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repo_id stringlengths 12 110 | file_path stringlengths 24 164 | content stringlengths 3 89.3M | __index_level_0__ int64 0 0 |
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public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/compat.py | """
Helpers for sharing tests between DataFrame/Series
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from pandas import DataFrame
if TYPE_CHECKING:
from pandas._typing import DtypeObj
def get_dtype(obj) -> DtypeObj:
if isinstance(obj, DataFrame):
# Note: we are assuming on... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/_warnings.py | from __future__ import annotations
from contextlib import (
contextmanager,
nullcontext,
)
import inspect
import re
import sys
from typing import (
TYPE_CHECKING,
Literal,
cast,
)
import warnings
if TYPE_CHECKING:
from collections.abc import (
Generator,
Sequence,
)
@cont... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_testing/__init__.py | from __future__ import annotations
import collections
from collections import Counter
from datetime import datetime
from decimal import Decimal
import operator
import os
import re
import string
from sys import byteorder
from typing import (
TYPE_CHECKING,
Callable,
ContextManager,
cast,
)
import numpy... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/compat/_constants.py | """
_constants
======
Constants relevant for the Python implementation.
"""
from __future__ import annotations
import platform
import sys
import sysconfig
IS64 = sys.maxsize > 2**32
PY310 = sys.version_info >= (3, 10)
PY311 = sys.version_info >= (3, 11)
PY312 = sys.version_info >= (3, 12)
PYPY = platform.python_im... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/compat/compressors.py | """
Patched ``BZ2File`` and ``LZMAFile`` to handle pickle protocol 5.
"""
from __future__ import annotations
from pickle import PickleBuffer
from pandas.compat._constants import PY310
try:
import bz2
has_bz2 = True
except ImportError:
has_bz2 = False
try:
import lzma
has_lzma = True
except Im... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/compat/pyarrow.py | """ support pyarrow compatibility across versions """
from __future__ import annotations
from pandas.util.version import Version
try:
import pyarrow as pa
_palv = Version(Version(pa.__version__).base_version)
pa_version_under10p1 = _palv < Version("10.0.1")
pa_version_under11p0 = _palv < Version("11... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/compat/_optional.py | from __future__ import annotations
import importlib
import sys
from typing import TYPE_CHECKING
import warnings
from pandas.util._exceptions import find_stack_level
from pandas.util.version import Version
if TYPE_CHECKING:
import types
# Update install.rst & setup.cfg when updating versions!
VERSIONS = {
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/compat/__init__.py | """
compat
======
Cross-compatible functions for different versions of Python.
Other items:
* platform checker
"""
from __future__ import annotations
import os
import platform
import sys
from typing import TYPE_CHECKING
from pandas.compat._constants import (
IS64,
ISMUSL,
PY310,
PY311,
PY312,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/compat/pickle_compat.py | """
Support pre-0.12 series pickle compatibility.
"""
from __future__ import annotations
import contextlib
import copy
import io
import pickle as pkl
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs.arrays import NDArrayBacked
from pandas._libs.tslibs import BaseOffset
from pandas import Index
... | 0 |
public_repos/pandas/pandas/compat | public_repos/pandas/pandas/compat/numpy/function.py | """
For compatibility with numpy libraries, pandas functions or methods have to
accept '*args' and '**kwargs' parameters to accommodate numpy arguments that
are not actually used or respected in the pandas implementation.
To ensure that users do not abuse these parameters, validation is performed in
'validators.py' to... | 0 |
public_repos/pandas/pandas/compat | public_repos/pandas/pandas/compat/numpy/__init__.py | """ support numpy compatibility across versions """
import warnings
import numpy as np
from pandas.util.version import Version
# numpy versioning
_np_version = np.__version__
_nlv = Version(_np_version)
np_version_lt1p23 = _nlv < Version("1.23")
np_version_gte1p24 = _nlv >= Version("1.24")
np_version_gte1p24p3 = _nl... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/arrays/__init__.py | """
All of pandas' ExtensionArrays.
See :ref:`extending.extension-types` for more.
"""
from pandas.core.arrays import (
ArrowExtensionArray,
ArrowStringArray,
BooleanArray,
Categorical,
DatetimeArray,
FloatingArray,
IntegerArray,
IntervalArray,
NumpyExtensionArray,
PeriodArray,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashtable.pxd | from numpy cimport (
intp_t,
ndarray,
)
from pandas._libs.khash cimport (
complex64_t,
complex128_t,
float32_t,
float64_t,
int8_t,
int16_t,
int32_t,
int64_t,
kh_complex64_t,
kh_complex128_t,
kh_float32_t,
kh_float64_t,
kh_int8_t,
kh_int16_t,
kh_int32_... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/byteswap.pyx | """
The following are faster versions of struct.unpack that avoid the overhead of Python
function calls.
In the SAS7BDAT parser, they may be called up to (n_rows * n_cols) times.
"""
from cython cimport Py_ssize_t
from libc.stdint cimport (
uint16_t,
uint32_t,
uint64_t,
)
from libc.string cimport memcpy
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/khash_for_primitive_helper.pxi.in | """
Template for wrapping khash-tables for each primitive `dtype`
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
{{py:
# name, c_type
primitive_types = [('int64', 'int64_t'),
('uint64', 'uint64_t'),
('float64', 'float64_t'),
('int3... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashtable.pyi | from typing import (
Any,
Hashable,
Literal,
)
import numpy as np
from pandas._typing import npt
def unique_label_indices(
labels: np.ndarray, # const int64_t[:]
) -> np.ndarray: ...
class Factorizer:
count: int
uniques: Any
def __init__(self, size_hint: int) -> None: ...
def get_co... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/arrays.pyi | from typing import Sequence
import numpy as np
from pandas._typing import (
AxisInt,
DtypeObj,
Self,
Shape,
)
class NDArrayBacked:
_dtype: DtypeObj
_ndarray: np.ndarray
def __init__(self, values: np.ndarray, dtype: DtypeObj) -> None: ...
@classmethod
def _simple_new(cls, values: n... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/sparse_op_helper.pxi.in | """
Template for each `dtype` helper function for sparse ops
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
# ----------------------------------------------------------------------
# Sparse op
# ----------------------------------------------------------------------
ctypedef fused sparse_... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/join.pyx | cimport cython
from cython cimport Py_ssize_t
import numpy as np
cimport numpy as cnp
from numpy cimport (
int64_t,
intp_t,
ndarray,
)
cnp.import_array()
from pandas._libs.algos import groupsort_indexer
from pandas._libs.dtypes cimport (
numeric_object_t,
numeric_t,
)
@cython.wraparound(False)... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/parsers.pyi | from typing import (
Hashable,
Literal,
)
import numpy as np
from pandas._typing import (
ArrayLike,
Dtype,
npt,
)
STR_NA_VALUES: set[str]
DEFAULT_BUFFER_HEURISTIC: int
def sanitize_objects(
values: npt.NDArray[np.object_],
na_values: set,
) -> int: ...
class TextReader:
unnamed_col... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/reshape.pyi | import numpy as np
from pandas._typing import npt
def unstack(
values: np.ndarray, # reshape_t[:, :]
mask: np.ndarray, # const uint8_t[:]
stride: int,
length: int,
width: int,
new_values: np.ndarray, # reshape_t[:, :]
new_mask: np.ndarray, # uint8_t[:, :]
) -> None: ...
def explode(
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/internals.pyx | from collections import defaultdict
import weakref
cimport cython
from cpython.pyport cimport PY_SSIZE_T_MAX
from cpython.slice cimport PySlice_GetIndicesEx
from cython cimport Py_ssize_t
import numpy as np
cimport numpy as cnp
from numpy cimport (
NPY_INTP,
int64_t,
intp_t,
ndarray,
)
cnp.import_ar... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/algos_common_helper.pxi.in | """
Template for each `dtype` helper function using 1-d template
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
# ----------------------------------------------------------------------
# ensure_dtype
# ----------------------------------------------------------------------
def ensure_pla... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/lib.pxd | from numpy cimport ndarray
cdef bint c_is_list_like(object, bint) except -1
cpdef ndarray eq_NA_compat(ndarray[object] arr, object key)
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/algos_take_helper.pxi.in | """
Template for each `dtype` helper function for take
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
# ----------------------------------------------------------------------
# take_1d, take_2d
# ----------------------------------------------------------------------
{{py:
# c_type_in, ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashtable_class_helper.pxi.in | """
Template for each `dtype` helper function for hashtable
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
{{py:
# name
complex_types = ['complex64',
'complex128']
}}
{{for name in complex_types}}
cdef kh{{name}}_t to_kh{{name}}_t({{name}}_t val) noexcept nogil:
cd... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/algos.pxd | from pandas._libs.dtypes cimport (
numeric_object_t,
numeric_t,
)
cdef numeric_t kth_smallest_c(numeric_t* arr, Py_ssize_t k, Py_ssize_t n) noexcept nogil
cdef enum TiebreakEnumType:
TIEBREAK_AVERAGE
TIEBREAK_MIN,
TIEBREAK_MAX
TIEBREAK_FIRST
TIEBREAK_FIRST_DESCENDING
TIEBREAK_DENSE
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/properties.pyx | from cpython.dict cimport (
PyDict_Contains,
PyDict_GetItem,
PyDict_SetItem,
)
from cython cimport Py_ssize_t
cdef class CachedProperty:
cdef readonly:
object fget, name, __doc__
def __init__(self, fget):
self.fget = fget
self.name = fget.__name__
self.__doc__ = g... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/ops_dispatch.pyi | import numpy as np
def maybe_dispatch_ufunc_to_dunder_op(
self, ufunc: np.ufunc, method: str, *inputs, **kwargs
): ...
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/lib.pyx | from collections import abc
from decimal import Decimal
from enum import Enum
from sys import getsizeof
from typing import (
Literal,
_GenericAlias,
)
cimport cython
from cpython.datetime cimport (
PyDate_Check,
PyDateTime_Check,
PyDelta_Check,
PyTime_Check,
date,
datetime,
import_d... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/meson.build | _algos_take_helper = custom_target('algos_take_helper_pxi',
output: 'algos_take_helper.pxi',
input: 'algos_take_helper.pxi.in',
command: [
py, tempita, '@INPUT@', '-o', '@OUTDIR@'
]
)
_algos_common_helper = custom_target('algos_common_helper_pxi',
output: 'algos_common_helper.pxi',
input... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/sparse.pyx | cimport cython
import numpy as np
cimport numpy as cnp
from libc.math cimport (
INFINITY as INF,
NAN as NaN,
)
from numpy cimport (
float64_t,
int8_t,
int32_t,
int64_t,
ndarray,
uint8_t,
)
cnp.import_array()
# -------------------------------------------------------------------------... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/testing.pyx | import cmath
import math
import warnings
import numpy as np
from numpy cimport import_array
import_array()
from pandas._libs.missing cimport (
checknull,
is_matching_na,
)
from pandas._libs.util cimport (
is_array,
is_complex_object,
is_real_number_object,
)
from pandas.util._exceptions import ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/groupby.pyx | cimport cython
from cython cimport (
Py_ssize_t,
floating,
)
from libc.math cimport (
NAN,
sqrt,
)
from libc.stdlib cimport (
free,
malloc,
)
import numpy as np
cimport numpy as cnp
from numpy cimport (
complex64_t,
complex128_t,
float32_t,
float64_t,
int8_t,
int64_t,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/util.pxd | cimport numpy as cnp
from libc.stdint cimport (
INT8_MAX,
INT8_MIN,
INT16_MAX,
INT16_MIN,
INT32_MAX,
INT32_MIN,
INT64_MAX,
INT64_MIN,
UINT8_MAX,
UINT16_MAX,
UINT32_MAX,
UINT64_MAX,
)
from pandas._libs.tslibs.util cimport *
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/sas.pyx | # cython: language_level=3, initializedcheck=False
# cython: warn.maybe_uninitialized=True, warn.unused=True
from cython cimport Py_ssize_t
from libc.stddef cimport size_t
from libc.stdint cimport (
int64_t,
uint8_t,
uint16_t,
uint32_t,
uint64_t,
)
from libc.stdlib cimport (
calloc,
free,
)
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/missing.pxd | from numpy cimport (
ndarray,
uint8_t,
)
cpdef bint is_matching_na(object left, object right, bint nan_matches_none=*)
cpdef bint check_na_tuples_nonequal(object left, object right)
cpdef bint checknull(object val, bint inf_as_na=*)
cpdef ndarray[uint8_t] isnaobj(ndarray arr, bint inf_as_na=*)
cdef bint is_... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/index.pyx | cimport cython
from cpython.sequence cimport PySequence_GetItem
import numpy as np
cimport numpy as cnp
from numpy cimport (
int64_t,
intp_t,
ndarray,
uint8_t,
uint64_t,
)
cnp.import_array()
from pandas._libs cimport util
from pandas._libs.hashtable cimport HashTable
from pandas._libs.tslibs.na... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/arrays.pyx | """
Cython implementations for internal ExtensionArrays.
"""
cimport cython
import numpy as np
cimport numpy as cnp
from cpython cimport PyErr_Clear
from numpy cimport ndarray
cnp.import_array()
@cython.freelist(16)
cdef class NDArrayBacked:
"""
Implementing these methods in cython improves performance qui... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/ops.pyi | from typing import (
Any,
Callable,
Iterable,
Literal,
TypeAlias,
overload,
)
import numpy as np
from pandas._typing import npt
_BinOp: TypeAlias = Callable[[Any, Any], Any]
_BoolOp: TypeAlias = Callable[[Any, Any], bool]
def scalar_compare(
values: np.ndarray, # object[:]
val: obje... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/json.pyi | from typing import (
Any,
Callable,
)
def ujson_dumps(
obj: Any,
ensure_ascii: bool = ...,
double_precision: int = ...,
indent: int = ...,
orient: str = ...,
date_unit: str = ...,
iso_dates: bool = ...,
default_handler: None
| Callable[[Any], str | float | bool | list | dict... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/index_class_helper.pxi.in | """
Template for functions of IndexEngine subclasses.
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
# ----------------------------------------------------------------------
# IndexEngine Subclass Methods
# ----------------------------------------------------------------------
{{py:
# n... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/writers.pyx | cimport cython
from cython cimport Py_ssize_t
import numpy as np
from cpython cimport (
PyBytes_GET_SIZE,
PyUnicode_GET_LENGTH,
)
from numpy cimport (
ndarray,
uint8_t,
)
ctypedef fused pandas_string:
str
bytes
@cython.boundscheck(False)
@cython.wraparound(False)
def write_csv_rows(
list... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashing.pyx | # Translated from the reference implementation
# at https://github.com/veorq/SipHash
cimport cython
from libc.stdlib cimport (
free,
malloc,
)
import numpy as np
from numpy cimport (
import_array,
ndarray,
uint8_t,
uint64_t,
)
import_array()
from pandas._libs.util cimport is_nan
@cython.b... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/arrays.pxd |
from numpy cimport ndarray
cdef class NDArrayBacked:
cdef:
readonly ndarray _ndarray
readonly object _dtype
cpdef NDArrayBacked _from_backing_data(self, ndarray values)
cpdef __setstate__(self, state)
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/interval.pyi | from typing import (
Any,
Generic,
TypeVar,
overload,
)
import numpy as np
import numpy.typing as npt
from pandas._typing import (
IntervalClosedType,
Timedelta,
Timestamp,
)
VALID_CLOSED: frozenset[str]
_OrderableScalarT = TypeVar("_OrderableScalarT", int, float)
_OrderableTimesT = Type... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/parsers.pyx | # Copyright (c) 2012, Lambda Foundry, Inc.
# See LICENSE for the license
from collections import defaultdict
from csv import (
QUOTE_MINIMAL,
QUOTE_NONE,
QUOTE_NONNUMERIC,
)
import time
import warnings
from pandas.util._exceptions import find_stack_level
from pandas import StringDtype
from pandas.core.arr... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/missing.pyx | from decimal import Decimal
import numbers
from sys import maxsize
cimport cython
from cpython.datetime cimport (
date,
time,
timedelta,
)
from cython cimport Py_ssize_t
import numpy as np
cimport numpy as cnp
from numpy cimport (
flatiter,
float64_t,
int64_t,
ndarray,
uint8_t,
)
cnp... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/sas.pyi | from pandas.io.sas.sas7bdat import SAS7BDATReader
class Parser:
def __init__(self, parser: SAS7BDATReader) -> None: ...
def read(self, nrows: int) -> None: ...
def get_subheader_index(signature: bytes) -> int: ...
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashtable.pyx | cimport cython
from cpython.mem cimport (
PyMem_Free,
PyMem_Malloc,
)
from cpython.ref cimport (
Py_INCREF,
PyObject,
)
from libc.stdlib cimport (
free,
malloc,
)
import numpy as np
cimport numpy as cnp
from numpy cimport ndarray
cnp.import_array()
from pandas._libs cimport util
from pandas... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/reshape.pyx | cimport cython
from cython cimport Py_ssize_t
from numpy cimport (
int64_t,
ndarray,
uint8_t,
)
import numpy as np
cimport numpy as cnp
from libc.math cimport NAN
cnp.import_array()
from pandas._libs.dtypes cimport numeric_object_t
from pandas._libs.lib cimport c_is_list_like
@cython.wraparound(False)... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/tslib.pyi | from datetime import tzinfo
import numpy as np
from pandas._typing import npt
def format_array_from_datetime(
values: npt.NDArray[np.int64],
tz: tzinfo | None = ...,
format: str | None = ...,
na_rep: str | float = ...,
reso: int = ..., # NPY_DATETIMEUNIT
) -> npt.NDArray[np.object_]: ...
def arr... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/internals.pyi | from typing import (
Iterator,
Sequence,
final,
overload,
)
import weakref
import numpy as np
from pandas._typing import (
ArrayLike,
Self,
npt,
)
from pandas import Index
from pandas.core.internals.blocks import Block as B
def slice_len(slc: slice, objlen: int = ...) -> int: ...
def get... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/byteswap.pyi | def read_float_with_byteswap(data: bytes, offset: int, byteswap: bool) -> float: ...
def read_double_with_byteswap(data: bytes, offset: int, byteswap: bool) -> float: ...
def read_uint16_with_byteswap(data: bytes, offset: int, byteswap: bool) -> int: ...
def read_uint32_with_byteswap(data: bytes, offset: int, byteswap:... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/algos.pyx | cimport cython
from cython cimport Py_ssize_t
from libc.math cimport (
fabs,
sqrt,
)
from libc.stdlib cimport (
free,
malloc,
)
from libc.string cimport memmove
import numpy as np
cimport numpy as cnp
from numpy cimport (
NPY_FLOAT64,
NPY_INT8,
NPY_INT16,
NPY_INT32,
NPY_INT64,
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/index.pyi | import numpy as np
from pandas._typing import npt
from pandas import MultiIndex
from pandas.core.arrays import ExtensionArray
multiindex_nulls_shift: int
class IndexEngine:
over_size_threshold: bool
def __init__(self, values: np.ndarray) -> None: ...
def __contains__(self, val: object) -> bool: ...
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashtable_func_helper.pxi.in | """
Template for each `dtype` helper function for hashtable
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
{{py:
# name, dtype, ttype, c_type, to_c_type
dtypes = [('Complex128', 'complex128', 'complex128',
'khcomplex128_t', 'to_khcomplex128_t'),
('Compl... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/intervaltree.pxi.in | """
Template for intervaltree
WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
"""
from pandas._libs.algos import is_monotonic
ctypedef fused int_scalar_t:
int64_t
float64_t
ctypedef fused uint_scalar_t:
uint64_t
float64_t
ctypedef fused scalar_t:
int_scalar_t
uint_sc... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/ops_dispatch.pyx | DISPATCHED_UFUNCS = {
"add",
"sub",
"mul",
"pow",
"mod",
"floordiv",
"truediv",
"divmod",
"eq",
"ne",
"lt",
"gt",
"le",
"ge",
"remainder",
"matmul",
"or",
"xor",
"and",
"neg",
"pos",
"abs",
}
UNARY_UFUNCS = {
"neg",
"pos",
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/sparse.pyi | from typing import Sequence
import numpy as np
from pandas._typing import (
Self,
npt,
)
class SparseIndex:
length: int
npoints: int
def __init__(self) -> None: ...
@property
def ngaps(self) -> int: ...
@property
def nbytes(self) -> int: ...
@property
def indices(self) -> ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/writers.pyi | import numpy as np
from pandas._typing import ArrayLike
def write_csv_rows(
data: list[ArrayLike],
data_index: np.ndarray,
nlevels: int,
cols: np.ndarray,
writer: object, # _csv.writer
) -> None: ...
def convert_json_to_lines(arr: str) -> str: ...
def max_len_string_array(
arr: np.ndarray, #... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/khash.pxd | from cpython.object cimport PyObject
from numpy cimport (
complex64_t,
complex128_t,
float32_t,
float64_t,
int8_t,
int16_t,
int32_t,
int64_t,
uint8_t,
uint16_t,
uint32_t,
uint64_t,
)
cdef extern from "pandas/vendored/klib/khash_python.h":
const int KHASH_TRACE_DOMAI... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/indexing.pyi | from typing import (
Generic,
TypeVar,
)
from pandas.core.indexing import IndexingMixin
_IndexingMixinT = TypeVar("_IndexingMixinT", bound=IndexingMixin)
class NDFrameIndexerBase(Generic[_IndexingMixinT]):
name: str
# in practice obj is either a DataFrame or a Series
obj: _IndexingMixinT
def... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/tslib.pyx | import warnings
from pandas.util._exceptions import find_stack_level
cimport cython
from datetime import timezone
from cpython.datetime cimport (
PyDate_Check,
PyDateTime_Check,
datetime,
import_datetime,
timedelta,
tzinfo,
)
from cpython.object cimport PyObject
# import datetime C API
impo... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/missing.pyi | import numpy as np
from numpy import typing as npt
class NAType:
def __new__(cls, *args, **kwargs): ...
NA: NAType
def is_matching_na(
left: object, right: object, nan_matches_none: bool = ...
) -> bool: ...
def isposinf_scalar(val: object) -> bool: ...
def isneginf_scalar(val: object) -> bool: ...
def check... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/indexing.pyx | cdef class NDFrameIndexerBase:
"""
A base class for _NDFrameIndexer for fast instantiation and attribute access.
"""
cdef:
Py_ssize_t _ndim
cdef public:
str name
object obj
def __init__(self, name: str, obj):
self.obj = obj
self.name = name
self.... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/join.pyi | import numpy as np
from pandas._typing import npt
def inner_join(
left: np.ndarray, # const intp_t[:]
right: np.ndarray, # const intp_t[:]
max_groups: int,
sort: bool = ...,
) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
def left_outer_join(
left: np.ndarray, # const intp_t[:]
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/ops.pyx | import operator
cimport cython
from cpython.object cimport (
Py_EQ,
Py_GE,
Py_GT,
Py_LE,
Py_LT,
Py_NE,
PyObject_RichCompareBool,
)
from cython cimport Py_ssize_t
import numpy as np
from numpy cimport (
import_array,
ndarray,
uint8_t,
)
import_array()
from pandas._libs.missi... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/lib.pyi | # TODO(npdtypes): Many types specified here can be made more specific/accurate;
# the more specific versions are specified in comments
from decimal import Decimal
from typing import (
Any,
Callable,
Final,
Generator,
Hashable,
Literal,
TypeAlias,
overload,
)
import numpy as np
from pa... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/interval.pyx | import numbers
from operator import (
le,
lt,
)
from cpython.datetime cimport (
PyDelta_Check,
import_datetime,
)
import_datetime()
cimport cython
from cpython.object cimport PyObject_RichCompare
from cython cimport Py_ssize_t
import numpy as np
cimport numpy as cnp
from numpy cimport (
NPY_QUI... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/groupby.pyi | from typing import Literal
import numpy as np
from pandas._typing import npt
def group_median_float64(
out: np.ndarray, # ndarray[float64_t, ndim=2]
counts: npt.NDArray[np.int64],
values: np.ndarray, # ndarray[float64_t, ndim=2]
labels: npt.NDArray[np.int64],
min_count: int = ..., # Py_ssize_t... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/dtypes.pxd | """
Common location for shared fused types
"""
from numpy cimport (
float32_t,
float64_t,
int8_t,
int16_t,
int32_t,
int64_t,
uint8_t,
uint16_t,
uint32_t,
uint64_t,
)
# All numeric types except complex
ctypedef fused numeric_t:
int8_t
int16_t
int32_t
int64_t
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/algos.pyi | from typing import Any
import numpy as np
from pandas._typing import npt
class Infinity:
def __eq__(self, other) -> bool: ...
def __ne__(self, other) -> bool: ...
def __lt__(self, other) -> bool: ...
def __le__(self, other) -> bool: ...
def __gt__(self, other) -> bool: ...
def __ge__(self, ot... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/__init__.py | __all__ = [
"NaT",
"NaTType",
"OutOfBoundsDatetime",
"Period",
"Timedelta",
"Timestamp",
"iNaT",
"Interval",
]
# Below imports needs to happen first to ensure pandas top level
# module gets monkeypatched with the pandas_datetime_CAPI
# see pandas_datetime_exec in pd_datetime.c
import p... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/testing.pyi | def assert_dict_equal(a, b, compare_keys: bool = ...): ...
def assert_almost_equal(
a,
b,
rtol: float = ...,
atol: float = ...,
check_dtype: bool = ...,
obj=...,
lobj=...,
robj=...,
index_values=...,
): ...
| 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/properties.pyi | from typing import (
Sequence,
overload,
)
from pandas._typing import (
AnyArrayLike,
DataFrame,
Index,
Series,
)
# note: this is a lie to make type checkers happy (they special
# case property). cache_readonly uses attribute names similar to
# property (fget) but it does not provide fset and ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/_libs/hashing.pyi | import numpy as np
from pandas._typing import npt
def hash_object_array(
arr: npt.NDArray[np.object_],
key: str,
encoding: str = ...,
) -> npt.NDArray[np.uint64]: ...
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/window/meson.build | py.extension_module(
'aggregations',
['aggregations.pyx'],
cython_args: ['-X always_allow_keywords=true'],
include_directories: [inc_np, inc_pd],
subdir: 'pandas/_libs/window',
override_options : ['cython_language=cpp'],
install: true
)
py.extension_module(
'indexers',
['indexers.py... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/window/aggregations.pyi | from typing import (
Any,
Callable,
Literal,
)
import numpy as np
from pandas._typing import (
WindowingRankType,
npt,
)
def roll_sum(
values: np.ndarray, # const float64_t[:]
start: np.ndarray, # np.ndarray[np.int64]
end: np.ndarray, # np.ndarray[np.int64]
minp: int, # int64_... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/window/indexers.pyi | import numpy as np
from pandas._typing import npt
def calculate_variable_window_bounds(
num_values: int, # int64_t
window_size: int, # int64_t
min_periods,
center: bool,
closed: str | None,
index: np.ndarray, # const int64_t[:]
) -> tuple[npt.NDArray[np.int64], npt.NDArray[np.int64]]: ...
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/window/indexers.pyx | # cython: boundscheck=False, wraparound=False, cdivision=True
import numpy as np
from numpy cimport (
int64_t,
ndarray,
)
# Cython routines for window indexers
def calculate_variable_window_bounds(
int64_t num_values,
int64_t window_size,
object min_periods, # unused but here to match get_wind... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/window/aggregations.pyx | # cython: boundscheck=False, wraparound=False, cdivision=True
from libc.math cimport (
round,
signbit,
sqrt,
)
from libcpp.deque cimport deque
from pandas._libs.algos cimport TiebreakEnumType
import numpy as np
cimport numpy as cnp
from numpy cimport (
float32_t,
float64_t,
int64_t,
ndar... | 0 |
public_repos/pandas/pandas/_libs/include | public_repos/pandas/pandas/_libs/include/pandas/inline_helper.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
*/
#pragma once
#ifndef PANDAS_INLINE
#if defined(__clang__)
#define PANDAS_INLINE static __inline__ __attribute__((... | 0 |
public_repos/pandas/pandas/_libs/include | public_repos/pandas/pandas/_libs/include/pandas/portable.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
*/
#pragma once
#include <string.h>
#if defined(_MSC_VER)
#define strcasecmp(s1, s2) _stricmp(s1, s2)
#endif
// GH... | 0 |
public_repos/pandas/pandas/_libs/include | public_repos/pandas/pandas/_libs/include/pandas/skiplist.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
Flexibly-sized, index-able skiplist data structure for maintaining a sorted
list of values
Port of Wes McKinney's Cy... | 0 |
public_repos/pandas/pandas/_libs/include/pandas | public_repos/pandas/pandas/_libs/include/pandas/datetime/pd_datetime.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
Written by Mark Wiebe (mwwiebe@gmail.com)
Copyright (c) 2011 by Enthought, Inc.
Copyright (c) 2005-2011, NumPy Devel... | 0 |
public_repos/pandas/pandas/_libs/include/pandas | public_repos/pandas/pandas/_libs/include/pandas/datetime/date_conversions.h | /*
Copyright (c) 2020, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
*/
#pragma once
#define PY_SSIZE_T_CLEAN
#include <Python.h>
#include <numpy/ndarraytypes.h>
// Scales value inplace ... | 0 |
public_repos/pandas/pandas/_libs/include/pandas | public_repos/pandas/pandas/_libs/include/pandas/parser/io.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
*/
#pragma once
#define PY_SSIZE_T_CLEAN
#include "tokenizer.h"
#include <Python.h>
#define FS(source) ((file_sourc... | 0 |
public_repos/pandas/pandas/_libs/include/pandas | public_repos/pandas/pandas/_libs/include/pandas/parser/tokenizer.h | /*
Copyright (c) 2012, Lambda Foundry, Inc., except where noted
Incorporates components of WarrenWeckesser/textreader, licensed under 3-clause
BSD
See LICENSE for the license
*/
#pragma once
#define PY_SSIZE_T_CLEAN
#include <Python.h>
#define ERROR_NO_DIGITS 1
#define ERROR_OVERFLOW 2
#define ERROR_INVALID_CHAR... | 0 |
public_repos/pandas/pandas/_libs/include/pandas | public_repos/pandas/pandas/_libs/include/pandas/parser/pd_parser.h | /*
Copyright (c) 2023, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
*/
#pragma once
#ifdef __cplusplus
extern "C" {
#endif
#define PY_SSIZE_T_CLEAN
#include "pandas/parser/tokenizer.h"
#include <Python.h>
typedef struct {
int (*to_double)(char *, double... | 0 |
public_repos/pandas/pandas/_libs/include/pandas/vendored/numpy | public_repos/pandas/pandas/_libs/include/pandas/vendored/numpy/datetime/np_datetime_strings.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
Written by Mark Wiebe (mwwiebe@gmail.com)
Copyright (c) 2011 by Enthought, Inc.
Copyright (c) 2005-2011, NumPy Deve... | 0 |
public_repos/pandas/pandas/_libs/include/pandas/vendored/numpy | public_repos/pandas/pandas/_libs/include/pandas/vendored/numpy/datetime/np_datetime.h | /*
Copyright (c) 2016, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
The full license is in the LICENSE file, distributed with this software.
Copyright (c) 2005-2011, NumPy Developers
All rights reserved.
This file is derived from NumPy 1.7. See NUMPY_LICEN... | 0 |
public_repos/pandas/pandas/_libs/include/pandas/vendored/ujson | public_repos/pandas/pandas/_libs/include/pandas/vendored/ujson/python/version.h | /*
Copyright (c) 2011-2013, ESN Social Software AB and Jonas Tarnstrom
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, t... | 0 |
public_repos/pandas/pandas/_libs/include/pandas/vendored/ujson | public_repos/pandas/pandas/_libs/include/pandas/vendored/ujson/lib/ultrajson.h | /*
Copyright (c) 2011-2013, ESN Social Software AB and Jonas Tarnstrom
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, t... | 0 |
public_repos/pandas/pandas/_libs/include/pandas/vendored | public_repos/pandas/pandas/_libs/include/pandas/vendored/klib/khash.h | // Licence at LICENSES/KLIB_LICENSE
/*
An example:
#include "khash.h"
KHASH_MAP_INIT_INT(32, char)
int main() {
int ret, is_missing;
khiter_t k;
khash_t(32) *h = kh_init(32);
k = kh_put(32, h, 5, &ret);
if (!ret) kh_del(32, h, k);
kh_value(h, k) = 10;
k = kh_g... | 0 |
public_repos/pandas/pandas/_libs/include/pandas/vendored | public_repos/pandas/pandas/_libs/include/pandas/vendored/klib/khash_python.h | // Licence at LICENSES/KLIB_LICENSE
#include <Python.h>
#include <string.h>
typedef struct {
float real;
float imag;
} khcomplex64_t;
typedef struct {
double real;
double imag;
} khcomplex128_t;
// khash should report usage to tracemalloc
#if PY_VERSION_HEX >= 0x03060000
#include <pymem.h>
#if PY_VERSION_HEX... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/np_datetime.pyi | import numpy as np
from pandas._typing import npt
class OutOfBoundsDatetime(ValueError): ...
class OutOfBoundsTimedelta(ValueError): ...
# only exposed for testing
def py_get_unit_from_dtype(dtype: np.dtype): ...
def py_td64_to_tdstruct(td64: int, unit: int) -> dict: ...
def astype_overflowsafe(
values: np.ndarr... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/np_datetime.pyx | from cpython.datetime cimport (
PyDateTime_CheckExact,
PyDateTime_DATE_GET_HOUR,
PyDateTime_DATE_GET_MICROSECOND,
PyDateTime_DATE_GET_MINUTE,
PyDateTime_DATE_GET_SECOND,
PyDateTime_GET_DAY,
PyDateTime_GET_MONTH,
PyDateTime_GET_YEAR,
import_datetime,
)
from cpython.object cimport (
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/ccalendar.pyx | # cython: boundscheck=False
"""
Cython implementations of functions resembling the stdlib calendar module
"""
cimport cython
from numpy cimport (
int32_t,
int64_t,
)
# ----------------------------------------------------------------------
# Constants
# Slightly more performant cython lookups than a 2D table
#... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/conversion.pyi | from datetime import (
datetime,
tzinfo,
)
import numpy as np
DT64NS_DTYPE: np.dtype
TD64NS_DTYPE: np.dtype
def precision_from_unit(
in_reso: int,
out_reso: int = ...,
) -> tuple[int, int]: ... # (int64_t, _)
def localize_pydatetime(dt: datetime, tz: tzinfo | None) -> datetime: ...
| 0 |
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