1,43 @@
+# Copyright (c) 2018-2019 hippo91 <guillaume.peillex@gmail.com>
+
+# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
+# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER
+
+
+"""Astroid hooks for numpy.core.numeric module."""
+
+import functools
+import astroid
+from brain_numpy_utils import looks_like_numpy_member, infer_numpy_member
+
+
+def numpy_core_numeric_transform():
+    return astroid.parse(
+        """
+    # different functions defined in numeric.py
+    import numpy
+    def zeros_like(a, dtype=None, order='K', subok=True): return numpy.ndarray((0, 0))
+    def ones_like(a, dtype=None, order='K', subok=True): return numpy.ndarray((0, 0))
+    def full_like(a, fill_value, dtype=None, order='K', subok=True): return numpy.ndarray((0, 0))
+        """
+    )
+
+
+astroid.register_module_extender(
+    astroid.MANAGER, "numpy.core.numeric", numpy_core_numeric_transform
+)
+
+
+METHODS_TO_BE_INFERRED = {
+    "ones": """def ones(shape, dtype=None, order='C'):
+            return numpy.ndarray([0, 0])"""
+}
+
+
+for method_name, function_src in METHODS_TO_BE_INFERRED.items():
+    inference_function = functools.partial(infer_numpy_member, function_src)
+    astroid.MANAGER.register_transform(
+        astroid.Attribute,
+        astroid.inference_tip(inference_function),
+        functools.partial(looks_like_numpy_member, method_name),
+    )