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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/_libs | public_repos/pandas/pandas/_libs/tslibs/period.pyx | import re
cimport numpy as cnp
from cpython.object cimport (
Py_EQ,
Py_NE,
PyObject,
PyObject_RichCompare,
PyObject_RichCompareBool,
)
from numpy cimport (
int32_t,
int64_t,
ndarray,
)
import numpy as np
cnp.import_array()
cimport cython
from cpython.datetime cimport (
PyDate_Che... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/parsing.pyx | """
Parsing functions for datetime and datetime-like strings.
"""
import re
import time
import warnings
from pandas.util._exceptions import find_stack_level
cimport cython
from cpython.datetime cimport (
datetime,
datetime_new,
import_datetime,
timedelta,
tzinfo,
)
from datetime import timezone
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/strptime.pyi | import numpy as np
from pandas._typing import npt
def array_strptime(
values: npt.NDArray[np.object_],
fmt: str | None,
exact: bool = ...,
errors: str = ...,
utc: bool = ...,
creso: int = ..., # NPY_DATETIMEUNIT
) -> tuple[np.ndarray, np.ndarray]: ...
# first ndarray is M8[ns], second is obj... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/tzconversion.pyx | """
timezone conversion
"""
cimport cython
from cpython.datetime cimport (
PyDelta_Check,
datetime,
datetime_new,
import_datetime,
timedelta,
tzinfo,
)
from cython cimport Py_ssize_t
import_datetime()
import numpy as np
import pytz
cimport numpy as cnp
from numpy cimport (
int64_t,
in... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/fields.pyx | """
Functions for accessing attributes of Timestamp/datetime64/datetime-like
objects and arrays
"""
from locale import LC_TIME
from _strptime import LocaleTime
cimport cython
from cython cimport Py_ssize_t
import numpy as np
cimport numpy as cnp
from numpy cimport (
int8_t,
int32_t,
int64_t,
ndarray... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timezones.pxd | from cpython.datetime cimport (
datetime,
timedelta,
tzinfo,
)
cdef tzinfo utc_stdlib
cpdef bint is_utc(tzinfo tz)
cdef bint is_tzlocal(tzinfo tz)
cdef bint is_zoneinfo(tzinfo tz)
cdef bint treat_tz_as_pytz(tzinfo tz)
cpdef bint tz_compare(tzinfo start, tzinfo end)
cpdef object get_timezone(tzinfo tz)
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/dtypes.pyx | # period frequency constants corresponding to scikits timeseries
# originals
from enum import Enum
import warnings
from pandas.util._exceptions import find_stack_level
from pandas._libs.tslibs.ccalendar cimport c_MONTH_NUMBERS
from pandas._libs.tslibs.np_datetime cimport (
NPY_DATETIMEUNIT,
get_conversion_fac... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/dtypes.pyi | from enum import Enum
OFFSET_TO_PERIOD_FREQSTR: dict[str, str]
def periods_per_day(reso: int = ...) -> int: ...
def periods_per_second(reso: int) -> int: ...
def is_supported_unit(reso: int) -> bool: ...
def npy_unit_to_abbrev(unit: int) -> str: ...
def get_supported_reso(reso: int) -> int: ...
def abbrev_to_npy_unit... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/meson.build | tslibs_sources = {
# Dict of extension name -> dict of {sources, include_dirs, and deps}
# numpy include dir is implicitly included
'base': {'sources': ['base.pyx']},
'ccalendar': {'sources': ['ccalendar.pyx']},
'dtypes': {'sources': ['dtypes.pyx']},
'conversion': {'sources': ['conversion.pyx']}... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timedeltas.pyi | from datetime import timedelta
from typing import (
ClassVar,
Literal,
TypeAlias,
TypeVar,
overload,
)
import numpy as np
from pandas._libs.tslibs import (
NaTType,
Tick,
)
from pandas._typing import (
Frequency,
Self,
npt,
)
# This should be kept consistent with the keys in t... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/np_datetime.pxd | cimport numpy as cnp
from cpython.datetime cimport (
date,
datetime,
)
from numpy cimport (
int32_t,
int64_t,
npy_datetime,
npy_timedelta,
)
# TODO(cython3): most of these can be cimported directly from numpy
cdef extern from "numpy/ndarraytypes.h":
ctypedef struct npy_datetimestruct:
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/util.pxd |
from cpython.object cimport PyTypeObject
from cpython.unicode cimport PyUnicode_AsUTF8AndSize
cdef extern from "Python.h":
# Note: importing extern-style allows us to declare these as nogil
# functions, whereas `from cpython cimport` does not.
bint PyBool_Check(object obj) nogil
bint PyFloat_Check(ob... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/nattype.pyi | from datetime import (
datetime,
timedelta,
tzinfo as _tzinfo,
)
import typing
import numpy as np
from pandas._libs.tslibs.period import Period
NaT: NaTType
iNaT: int
nat_strings: set[str]
_NaTComparisonTypes: typing.TypeAlias = (
datetime | timedelta | Period | np.datetime64 | np.timedelta64
)
cla... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/conversion.pxd | from cpython.datetime cimport (
datetime,
tzinfo,
)
from numpy cimport (
int32_t,
int64_t,
ndarray,
)
from pandas._libs.tslibs.np_datetime cimport (
NPY_DATETIMEUNIT,
npy_datetimestruct,
)
from pandas._libs.tslibs.timestamps cimport _Timestamp
from pandas._libs.tslibs.timezones cimport tz_c... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/offsets.pxd | from numpy cimport int64_t
cpdef to_offset(object obj, bint is_period=*)
cdef bint is_offset_object(object obj)
cdef bint is_tick_object(object obj)
cdef class BaseOffset:
cdef readonly:
int64_t n
bint normalize
dict _cache
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/strptime.pyx | """Strptime-related classes and functions.
TimeRE, _calc_julian_from_U_or_W are vendored
from the standard library, see
https://github.com/python/cpython/blob/main/Lib/_strptime.py
Licence at LICENSES/PSF_LICENSE
The original module-level docstring follows.
Strptime-related classes and functions.
CLASSES:
LocaleT... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/base.pxd | from cpython.datetime cimport datetime
cdef class ABCTimestamp(datetime):
pass
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timedeltas.pxd | from cpython.datetime cimport timedelta
from numpy cimport int64_t
from .np_datetime cimport NPY_DATETIMEUNIT
cpdef int64_t get_unit_for_round(freq, NPY_DATETIMEUNIT creso) except? -1
# Exposed for tslib, not intended for outside use.
cpdef int64_t delta_to_nanoseconds(
delta, NPY_DATETIMEUNIT reso=*, bint round... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timezones.pyx | from datetime import (
timedelta,
timezone,
)
from pandas.compat._optional import import_optional_dependency
try:
# py39+
import zoneinfo
from zoneinfo import ZoneInfo
except ImportError:
zoneinfo = None
ZoneInfo = None
from cpython.datetime cimport (
datetime,
timedelta,
tzin... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/vectorized.pyi | """
For cython types that cannot be represented precisely, closest-available
python equivalents are used, and the precise types kept as adjacent comments.
"""
from datetime import tzinfo
import numpy as np
from pandas._libs.tslibs.dtypes import Resolution
from pandas._typing import npt
def dt64arr_to_periodarr(
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/nattype.pxd | from cpython.datetime cimport datetime
from numpy cimport int64_t
cdef int64_t NPY_NAT
cdef set c_nat_strings
cdef class _NaT(datetime):
cdef readonly:
int64_t _value
cdef _NaT c_NaT
cdef bint checknull_with_nat(object val)
cdef bint is_dt64nat(object val)
cdef bint is_td64nat(object val)
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/parsing.pyi | from datetime import datetime
import numpy as np
from pandas._typing import npt
class DateParseError(ValueError): ...
def py_parse_datetime_string(
date_string: str,
dayfirst: bool = ...,
yearfirst: bool = ...,
) -> datetime: ...
def parse_datetime_string_with_reso(
date_string: str,
freq: str |... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timestamps.pxd | from cpython.datetime cimport (
datetime,
tzinfo,
)
from numpy cimport int64_t
from pandas._libs.tslibs.base cimport ABCTimestamp
from pandas._libs.tslibs.np_datetime cimport (
NPY_DATETIMEUNIT,
npy_datetimestruct,
)
from pandas._libs.tslibs.offsets cimport BaseOffset
cdef _Timestamp create_timestamp... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/strptime.pxd | from cpython.datetime cimport (
datetime,
tzinfo,
)
from numpy cimport int64_t
from pandas._libs.tslibs.np_datetime cimport NPY_DATETIMEUNIT
cdef bint parse_today_now(
str val, int64_t* iresult, bint utc, NPY_DATETIMEUNIT creso, bint infer_reso=*
)
cdef class DatetimeParseState:
cdef:
# See... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timezones.pyi | from datetime import (
datetime,
tzinfo,
)
from typing import Callable
import numpy as np
# imported from dateutil.tz
dateutil_gettz: Callable[[str], tzinfo]
def tz_standardize(tz: tzinfo) -> tzinfo: ...
def tz_compare(start: tzinfo | None, end: tzinfo | None) -> bool: ...
def infer_tzinfo(
start: dateti... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/base.pyx | """
We define base classes that will be inherited by Timestamp, Timedelta, etc
in order to allow for fast isinstance checks without circular dependency issues.
This is analogous to core.dtypes.generic.
"""
from cpython.datetime cimport datetime
cdef class ABCTimestamp(datetime):
pass
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/fields.pyi | import numpy as np
from pandas._typing import npt
def build_field_sarray(
dtindex: npt.NDArray[np.int64], # const int64_t[:]
reso: int, # NPY_DATETIMEUNIT
) -> np.ndarray: ...
def month_position_check(fields, weekdays) -> str | None: ...
def get_date_name_field(
dtindex: npt.NDArray[np.int64], # const ... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timestamps.pyx | """
_Timestamp is a c-defined subclass of datetime.datetime
_Timestamp is PITA. Because we inherit from datetime, which has very specific
construction requirements, we need to do object instantiation in python
(see Timestamp class below). This will serve as a C extension type that
shadows the python class, where we do... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/nattype.pyx | from cpython.datetime cimport (
PyDate_Check,
PyDateTime_Check,
PyDelta_Check,
datetime,
import_datetime,
)
import_datetime()
from cpython.object cimport (
Py_EQ,
Py_NE,
PyObject_RichCompare,
)
import numpy as np
cimport numpy as cnp
from numpy cimport int64_t
cnp.import_array()
cim... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/tzconversion.pyi | from datetime import (
timedelta,
tzinfo,
)
from typing import Iterable
import numpy as np
from pandas._typing import npt
# tz_convert_from_utc_single exposed for testing
def tz_convert_from_utc_single(
utc_val: np.int64, tz: tzinfo, creso: int = ...
) -> np.int64: ...
def tz_localize_to_utc(
vals: n... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/ccalendar.pxd | from cython cimport Py_ssize_t
from numpy cimport (
int32_t,
int64_t,
)
ctypedef (int32_t, int32_t, int32_t) iso_calendar_t
cdef int dayofweek(int y, int m, int d) noexcept nogil
cdef bint is_leapyear(int64_t year) noexcept nogil
cpdef int32_t get_days_in_month(int year, Py_ssize_t month) noexcept nogil
cpdef... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/period.pyi | from datetime import timedelta
from typing import Literal
import numpy as np
from pandas._libs.tslibs.dtypes import PeriodDtypeBase
from pandas._libs.tslibs.nattype import NaTType
from pandas._libs.tslibs.offsets import BaseOffset
from pandas._libs.tslibs.timestamps import Timestamp
from pandas._typing import (
F... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/parsing.pxd | from cpython.datetime cimport datetime
from pandas._libs.tslibs.np_datetime cimport NPY_DATETIMEUNIT
cpdef str get_rule_month(str source)
cpdef quarter_to_myear(int year, int quarter, str freq)
cdef datetime parse_datetime_string(
str date_string,
bint dayfirst,
bint yearfirst,
NPY_DATETIMEUNIT* out... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timedeltas.pyx | import collections
import warnings
from pandas.util._exceptions import find_stack_level
cimport cython
from cpython.object cimport (
Py_EQ,
Py_GE,
Py_GT,
Py_LE,
Py_LT,
Py_NE,
PyObject,
PyObject_RichCompare,
)
import numpy as np
cimport numpy as cnp
from numpy cimport (
int64_t,
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/timestamps.pyi | from datetime import (
date as _date,
datetime,
time as _time,
timedelta,
tzinfo as _tzinfo,
)
from time import struct_time
from typing import (
ClassVar,
Literal,
TypeAlias,
TypeVar,
overload,
)
import numpy as np
from pandas._libs.tslibs import (
BaseOffset,
NaTType,
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/vectorized.pyx | cimport cython
cimport numpy as cnp
from cpython.datetime cimport (
date,
datetime,
time,
tzinfo,
)
from numpy cimport (
int64_t,
ndarray,
)
cnp.import_array()
from .dtypes import Resolution
from .dtypes cimport (
c_Resolution,
periods_per_day,
)
from .nattype cimport (
NPY_NAT,
... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/offsets.pyi | from datetime import (
datetime,
time,
timedelta,
)
from typing import (
Any,
Collection,
Literal,
TypeVar,
overload,
)
import numpy as np
from pandas._libs.tslibs.nattype import NaTType
from pandas._typing import (
OffsetCalendar,
Self,
npt,
)
from .timedeltas import Time... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/tzconversion.pxd | from cpython.datetime cimport tzinfo
from numpy cimport (
int64_t,
intp_t,
ndarray,
)
from pandas._libs.tslibs.np_datetime cimport NPY_DATETIMEUNIT
cpdef int64_t tz_convert_from_utc_single(
int64_t utc_val, tzinfo tz, NPY_DATETIMEUNIT creso=*
) except? -1
cdef int64_t tz_localize_to_utc_single(
i... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/dtypes.pxd | from numpy cimport int64_t
from pandas._libs.tslibs.np_datetime cimport NPY_DATETIMEUNIT
cpdef str npy_unit_to_abbrev(NPY_DATETIMEUNIT unit)
cpdef NPY_DATETIMEUNIT abbrev_to_npy_unit(str abbrev)
cdef NPY_DATETIMEUNIT freq_group_code_to_npy_unit(int freq) noexcept nogil
cpdef int64_t periods_per_day(NPY_DATETIMEUNIT ... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/period.pxd | from numpy cimport int64_t
from .np_datetime cimport npy_datetimestruct
cdef bint is_period_object(object obj)
cdef int64_t get_period_ordinal(npy_datetimestruct *dts, int freq) noexcept nogil
| 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/conversion.pyx | import numpy as np
cimport numpy as cnp
from libc.math cimport log10
from numpy cimport (
int32_t,
int64_t,
)
cnp.import_array()
# stdlib datetime imports
from datetime import timezone
from cpython.datetime cimport (
PyDate_Check,
PyDateTime_Check,
datetime,
import_datetime,
time,
t... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/ccalendar.pyi | DAYS: list[str]
MONTH_ALIASES: dict[int, str]
MONTH_NUMBERS: dict[str, int]
MONTHS: list[str]
int_to_weekday: dict[int, str]
def get_firstbday(year: int, month: int) -> int: ...
def get_lastbday(year: int, month: int) -> int: ...
def get_day_of_year(year: int, month: int, day: int) -> int: ...
def get_iso_calendar(yea... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/__init__.py | __all__ = [
"dtypes",
"localize_pydatetime",
"NaT",
"NaTType",
"iNaT",
"nat_strings",
"OutOfBoundsDatetime",
"OutOfBoundsTimedelta",
"IncompatibleFrequency",
"Period",
"Resolution",
"Timedelta",
"normalize_i8_timestamps",
"is_date_array_normalized",
"dt64arr_t... | 0 |
public_repos/pandas/pandas/_libs | public_repos/pandas/pandas/_libs/tslibs/offsets.pyx | import re
import time
import warnings
from pandas.util._exceptions import find_stack_level
cimport cython
from cpython.datetime cimport (
PyDate_Check,
PyDateTime_Check,
PyDelta_Check,
date,
datetime,
import_datetime,
time as dt_time,
timedelta,
)
import warnings
import_datetime()
i... | 0 |
public_repos/pandas/pandas/_libs/src | public_repos/pandas/pandas/_libs/src/datetime/pd_datetime.c | /*
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/src | public_repos/pandas/pandas/_libs/src/datetime/date_conversions.c | /*
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.
*/
// Conversion routines that are useful for serialization,
// but which don't interact with JSON objects directly
#i... | 0 |
public_repos/pandas/pandas/_libs/src | public_repos/pandas/pandas/_libs/src/parser/io.c | /*
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.
*/
#include "pandas/parser/io.h"
/*
On-disk FILE, uncompressed
*/
void *new_rd_source(PyObject *obj) {
rd_sourc... | 0 |
public_repos/pandas/pandas/_libs/src | public_repos/pandas/pandas/_libs/src/parser/tokenizer.c | /*
Copyright (c) 2012, Lambda Foundry, Inc., except where noted
Incorporates components of WarrenWeckesser/textreader, licensed under 3-clause
BSD
See LICENSE for the license
*/
/*
Low-level ascii-file processing for pandas. Combines some elements from
Python's built-in csv module and Warren Weckesser's textreade... | 0 |
public_repos/pandas/pandas/_libs/src | public_repos/pandas/pandas/_libs/src/parser/pd_parser.c | /*
Copyright (c) 2023, PyData Development Team
All rights reserved.
Distributed under the terms of the BSD Simplified License.
*/
#define _PANDAS_PARSER_IMPL
#include "pandas/parser/pd_parser.h"
#include "pandas/parser/io.h"
static int to_double(char *item, double *p_value, char sci, char decimal,
... | 0 |
public_repos/pandas/pandas/_libs/src/vendored/numpy | public_repos/pandas/pandas/_libs/src/vendored/numpy/datetime/np_datetime_strings.c | /*
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/src/vendored/numpy | public_repos/pandas/pandas/_libs/src/vendored/numpy/datetime/np_datetime.c | /*
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/src/vendored/ujson | public_repos/pandas/pandas/_libs/src/vendored/ujson/python/ujson.c | /*
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, this list o... | 0 |
public_repos/pandas/pandas/_libs/src/vendored/ujson | public_repos/pandas/pandas/_libs/src/vendored/ujson/python/objToJSON.c | /*
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, this list o... | 0 |
public_repos/pandas/pandas/_libs/src/vendored/ujson | public_repos/pandas/pandas/_libs/src/vendored/ujson/python/JSONtoObj.c | /*
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/src/vendored/ujson | public_repos/pandas/pandas/_libs/src/vendored/ujson/lib/ultrajsonenc.c | /*
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/src/vendored/ujson | public_repos/pandas/pandas/_libs/src/vendored/ujson/lib/ultrajsondec.c | /*
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, this list o... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/errors/__init__.py | """
Expose public exceptions & warnings
"""
from __future__ import annotations
import ctypes
from pandas._config.config import OptionError
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
OutOfBoundsTimedelta,
)
from pandas.util.version import InvalidVersion
class IntCastingNaNError(ValueError):
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_sorting.py | from collections import defaultdict
from datetime import datetime
from itertools import product
import numpy as np
import pytest
from pandas import (
NA,
DataFrame,
MultiIndex,
Series,
array,
concat,
merge,
)
import pandas._testing as tm
from pandas.core.algorithms import safe_sort
import ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_aggregation.py | import numpy as np
import pytest
from pandas.core.apply import (
_make_unique_kwarg_list,
maybe_mangle_lambdas,
)
def test_maybe_mangle_lambdas_passthrough():
assert maybe_mangle_lambdas("mean") == "mean"
assert maybe_mangle_lambdas(lambda x: x).__name__ == "<lambda>"
# don't mangel single lambda... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_take.py | from datetime import datetime
import numpy as np
import pytest
from pandas._libs import iNaT
import pandas._testing as tm
import pandas.core.algorithms as algos
@pytest.fixture(
params=[
(np.int8, np.int16(127), np.int8),
(np.int8, np.int16(128), np.int16),
(np.int32, 1, np.int32),
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_multilevel.py | import datetime
import numpy as np
import pytest
import pandas as pd
from pandas import (
DataFrame,
MultiIndex,
Series,
)
import pandas._testing as tm
class TestMultiLevel:
def test_reindex_level(self, multiindex_year_month_day_dataframe_random_data):
# axis=0
ymd = multiindex_year_... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_common.py | import collections
from functools import partial
import string
import subprocess
import sys
import textwrap
import numpy as np
import pytest
import pandas as pd
from pandas import Series
import pandas._testing as tm
from pandas.core import ops
import pandas.core.common as com
from pandas.util.version import Version
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_downstream.py | """
Testing that we work in the downstream packages
"""
import array
import subprocess
import sys
import numpy as np
import pytest
from pandas.errors import IntCastingNaNError
import pandas.util._test_decorators as td
import pandas as pd
from pandas import (
DataFrame,
DatetimeIndex,
Series,
Timedelt... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_nanops.py | from functools import partial
import numpy as np
import pytest
import pandas.util._test_decorators as td
from pandas.core.dtypes.common import is_integer_dtype
import pandas as pd
from pandas import (
Series,
isna,
)
import pandas._testing as tm
from pandas.core import nanops
from pandas.core.arrays import ... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_register_accessor.py | from collections.abc import Generator
import contextlib
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.core import accessor
def test_dirname_mixin() -> None:
# GH37173
class X(accessor.DirNamesMixin):
x = 1
y: int
def __init__(self) -> None:
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_optional_dependency.py | import sys
import types
import pytest
from pandas.compat._optional import (
VERSIONS,
import_optional_dependency,
)
import pandas._testing as tm
def test_import_optional():
match = "Missing .*notapackage.* pip .* conda .* notapackage"
with pytest.raises(ImportError, match=match) as exc_info:
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_flags.py | import pytest
import pandas as pd
class TestFlags:
def test_equality(self):
a = pd.DataFrame().set_flags(allows_duplicate_labels=True).flags
b = pd.DataFrame().set_flags(allows_duplicate_labels=False).flags
assert a == a
assert b == b
assert a != b
assert a != 2
... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_expressions.py | import operator
import re
import numpy as np
import pytest
from pandas import option_context
import pandas._testing as tm
from pandas.core.api import (
DataFrame,
Index,
Series,
)
from pandas.core.computation import expressions as expr
@pytest.fixture
def _frame():
return DataFrame(
np.rando... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_errors.py | import pytest
from pandas.errors import (
AbstractMethodError,
UndefinedVariableError,
)
import pandas as pd
@pytest.mark.parametrize(
"exc",
[
"AttributeConflictWarning",
"CSSWarning",
"CategoricalConversionWarning",
"ClosedFileError",
"DataError",
"D... | 0 |
public_repos/pandas/pandas | public_repos/pandas/pandas/tests/test_algos.py | from datetime import datetime
import struct
import numpy as np
import pytest
from pandas._libs import (
algos as libalgos,
hashtable as ht,
)
from pandas.core.dtypes.common import (
is_bool_dtype,
is_complex_dtype,
is_float_dtype,
is_integer_dtype,
is_object_dtype,
)
from pandas.core.dtyp... | 0 |
public_repos/pandas/pandas/tests | public_repos/pandas/pandas/tests/scalar/test_nat.py | from datetime import (
datetime,
timedelta,
)
import operator
import numpy as np
import pytest
import pytz
from pandas._libs.tslibs import iNaT
from pandas.compat.numpy import np_version_gte1p24p3
from pandas import (
DatetimeIndex,
DatetimeTZDtype,
Index,
NaT,
Period,
Series,
Tim... | 0 |
public_repos/pandas/pandas/tests | public_repos/pandas/pandas/tests/scalar/test_na_scalar.py | from datetime import (
date,
time,
timedelta,
)
import pickle
import numpy as np
import pytest
from pandas._libs.missing import NA
from pandas.core.dtypes.common import is_scalar
import pandas as pd
import pandas._testing as tm
def test_singleton():
assert NA is NA
new_NA = type(NA)()
asse... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timestamp/test_timestamp.py | """ test the scalar Timestamp """
import calendar
from datetime import (
datetime,
timedelta,
timezone,
)
import locale
import time
import unicodedata
from dateutil.tz import (
tzlocal,
tzutc,
)
from hypothesis import (
given,
strategies as st,
)
import numpy as np
import pytest
import pyt... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timestamp/test_formats.py | from datetime import datetime
import pprint
import dateutil.tz
import pytest
import pytz # a test below uses pytz but only inside a `eval` call
from pandas import Timestamp
ts_no_ns = Timestamp(
year=2019,
month=5,
day=18,
hour=15,
minute=17,
second=8,
microsecond=132263,
)
ts_no_ns_year... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timestamp/test_timezones.py | """
Tests for Timestamp timezone-related methods
"""
from datetime import datetime
from pandas._libs.tslibs import timezones
from pandas import Timestamp
try:
from zoneinfo import ZoneInfo
except ImportError:
# Cannot assign to a type
ZoneInfo = None # type: ignore[misc, assignment]
class TestTimestam... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timestamp/test_comparisons.py | from datetime import (
datetime,
timedelta,
)
import operator
import numpy as np
import pytest
from pandas import Timestamp
import pandas._testing as tm
class TestTimestampComparison:
def test_compare_non_nano_dt64(self):
# don't raise when converting dt64 to Timestamp in __richcmp__
dt ... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timestamp/test_arithmetic.py | from datetime import (
datetime,
timedelta,
timezone,
)
from dateutil.tz import gettz
import numpy as np
import pytest
import pytz
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
OutOfBoundsTimedelta,
Timedelta,
Timestamp,
offsets,
to_offset,
)
import pandas._testing as tm
... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timestamp/test_constructors.py | import calendar
from datetime import (
date,
datetime,
timedelta,
timezone,
)
import zoneinfo
import dateutil.tz
from dateutil.tz import (
gettz,
tzoffset,
tzutc,
)
import numpy as np
import pytest
import pytz
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from pandas.compat import... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_to_julian_date.py | from pandas import Timestamp
class TestTimestampToJulianDate:
def test_compare_1700(self):
ts = Timestamp("1700-06-23")
res = ts.to_julian_date()
assert res == 2_342_145.5
def test_compare_2000(self):
ts = Timestamp("2000-04-12")
res = ts.to_julian_date()
asser... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_as_unit.py | import pytest
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from pandas.errors import OutOfBoundsDatetime
from pandas import Timestamp
class TestTimestampAsUnit:
def test_as_unit(self):
ts = Timestamp("1970-01-01").as_unit("ns")
assert ts.unit == "ns"
assert ts.as_unit("ns") is... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_to_pydatetime.py | from datetime import (
datetime,
timedelta,
)
import pytz
from pandas._libs.tslibs.timezones import dateutil_gettz as gettz
import pandas.util._test_decorators as td
from pandas import Timestamp
import pandas._testing as tm
class TestTimestampToPyDatetime:
def test_to_pydatetime_fold(self):
# G... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_timestamp_method.py | # NB: This is for the Timestamp.timestamp *method* specifically, not
# the Timestamp class in general.
from pytz import utc
from pandas._libs.tslibs import Timestamp
import pandas.util._test_decorators as td
import pandas._testing as tm
class TestTimestampMethod:
@td.skip_if_windows
def test_timestamp(self... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_replace.py | from datetime import datetime
from dateutil.tz import gettz
import numpy as np
import pytest
import pytz
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
Timestamp,
conversion,
)
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
import pandas.util._test_decorators as td
import pandas._testing ... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_tz_localize.py | from datetime import timedelta
import re
from dateutil.tz import gettz
import pytest
import pytz
from pytz.exceptions import (
AmbiguousTimeError,
NonExistentTimeError,
)
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from pandas.errors import OutOfBoundsDatetime
from pandas import (
NaT,
Tim... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_normalize.py | import pytest
from pandas._libs.tslibs import Timestamp
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
class TestTimestampNormalize:
@pytest.mark.parametrize("arg", ["2013-11-30", "2013-11-30 12:00:00"])
@pytest.mark.parametrize("unit", ["ns", "us", "ms", "s"])
def test_normalize(self, tz_naive_f... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_tz_convert.py | import dateutil
import pytest
from pandas._libs.tslibs import timezones
import pandas.util._test_decorators as td
from pandas import Timestamp
try:
from zoneinfo import ZoneInfo
except ImportError:
# Cannot assign to a type
ZoneInfo = None # type: ignore[misc, assignment]
class TestTimestampTZConvert:... | 0 |
public_repos/pandas/pandas/tests/scalar/timestamp | public_repos/pandas/pandas/tests/scalar/timestamp/methods/test_round.py | from hypothesis import (
given,
strategies as st,
)
import numpy as np
import pytest
import pytz
from pandas._libs import lib
from pandas._libs.tslibs import (
NaT,
OutOfBoundsDatetime,
Timedelta,
Timestamp,
iNaT,
to_offset,
)
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from ... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/period/test_period.py | from datetime import (
date,
datetime,
timedelta,
)
import numpy as np
import pytest
from pandas._libs.tslibs import (
iNaT,
period as libperiod,
)
from pandas._libs.tslibs.ccalendar import (
DAYS,
MONTHS,
)
from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime
from pandas._libs.... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/period/test_asfreq.py | import pytest
from pandas._libs.tslibs.period import INVALID_FREQ_ERR_MSG
from pandas.errors import OutOfBoundsDatetime
from pandas import (
Period,
Timestamp,
offsets,
)
import pandas._testing as tm
bday_msg = "Period with BDay freq is deprecated"
class TestFreqConversion:
"""Test frequency conver... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timedelta/test_timedelta.py | """ test the scalar Timedelta """
from datetime import timedelta
import sys
from hypothesis import (
given,
strategies as st,
)
import numpy as np
import pytest
from pandas._libs import lib
from pandas._libs.tslibs import (
NaT,
iNaT,
)
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from panda... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timedelta/test_formats.py | import pytest
from pandas import Timedelta
@pytest.mark.parametrize(
"td, expected_repr",
[
(Timedelta(10, unit="d"), "Timedelta('10 days 00:00:00')"),
(Timedelta(10, unit="s"), "Timedelta('0 days 00:00:10')"),
(Timedelta(10, unit="ms"), "Timedelta('0 days 00:00:00.010000')"),
... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timedelta/test_arithmetic.py | """
Tests for scalar Timedelta arithmetic ops
"""
from datetime import (
datetime,
timedelta,
)
import operator
import numpy as np
import pytest
from pandas.errors import OutOfBoundsTimedelta
import pandas as pd
from pandas import (
NaT,
Timedelta,
Timestamp,
offsets,
)
import pandas._testing... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/timedelta/test_constructors.py | from datetime import timedelta
from itertools import product
import numpy as np
import pytest
from pandas._libs.tslibs import OutOfBoundsTimedelta
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from pandas import (
Index,
NaT,
Timedelta,
TimedeltaIndex,
offsets,
to_timedelta,
)
import... | 0 |
public_repos/pandas/pandas/tests/scalar/timedelta | public_repos/pandas/pandas/tests/scalar/timedelta/methods/test_as_unit.py | import pytest
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from pandas.errors import OutOfBoundsTimedelta
from pandas import Timedelta
class TestAsUnit:
def test_as_unit(self):
td = Timedelta(days=1)
assert td.as_unit("ns") is td
res = td.as_unit("us")
assert res._val... | 0 |
public_repos/pandas/pandas/tests/scalar/timedelta | public_repos/pandas/pandas/tests/scalar/timedelta/methods/test_round.py | from hypothesis import (
given,
strategies as st,
)
import numpy as np
import pytest
from pandas._libs import lib
from pandas._libs.tslibs import iNaT
from pandas.errors import OutOfBoundsTimedelta
from pandas import Timedelta
class TestTimedeltaRound:
@pytest.mark.parametrize(
"freq,s1,s2",
... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/interval/test_ops.py | """Tests for Interval-Interval operations, such as overlaps, contains, etc."""
import pytest
from pandas import (
Interval,
Timedelta,
Timestamp,
)
@pytest.fixture(
params=[
(Timedelta("0 days"), Timedelta("1 day")),
(Timestamp("2018-01-01"), Timedelta("1 day")),
(0, 1),
]... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/interval/test_arithmetic.py | from datetime import timedelta
import numpy as np
import pytest
from pandas import (
Interval,
Timedelta,
Timestamp,
)
@pytest.mark.parametrize("method", ["__add__", "__sub__"])
@pytest.mark.parametrize(
"interval",
[
Interval(Timestamp("2017-01-01 00:00:00"), Timestamp("2018-01-01 00:00... | 0 |
public_repos/pandas/pandas/tests/scalar | public_repos/pandas/pandas/tests/scalar/interval/test_interval.py | import numpy as np
import pytest
from pandas import (
Interval,
Period,
Timedelta,
Timestamp,
)
import pandas._testing as tm
import pandas.core.common as com
@pytest.fixture
def interval():
return Interval(0, 1)
class TestInterval:
def test_properties(self, interval):
assert interva... | 0 |
public_repos/pandas/pandas/tests | public_repos/pandas/pandas/tests/window/test_rolling.py | from datetime import (
datetime,
timedelta,
)
import numpy as np
import pytest
from pandas.compat import (
IS64,
is_platform_arm,
is_platform_power,
)
from pandas import (
DataFrame,
DatetimeIndex,
MultiIndex,
Series,
Timedelta,
Timestamp,
date_range,
period_range,... | 0 |
public_repos/pandas/pandas/tests | public_repos/pandas/pandas/tests/window/test_apply.py | import numpy as np
import pytest
from pandas import (
DataFrame,
Index,
MultiIndex,
Series,
Timestamp,
concat,
date_range,
isna,
notna,
)
import pandas._testing as tm
from pandas.tseries import offsets
# suppress warnings about empty slices, as we are deliberately testing
# with a... | 0 |
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