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values | stars int64 0 1k | created_date stringdate 2023-07-10 19:21:08 2025-07-09 19:11:45 | license stringclasses 4
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import contextlib\nimport re\nimport sys\nimport types\nimport unittest\nimport warnings\nfrom collections.abc import Callable\nfrom pathlib import Path\nfrom typing import Any, TypeVar, assert_type\n\nimport numpy as np\nimport numpy.typing as npt\n\nAR_f8: npt.NDArray[np.float64]\nAR_i8: npt.NDArray[np.int64]\n\nbool... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\testing.pyi | testing.pyi | Other | 8,641 | 0.85 | 0.045455 | 0 | vue-tools | 717 | 2024-03-02T04:43:00.997963 | Apache-2.0 | true | 513d00efee4246221943f21593af8959 |
from typing import Any, TypeVar, assert_type\n\nimport numpy as np\nimport numpy.typing as npt\n\n_ScalarT = TypeVar("_ScalarT", bound=np.generic)\n\ndef func1(ar: npt.NDArray[_ScalarT], a: int) -> npt.NDArray[_ScalarT]: ...\n\ndef func2(ar: npt.NDArray[np.number], a: str) -> npt.NDArray[np.float64]: ...\n\nAR_b: npt.N... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\twodim_base.pyi | twodim_base.pyi | Other | 4,382 | 0.85 | 0.013793 | 0 | node-utils | 403 | 2025-04-29T09:41:23.903248 | BSD-3-Clause | true | 5a809b0ab5571dd26f00923623294652 |
from typing import Any, Literal, assert_type\n\nimport numpy as np\nimport numpy.typing as npt\n\nf8: np.float64\nf: float\n\n# NOTE: Avoid importing the platform specific `np.float128` type\nAR_i8: npt.NDArray[np.int64]\nAR_i4: npt.NDArray[np.int32]\nAR_f2: npt.NDArray[np.float16]\nAR_f8: npt.NDArray[np.float64]\nAR_f... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\type_check.pyi | type_check.pyi | Other | 2,459 | 0.95 | 0.014925 | 0.019231 | react-lib | 38 | 2025-04-06T20:01:10.046726 | BSD-3-Clause | true | f3833d78c6543c7e568e8ad9363dbb5b |
from typing import Any, assert_type\n\nimport numpy as np\nimport numpy.typing as npt\n\nAR_LIKE_b: list[bool]\nAR_LIKE_u: list[np.uint32]\nAR_LIKE_i: list[int]\nAR_LIKE_f: list[float]\nAR_LIKE_O: list[np.object_]\n\nAR_U: npt.NDArray[np.str_]\n\nassert_type(np.fix(AR_LIKE_b), npt.NDArray[np.floating])\nassert_type(np.... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\ufunclike.pyi | ufunclike.pyi | Other | 1,214 | 0.85 | 0 | 0 | react-lib | 61 | 2024-01-09T13:50:18.387259 | BSD-3-Clause | true | 91fcbdd7216b4801649d74fa74b70c42 |
from typing import Any, Literal, NoReturn, assert_type\n\nimport numpy as np\nimport numpy.typing as npt\n\ni8: np.int64\nf8: np.float64\nAR_f8: npt.NDArray[np.float64]\nAR_i8: npt.NDArray[np.int64]\n\nassert_type(np.absolute.__doc__, str)\nassert_type(np.absolute.types, list[str])\n\nassert_type(np.absolute.__name__, ... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\ufuncs.pyi | ufuncs.pyi | Other | 4,912 | 0.85 | 0 | 0 | node-utils | 449 | 2024-06-30T01:42:27.579087 | Apache-2.0 | true | 9a6cd1cc6758fe56d7b78163066e3c4e |
"""Typing tests for `_core._ufunc_config`."""\n\nfrom collections.abc import Callable\nfrom typing import Any, assert_type\n\nfrom _typeshed import SupportsWrite\n\nimport numpy as np\n\ndef func(a: str, b: int) -> None: ...\n\nclass Write:\n def write(self, value: str) -> None: ...\n\nassert_type(np.seterr(all=None... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\ufunc_config.pyi | ufunc_config.pyi | Other | 1,192 | 0.85 | 0.133333 | 0 | vue-tools | 866 | 2024-08-30T07:59:44.851444 | Apache-2.0 | true | 3286011ff3534ebdb4daddd66dc3cd08 |
from typing import assert_type\n\nimport numpy.exceptions as ex\n\nassert_type(ex.ModuleDeprecationWarning(), ex.ModuleDeprecationWarning)\nassert_type(ex.VisibleDeprecationWarning(), ex.VisibleDeprecationWarning)\nassert_type(ex.ComplexWarning(), ex.ComplexWarning)\nassert_type(ex.RankWarning(), ex.RankWarning)\nasser... | .venv\Lib\site-packages\numpy\typing\tests\data\reveal\warnings_and_errors.pyi | warnings_and_errors.pyi | Other | 460 | 0.85 | 0 | 0 | vue-tools | 71 | 2024-03-08T22:12:07.449027 | BSD-3-Clause | true | 67534135349f16420bd04ef9690af470 |
\n\n | .venv\Lib\site-packages\numpy\typing\tests\__pycache__\test_isfile.cpython-313.pyc | test_isfile.cpython-313.pyc | Other | 1,606 | 0.8 | 0.035714 | 0 | python-kit | 355 | 2024-11-04T22:18:58.481033 | BSD-3-Clause | true | 08d4cac39e84563713f6e6b4ad2eaf7c |
\n\n | .venv\Lib\site-packages\numpy\typing\tests\__pycache__\test_runtime.cpython-313.pyc | test_runtime.cpython-313.pyc | Other | 6,053 | 0.8 | 0 | 0.037037 | python-kit | 834 | 2024-12-31T23:17:37.313818 | MIT | true | 91f973c59187dcd75c05c2e3a2f2a8d8 |
\n\n | .venv\Lib\site-packages\numpy\typing\tests\__pycache__\test_typing.cpython-313.pyc | test_typing.cpython-313.pyc | Other | 9,461 | 0.95 | 0.030303 | 0.011765 | awesome-app | 373 | 2024-10-28T12:54:07.980186 | GPL-3.0 | true | 663ff95c425c7b15e944ea25c389605e |
\n\n | .venv\Lib\site-packages\numpy\typing\tests\__pycache__\__init__.cpython-313.pyc | __init__.cpython-313.pyc | Other | 193 | 0.7 | 0 | 0 | python-kit | 782 | 2023-07-22T01:57:23.437174 | GPL-3.0 | true | 368b3315f33019d0372da189537c28de |
\n\n | .venv\Lib\site-packages\numpy\typing\__pycache__\mypy_plugin.cpython-313.pyc | mypy_plugin.cpython-313.pyc | Other | 8,501 | 0.95 | 0.034783 | 0.05 | vue-tools | 574 | 2024-04-28T10:27:24.749169 | MIT | false | 9195a1fa109814c7e888bfcbc9ce1e53 |
\n\n | .venv\Lib\site-packages\numpy\typing\__pycache__\__init__.cpython-313.pyc | __init__.cpython-313.pyc | Other | 6,541 | 0.95 | 0.044693 | 0.023077 | react-lib | 614 | 2025-07-08T10:41:48.999691 | Apache-2.0 | false | d714ecc15d1caf104d0f40635685dfd7 |
"""Array printing function\n\n$Id: arrayprint.py,v 1.9 2005/09/13 13:58:44 teoliphant Exp $\n\n"""\n__all__ = ["array2string", "array_str", "array_repr",\n "set_printoptions", "get_printoptions", "printoptions",\n "format_float_positional", "format_float_scientific"]\n__docformat__ = 'restructuredte... | .venv\Lib\site-packages\numpy\_core\arrayprint.py | arrayprint.py | Python | 67,053 | 0.75 | 0.181408 | 0.068733 | awesome-app | 369 | 2023-09-26T02:50:03.731005 | GPL-3.0 | false | 16e96d175b08275a568a3aca4fbd67be |
from collections.abc import Callable\n\n# Using a private class is by no means ideal, but it is simply a consequence\n# of a `contextlib.context` returning an instance of aforementioned class\nfrom contextlib import _GeneratorContextManager\nfrom typing import (\n Any,\n Final,\n Literal,\n SupportsIndex,\n... | .venv\Lib\site-packages\numpy\_core\arrayprint.pyi | arrayprint.pyi | Other | 7,209 | 0.95 | 0.067227 | 0.053333 | python-kit | 257 | 2023-11-12T12:35:19.876079 | BSD-3-Clause | false | cb70fd2e8ce9e3708387a355a02abdcb |
"""Simple script to compute the api hash of the current API.\n\nThe API has is defined by numpy_api_order and ufunc_api_order.\n\n"""\nfrom os.path import dirname\n\nfrom code_generators.genapi import fullapi_hash\nfrom code_generators.numpy_api import full_api\n\nif __name__ == '__main__':\n curdir = dirname(__file... | .venv\Lib\site-packages\numpy\_core\cversions.py | cversions.py | Python | 360 | 0.85 | 0.076923 | 0 | awesome-app | 642 | 2024-01-24T16:17:39.260116 | MIT | false | f995e727741d37f76c92ec98ef1cf399 |
"""\nThis module contains a set of functions for vectorized string\noperations and methods.\n\n.. note::\n The `chararray` class exists for backwards compatibility with\n Numarray, it is not recommended for new development. Starting from numpy\n 1.4, if one needs arrays of strings, it is recommended to use arrays... | .venv\Lib\site-packages\numpy\_core\defchararray.py | defchararray.py | Python | 39,434 | 0.95 | 0.111423 | 0.018486 | react-lib | 998 | 2023-12-06T01:50:13.429241 | MIT | false | 6f4c91d69c1a5825373c8133a5462031 |
from typing import Any, Self, SupportsIndex, SupportsInt, TypeAlias, overload\nfrom typing import Literal as L\n\nfrom typing_extensions import TypeVar\n\nimport numpy as np\nfrom numpy import (\n _OrderKACF,\n _SupportsBuffer,\n bytes_,\n dtype,\n int_,\n ndarray,\n object_,\n str_,\n)\nfrom nu... | .venv\Lib\site-packages\numpy\_core\defchararray.pyi | defchararray.pyi | Other | 27,957 | 0.95 | 0.215668 | 0.00499 | node-utils | 888 | 2024-12-22T19:32:53.185599 | GPL-3.0 | false | 3c39894a2696c19a1140cd197fc9dfc4 |
"""\nImplementation of optimized einsum.\n\n"""\nimport itertools\nimport operator\n\nfrom numpy._core.multiarray import c_einsum\nfrom numpy._core.numeric import asanyarray, tensordot\nfrom numpy._core.overrides import array_function_dispatch\n\n__all__ = ['einsum', 'einsum_path']\n\n# importing string for string.asci... | .venv\Lib\site-packages\numpy\_core\einsumfunc.py | einsumfunc.py | Python | 54,318 | 0.75 | 0.122163 | 0.112825 | python-kit | 597 | 2024-07-10T18:52:52.066161 | MIT | false | e34f08e11bc09daa72e1c7e1d28ab099 |
from collections.abc import Sequence\nfrom typing import Any, Literal, TypeAlias, TypeVar, overload\n\nimport numpy as np\nfrom numpy import _OrderKACF, number\nfrom numpy._typing import (\n NDArray,\n _ArrayLikeBool_co,\n _ArrayLikeComplex_co,\n _ArrayLikeFloat_co,\n _ArrayLikeInt_co,\n _ArrayLikeObj... | .venv\Lib\site-packages\numpy\_core\einsumfunc.pyi | einsumfunc.pyi | Other | 5,077 | 0.95 | 0.076087 | 0.129944 | react-lib | 390 | 2024-10-03T06:59:35.618328 | MIT | false | e4b12fe4445a87121e15461caab623e8 |
# ruff: noqa: ANN401\nfrom collections.abc import Sequence\nfrom typing import (\n Any,\n Literal,\n Never,\n Protocol,\n SupportsIndex,\n TypeAlias,\n TypeVar,\n overload,\n type_check_only,\n)\n\nfrom _typeshed import Incomplete\nfrom typing_extensions import deprecated\n\nimport numpy as n... | .venv\Lib\site-packages\numpy\_core\fromnumeric.pyi | fromnumeric.pyi | Other | 43,784 | 0.95 | 0.111429 | 0.063529 | node-utils | 245 | 2024-07-13T04:40:33.305778 | GPL-3.0 | false | 571317298b7bad985833061938a96395 |
import functools\nimport operator\nimport types\nimport warnings\n\nimport numpy as np\nfrom numpy._core import overrides\nfrom numpy._core._multiarray_umath import _array_converter\nfrom numpy._core.multiarray import add_docstring\n\nfrom . import numeric as _nx\nfrom .numeric import asanyarray, nan, ndim, result_type... | .venv\Lib\site-packages\numpy\_core\function_base.py | function_base.py | Python | 20,228 | 0.95 | 0.108257 | 0.043956 | vue-tools | 471 | 2024-02-22T08:49:52.025738 | BSD-3-Clause | false | 45883af1fb86ae1f231dd7c2bf6891d4 |
from typing import Literal as L\nfrom typing import SupportsIndex, TypeAlias, TypeVar, overload\n\nfrom _typeshed import Incomplete\n\nimport numpy as np\nfrom numpy._typing import (\n DTypeLike,\n NDArray,\n _ArrayLikeComplex_co,\n _ArrayLikeFloat_co,\n _DTypeLike,\n)\nfrom numpy._typing._array_like imp... | .venv\Lib\site-packages\numpy\_core\function_base.pyi | function_base.pyi | Other | 7,342 | 0.85 | 0.086331 | 0.048327 | react-lib | 701 | 2023-08-03T09:21:20.840477 | Apache-2.0 | false | 659bbac0d82f32deaa00adf7155a52a0 |
"""Machine limits for Float32 and Float64 and (long double) if available...\n\n"""\n__all__ = ['finfo', 'iinfo']\n\nimport types\nimport warnings\n\nfrom numpy._utils import set_module\n\nfrom . import numeric\nfrom . import numerictypes as ntypes\nfrom ._machar import MachAr\nfrom .numeric import array, inf, nan\nfrom... | .venv\Lib\site-packages\numpy\_core\getlimits.py | getlimits.py | Python | 26,849 | 0.95 | 0.15508 | 0.079148 | python-kit | 521 | 2024-07-30T13:55:21.423890 | Apache-2.0 | false | 4a2f1131027bc3a4147496758573c1ed |
from numpy import finfo, iinfo\n\n__all__ = ["finfo", "iinfo"]\n | .venv\Lib\site-packages\numpy\_core\getlimits.pyi | getlimits.pyi | Other | 64 | 0.65 | 0 | 0 | react-lib | 205 | 2024-12-10T08:00:53.630216 | GPL-3.0 | false | 1261c9f9590eee251f7aac779f41fe4b |
import operator\nfrom contextlib import nullcontext\n\nimport numpy as np\nfrom numpy._utils import set_module\n\nfrom .numeric import dtype, ndarray, uint8\n\n__all__ = ['memmap']\n\ndtypedescr = dtype\nvalid_filemodes = ["r", "c", "r+", "w+"]\nwriteable_filemodes = ["r+", "w+"]\n\nmode_equivalents = {\n "readonly"... | .venv\Lib\site-packages\numpy\_core\memmap.py | memmap.py | Python | 13,014 | 0.95 | 0.118457 | 0.05137 | python-kit | 316 | 2024-02-13T09:22:09.937721 | BSD-3-Clause | false | dacdb0f3c2e0c696f6c93a651437fc8b |
from numpy import memmap\n\n__all__ = ["memmap"]\n | .venv\Lib\site-packages\numpy\_core\memmap.pyi | memmap.pyi | Other | 50 | 0.65 | 0 | 0 | vue-tools | 862 | 2023-11-21T22:30:32.445557 | GPL-3.0 | false | 27d6f79490050803fc71c5e3ad341fa1 |
"""\nCreate the numpy._core.multiarray namespace for backward compatibility.\nIn v1.16 the multiarray and umath c-extension modules were merged into\na single _multiarray_umath extension module. So we replicate the old\nnamespace by importing from the extension module.\n\n"""\n\nimport functools\n\nfrom . import _multi... | .venv\Lib\site-packages\numpy\_core\multiarray.py | multiarray.py | Python | 59,917 | 0.75 | 0.057889 | 0.018646 | node-utils | 603 | 2025-05-16T02:11:46.025392 | MIT | false | 9e867577b52f3c569f591e4194aa2424 |
# TODO: Sort out any and all missing functions in this namespace\nimport datetime as dt\nfrom collections.abc import Callable, Iterable, Sequence\nfrom typing import (\n Any,\n ClassVar,\n Final,\n Protocol,\n SupportsIndex,\n TypeAlias,\n TypedDict,\n TypeVar,\n Unpack,\n final,\n over... | .venv\Lib\site-packages\numpy\_core\multiarray.pyi | multiarray.pyi | Other | 33,435 | 0.95 | 0.109728 | 0.070033 | vue-tools | 803 | 2024-08-05T16:17:00.601272 | Apache-2.0 | false | 8790de7634a5aed5bc78709b30732e08 |
import builtins\nimport functools\nimport itertools\nimport math\nimport numbers\nimport operator\nimport sys\nimport warnings\n\nimport numpy as np\nfrom numpy.exceptions import AxisError\n\nfrom . import multiarray, numerictypes, overrides, shape_base, umath\nfrom . import numerictypes as nt\nfrom ._ufunc_config impo... | .venv\Lib\site-packages\numpy\_core\numeric.py | numeric.py | Python | 85,082 | 0.75 | 0.094928 | 0.0253 | node-utils | 612 | 2024-04-13T01:00:36.368215 | Apache-2.0 | false | acbc378071b06ce7ea6cc0f74b5b5fa2 |
from collections.abc import Callable, Sequence\nfrom typing import (\n Any,\n Final,\n Never,\n NoReturn,\n SupportsAbs,\n SupportsIndex,\n TypeAlias,\n TypeGuard,\n TypeVar,\n Unpack,\n overload,\n)\nfrom typing import Literal as L\n\nimport numpy as np\nfrom numpy import (\n False_... | .venv\Lib\site-packages\numpy\_core\numeric.pyi | numeric.pyi | Other | 19,924 | 0.95 | 0.112245 | 0.050648 | node-utils | 615 | 2024-11-10T06:23:16.048547 | GPL-3.0 | false | 2b32b84ca80263ef54a76be84833a0ae |
"""\nnumerictypes: Define the numeric type objects\n\nThis module is designed so "from numerictypes import \\*" is safe.\nExported symbols include:\n\n Dictionary with all registered number types (including aliases):\n sctypeDict\n\n Type objects (not all will be available, depends on platform):\n see variabl... | .venv\Lib\site-packages\numpy\_core\numerictypes.py | numerictypes.py | Python | 16,590 | 0.95 | 0.112164 | 0.040856 | react-lib | 868 | 2024-04-02T13:29:29.349529 | GPL-3.0 | false | 2e4da94b83bea76b0fa28870fb524478 |
import builtins\nfrom typing import Any, TypedDict, type_check_only\nfrom typing import Literal as L\n\nimport numpy as np\nfrom numpy import (\n bool,\n bool_,\n byte,\n bytes_,\n cdouble,\n character,\n clongdouble,\n complex64,\n complex128,\n complexfloating,\n csingle,\n datetim... | .venv\Lib\site-packages\numpy\_core\numerictypes.pyi | numerictypes.pyi | Other | 3,462 | 0.95 | 0.015625 | 0 | vue-tools | 258 | 2023-09-23T02:20:27.622676 | GPL-3.0 | false | 6a1148f1875bfdc4566169a1ff523093 |
"""Implementation of __array_function__ overrides from NEP-18."""\nimport collections\nimport functools\n\nfrom numpy._core._multiarray_umath import (\n _ArrayFunctionDispatcher,\n _get_implementing_args,\n add_docstring,\n)\nfrom numpy._utils import set_module # noqa: F401\nfrom numpy._utils._inspect import ... | .venv\Lib\site-packages\numpy\_core\overrides.py | overrides.py | Python | 7,424 | 0.95 | 0.245902 | 0.013605 | vue-tools | 127 | 2024-03-22T00:09:31.761842 | BSD-3-Clause | false | abcf7baa90078b1864c18cc7170aea96 |
from collections.abc import Callable, Iterable\nfrom typing import Any, Final, NamedTuple, ParamSpec, TypeVar\n\nfrom numpy._typing import _SupportsArrayFunc\n\n_T = TypeVar("_T")\n_Tss = ParamSpec("_Tss")\n_FuncT = TypeVar("_FuncT", bound=Callable[..., object])\n\n###\n\nARRAY_FUNCTIONS: set[Callable[..., Any]] = ...\... | .venv\Lib\site-packages\numpy\_core\overrides.pyi | overrides.pyi | Other | 1,761 | 0.95 | 0.145833 | 0.205128 | react-lib | 546 | 2023-10-21T04:24:19.765541 | BSD-3-Clause | false | 5cc5cb08a0c9ba8a1e34500138adf8cf |
"""\nStores and defines the low-level format_options context variable.\n\nThis is defined in its own file outside of the arrayprint module\nso we can import it from C while initializing the multiarray\nC module during import without introducing circular dependencies.\n"""\n\nimport sys\nfrom contextvars import ContextV... | .venv\Lib\site-packages\numpy\_core\printoptions.py | printoptions.py | Python | 1,088 | 0.95 | 0.03125 | 0.074074 | react-lib | 465 | 2024-07-30T02:42:07.109882 | MIT | false | 4d91a211dbc14ffa5b97d3b83af10645 |
from collections.abc import Callable\nfrom contextvars import ContextVar\nfrom typing import Any, Final, TypedDict\n\nfrom .arrayprint import _FormatDict\n\n__all__ = ["format_options"]\n\n###\n\nclass _FormatOptionsDict(TypedDict):\n edgeitems: int\n threshold: int\n floatmode: str\n precision: int\n su... | .venv\Lib\site-packages\numpy\_core\printoptions.pyi | printoptions.pyi | Other | 622 | 0.95 | 0.035714 | 0.090909 | node-utils | 411 | 2024-10-05T14:14:54.492386 | BSD-3-Clause | false | 3167fea396a6eedeb8b8b706a8867843 |
"""\nThis module contains a set of functions for record arrays.\n"""\nimport os\nimport warnings\nfrom collections import Counter\nfrom contextlib import nullcontext\n\nfrom numpy._utils import set_module\n\nfrom . import numeric as sb\nfrom . import numerictypes as nt\nfrom .arrayprint import _get_legacy_print_mode\n\... | .venv\Lib\site-packages\numpy\_core\records.py | records.py | Python | 37,856 | 0.95 | 0.163453 | 0.078261 | python-kit | 972 | 2024-01-05T13:03:03.670778 | GPL-3.0 | false | c4fe451f78cc42c1990de6ec0f5b7e89 |
# ruff: noqa: ANN401\n# pyright: reportSelfClsParameterName=false\nfrom collections.abc import Iterable, Sequence\nfrom typing import (\n Any,\n ClassVar,\n Literal,\n Protocol,\n SupportsIndex,\n TypeAlias,\n overload,\n type_check_only,\n)\n\nfrom _typeshed import StrOrBytesPath\nfrom typing_e... | .venv\Lib\site-packages\numpy\_core\records.pyi | records.pyi | Other | 9,268 | 0.95 | 0.108108 | 0.063291 | awesome-app | 314 | 2024-04-13T13:33:10.437196 | BSD-3-Clause | false | bdcc9d3ad9713276da7f13fb9804aed3 |
__all__ = ['atleast_1d', 'atleast_2d', 'atleast_3d', 'block', 'hstack',\n 'stack', 'unstack', 'vstack']\n\nimport functools\nimport itertools\nimport operator\n\nfrom . import fromnumeric as _from_nx\nfrom . import numeric as _nx\nfrom . import overrides\nfrom .multiarray import array, asanyarray, normalize_a... | .venv\Lib\site-packages\numpy\_core\shape_base.py | shape_base.py | Python | 33,736 | 0.95 | 0.11022 | 0.073383 | react-lib | 512 | 2025-05-28T16:10:44.996036 | GPL-3.0 | false | 82fc6b317d7a43d360a4be1cfe8bc1c2 |
from collections.abc import Sequence\nfrom typing import Any, SupportsIndex, TypeVar, overload\n\nfrom numpy import _CastingKind, generic\nfrom numpy._typing import ArrayLike, DTypeLike, NDArray, _ArrayLike, _DTypeLike\n\n__all__ = [\n "atleast_1d",\n "atleast_2d",\n "atleast_3d",\n "block",\n "hstack",\... | .venv\Lib\site-packages\numpy\_core\shape_base.pyi | shape_base.pyi | Other | 4,928 | 0.95 | 0.188571 | 0.104294 | react-lib | 357 | 2024-08-31T20:00:21.872165 | GPL-3.0 | false | 84b6d1c38797881973993dbdbb1ef57c |
"""\nThis module contains a set of functions for vectorized string\noperations.\n"""\n\nimport functools\nimport sys\n\nimport numpy as np\nfrom numpy import (\n add,\n equal,\n greater,\n greater_equal,\n less,\n less_equal,\n not_equal,\n)\nfrom numpy import (\n multiply as _multiply_ufunc,\n)... | .venv\Lib\site-packages\numpy\_core\strings.py | strings.py | Python | 52,465 | 0.75 | 0.067471 | 0.013268 | react-lib | 677 | 2023-08-02T10:08:07.401057 | GPL-3.0 | false | 414afd2eed2576e17e2f44c873605299 |
from typing import TypeAlias, overload\n\nimport numpy as np\nfrom numpy._typing import NDArray, _AnyShape, _SupportsArray\nfrom numpy._typing import _ArrayLikeAnyString_co as UST_co\nfrom numpy._typing import _ArrayLikeBytes_co as S_co\nfrom numpy._typing import _ArrayLikeInt_co as i_co\nfrom numpy._typing import _Arr... | .venv\Lib\site-packages\numpy\_core\strings.pyi | strings.pyi | Other | 14,013 | 0.95 | 0.264188 | 0.002123 | awesome-app | 290 | 2024-06-26T10:54:44.824590 | Apache-2.0 | false | e13b962d5a7cfc6b164956b64636d6ac |
"""\nCreate the numpy._core.umath namespace for backward compatibility. In v1.16\nthe multiarray and umath c-extension modules were merged into a single\n_multiarray_umath extension module. So we replicate the old namespace\nby importing from the extension module.\n\n"""\n\nimport numpy\n\nfrom . import _multiarray_uma... | .venv\Lib\site-packages\numpy\_core\umath.py | umath.py | Python | 2,190 | 0.95 | 0.05 | 0.072727 | vue-tools | 172 | 2024-11-22T07:28:41.887589 | GPL-3.0 | false | 3c01b8cc67783ad630f9a746ab5012c4 |
from numpy import (\n absolute,\n add,\n arccos,\n arccosh,\n arcsin,\n arcsinh,\n arctan,\n arctan2,\n arctanh,\n bitwise_and,\n bitwise_count,\n bitwise_or,\n bitwise_xor,\n cbrt,\n ceil,\n conj,\n conjugate,\n copysign,\n cos,\n cosh,\n deg2rad,\n deg... | .venv\Lib\site-packages\numpy\_core\umath.pyi | umath.pyi | Other | 2,840 | 0.85 | 0 | 0 | react-lib | 178 | 2023-10-11T11:13:40.783793 | Apache-2.0 | false | 82ae63f03248984c7273c328164ab02f |
from .overrides import get_array_function_like_doc as get_array_function_like_doc\n\ndef refer_to_array_attribute(attr: str, method: bool = True) -> tuple[str, str]: ...\n | .venv\Lib\site-packages\numpy\_core\_add_newdocs.pyi | _add_newdocs.pyi | Other | 171 | 0.85 | 0.333333 | 0 | vue-tools | 63 | 2024-06-22T18:58:48.820127 | MIT | false | 2a1d81b1743028667859959de814ff20 |
"""\nThis file is separate from ``_add_newdocs.py`` so that it can be mocked out by\nour sphinx ``conf.py`` during doc builds, where we want to avoid showing\nplatform-dependent information.\n"""\nimport os\nimport sys\n\nfrom numpy._core import dtype\nfrom numpy._core import numerictypes as _numerictypes\nfrom numpy._... | .venv\Lib\site-packages\numpy\_core\_add_newdocs_scalars.py | _add_newdocs_scalars.py | Python | 12,990 | 0.95 | 0.087179 | 0.035032 | awesome-app | 502 | 2023-08-01T22:04:32.461439 | BSD-3-Clause | false | cf2707671a9e224b36b5aa3bf3c1eaf6 |
from collections.abc import Iterable\nfrom typing import Final\n\nimport numpy as np\n\npossible_aliases: Final[list[tuple[type[np.number], str, str]]] = ...\n_system: Final[str] = ...\n_machine: Final[str] = ...\n_doc_alias_string: Final[str] = ...\n_bool_docstring: Final[str] = ...\nint_name: str = ...\nfloat_name: s... | .venv\Lib\site-packages\numpy\_core\_add_newdocs_scalars.pyi | _add_newdocs_scalars.pyi | Other | 589 | 0.85 | 0.1875 | 0 | react-lib | 986 | 2023-11-15T02:27:55.268621 | MIT | false | 517491d587464246187acf165900f285 |
"""\nFunctions in the ``as*array`` family that promote array-likes into arrays.\n\n`require` fits this category despite its name not matching this pattern.\n"""\nfrom .multiarray import array, asanyarray\nfrom .overrides import (\n array_function_dispatch,\n finalize_array_function_like,\n set_module,\n)\n\n__... | .venv\Lib\site-packages\numpy\_core\_asarray.py | _asarray.py | Python | 4,045 | 0.85 | 0.089552 | 0.054545 | react-lib | 602 | 2025-01-03T04:28:01.491478 | MIT | false | ef8976c101722a9568fd5b117dda8f31 |
from collections.abc import Iterable\nfrom typing import Any, Literal, TypeAlias, TypeVar, overload\n\nfrom numpy._typing import DTypeLike, NDArray, _SupportsArrayFunc\n\n_ArrayT = TypeVar("_ArrayT", bound=NDArray[Any])\n\n_Requirements: TypeAlias = Literal[\n "C", "C_CONTIGUOUS", "CONTIGUOUS",\n "F", "F_CONTIGUO... | .venv\Lib\site-packages\numpy\_core\_asarray.pyi | _asarray.pyi | Other | 1,114 | 0.85 | 0.073171 | 0.081081 | react-lib | 519 | 2024-02-25T16:34:01.569434 | GPL-3.0 | false | 17b3cd37d08437206c31bd4f6b765031 |
"""\nA place for code to be called from the implementation of np.dtype\n\nString handling is much easier to do correctly in python.\n"""\nimport numpy as np\n\n_kind_to_stem = {\n 'u': 'uint',\n 'i': 'int',\n 'c': 'complex',\n 'f': 'float',\n 'b': 'bool',\n 'V': 'void',\n 'O': 'object',\n 'M': '... | .venv\Lib\site-packages\numpy\_core\_dtype.py | _dtype.py | Python | 10,913 | 0.95 | 0.166667 | 0.112281 | vue-tools | 669 | 2025-06-18T02:08:20.362922 | Apache-2.0 | false | 39a1a9b2b80154498745cf4f81ea396a |
from typing import Final, TypeAlias, TypedDict, overload, type_check_only\nfrom typing import Literal as L\n\nfrom typing_extensions import ReadOnly, TypeVar\n\nimport numpy as np\n\n###\n\n_T = TypeVar("_T")\n\n_Name: TypeAlias = L["uint", "int", "complex", "float", "bool", "void", "object", "datetime", "timedelta", "... | .venv\Lib\site-packages\numpy\_core\_dtype.pyi | _dtype.pyi | Other | 1,909 | 0.95 | 0.327586 | 0.130435 | vue-tools | 916 | 2024-08-14T09:00:40.841222 | MIT | false | 129efdc74435f45db2d52a3e73e541b0 |
"""\nConversion from ctypes to dtype.\n\nIn an ideal world, we could achieve this through the PEP3118 buffer protocol,\nsomething like::\n\n def dtype_from_ctypes_type(t):\n # needed to ensure that the shape of `t` is within memoryview.format\n class DummyStruct(ctypes.Structure):\n _fields_... | .venv\Lib\site-packages\numpy\_core\_dtype_ctypes.py | _dtype_ctypes.py | Python | 3,846 | 0.95 | 0.15 | 0.121212 | react-lib | 470 | 2024-03-10T04:10:25.283083 | BSD-3-Clause | false | 892d3f75bf2571bb2f7de0dd6d5d3189 |
import _ctypes\nimport ctypes as ct\nfrom typing import Any, overload\n\nimport numpy as np\n\n#\n@overload\ndef dtype_from_ctypes_type(t: type[_ctypes.Array[Any] | _ctypes.Structure]) -> np.dtype[np.void]: ...\n@overload\ndef dtype_from_ctypes_type(t: type[ct.c_bool]) -> np.dtype[np.bool]: ...\n@overload\ndef dtype_fr... | .venv\Lib\site-packages\numpy\_core\_dtype_ctypes.pyi | _dtype_ctypes.pyi | Other | 3,765 | 0.95 | 0.433735 | 0.064103 | vue-tools | 252 | 2023-10-07T05:05:35.140002 | BSD-3-Clause | false | d8cbbb30a1dae25a89dd71e48ae4cc30 |
"""\nVarious richly-typed exceptions, that also help us deal with string formatting\nin python where it's easier.\n\nBy putting the formatting in `__str__`, we also avoid paying the cost for\nusers who silence the exceptions.\n"""\n\ndef _unpack_tuple(tup):\n if len(tup) == 1:\n return tup[0]\n else:\n ... | .venv\Lib\site-packages\numpy\_core\_exceptions.py | _exceptions.py | Python | 5,321 | 0.95 | 0.246914 | 0.069231 | python-kit | 338 | 2025-04-16T12:03:13.480017 | BSD-3-Clause | false | e282f1f797153aa857726446a5eb85a4 |
from collections.abc import Iterable\nfrom typing import Any, Final, TypeVar, overload\n\nimport numpy as np\nfrom numpy import _CastingKind\nfrom numpy._utils import set_module as set_module\n\n###\n\n_T = TypeVar("_T")\n_TupleT = TypeVar("_TupleT", bound=tuple[()] | tuple[Any, Any, *tuple[Any, ...]])\n_ExceptionT = T... | .venv\Lib\site-packages\numpy\_core\_exceptions.pyi | _exceptions.pyi | Other | 1,955 | 0.95 | 0.345455 | 0.046512 | react-lib | 752 | 2024-05-09T20:05:10.535395 | MIT | false | 471ee4b6aff3edae76d803e6cfb77d07 |
"""\nA place for internal code\n\nSome things are more easily handled Python.\n\n"""\nimport ast\nimport math\nimport re\nimport sys\nimport warnings\n\nfrom numpy import _NoValue\nfrom numpy.exceptions import DTypePromotionError\n\nfrom .multiarray import StringDType, array, dtype, promote_types\n\ntry:\n import ct... | .venv\Lib\site-packages\numpy\_core\_internal.py | _internal.py | Python | 29,939 | 0.95 | 0.201461 | 0.082614 | vue-tools | 436 | 2024-04-22T19:48:22.303877 | MIT | false | 8345580ded38c5762393f9da868d8f3c |
import ctypes as ct\nimport re\nfrom collections.abc import Callable, Iterable\nfrom typing import Any, Final, Generic, Self, overload\n\nfrom typing_extensions import TypeVar, deprecated\n\nimport numpy as np\nimport numpy.typing as npt\nfrom numpy.ctypeslib import c_intp\n\n_CastT = TypeVar("_CastT", bound=ct._CanCas... | .venv\Lib\site-packages\numpy\_core\_internal.pyi | _internal.pyi | Other | 2,726 | 0.95 | 0.333333 | 0.122807 | python-kit | 130 | 2024-09-23T18:48:19.235763 | GPL-3.0 | false | e57da0f32222dc4a72676dd16ebfa6c6 |
"""\nMachine arithmetic - determine the parameters of the\nfloating-point arithmetic system\n\nAuthor: Pearu Peterson, September 2003\n\n"""\n__all__ = ['MachAr']\n\nfrom ._ufunc_config import errstate\nfrom .fromnumeric import any\n\n# Need to speed this up...especially for longdouble\n\n# Deprecated 2021-10-20, NumPy... | .venv\Lib\site-packages\numpy\_core\_machar.py | _machar.py | Python | 11,924 | 0.95 | 0.140845 | 0.046296 | node-utils | 386 | 2023-11-01T22:44:13.041783 | Apache-2.0 | false | feeeac0e5366c1a39870d61c654f8560 |
from collections.abc import Iterable\nfrom typing import Any, Final, TypeVar, overload\n\nimport numpy as np\nfrom numpy import _CastingKind\nfrom numpy._utils import set_module as set_module\n\n###\n\n_T = TypeVar("_T")\n_TupleT = TypeVar("_TupleT", bound=tuple[()] | tuple[Any, Any, *tuple[Any, ...]])\n_ExceptionT = T... | .venv\Lib\site-packages\numpy\_core\_machar.pyi | _machar.pyi | Other | 1,955 | 0.95 | 0.345455 | 0.046512 | awesome-app | 90 | 2024-07-07T03:37:19.175192 | MIT | false | 471ee4b6aff3edae76d803e6cfb77d07 |
"""\nArray methods which are called by both the C-code for the method\nand the Python code for the NumPy-namespace function\n\n"""\nimport os\nimport pickle\nimport warnings\nfrom contextlib import nullcontext\n\nimport numpy as np\nfrom numpy._core import multiarray as mu\nfrom numpy._core import numerictypes as nt\nf... | .venv\Lib\site-packages\numpy\_core\_methods.py | _methods.py | Python | 9,685 | 0.95 | 0.231373 | 0.165138 | awesome-app | 46 | 2024-12-03T08:24:02.197085 | BSD-3-Clause | false | 2740e3b74074983adc0a5335b8fbbf31 |
from collections.abc import Callable\nfrom typing import Any, Concatenate, TypeAlias\n\nimport numpy as np\n\nfrom . import _exceptions as _exceptions\n\n###\n\n_Reduce2: TypeAlias = Callable[Concatenate[object, ...], Any]\n\n###\n\nbool_dt: np.dtype[np.bool] = ...\numr_maximum: _Reduce2 = ...\numr_minimum: _Reduce2 = ... | .venv\Lib\site-packages\numpy\_core\_methods.pyi | _methods.pyi | Other | 548 | 0.95 | 0 | 0.125 | react-lib | 628 | 2024-12-04T06:01:33.963665 | GPL-3.0 | false | 8c911b120ba9a6bb15acbb74016b8158 |
!<arch>\n/ -1 0 256 `\n | .venv\Lib\site-packages\numpy\_core\_multiarray_tests.cp313-win_amd64.lib | _multiarray_tests.cp313-win_amd64.lib | Other | 2,418 | 0.8 | 0 | 0 | vue-tools | 155 | 2024-01-17T22:04:25.879772 | GPL-3.0 | true | 9033940c038962dabe3f2fd4fafe2b7c |
MZ | .venv\Lib\site-packages\numpy\_core\_multiarray_tests.cp313-win_amd64.pyd | _multiarray_tests.cp313-win_amd64.pyd | Other | 63,488 | 0.95 | 0.032448 | 0.00597 | awesome-app | 155 | 2023-08-05T07:19:26.393389 | GPL-3.0 | true | 62248b2455df94d63ece8573bc62da6b |
!<arch>\n/ -1 0 210 `\n | .venv\Lib\site-packages\numpy\_core\_multiarray_umath.cp313-win_amd64.lib | _multiarray_umath.cp313-win_amd64.lib | Other | 2,192 | 0.8 | 0 | 0 | vue-tools | 824 | 2025-03-05T11:18:33.755178 | GPL-3.0 | false | 267cc0beae0ae05dd3e6f5a8f5e2fccd |
!<arch>\n/ -1 0 218 `\n | .venv\Lib\site-packages\numpy\_core\_operand_flag_tests.cp313-win_amd64.lib | _operand_flag_tests.cp313-win_amd64.lib | Other | 2,228 | 0.8 | 0 | 0 | python-kit | 203 | 2024-12-23T13:56:46.579417 | BSD-3-Clause | true | db45bc3d7acf2174f201130ca9ec0689 |
MZ | .venv\Lib\site-packages\numpy\_core\_operand_flag_tests.cp313-win_amd64.pyd | _operand_flag_tests.cp313-win_amd64.pyd | Other | 12,288 | 0.95 | 0.016667 | 0 | python-kit | 452 | 2024-09-06T02:22:41.208382 | MIT | true | cd75a241970013476e679f1d0153a86f |
!<arch>\n/ -1 0 202 `\n | .venv\Lib\site-packages\numpy\_core\_rational_tests.cp313-win_amd64.lib | _rational_tests.cp313-win_amd64.lib | Other | 2,156 | 0.8 | 0 | 0 | vue-tools | 822 | 2023-11-15T08:37:50.377033 | Apache-2.0 | true | 23cf9c903fbdaa046a67d04fa1414d7d |
MZ | .venv\Lib\site-packages\numpy\_core\_rational_tests.cp313-win_amd64.pyd | _rational_tests.cp313-win_amd64.pyd | Other | 39,936 | 0.95 | 0.004274 | 0.012876 | python-kit | 236 | 2023-10-28T16:46:04.441700 | BSD-3-Clause | true | 39db811a75a5f13101e727aeeb38fdd6 |
!<arch>\n/ -1 0 162 `\n | .venv\Lib\site-packages\numpy\_core\_simd.cp313-win_amd64.lib | _simd.cp313-win_amd64.lib | Other | 1,976 | 0.8 | 0 | 0 | react-lib | 323 | 2025-01-12T08:58:26.029617 | Apache-2.0 | false | c4d7ad23c66cd2e4e08068dc8919730b |
from types import ModuleType\nfrom typing import TypedDict, type_check_only\n\n# NOTE: these 5 are only defined on systems with an intel processor\nSSE42: ModuleType | None = ...\nFMA3: ModuleType | None = ...\nAVX2: ModuleType | None = ...\nAVX512F: ModuleType | None = ...\nAVX512_SKX: ModuleType | None = ...\n\nbasel... | .venv\Lib\site-packages\numpy\_core\_simd.pyi | _simd.pyi | Other | 694 | 0.95 | 0.12 | 0.05 | react-lib | 128 | 2025-03-06T12:52:34.452603 | Apache-2.0 | false | 2d5d712cd9758943395ee4e62b31e3a6 |
"""\nString-handling utilities to avoid locale-dependence.\n\nUsed primarily to generate type name aliases.\n"""\n# "import string" is costly to import!\n# Construct the translation tables directly\n# "A" = chr(65), "a" = chr(97)\n_all_chars = tuple(map(chr, range(256)))\n_ascii_upper = _all_chars[65:65 + 26]\n_ascii... | .venv\Lib\site-packages\numpy\_core\_string_helpers.py | _string_helpers.py | Python | 2,945 | 0.95 | 0.07 | 0.037037 | react-lib | 635 | 2024-09-05T08:43:00.609139 | GPL-3.0 | false | 1a3a8b66f1e7f6e51c7ce3724d6275e8 |
from typing import Final\n\n_all_chars: Final[tuple[str, ...]] = ...\n_ascii_upper: Final[tuple[str, ...]] = ...\n_ascii_lower: Final[tuple[str, ...]] = ...\n\nLOWER_TABLE: Final[tuple[str, ...]] = ...\nUPPER_TABLE: Final[tuple[str, ...]] = ...\n\ndef english_lower(s: str) -> str: ...\ndef english_upper(s: str) -> str:... | .venv\Lib\site-packages\numpy\_core\_string_helpers.pyi | _string_helpers.pyi | Other | 370 | 0.85 | 0.25 | 0 | node-utils | 64 | 2024-04-01T16:39:21.022748 | BSD-3-Clause | false | 1c8fed39509d4ecad6e1b47a739f99b9 |
!<arch>\n/ -1 0 218 `\n | .venv\Lib\site-packages\numpy\_core\_struct_ufunc_tests.cp313-win_amd64.lib | _struct_ufunc_tests.cp313-win_amd64.lib | Other | 2,228 | 0.8 | 0 | 0 | node-utils | 86 | 2025-03-05T18:06:35.958062 | MIT | true | f84a82856ffcb6f72e13e1ac6897e8c0 |
MZ | .venv\Lib\site-packages\numpy\_core\_struct_ufunc_tests.cp313-win_amd64.pyd | _struct_ufunc_tests.cp313-win_amd64.pyd | Other | 14,336 | 0.95 | 0.014493 | 0.014493 | awesome-app | 246 | 2025-06-17T09:46:44.497193 | Apache-2.0 | true | a1f4cda13512e5db0845fd31f2674bf7 |
"""\nDue to compatibility, numpy has a very large number of different naming\nconventions for the scalar types (those subclassing from `numpy.generic`).\nThis file produces a convoluted set of dictionaries mapping names to types,\nand sometimes other mappings too.\n\n.. data:: allTypes\n A dictionary of names to typ... | .venv\Lib\site-packages\numpy\_core\_type_aliases.py | _type_aliases.py | Python | 3,608 | 0.95 | 0.12605 | 0.125 | vue-tools | 960 | 2024-09-14T15:35:10.019347 | BSD-3-Clause | false | ea60b444435ebcee365dd91721173200 |
from collections.abc import Collection\nfrom typing import Final, TypeAlias, TypedDict, type_check_only\nfrom typing import Literal as L\n\nimport numpy as np\n\n__all__ = (\n "_abstract_type_names",\n "_aliases",\n "_extra_aliases",\n "allTypes",\n "c_names_dict",\n "sctypeDict",\n "sctypes",\n)\n... | .venv\Lib\site-packages\numpy\_core\_type_aliases.pyi | _type_aliases.pyi | Other | 2,485 | 0.85 | 0.041237 | 0 | node-utils | 327 | 2023-08-02T03:40:40.715009 | GPL-3.0 | false | 26d9adb59380208fb7ab838fa4df952c |
"""\nFunctions for changing global ufunc configuration\n\nThis provides helpers which wrap `_get_extobj_dict` and `_make_extobj`, and\n`_extobj_contextvar` from umath.\n"""\nimport functools\n\nfrom numpy._utils import set_module\n\nfrom .umath import _extobj_contextvar, _get_extobj_dict, _make_extobj\n\n__all__ = [\n ... | .venv\Lib\site-packages\numpy\_core\_ufunc_config.py | _ufunc_config.py | Python | 15,541 | 0.95 | 0.096115 | 0.020566 | node-utils | 481 | 2024-03-22T13:41:18.785554 | Apache-2.0 | false | faaaea6e1bdd9673c579c3011252314a |
from collections.abc import Callable\nfrom typing import Any, Literal, TypeAlias, TypedDict, type_check_only\n\nfrom _typeshed import SupportsWrite\n\nfrom numpy import errstate as errstate\n\n_ErrKind: TypeAlias = Literal["ignore", "warn", "raise", "call", "print", "log"]\n_ErrFunc: TypeAlias = Callable[[str, int], An... | .venv\Lib\site-packages\numpy\_core\_ufunc_config.pyi | _ufunc_config.pyi | Other | 1,004 | 0.95 | 0.28125 | 0.038462 | react-lib | 755 | 2024-05-05T08:13:24.752228 | GPL-3.0 | false | cdaf1cc0b9841d459268b54032328d36 |
!<arch>\n/ -1 0 190 `\n | .venv\Lib\site-packages\numpy\_core\_umath_tests.cp313-win_amd64.lib | _umath_tests.cp313-win_amd64.lib | Other | 2,104 | 0.8 | 0 | 0 | react-lib | 891 | 2023-08-02T23:49:49.627095 | Apache-2.0 | true | 2e3d912afdc52a3f417f52119b6d62fb |
MZ | .venv\Lib\site-packages\numpy\_core\_umath_tests.cp313-win_amd64.pyd | _umath_tests.cp313-win_amd64.pyd | Other | 34,304 | 0.95 | 0.013953 | 0.013953 | node-utils | 510 | 2024-02-02T01:19:05.461590 | BSD-3-Clause | true | 95d2a9be8b0a3fb50e0cc5fef222398e |
"""\nContains the core of NumPy: ndarray, ufuncs, dtypes, etc.\n\nPlease note that this module is private. All functions and objects\nare available in the main ``numpy`` namespace - use that instead.\n\n"""\n\nimport os\n\nfrom numpy.version import version as __version__\n\n# disables OpenBLAS affinity setting of the ... | .venv\Lib\site-packages\numpy\_core\__init__.py | __init__.py | Python | 5,728 | 0.95 | 0.102151 | 0.162162 | python-kit | 418 | 2025-03-25T03:46:11.805569 | MIT | false | c32ac8bd8ea61f6bd99b5f68505ec834 |
# NOTE: The `np._core` namespace is deliberately kept empty due to it\n# being private\n | .venv\Lib\site-packages\numpy\_core\__init__.pyi | __init__.pyi | Other | 88 | 0.6 | 0 | 1 | react-lib | 919 | 2025-03-22T11:56:12.545401 | Apache-2.0 | false | bc05219a18cefbf5cf2aae9837e1ce52 |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_ARRAYOBJECT_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_ARRAYOBJECT_H_\n#define Py_ARRAYOBJECT_H\n\n#include "ndarrayobject.h"\n\n#endif /* NUMPY_CORE_INCLUDE_NUMPY_ARRAYOBJECT_H_ */\n | .venv\Lib\site-packages\numpy\_core\include\numpy\arrayobject.h | arrayobject.h | C | 211 | 0.95 | 0 | 1 | python-kit | 845 | 2025-04-24T02:57:19.057888 | GPL-3.0 | false | 09997308b2290c3bc281bc317e6fc5a1 |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_ARRAYSCALARS_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_ARRAYSCALARS_H_\n\n#ifndef _MULTIARRAYMODULE\ntypedef struct {\n PyObject_HEAD\n npy_bool obval;\n} PyBoolScalarObject;\n#endif\n\n\ntypedef struct {\n PyObject_HEAD\n signed char obval;\n} PyByteScalarObject;... | .venv\Lib\site-packages\numpy\_core\include\numpy\arrayscalars.h | arrayscalars.h | C | 4,439 | 0.95 | 0.015306 | 0.209459 | react-lib | 843 | 2023-09-15T22:27:56.655969 | Apache-2.0 | false | e956f443f0d79d539f5248b8f9aebb23 |
/*\n * The public DType API\n */\n\n#ifndef NUMPY_CORE_INCLUDE_NUMPY___DTYPE_API_H_\n#define NUMPY_CORE_INCLUDE_NUMPY___DTYPE_API_H_\n\nstruct PyArrayMethodObject_tag;\n\n/*\n * Largely opaque struct for DType classes (i.e. metaclass instances).\n * The internal definition is currently in `ndarraytypes.h` (export is a ... | .venv\Lib\site-packages\numpy\_core\include\numpy\dtype_api.h | dtype_api.h | C | 19,718 | 0.95 | 0.147917 | 0.751825 | awesome-app | 923 | 2024-02-19T21:59:11.199307 | MIT | false | f964e255d8831708fbcbfdced0e10121 |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_HALFFLOAT_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_HALFFLOAT_H_\n\n#include <Python.h>\n#include <numpy/npy_math.h>\n\n#ifdef __cplusplus\nextern "C" {\n#endif\n\n/*\n * Half-precision routines\n */\n\n/* Conversions */\nfloat npy_half_to_float(npy_half h);\ndouble npy_half_to_double(npy_ha... | .venv\Lib\site-packages\numpy\_core\include\numpy\halffloat.h | halffloat.h | C | 2,029 | 0.95 | 0.014286 | 0.525424 | python-kit | 158 | 2023-10-29T15:09:09.868295 | Apache-2.0 | false | 30abfb26f7896504e978b52afb6b9e06 |
/*\n * DON'T INCLUDE THIS DIRECTLY.\n */\n#ifndef NUMPY_CORE_INCLUDE_NUMPY_NDARRAYOBJECT_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NDARRAYOBJECT_H_\n\n#ifdef __cplusplus\nextern "C" {\n#endif\n\n#include <Python.h>\n#include "ndarraytypes.h"\n#include "dtype_api.h"\n\n/* Includes the "function" C-API -- these are all stored... | .venv\Lib\site-packages\numpy\_core\include\numpy\ndarrayobject.h | ndarrayobject.h | C | 12,361 | 0.95 | 0.069079 | 0.444915 | react-lib | 652 | 2024-08-03T21:21:29.455074 | MIT | false | 415a16200e35b304555a9929aa60141c |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_NDARRAYTYPES_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NDARRAYTYPES_H_\n\n#include "npy_common.h"\n#include "npy_endian.h"\n#include "npy_cpu.h"\n#include "utils.h"\n\n#ifdef __cplusplus\nextern "C" {\n#endif\n\n#define NPY_NO_EXPORT NPY_VISIBILITY_HIDDEN\n\n/* Always allow threading unless ... | .venv\Lib\site-packages\numpy\_core\include\numpy\ndarraytypes.h | ndarraytypes.h | C | 67,760 | 0.75 | 0.065641 | 0.574685 | python-kit | 381 | 2024-08-11T23:17:54.207200 | BSD-3-Clause | false | 185d4395a5f61b640db66856f8cd75f7 |
/*\n * This header file defines relevant features which:\n * - Require runtime inspection depending on the NumPy version.\n * - May be needed when compiling with an older version of NumPy to allow\n * a smooth transition.\n *\n * As such, it is shipped with NumPy 2.0, but designed to be vendored in full\n * or parts ... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_2_compat.h | npy_2_compat.h | C | 8,795 | 0.95 | 0.11245 | 0.581818 | awesome-app | 878 | 2025-05-15T19:15:18.136419 | MIT | false | ba47551381833f768631cd5132d16b16 |
/* This header is designed to be copy-pasted into downstream packages, since it provides\n a compatibility layer between the old C struct complex types and the new native C99\n complex types. The new macros are in numpy/npy_math.h, which is why it is included here. */\n#ifndef NUMPY_CORE_INCLUDE_NUMPY_NPY_2_COMPLEX... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_2_complexcompat.h | npy_2_complexcompat.h | C | 885 | 0.95 | 0 | 0.92 | node-utils | 233 | 2025-05-05T22:12:32.810445 | BSD-3-Clause | false | 6aeabbf500c8b675aef5c6e6fcbf2296 |
/*\n * This is a convenience header file providing compatibility utilities\n * for supporting different minor versions of Python 3.\n * It was originally used to support the transition from Python 2,\n * hence the "3k" naming.\n *\n * If you want to use this for your own projects, it's recommended to make a\n * copy of... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_3kcompat.h | npy_3kcompat.h | C | 10,022 | 0.95 | 0.109626 | 0.237952 | python-kit | 748 | 2025-04-30T07:06:08.115392 | MIT | false | 21a649152e66026b2667b478d5e8f6c3 |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_NPY_COMMON_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NPY_COMMON_H_\n\n/* need Python.h for npy_intp, npy_uintp */\n#include <Python.h>\n\n/* numpconfig.h is auto-generated */\n#include "numpyconfig.h"\n#ifdef HAVE_NPY_CONFIG_H\n#include <npy_config.h>\n#endif\n\n/*\n * using static inline mo... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_common.h | npy_common.h | C | 33,563 | 0.95 | 0.03173 | 0.849119 | vue-tools | 386 | 2024-07-23T06:24:53.023642 | BSD-3-Clause | false | 4fecb0c4aa3a61894dbeabbfe870e12d |
/*\n * This set (target) cpu specific macros:\n * - Possible values:\n * NPY_CPU_X86\n * NPY_CPU_AMD64\n * NPY_CPU_PPC\n * NPY_CPU_PPC64\n * NPY_CPU_PPC64LE\n * NPY_CPU_SPARC\n * NPY_CPU_S390\n * NPY_CPU_IA64\n ... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_cpu.h | npy_cpu.h | C | 4,349 | 0.95 | 0.056452 | 0.983333 | vue-tools | 505 | 2024-06-20T17:46:13.034579 | Apache-2.0 | false | de54f9ac02af7b10a1098bd3dada1d6e |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_NPY_ENDIAN_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NPY_ENDIAN_H_\n\n/*\n * NPY_BYTE_ORDER is set to the same value as BYTE_ORDER set by glibc in\n * endian.h\n */\n\n#if defined(NPY_HAVE_ENDIAN_H) || defined(NPY_HAVE_SYS_ENDIAN_H)\n /* Use endian.h if available */\n\n #if defined(NPY... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_endian.h | npy_endian.h | C | 2,912 | 0.95 | 0.064103 | 0.61194 | awesome-app | 513 | 2024-04-17T03:08:09.316170 | Apache-2.0 | false | 46484be9ec6b29b73f863017eb51e8fd |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_NPY_MATH_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NPY_MATH_H_\n\n#include <numpy/npy_common.h>\n\n#include <math.h>\n\n/* By adding static inline specifiers to npy_math function definitions when\n appropriate, compiler is given the opportunity to optimize */\n#if NPY_INLINE_MATH\n#define ... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_math.h | npy_math.h | C | 19,460 | 0.95 | 0.031561 | 0.512671 | node-utils | 69 | 2024-08-27T01:12:50.706523 | MIT | false | 85ca6cd78afd023523342f9b941be867 |
/*\n * This include file is provided for inclusion in Cython *.pyd files where\n * one would like to define the NPY_NO_DEPRECATED_API macro. It can be\n * included by\n *\n * cdef extern from "npy_no_deprecated_api.h": pass\n *\n */\n#ifndef NPY_NO_DEPRECATED_API\n\n/* put this check here since there may be multiple in... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_no_deprecated_api.h | npy_no_deprecated_api.h | C | 698 | 0.95 | 0.1 | 0.888889 | react-lib | 665 | 2025-04-11T00:03:38.799130 | Apache-2.0 | false | c735cd1c24e6c99ab591477f76f9d138 |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_NPY_OS_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NPY_OS_H_\n\n#if defined(linux) || defined(__linux) || defined(__linux__)\n #define NPY_OS_LINUX\n#elif defined(__FreeBSD__) || defined(__NetBSD__) || \\n defined(__OpenBSD__) || defined(__DragonFly__)\n #define NPY_OS_BSD\n ... | .venv\Lib\site-packages\numpy\_core\include\numpy\npy_os.h | npy_os.h | C | 1,298 | 0.95 | 0.071429 | 0.975 | awesome-app | 421 | 2024-01-08T18:46:15.464624 | GPL-3.0 | false | 6543fdc6b9b24cef66312b10f96ad9c8 |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_NPY_NUMPYCONFIG_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_NPY_NUMPYCONFIG_H_\n\n#include "_numpyconfig.h"\n\n/*\n * On Mac OS X, because there is only one configuration stage for all the archs\n * in universal builds, any macro which depends on the arch needs to be\n * hardcoded.\n *\n * Not... | .venv\Lib\site-packages\numpy\_core\include\numpy\numpyconfig.h | numpyconfig.h | C | 7,515 | 0.95 | 0.082418 | 1 | awesome-app | 789 | 2023-12-01T16:47:07.665732 | Apache-2.0 | false | d0bb4ca911d6d656cc651b4ab7a76a5c |
#ifndef NUMPY_CORE_INCLUDE_NUMPY_UFUNCOBJECT_H_\n#define NUMPY_CORE_INCLUDE_NUMPY_UFUNCOBJECT_H_\n\n#include <numpy/npy_math.h>\n#include <numpy/npy_common.h>\n\n#ifdef __cplusplus\nextern "C" {\n#endif\n\n/*\n * The legacy generic inner loop for a standard element-wise or\n * generalized ufunc.\n */\ntypedef void (*Py... | .venv\Lib\site-packages\numpy\_core\include\numpy\ufuncobject.h | ufuncobject.h | C | 12,123 | 0.95 | 0.145773 | 0.763514 | react-lib | 164 | 2025-02-26T22:07:20.189253 | GPL-3.0 | false | 331697346edfe6b5e4a17e8322a034ab |
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