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stud178862 67f7e7da7d changed to full name 2025-09-22 17:23:14 +03:00
stud178862 946c54400a added README.md 2025-09-22 17:02:09 +03:00
6517 changed files with 0 additions and 1111865 deletions
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.venv/
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.venv/
# Created by venv; see https://docs.python.org/3/library/venv.html
output.txt
@@ -1,24 +0,0 @@
# -*- coding: utf-8 -*-
import sys
try:
from ._version import version as __version__
except ImportError:
__version__ = 'unknown'
__all__ = ['easter', 'parser', 'relativedelta', 'rrule', 'tz',
'utils', 'zoneinfo']
def __getattr__(name):
import importlib
if name in __all__:
return importlib.import_module("." + name, __name__)
raise AttributeError(
"module {!r} has not attribute {!r}".format(__name__, name)
)
def __dir__():
# __dir__ should include all the lazy-importable modules as well.
return [x for x in globals() if x not in sys.modules] + __all__
@@ -1,43 +0,0 @@
"""
Common code used in multiple modules.
"""
class weekday(object):
__slots__ = ["weekday", "n"]
def __init__(self, weekday, n=None):
self.weekday = weekday
self.n = n
def __call__(self, n):
if n == self.n:
return self
else:
return self.__class__(self.weekday, n)
def __eq__(self, other):
try:
if self.weekday != other.weekday or self.n != other.n:
return False
except AttributeError:
return False
return True
def __hash__(self):
return hash((
self.weekday,
self.n,
))
def __ne__(self, other):
return not (self == other)
def __repr__(self):
s = ("MO", "TU", "WE", "TH", "FR", "SA", "SU")[self.weekday]
if not self.n:
return s
else:
return "%s(%+d)" % (s, self.n)
# vim:ts=4:sw=4:et
@@ -1,4 +0,0 @@
# file generated by setuptools_scm
# don't change, don't track in version control
__version__ = version = '2.9.0.post0'
__version_tuple__ = version_tuple = (2, 9, 0)
@@ -1,89 +0,0 @@
# -*- coding: utf-8 -*-
"""
This module offers a generic Easter computing method for any given year, using
Western, Orthodox or Julian algorithms.
"""
import datetime
__all__ = ["easter", "EASTER_JULIAN", "EASTER_ORTHODOX", "EASTER_WESTERN"]
EASTER_JULIAN = 1
EASTER_ORTHODOX = 2
EASTER_WESTERN = 3
def easter(year, method=EASTER_WESTERN):
"""
This method was ported from the work done by GM Arts,
on top of the algorithm by Claus Tondering, which was
based in part on the algorithm of Ouding (1940), as
quoted in "Explanatory Supplement to the Astronomical
Almanac", P. Kenneth Seidelmann, editor.
This algorithm implements three different Easter
calculation methods:
1. Original calculation in Julian calendar, valid in
dates after 326 AD
2. Original method, with date converted to Gregorian
calendar, valid in years 1583 to 4099
3. Revised method, in Gregorian calendar, valid in
years 1583 to 4099 as well
These methods are represented by the constants:
* ``EASTER_JULIAN = 1``
* ``EASTER_ORTHODOX = 2``
* ``EASTER_WESTERN = 3``
The default method is method 3.
More about the algorithm may be found at:
`GM Arts: Easter Algorithms <http://www.gmarts.org/index.php?go=415>`_
and
`The Calendar FAQ: Easter <https://www.tondering.dk/claus/cal/easter.php>`_
"""
if not (1 <= method <= 3):
raise ValueError("invalid method")
# g - Golden year - 1
# c - Century
# h - (23 - Epact) mod 30
# i - Number of days from March 21 to Paschal Full Moon
# j - Weekday for PFM (0=Sunday, etc)
# p - Number of days from March 21 to Sunday on or before PFM
# (-6 to 28 methods 1 & 3, to 56 for method 2)
# e - Extra days to add for method 2 (converting Julian
# date to Gregorian date)
y = year
g = y % 19
e = 0
if method < 3:
# Old method
i = (19*g + 15) % 30
j = (y + y//4 + i) % 7
if method == 2:
# Extra dates to convert Julian to Gregorian date
e = 10
if y > 1600:
e = e + y//100 - 16 - (y//100 - 16)//4
else:
# New method
c = y//100
h = (c - c//4 - (8*c + 13)//25 + 19*g + 15) % 30
i = h - (h//28)*(1 - (h//28)*(29//(h + 1))*((21 - g)//11))
j = (y + y//4 + i + 2 - c + c//4) % 7
# p can be from -6 to 56 corresponding to dates 22 March to 23 May
# (later dates apply to method 2, although 23 May never actually occurs)
p = i - j + e
d = 1 + (p + 27 + (p + 6)//40) % 31
m = 3 + (p + 26)//30
return datetime.date(int(y), int(m), int(d))
@@ -1,61 +0,0 @@
# -*- coding: utf-8 -*-
from ._parser import parse, parser, parserinfo, ParserError
from ._parser import DEFAULTPARSER, DEFAULTTZPARSER
from ._parser import UnknownTimezoneWarning
from ._parser import __doc__
from .isoparser import isoparser, isoparse
__all__ = ['parse', 'parser', 'parserinfo',
'isoparse', 'isoparser',
'ParserError',
'UnknownTimezoneWarning']
###
# Deprecate portions of the private interface so that downstream code that
# is improperly relying on it is given *some* notice.
def __deprecated_private_func(f):
from functools import wraps
import warnings
msg = ('{name} is a private function and may break without warning, '
'it will be moved and or renamed in future versions.')
msg = msg.format(name=f.__name__)
@wraps(f)
def deprecated_func(*args, **kwargs):
warnings.warn(msg, DeprecationWarning)
return f(*args, **kwargs)
return deprecated_func
def __deprecate_private_class(c):
import warnings
msg = ('{name} is a private class and may break without warning, '
'it will be moved and or renamed in future versions.')
msg = msg.format(name=c.__name__)
class private_class(c):
__doc__ = c.__doc__
def __init__(self, *args, **kwargs):
warnings.warn(msg, DeprecationWarning)
super(private_class, self).__init__(*args, **kwargs)
private_class.__name__ = c.__name__
return private_class
from ._parser import _timelex, _resultbase
from ._parser import _tzparser, _parsetz
_timelex = __deprecate_private_class(_timelex)
_tzparser = __deprecate_private_class(_tzparser)
_resultbase = __deprecate_private_class(_resultbase)
_parsetz = __deprecated_private_func(_parsetz)
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# -*- coding: utf-8 -*-
"""
This module offers a parser for ISO-8601 strings
It is intended to support all valid date, time and datetime formats per the
ISO-8601 specification.
..versionadded:: 2.7.0
"""
from datetime import datetime, timedelta, time, date
import calendar
from dateutil import tz
from functools import wraps
import re
import six
__all__ = ["isoparse", "isoparser"]
def _takes_ascii(f):
@wraps(f)
def func(self, str_in, *args, **kwargs):
# If it's a stream, read the whole thing
str_in = getattr(str_in, 'read', lambda: str_in)()
# If it's unicode, turn it into bytes, since ISO-8601 only covers ASCII
if isinstance(str_in, six.text_type):
# ASCII is the same in UTF-8
try:
str_in = str_in.encode('ascii')
except UnicodeEncodeError as e:
msg = 'ISO-8601 strings should contain only ASCII characters'
six.raise_from(ValueError(msg), e)
return f(self, str_in, *args, **kwargs)
return func
class isoparser(object):
def __init__(self, sep=None):
"""
:param sep:
A single character that separates date and time portions. If
``None``, the parser will accept any single character.
For strict ISO-8601 adherence, pass ``'T'``.
"""
if sep is not None:
if (len(sep) != 1 or ord(sep) >= 128 or sep in '0123456789'):
raise ValueError('Separator must be a single, non-numeric ' +
'ASCII character')
sep = sep.encode('ascii')
self._sep = sep
@_takes_ascii
def isoparse(self, dt_str):
"""
Parse an ISO-8601 datetime string into a :class:`datetime.datetime`.
An ISO-8601 datetime string consists of a date portion, followed
optionally by a time portion - the date and time portions are separated
by a single character separator, which is ``T`` in the official
standard. Incomplete date formats (such as ``YYYY-MM``) may *not* be
combined with a time portion.
Supported date formats are:
Common:
- ``YYYY``
- ``YYYY-MM``
- ``YYYY-MM-DD`` or ``YYYYMMDD``
Uncommon:
- ``YYYY-Www`` or ``YYYYWww`` - ISO week (day defaults to 0)
- ``YYYY-Www-D`` or ``YYYYWwwD`` - ISO week and day
The ISO week and day numbering follows the same logic as
:func:`datetime.date.isocalendar`.
Supported time formats are:
- ``hh``
- ``hh:mm`` or ``hhmm``
- ``hh:mm:ss`` or ``hhmmss``
- ``hh:mm:ss.ssssss`` (Up to 6 sub-second digits)
Midnight is a special case for `hh`, as the standard supports both
00:00 and 24:00 as a representation. The decimal separator can be
either a dot or a comma.
.. caution::
Support for fractional components other than seconds is part of the
ISO-8601 standard, but is not currently implemented in this parser.
Supported time zone offset formats are:
- `Z` (UTC)
- `±HH:MM`
- `±HHMM`
- `±HH`
Offsets will be represented as :class:`dateutil.tz.tzoffset` objects,
with the exception of UTC, which will be represented as
:class:`dateutil.tz.tzutc`. Time zone offsets equivalent to UTC (such
as `+00:00`) will also be represented as :class:`dateutil.tz.tzutc`.
:param dt_str:
A string or stream containing only an ISO-8601 datetime string
:return:
Returns a :class:`datetime.datetime` representing the string.
Unspecified components default to their lowest value.
.. warning::
As of version 2.7.0, the strictness of the parser should not be
considered a stable part of the contract. Any valid ISO-8601 string
that parses correctly with the default settings will continue to
parse correctly in future versions, but invalid strings that
currently fail (e.g. ``2017-01-01T00:00+00:00:00``) are not
guaranteed to continue failing in future versions if they encode
a valid date.
.. versionadded:: 2.7.0
"""
components, pos = self._parse_isodate(dt_str)
if len(dt_str) > pos:
if self._sep is None or dt_str[pos:pos + 1] == self._sep:
components += self._parse_isotime(dt_str[pos + 1:])
else:
raise ValueError('String contains unknown ISO components')
if len(components) > 3 and components[3] == 24:
components[3] = 0
return datetime(*components) + timedelta(days=1)
return datetime(*components)
@_takes_ascii
def parse_isodate(self, datestr):
"""
Parse the date portion of an ISO string.
:param datestr:
The string portion of an ISO string, without a separator
:return:
Returns a :class:`datetime.date` object
"""
components, pos = self._parse_isodate(datestr)
if pos < len(datestr):
raise ValueError('String contains unknown ISO ' +
'components: {!r}'.format(datestr.decode('ascii')))
return date(*components)
@_takes_ascii
def parse_isotime(self, timestr):
"""
Parse the time portion of an ISO string.
:param timestr:
The time portion of an ISO string, without a separator
:return:
Returns a :class:`datetime.time` object
"""
components = self._parse_isotime(timestr)
if components[0] == 24:
components[0] = 0
return time(*components)
@_takes_ascii
def parse_tzstr(self, tzstr, zero_as_utc=True):
"""
Parse a valid ISO time zone string.
See :func:`isoparser.isoparse` for details on supported formats.
:param tzstr:
A string representing an ISO time zone offset
:param zero_as_utc:
Whether to return :class:`dateutil.tz.tzutc` for zero-offset zones
:return:
Returns :class:`dateutil.tz.tzoffset` for offsets and
:class:`dateutil.tz.tzutc` for ``Z`` and (if ``zero_as_utc`` is
specified) offsets equivalent to UTC.
"""
return self._parse_tzstr(tzstr, zero_as_utc=zero_as_utc)
# Constants
_DATE_SEP = b'-'
_TIME_SEP = b':'
_FRACTION_REGEX = re.compile(b'[\\.,]([0-9]+)')
def _parse_isodate(self, dt_str):
try:
return self._parse_isodate_common(dt_str)
except ValueError:
return self._parse_isodate_uncommon(dt_str)
def _parse_isodate_common(self, dt_str):
len_str = len(dt_str)
components = [1, 1, 1]
if len_str < 4:
raise ValueError('ISO string too short')
# Year
components[0] = int(dt_str[0:4])
pos = 4
if pos >= len_str:
return components, pos
has_sep = dt_str[pos:pos + 1] == self._DATE_SEP
if has_sep:
pos += 1
# Month
if len_str - pos < 2:
raise ValueError('Invalid common month')
components[1] = int(dt_str[pos:pos + 2])
pos += 2
if pos >= len_str:
if has_sep:
return components, pos
else:
raise ValueError('Invalid ISO format')
if has_sep:
if dt_str[pos:pos + 1] != self._DATE_SEP:
raise ValueError('Invalid separator in ISO string')
pos += 1
# Day
if len_str - pos < 2:
raise ValueError('Invalid common day')
components[2] = int(dt_str[pos:pos + 2])
return components, pos + 2
def _parse_isodate_uncommon(self, dt_str):
if len(dt_str) < 4:
raise ValueError('ISO string too short')
# All ISO formats start with the year
year = int(dt_str[0:4])
has_sep = dt_str[4:5] == self._DATE_SEP
pos = 4 + has_sep # Skip '-' if it's there
if dt_str[pos:pos + 1] == b'W':
# YYYY-?Www-?D?
pos += 1
weekno = int(dt_str[pos:pos + 2])
pos += 2
dayno = 1
if len(dt_str) > pos:
if (dt_str[pos:pos + 1] == self._DATE_SEP) != has_sep:
raise ValueError('Inconsistent use of dash separator')
pos += has_sep
dayno = int(dt_str[pos:pos + 1])
pos += 1
base_date = self._calculate_weekdate(year, weekno, dayno)
else:
# YYYYDDD or YYYY-DDD
if len(dt_str) - pos < 3:
raise ValueError('Invalid ordinal day')
ordinal_day = int(dt_str[pos:pos + 3])
pos += 3
if ordinal_day < 1 or ordinal_day > (365 + calendar.isleap(year)):
raise ValueError('Invalid ordinal day' +
' {} for year {}'.format(ordinal_day, year))
base_date = date(year, 1, 1) + timedelta(days=ordinal_day - 1)
components = [base_date.year, base_date.month, base_date.day]
return components, pos
def _calculate_weekdate(self, year, week, day):
"""
Calculate the day of corresponding to the ISO year-week-day calendar.
This function is effectively the inverse of
:func:`datetime.date.isocalendar`.
:param year:
The year in the ISO calendar
:param week:
The week in the ISO calendar - range is [1, 53]
:param day:
The day in the ISO calendar - range is [1 (MON), 7 (SUN)]
:return:
Returns a :class:`datetime.date`
"""
if not 0 < week < 54:
raise ValueError('Invalid week: {}'.format(week))
if not 0 < day < 8: # Range is 1-7
raise ValueError('Invalid weekday: {}'.format(day))
# Get week 1 for the specific year:
jan_4 = date(year, 1, 4) # Week 1 always has January 4th in it
week_1 = jan_4 - timedelta(days=jan_4.isocalendar()[2] - 1)
# Now add the specific number of weeks and days to get what we want
week_offset = (week - 1) * 7 + (day - 1)
return week_1 + timedelta(days=week_offset)
def _parse_isotime(self, timestr):
len_str = len(timestr)
components = [0, 0, 0, 0, None]
pos = 0
comp = -1
if len_str < 2:
raise ValueError('ISO time too short')
has_sep = False
while pos < len_str and comp < 5:
comp += 1
if timestr[pos:pos + 1] in b'-+Zz':
# Detect time zone boundary
components[-1] = self._parse_tzstr(timestr[pos:])
pos = len_str
break
if comp == 1 and timestr[pos:pos+1] == self._TIME_SEP:
has_sep = True
pos += 1
elif comp == 2 and has_sep:
if timestr[pos:pos+1] != self._TIME_SEP:
raise ValueError('Inconsistent use of colon separator')
pos += 1
if comp < 3:
# Hour, minute, second
components[comp] = int(timestr[pos:pos + 2])
pos += 2
if comp == 3:
# Fraction of a second
frac = self._FRACTION_REGEX.match(timestr[pos:])
if not frac:
continue
us_str = frac.group(1)[:6] # Truncate to microseconds
components[comp] = int(us_str) * 10**(6 - len(us_str))
pos += len(frac.group())
if pos < len_str:
raise ValueError('Unused components in ISO string')
if components[0] == 24:
# Standard supports 00:00 and 24:00 as representations of midnight
if any(component != 0 for component in components[1:4]):
raise ValueError('Hour may only be 24 at 24:00:00.000')
return components
def _parse_tzstr(self, tzstr, zero_as_utc=True):
if tzstr == b'Z' or tzstr == b'z':
return tz.UTC
if len(tzstr) not in {3, 5, 6}:
raise ValueError('Time zone offset must be 1, 3, 5 or 6 characters')
if tzstr[0:1] == b'-':
mult = -1
elif tzstr[0:1] == b'+':
mult = 1
else:
raise ValueError('Time zone offset requires sign')
hours = int(tzstr[1:3])
if len(tzstr) == 3:
minutes = 0
else:
minutes = int(tzstr[(4 if tzstr[3:4] == self._TIME_SEP else 3):])
if zero_as_utc and hours == 0 and minutes == 0:
return tz.UTC
else:
if minutes > 59:
raise ValueError('Invalid minutes in time zone offset')
if hours > 23:
raise ValueError('Invalid hours in time zone offset')
return tz.tzoffset(None, mult * (hours * 60 + minutes) * 60)
DEFAULT_ISOPARSER = isoparser()
isoparse = DEFAULT_ISOPARSER.isoparse
@@ -1,599 +0,0 @@
# -*- coding: utf-8 -*-
import datetime
import calendar
import operator
from math import copysign
from six import integer_types
from warnings import warn
from ._common import weekday
MO, TU, WE, TH, FR, SA, SU = weekdays = tuple(weekday(x) for x in range(7))
__all__ = ["relativedelta", "MO", "TU", "WE", "TH", "FR", "SA", "SU"]
class relativedelta(object):
"""
The relativedelta type is designed to be applied to an existing datetime and
can replace specific components of that datetime, or represents an interval
of time.
It is based on the specification of the excellent work done by M.-A. Lemburg
in his
`mx.DateTime <https://www.egenix.com/products/python/mxBase/mxDateTime/>`_ extension.
However, notice that this type does *NOT* implement the same algorithm as
his work. Do *NOT* expect it to behave like mx.DateTime's counterpart.
There are two different ways to build a relativedelta instance. The
first one is passing it two date/datetime classes::
relativedelta(datetime1, datetime2)
The second one is passing it any number of the following keyword arguments::
relativedelta(arg1=x,arg2=y,arg3=z...)
year, month, day, hour, minute, second, microsecond:
Absolute information (argument is singular); adding or subtracting a
relativedelta with absolute information does not perform an arithmetic
operation, but rather REPLACES the corresponding value in the
original datetime with the value(s) in relativedelta.
years, months, weeks, days, hours, minutes, seconds, microseconds:
Relative information, may be negative (argument is plural); adding
or subtracting a relativedelta with relative information performs
the corresponding arithmetic operation on the original datetime value
with the information in the relativedelta.
weekday:
One of the weekday instances (MO, TU, etc) available in the
relativedelta module. These instances may receive a parameter N,
specifying the Nth weekday, which could be positive or negative
(like MO(+1) or MO(-2)). Not specifying it is the same as specifying
+1. You can also use an integer, where 0=MO. This argument is always
relative e.g. if the calculated date is already Monday, using MO(1)
or MO(-1) won't change the day. To effectively make it absolute, use
it in combination with the day argument (e.g. day=1, MO(1) for first
Monday of the month).
leapdays:
Will add given days to the date found, if year is a leap
year, and the date found is post 28 of february.
yearday, nlyearday:
Set the yearday or the non-leap year day (jump leap days).
These are converted to day/month/leapdays information.
There are relative and absolute forms of the keyword
arguments. The plural is relative, and the singular is
absolute. For each argument in the order below, the absolute form
is applied first (by setting each attribute to that value) and
then the relative form (by adding the value to the attribute).
The order of attributes considered when this relativedelta is
added to a datetime is:
1. Year
2. Month
3. Day
4. Hours
5. Minutes
6. Seconds
7. Microseconds
Finally, weekday is applied, using the rule described above.
For example
>>> from datetime import datetime
>>> from dateutil.relativedelta import relativedelta, MO
>>> dt = datetime(2018, 4, 9, 13, 37, 0)
>>> delta = relativedelta(hours=25, day=1, weekday=MO(1))
>>> dt + delta
datetime.datetime(2018, 4, 2, 14, 37)
First, the day is set to 1 (the first of the month), then 25 hours
are added, to get to the 2nd day and 14th hour, finally the
weekday is applied, but since the 2nd is already a Monday there is
no effect.
"""
def __init__(self, dt1=None, dt2=None,
years=0, months=0, days=0, leapdays=0, weeks=0,
hours=0, minutes=0, seconds=0, microseconds=0,
year=None, month=None, day=None, weekday=None,
yearday=None, nlyearday=None,
hour=None, minute=None, second=None, microsecond=None):
if dt1 and dt2:
# datetime is a subclass of date. So both must be date
if not (isinstance(dt1, datetime.date) and
isinstance(dt2, datetime.date)):
raise TypeError("relativedelta only diffs datetime/date")
# We allow two dates, or two datetimes, so we coerce them to be
# of the same type
if (isinstance(dt1, datetime.datetime) !=
isinstance(dt2, datetime.datetime)):
if not isinstance(dt1, datetime.datetime):
dt1 = datetime.datetime.fromordinal(dt1.toordinal())
elif not isinstance(dt2, datetime.datetime):
dt2 = datetime.datetime.fromordinal(dt2.toordinal())
self.years = 0
self.months = 0
self.days = 0
self.leapdays = 0
self.hours = 0
self.minutes = 0
self.seconds = 0
self.microseconds = 0
self.year = None
self.month = None
self.day = None
self.weekday = None
self.hour = None
self.minute = None
self.second = None
self.microsecond = None
self._has_time = 0
# Get year / month delta between the two
months = (dt1.year - dt2.year) * 12 + (dt1.month - dt2.month)
self._set_months(months)
# Remove the year/month delta so the timedelta is just well-defined
# time units (seconds, days and microseconds)
dtm = self.__radd__(dt2)
# If we've overshot our target, make an adjustment
if dt1 < dt2:
compare = operator.gt
increment = 1
else:
compare = operator.lt
increment = -1
while compare(dt1, dtm):
months += increment
self._set_months(months)
dtm = self.__radd__(dt2)
# Get the timedelta between the "months-adjusted" date and dt1
delta = dt1 - dtm
self.seconds = delta.seconds + delta.days * 86400
self.microseconds = delta.microseconds
else:
# Check for non-integer values in integer-only quantities
if any(x is not None and x != int(x) for x in (years, months)):
raise ValueError("Non-integer years and months are "
"ambiguous and not currently supported.")
# Relative information
self.years = int(years)
self.months = int(months)
self.days = days + weeks * 7
self.leapdays = leapdays
self.hours = hours
self.minutes = minutes
self.seconds = seconds
self.microseconds = microseconds
# Absolute information
self.year = year
self.month = month
self.day = day
self.hour = hour
self.minute = minute
self.second = second
self.microsecond = microsecond
if any(x is not None and int(x) != x
for x in (year, month, day, hour,
minute, second, microsecond)):
# For now we'll deprecate floats - later it'll be an error.
warn("Non-integer value passed as absolute information. " +
"This is not a well-defined condition and will raise " +
"errors in future versions.", DeprecationWarning)
if isinstance(weekday, integer_types):
self.weekday = weekdays[weekday]
else:
self.weekday = weekday
yday = 0
if nlyearday:
yday = nlyearday
elif yearday:
yday = yearday
if yearday > 59:
self.leapdays = -1
if yday:
ydayidx = [31, 59, 90, 120, 151, 181, 212,
243, 273, 304, 334, 366]
for idx, ydays in enumerate(ydayidx):
if yday <= ydays:
self.month = idx+1
if idx == 0:
self.day = yday
else:
self.day = yday-ydayidx[idx-1]
break
else:
raise ValueError("invalid year day (%d)" % yday)
self._fix()
def _fix(self):
if abs(self.microseconds) > 999999:
s = _sign(self.microseconds)
div, mod = divmod(self.microseconds * s, 1000000)
self.microseconds = mod * s
self.seconds += div * s
if abs(self.seconds) > 59:
s = _sign(self.seconds)
div, mod = divmod(self.seconds * s, 60)
self.seconds = mod * s
self.minutes += div * s
if abs(self.minutes) > 59:
s = _sign(self.minutes)
div, mod = divmod(self.minutes * s, 60)
self.minutes = mod * s
self.hours += div * s
if abs(self.hours) > 23:
s = _sign(self.hours)
div, mod = divmod(self.hours * s, 24)
self.hours = mod * s
self.days += div * s
if abs(self.months) > 11:
s = _sign(self.months)
div, mod = divmod(self.months * s, 12)
self.months = mod * s
self.years += div * s
if (self.hours or self.minutes or self.seconds or self.microseconds
or self.hour is not None or self.minute is not None or
self.second is not None or self.microsecond is not None):
self._has_time = 1
else:
self._has_time = 0
@property
def weeks(self):
return int(self.days / 7.0)
@weeks.setter
def weeks(self, value):
self.days = self.days - (self.weeks * 7) + value * 7
def _set_months(self, months):
self.months = months
if abs(self.months) > 11:
s = _sign(self.months)
div, mod = divmod(self.months * s, 12)
self.months = mod * s
self.years = div * s
else:
self.years = 0
def normalized(self):
"""
Return a version of this object represented entirely using integer
values for the relative attributes.
>>> relativedelta(days=1.5, hours=2).normalized()
relativedelta(days=+1, hours=+14)
:return:
Returns a :class:`dateutil.relativedelta.relativedelta` object.
"""
# Cascade remainders down (rounding each to roughly nearest microsecond)
days = int(self.days)
hours_f = round(self.hours + 24 * (self.days - days), 11)
hours = int(hours_f)
minutes_f = round(self.minutes + 60 * (hours_f - hours), 10)
minutes = int(minutes_f)
seconds_f = round(self.seconds + 60 * (minutes_f - minutes), 8)
seconds = int(seconds_f)
microseconds = round(self.microseconds + 1e6 * (seconds_f - seconds))
# Constructor carries overflow back up with call to _fix()
return self.__class__(years=self.years, months=self.months,
days=days, hours=hours, minutes=minutes,
seconds=seconds, microseconds=microseconds,
leapdays=self.leapdays, year=self.year,
month=self.month, day=self.day,
weekday=self.weekday, hour=self.hour,
minute=self.minute, second=self.second,
microsecond=self.microsecond)
def __add__(self, other):
if isinstance(other, relativedelta):
return self.__class__(years=other.years + self.years,
months=other.months + self.months,
days=other.days + self.days,
hours=other.hours + self.hours,
minutes=other.minutes + self.minutes,
seconds=other.seconds + self.seconds,
microseconds=(other.microseconds +
self.microseconds),
leapdays=other.leapdays or self.leapdays,
year=(other.year if other.year is not None
else self.year),
month=(other.month if other.month is not None
else self.month),
day=(other.day if other.day is not None
else self.day),
weekday=(other.weekday if other.weekday is not None
else self.weekday),
hour=(other.hour if other.hour is not None
else self.hour),
minute=(other.minute if other.minute is not None
else self.minute),
second=(other.second if other.second is not None
else self.second),
microsecond=(other.microsecond if other.microsecond
is not None else
self.microsecond))
if isinstance(other, datetime.timedelta):
return self.__class__(years=self.years,
months=self.months,
days=self.days + other.days,
hours=self.hours,
minutes=self.minutes,
seconds=self.seconds + other.seconds,
microseconds=self.microseconds + other.microseconds,
leapdays=self.leapdays,
year=self.year,
month=self.month,
day=self.day,
weekday=self.weekday,
hour=self.hour,
minute=self.minute,
second=self.second,
microsecond=self.microsecond)
if not isinstance(other, datetime.date):
return NotImplemented
elif self._has_time and not isinstance(other, datetime.datetime):
other = datetime.datetime.fromordinal(other.toordinal())
year = (self.year or other.year)+self.years
month = self.month or other.month
if self.months:
assert 1 <= abs(self.months) <= 12
month += self.months
if month > 12:
year += 1
month -= 12
elif month < 1:
year -= 1
month += 12
day = min(calendar.monthrange(year, month)[1],
self.day or other.day)
repl = {"year": year, "month": month, "day": day}
for attr in ["hour", "minute", "second", "microsecond"]:
value = getattr(self, attr)
if value is not None:
repl[attr] = value
days = self.days
if self.leapdays and month > 2 and calendar.isleap(year):
days += self.leapdays
ret = (other.replace(**repl)
+ datetime.timedelta(days=days,
hours=self.hours,
minutes=self.minutes,
seconds=self.seconds,
microseconds=self.microseconds))
if self.weekday:
weekday, nth = self.weekday.weekday, self.weekday.n or 1
jumpdays = (abs(nth) - 1) * 7
if nth > 0:
jumpdays += (7 - ret.weekday() + weekday) % 7
else:
jumpdays += (ret.weekday() - weekday) % 7
jumpdays *= -1
ret += datetime.timedelta(days=jumpdays)
return ret
def __radd__(self, other):
return self.__add__(other)
def __rsub__(self, other):
return self.__neg__().__radd__(other)
def __sub__(self, other):
if not isinstance(other, relativedelta):
return NotImplemented # In case the other object defines __rsub__
return self.__class__(years=self.years - other.years,
months=self.months - other.months,
days=self.days - other.days,
hours=self.hours - other.hours,
minutes=self.minutes - other.minutes,
seconds=self.seconds - other.seconds,
microseconds=self.microseconds - other.microseconds,
leapdays=self.leapdays or other.leapdays,
year=(self.year if self.year is not None
else other.year),
month=(self.month if self.month is not None else
other.month),
day=(self.day if self.day is not None else
other.day),
weekday=(self.weekday if self.weekday is not None else
other.weekday),
hour=(self.hour if self.hour is not None else
other.hour),
minute=(self.minute if self.minute is not None else
other.minute),
second=(self.second if self.second is not None else
other.second),
microsecond=(self.microsecond if self.microsecond
is not None else
other.microsecond))
def __abs__(self):
return self.__class__(years=abs(self.years),
months=abs(self.months),
days=abs(self.days),
hours=abs(self.hours),
minutes=abs(self.minutes),
seconds=abs(self.seconds),
microseconds=abs(self.microseconds),
leapdays=self.leapdays,
year=self.year,
month=self.month,
day=self.day,
weekday=self.weekday,
hour=self.hour,
minute=self.minute,
second=self.second,
microsecond=self.microsecond)
def __neg__(self):
return self.__class__(years=-self.years,
months=-self.months,
days=-self.days,
hours=-self.hours,
minutes=-self.minutes,
seconds=-self.seconds,
microseconds=-self.microseconds,
leapdays=self.leapdays,
year=self.year,
month=self.month,
day=self.day,
weekday=self.weekday,
hour=self.hour,
minute=self.minute,
second=self.second,
microsecond=self.microsecond)
def __bool__(self):
return not (not self.years and
not self.months and
not self.days and
not self.hours and
not self.minutes and
not self.seconds and
not self.microseconds and
not self.leapdays and
self.year is None and
self.month is None and
self.day is None and
self.weekday is None and
self.hour is None and
self.minute is None and
self.second is None and
self.microsecond is None)
# Compatibility with Python 2.x
__nonzero__ = __bool__
def __mul__(self, other):
try:
f = float(other)
except TypeError:
return NotImplemented
return self.__class__(years=int(self.years * f),
months=int(self.months * f),
days=int(self.days * f),
hours=int(self.hours * f),
minutes=int(self.minutes * f),
seconds=int(self.seconds * f),
microseconds=int(self.microseconds * f),
leapdays=self.leapdays,
year=self.year,
month=self.month,
day=self.day,
weekday=self.weekday,
hour=self.hour,
minute=self.minute,
second=self.second,
microsecond=self.microsecond)
__rmul__ = __mul__
def __eq__(self, other):
if not isinstance(other, relativedelta):
return NotImplemented
if self.weekday or other.weekday:
if not self.weekday or not other.weekday:
return False
if self.weekday.weekday != other.weekday.weekday:
return False
n1, n2 = self.weekday.n, other.weekday.n
if n1 != n2 and not ((not n1 or n1 == 1) and (not n2 or n2 == 1)):
return False
return (self.years == other.years and
self.months == other.months and
self.days == other.days and
self.hours == other.hours and
self.minutes == other.minutes and
self.seconds == other.seconds and
self.microseconds == other.microseconds and
self.leapdays == other.leapdays and
self.year == other.year and
self.month == other.month and
self.day == other.day and
self.hour == other.hour and
self.minute == other.minute and
self.second == other.second and
self.microsecond == other.microsecond)
def __hash__(self):
return hash((
self.weekday,
self.years,
self.months,
self.days,
self.hours,
self.minutes,
self.seconds,
self.microseconds,
self.leapdays,
self.year,
self.month,
self.day,
self.hour,
self.minute,
self.second,
self.microsecond,
))
def __ne__(self, other):
return not self.__eq__(other)
def __div__(self, other):
try:
reciprocal = 1 / float(other)
except TypeError:
return NotImplemented
return self.__mul__(reciprocal)
__truediv__ = __div__
def __repr__(self):
l = []
for attr in ["years", "months", "days", "leapdays",
"hours", "minutes", "seconds", "microseconds"]:
value = getattr(self, attr)
if value:
l.append("{attr}={value:+g}".format(attr=attr, value=value))
for attr in ["year", "month", "day", "weekday",
"hour", "minute", "second", "microsecond"]:
value = getattr(self, attr)
if value is not None:
l.append("{attr}={value}".format(attr=attr, value=repr(value)))
return "{classname}({attrs})".format(classname=self.__class__.__name__,
attrs=", ".join(l))
def _sign(x):
return int(copysign(1, x))
# vim:ts=4:sw=4:et
File diff suppressed because it is too large Load Diff
@@ -1,12 +0,0 @@
# -*- coding: utf-8 -*-
from .tz import *
from .tz import __doc__
__all__ = ["tzutc", "tzoffset", "tzlocal", "tzfile", "tzrange",
"tzstr", "tzical", "tzwin", "tzwinlocal", "gettz",
"enfold", "datetime_ambiguous", "datetime_exists",
"resolve_imaginary", "UTC", "DeprecatedTzFormatWarning"]
class DeprecatedTzFormatWarning(Warning):
"""Warning raised when time zones are parsed from deprecated formats."""
@@ -1,419 +0,0 @@
from six import PY2
from functools import wraps
from datetime import datetime, timedelta, tzinfo
ZERO = timedelta(0)
__all__ = ['tzname_in_python2', 'enfold']
def tzname_in_python2(namefunc):
"""Change unicode output into bytestrings in Python 2
tzname() API changed in Python 3. It used to return bytes, but was changed
to unicode strings
"""
if PY2:
@wraps(namefunc)
def adjust_encoding(*args, **kwargs):
name = namefunc(*args, **kwargs)
if name is not None:
name = name.encode()
return name
return adjust_encoding
else:
return namefunc
# The following is adapted from Alexander Belopolsky's tz library
# https://github.com/abalkin/tz
if hasattr(datetime, 'fold'):
# This is the pre-python 3.6 fold situation
def enfold(dt, fold=1):
"""
Provides a unified interface for assigning the ``fold`` attribute to
datetimes both before and after the implementation of PEP-495.
:param fold:
The value for the ``fold`` attribute in the returned datetime. This
should be either 0 or 1.
:return:
Returns an object for which ``getattr(dt, 'fold', 0)`` returns
``fold`` for all versions of Python. In versions prior to
Python 3.6, this is a ``_DatetimeWithFold`` object, which is a
subclass of :py:class:`datetime.datetime` with the ``fold``
attribute added, if ``fold`` is 1.
.. versionadded:: 2.6.0
"""
return dt.replace(fold=fold)
else:
class _DatetimeWithFold(datetime):
"""
This is a class designed to provide a PEP 495-compliant interface for
Python versions before 3.6. It is used only for dates in a fold, so
the ``fold`` attribute is fixed at ``1``.
.. versionadded:: 2.6.0
"""
__slots__ = ()
def replace(self, *args, **kwargs):
"""
Return a datetime with the same attributes, except for those
attributes given new values by whichever keyword arguments are
specified. Note that tzinfo=None can be specified to create a naive
datetime from an aware datetime with no conversion of date and time
data.
This is reimplemented in ``_DatetimeWithFold`` because pypy3 will
return a ``datetime.datetime`` even if ``fold`` is unchanged.
"""
argnames = (
'year', 'month', 'day', 'hour', 'minute', 'second',
'microsecond', 'tzinfo'
)
for arg, argname in zip(args, argnames):
if argname in kwargs:
raise TypeError('Duplicate argument: {}'.format(argname))
kwargs[argname] = arg
for argname in argnames:
if argname not in kwargs:
kwargs[argname] = getattr(self, argname)
dt_class = self.__class__ if kwargs.get('fold', 1) else datetime
return dt_class(**kwargs)
@property
def fold(self):
return 1
def enfold(dt, fold=1):
"""
Provides a unified interface for assigning the ``fold`` attribute to
datetimes both before and after the implementation of PEP-495.
:param fold:
The value for the ``fold`` attribute in the returned datetime. This
should be either 0 or 1.
:return:
Returns an object for which ``getattr(dt, 'fold', 0)`` returns
``fold`` for all versions of Python. In versions prior to
Python 3.6, this is a ``_DatetimeWithFold`` object, which is a
subclass of :py:class:`datetime.datetime` with the ``fold``
attribute added, if ``fold`` is 1.
.. versionadded:: 2.6.0
"""
if getattr(dt, 'fold', 0) == fold:
return dt
args = dt.timetuple()[:6]
args += (dt.microsecond, dt.tzinfo)
if fold:
return _DatetimeWithFold(*args)
else:
return datetime(*args)
def _validate_fromutc_inputs(f):
"""
The CPython version of ``fromutc`` checks that the input is a ``datetime``
object and that ``self`` is attached as its ``tzinfo``.
"""
@wraps(f)
def fromutc(self, dt):
if not isinstance(dt, datetime):
raise TypeError("fromutc() requires a datetime argument")
if dt.tzinfo is not self:
raise ValueError("dt.tzinfo is not self")
return f(self, dt)
return fromutc
class _tzinfo(tzinfo):
"""
Base class for all ``dateutil`` ``tzinfo`` objects.
"""
def is_ambiguous(self, dt):
"""
Whether or not the "wall time" of a given datetime is ambiguous in this
zone.
:param dt:
A :py:class:`datetime.datetime`, naive or time zone aware.
:return:
Returns ``True`` if ambiguous, ``False`` otherwise.
.. versionadded:: 2.6.0
"""
dt = dt.replace(tzinfo=self)
wall_0 = enfold(dt, fold=0)
wall_1 = enfold(dt, fold=1)
same_offset = wall_0.utcoffset() == wall_1.utcoffset()
same_dt = wall_0.replace(tzinfo=None) == wall_1.replace(tzinfo=None)
return same_dt and not same_offset
def _fold_status(self, dt_utc, dt_wall):
"""
Determine the fold status of a "wall" datetime, given a representation
of the same datetime as a (naive) UTC datetime. This is calculated based
on the assumption that ``dt.utcoffset() - dt.dst()`` is constant for all
datetimes, and that this offset is the actual number of hours separating
``dt_utc`` and ``dt_wall``.
:param dt_utc:
Representation of the datetime as UTC
:param dt_wall:
Representation of the datetime as "wall time". This parameter must
either have a `fold` attribute or have a fold-naive
:class:`datetime.tzinfo` attached, otherwise the calculation may
fail.
"""
if self.is_ambiguous(dt_wall):
delta_wall = dt_wall - dt_utc
_fold = int(delta_wall == (dt_utc.utcoffset() - dt_utc.dst()))
else:
_fold = 0
return _fold
def _fold(self, dt):
return getattr(dt, 'fold', 0)
def _fromutc(self, dt):
"""
Given a timezone-aware datetime in a given timezone, calculates a
timezone-aware datetime in a new timezone.
Since this is the one time that we *know* we have an unambiguous
datetime object, we take this opportunity to determine whether the
datetime is ambiguous and in a "fold" state (e.g. if it's the first
occurrence, chronologically, of the ambiguous datetime).
:param dt:
A timezone-aware :class:`datetime.datetime` object.
"""
# Re-implement the algorithm from Python's datetime.py
dtoff = dt.utcoffset()
if dtoff is None:
raise ValueError("fromutc() requires a non-None utcoffset() "
"result")
# The original datetime.py code assumes that `dst()` defaults to
# zero during ambiguous times. PEP 495 inverts this presumption, so
# for pre-PEP 495 versions of python, we need to tweak the algorithm.
dtdst = dt.dst()
if dtdst is None:
raise ValueError("fromutc() requires a non-None dst() result")
delta = dtoff - dtdst
dt += delta
# Set fold=1 so we can default to being in the fold for
# ambiguous dates.
dtdst = enfold(dt, fold=1).dst()
if dtdst is None:
raise ValueError("fromutc(): dt.dst gave inconsistent "
"results; cannot convert")
return dt + dtdst
@_validate_fromutc_inputs
def fromutc(self, dt):
"""
Given a timezone-aware datetime in a given timezone, calculates a
timezone-aware datetime in a new timezone.
Since this is the one time that we *know* we have an unambiguous
datetime object, we take this opportunity to determine whether the
datetime is ambiguous and in a "fold" state (e.g. if it's the first
occurrence, chronologically, of the ambiguous datetime).
:param dt:
A timezone-aware :class:`datetime.datetime` object.
"""
dt_wall = self._fromutc(dt)
# Calculate the fold status given the two datetimes.
_fold = self._fold_status(dt, dt_wall)
# Set the default fold value for ambiguous dates
return enfold(dt_wall, fold=_fold)
class tzrangebase(_tzinfo):
"""
This is an abstract base class for time zones represented by an annual
transition into and out of DST. Child classes should implement the following
methods:
* ``__init__(self, *args, **kwargs)``
* ``transitions(self, year)`` - this is expected to return a tuple of
datetimes representing the DST on and off transitions in standard
time.
A fully initialized ``tzrangebase`` subclass should also provide the
following attributes:
* ``hasdst``: Boolean whether or not the zone uses DST.
* ``_dst_offset`` / ``_std_offset``: :class:`datetime.timedelta` objects
representing the respective UTC offsets.
* ``_dst_abbr`` / ``_std_abbr``: Strings representing the timezone short
abbreviations in DST and STD, respectively.
* ``_hasdst``: Whether or not the zone has DST.
.. versionadded:: 2.6.0
"""
def __init__(self):
raise NotImplementedError('tzrangebase is an abstract base class')
def utcoffset(self, dt):
isdst = self._isdst(dt)
if isdst is None:
return None
elif isdst:
return self._dst_offset
else:
return self._std_offset
def dst(self, dt):
isdst = self._isdst(dt)
if isdst is None:
return None
elif isdst:
return self._dst_base_offset
else:
return ZERO
@tzname_in_python2
def tzname(self, dt):
if self._isdst(dt):
return self._dst_abbr
else:
return self._std_abbr
def fromutc(self, dt):
""" Given a datetime in UTC, return local time """
if not isinstance(dt, datetime):
raise TypeError("fromutc() requires a datetime argument")
if dt.tzinfo is not self:
raise ValueError("dt.tzinfo is not self")
# Get transitions - if there are none, fixed offset
transitions = self.transitions(dt.year)
if transitions is None:
return dt + self.utcoffset(dt)
# Get the transition times in UTC
dston, dstoff = transitions
dston -= self._std_offset
dstoff -= self._std_offset
utc_transitions = (dston, dstoff)
dt_utc = dt.replace(tzinfo=None)
isdst = self._naive_isdst(dt_utc, utc_transitions)
if isdst:
dt_wall = dt + self._dst_offset
else:
dt_wall = dt + self._std_offset
_fold = int(not isdst and self.is_ambiguous(dt_wall))
return enfold(dt_wall, fold=_fold)
def is_ambiguous(self, dt):
"""
Whether or not the "wall time" of a given datetime is ambiguous in this
zone.
:param dt:
A :py:class:`datetime.datetime`, naive or time zone aware.
:return:
Returns ``True`` if ambiguous, ``False`` otherwise.
.. versionadded:: 2.6.0
"""
if not self.hasdst:
return False
start, end = self.transitions(dt.year)
dt = dt.replace(tzinfo=None)
return (end <= dt < end + self._dst_base_offset)
def _isdst(self, dt):
if not self.hasdst:
return False
elif dt is None:
return None
transitions = self.transitions(dt.year)
if transitions is None:
return False
dt = dt.replace(tzinfo=None)
isdst = self._naive_isdst(dt, transitions)
# Handle ambiguous dates
if not isdst and self.is_ambiguous(dt):
return not self._fold(dt)
else:
return isdst
def _naive_isdst(self, dt, transitions):
dston, dstoff = transitions
dt = dt.replace(tzinfo=None)
if dston < dstoff:
isdst = dston <= dt < dstoff
else:
isdst = not dstoff <= dt < dston
return isdst
@property
def _dst_base_offset(self):
return self._dst_offset - self._std_offset
__hash__ = None
def __ne__(self, other):
return not (self == other)
def __repr__(self):
return "%s(...)" % self.__class__.__name__
__reduce__ = object.__reduce__
@@ -1,80 +0,0 @@
from datetime import timedelta
import weakref
from collections import OrderedDict
from six.moves import _thread
class _TzSingleton(type):
def __init__(cls, *args, **kwargs):
cls.__instance = None
super(_TzSingleton, cls).__init__(*args, **kwargs)
def __call__(cls):
if cls.__instance is None:
cls.__instance = super(_TzSingleton, cls).__call__()
return cls.__instance
class _TzFactory(type):
def instance(cls, *args, **kwargs):
"""Alternate constructor that returns a fresh instance"""
return type.__call__(cls, *args, **kwargs)
class _TzOffsetFactory(_TzFactory):
def __init__(cls, *args, **kwargs):
cls.__instances = weakref.WeakValueDictionary()
cls.__strong_cache = OrderedDict()
cls.__strong_cache_size = 8
cls._cache_lock = _thread.allocate_lock()
def __call__(cls, name, offset):
if isinstance(offset, timedelta):
key = (name, offset.total_seconds())
else:
key = (name, offset)
instance = cls.__instances.get(key, None)
if instance is None:
instance = cls.__instances.setdefault(key,
cls.instance(name, offset))
# This lock may not be necessary in Python 3. See GH issue #901
with cls._cache_lock:
cls.__strong_cache[key] = cls.__strong_cache.pop(key, instance)
# Remove an item if the strong cache is overpopulated
if len(cls.__strong_cache) > cls.__strong_cache_size:
cls.__strong_cache.popitem(last=False)
return instance
class _TzStrFactory(_TzFactory):
def __init__(cls, *args, **kwargs):
cls.__instances = weakref.WeakValueDictionary()
cls.__strong_cache = OrderedDict()
cls.__strong_cache_size = 8
cls.__cache_lock = _thread.allocate_lock()
def __call__(cls, s, posix_offset=False):
key = (s, posix_offset)
instance = cls.__instances.get(key, None)
if instance is None:
instance = cls.__instances.setdefault(key,
cls.instance(s, posix_offset))
# This lock may not be necessary in Python 3. See GH issue #901
with cls.__cache_lock:
cls.__strong_cache[key] = cls.__strong_cache.pop(key, instance)
# Remove an item if the strong cache is overpopulated
if len(cls.__strong_cache) > cls.__strong_cache_size:
cls.__strong_cache.popitem(last=False)
return instance
File diff suppressed because it is too large Load Diff
-370
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@@ -1,370 +0,0 @@
# -*- coding: utf-8 -*-
"""
This module provides an interface to the native time zone data on Windows,
including :py:class:`datetime.tzinfo` implementations.
Attempting to import this module on a non-Windows platform will raise an
:py:obj:`ImportError`.
"""
# This code was originally contributed by Jeffrey Harris.
import datetime
import struct
from six.moves import winreg
from six import text_type
try:
import ctypes
from ctypes import wintypes
except ValueError:
# ValueError is raised on non-Windows systems for some horrible reason.
raise ImportError("Running tzwin on non-Windows system")
from ._common import tzrangebase
__all__ = ["tzwin", "tzwinlocal", "tzres"]
ONEWEEK = datetime.timedelta(7)
TZKEYNAMENT = r"SOFTWARE\Microsoft\Windows NT\CurrentVersion\Time Zones"
TZKEYNAME9X = r"SOFTWARE\Microsoft\Windows\CurrentVersion\Time Zones"
TZLOCALKEYNAME = r"SYSTEM\CurrentControlSet\Control\TimeZoneInformation"
def _settzkeyname():
handle = winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE)
try:
winreg.OpenKey(handle, TZKEYNAMENT).Close()
TZKEYNAME = TZKEYNAMENT
except WindowsError:
TZKEYNAME = TZKEYNAME9X
handle.Close()
return TZKEYNAME
TZKEYNAME = _settzkeyname()
class tzres(object):
"""
Class for accessing ``tzres.dll``, which contains timezone name related
resources.
.. versionadded:: 2.5.0
"""
p_wchar = ctypes.POINTER(wintypes.WCHAR) # Pointer to a wide char
def __init__(self, tzres_loc='tzres.dll'):
# Load the user32 DLL so we can load strings from tzres
user32 = ctypes.WinDLL('user32')
# Specify the LoadStringW function
user32.LoadStringW.argtypes = (wintypes.HINSTANCE,
wintypes.UINT,
wintypes.LPWSTR,
ctypes.c_int)
self.LoadStringW = user32.LoadStringW
self._tzres = ctypes.WinDLL(tzres_loc)
self.tzres_loc = tzres_loc
def load_name(self, offset):
"""
Load a timezone name from a DLL offset (integer).
>>> from dateutil.tzwin import tzres
>>> tzr = tzres()
>>> print(tzr.load_name(112))
'Eastern Standard Time'
:param offset:
A positive integer value referring to a string from the tzres dll.
.. note::
Offsets found in the registry are generally of the form
``@tzres.dll,-114``. The offset in this case is 114, not -114.
"""
resource = self.p_wchar()
lpBuffer = ctypes.cast(ctypes.byref(resource), wintypes.LPWSTR)
nchar = self.LoadStringW(self._tzres._handle, offset, lpBuffer, 0)
return resource[:nchar]
def name_from_string(self, tzname_str):
"""
Parse strings as returned from the Windows registry into the time zone
name as defined in the registry.
>>> from dateutil.tzwin import tzres
>>> tzr = tzres()
>>> print(tzr.name_from_string('@tzres.dll,-251'))
'Dateline Daylight Time'
>>> print(tzr.name_from_string('Eastern Standard Time'))
'Eastern Standard Time'
:param tzname_str:
A timezone name string as returned from a Windows registry key.
:return:
Returns the localized timezone string from tzres.dll if the string
is of the form `@tzres.dll,-offset`, else returns the input string.
"""
if not tzname_str.startswith('@'):
return tzname_str
name_splt = tzname_str.split(',-')
try:
offset = int(name_splt[1])
except:
raise ValueError("Malformed timezone string.")
return self.load_name(offset)
class tzwinbase(tzrangebase):
"""tzinfo class based on win32's timezones available in the registry."""
def __init__(self):
raise NotImplementedError('tzwinbase is an abstract base class')
def __eq__(self, other):
# Compare on all relevant dimensions, including name.
if not isinstance(other, tzwinbase):
return NotImplemented
return (self._std_offset == other._std_offset and
self._dst_offset == other._dst_offset and
self._stddayofweek == other._stddayofweek and
self._dstdayofweek == other._dstdayofweek and
self._stdweeknumber == other._stdweeknumber and
self._dstweeknumber == other._dstweeknumber and
self._stdhour == other._stdhour and
self._dsthour == other._dsthour and
self._stdminute == other._stdminute and
self._dstminute == other._dstminute and
self._std_abbr == other._std_abbr and
self._dst_abbr == other._dst_abbr)
@staticmethod
def list():
"""Return a list of all time zones known to the system."""
with winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE) as handle:
with winreg.OpenKey(handle, TZKEYNAME) as tzkey:
result = [winreg.EnumKey(tzkey, i)
for i in range(winreg.QueryInfoKey(tzkey)[0])]
return result
def display(self):
"""
Return the display name of the time zone.
"""
return self._display
def transitions(self, year):
"""
For a given year, get the DST on and off transition times, expressed
always on the standard time side. For zones with no transitions, this
function returns ``None``.
:param year:
The year whose transitions you would like to query.
:return:
Returns a :class:`tuple` of :class:`datetime.datetime` objects,
``(dston, dstoff)`` for zones with an annual DST transition, or
``None`` for fixed offset zones.
"""
if not self.hasdst:
return None
dston = picknthweekday(year, self._dstmonth, self._dstdayofweek,
self._dsthour, self._dstminute,
self._dstweeknumber)
dstoff = picknthweekday(year, self._stdmonth, self._stddayofweek,
self._stdhour, self._stdminute,
self._stdweeknumber)
# Ambiguous dates default to the STD side
dstoff -= self._dst_base_offset
return dston, dstoff
def _get_hasdst(self):
return self._dstmonth != 0
@property
def _dst_base_offset(self):
return self._dst_base_offset_
class tzwin(tzwinbase):
"""
Time zone object created from the zone info in the Windows registry
These are similar to :py:class:`dateutil.tz.tzrange` objects in that
the time zone data is provided in the format of a single offset rule
for either 0 or 2 time zone transitions per year.
:param: name
The name of a Windows time zone key, e.g. "Eastern Standard Time".
The full list of keys can be retrieved with :func:`tzwin.list`.
"""
def __init__(self, name):
self._name = name
with winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE) as handle:
tzkeyname = text_type("{kn}\\{name}").format(kn=TZKEYNAME, name=name)
with winreg.OpenKey(handle, tzkeyname) as tzkey:
keydict = valuestodict(tzkey)
self._std_abbr = keydict["Std"]
self._dst_abbr = keydict["Dlt"]
self._display = keydict["Display"]
# See http://ww_winreg.jsiinc.com/SUBA/tip0300/rh0398.htm
tup = struct.unpack("=3l16h", keydict["TZI"])
stdoffset = -tup[0]-tup[1] # Bias + StandardBias * -1
dstoffset = stdoffset-tup[2] # + DaylightBias * -1
self._std_offset = datetime.timedelta(minutes=stdoffset)
self._dst_offset = datetime.timedelta(minutes=dstoffset)
# for the meaning see the win32 TIME_ZONE_INFORMATION structure docs
# http://msdn.microsoft.com/en-us/library/windows/desktop/ms725481(v=vs.85).aspx
(self._stdmonth,
self._stddayofweek, # Sunday = 0
self._stdweeknumber, # Last = 5
self._stdhour,
self._stdminute) = tup[4:9]
(self._dstmonth,
self._dstdayofweek, # Sunday = 0
self._dstweeknumber, # Last = 5
self._dsthour,
self._dstminute) = tup[12:17]
self._dst_base_offset_ = self._dst_offset - self._std_offset
self.hasdst = self._get_hasdst()
def __repr__(self):
return "tzwin(%s)" % repr(self._name)
def __reduce__(self):
return (self.__class__, (self._name,))
class tzwinlocal(tzwinbase):
"""
Class representing the local time zone information in the Windows registry
While :class:`dateutil.tz.tzlocal` makes system calls (via the :mod:`time`
module) to retrieve time zone information, ``tzwinlocal`` retrieves the
rules directly from the Windows registry and creates an object like
:class:`dateutil.tz.tzwin`.
Because Windows does not have an equivalent of :func:`time.tzset`, on
Windows, :class:`dateutil.tz.tzlocal` instances will always reflect the
time zone settings *at the time that the process was started*, meaning
changes to the machine's time zone settings during the run of a program
on Windows will **not** be reflected by :class:`dateutil.tz.tzlocal`.
Because ``tzwinlocal`` reads the registry directly, it is unaffected by
this issue.
"""
def __init__(self):
with winreg.ConnectRegistry(None, winreg.HKEY_LOCAL_MACHINE) as handle:
with winreg.OpenKey(handle, TZLOCALKEYNAME) as tzlocalkey:
keydict = valuestodict(tzlocalkey)
self._std_abbr = keydict["StandardName"]
self._dst_abbr = keydict["DaylightName"]
try:
tzkeyname = text_type('{kn}\\{sn}').format(kn=TZKEYNAME,
sn=self._std_abbr)
with winreg.OpenKey(handle, tzkeyname) as tzkey:
_keydict = valuestodict(tzkey)
self._display = _keydict["Display"]
except OSError:
self._display = None
stdoffset = -keydict["Bias"]-keydict["StandardBias"]
dstoffset = stdoffset-keydict["DaylightBias"]
self._std_offset = datetime.timedelta(minutes=stdoffset)
self._dst_offset = datetime.timedelta(minutes=dstoffset)
# For reasons unclear, in this particular key, the day of week has been
# moved to the END of the SYSTEMTIME structure.
tup = struct.unpack("=8h", keydict["StandardStart"])
(self._stdmonth,
self._stdweeknumber, # Last = 5
self._stdhour,
self._stdminute) = tup[1:5]
self._stddayofweek = tup[7]
tup = struct.unpack("=8h", keydict["DaylightStart"])
(self._dstmonth,
self._dstweeknumber, # Last = 5
self._dsthour,
self._dstminute) = tup[1:5]
self._dstdayofweek = tup[7]
self._dst_base_offset_ = self._dst_offset - self._std_offset
self.hasdst = self._get_hasdst()
def __repr__(self):
return "tzwinlocal()"
def __str__(self):
# str will return the standard name, not the daylight name.
return "tzwinlocal(%s)" % repr(self._std_abbr)
def __reduce__(self):
return (self.__class__, ())
def picknthweekday(year, month, dayofweek, hour, minute, whichweek):
""" dayofweek == 0 means Sunday, whichweek 5 means last instance """
first = datetime.datetime(year, month, 1, hour, minute)
# This will work if dayofweek is ISO weekday (1-7) or Microsoft-style (0-6),
# Because 7 % 7 = 0
weekdayone = first.replace(day=((dayofweek - first.isoweekday()) % 7) + 1)
wd = weekdayone + ((whichweek - 1) * ONEWEEK)
if (wd.month != month):
wd -= ONEWEEK
return wd
def valuestodict(key):
"""Convert a registry key's values to a dictionary."""
dout = {}
size = winreg.QueryInfoKey(key)[1]
tz_res = None
for i in range(size):
key_name, value, dtype = winreg.EnumValue(key, i)
if dtype == winreg.REG_DWORD or dtype == winreg.REG_DWORD_LITTLE_ENDIAN:
# If it's a DWORD (32-bit integer), it's stored as unsigned - convert
# that to a proper signed integer
if value & (1 << 31):
value = value - (1 << 32)
elif dtype == winreg.REG_SZ:
# If it's a reference to the tzres DLL, load the actual string
if value.startswith('@tzres'):
tz_res = tz_res or tzres()
value = tz_res.name_from_string(value)
value = value.rstrip('\x00') # Remove trailing nulls
dout[key_name] = value
return dout
@@ -1,2 +0,0 @@
# tzwin has moved to dateutil.tz.win
from .tz.win import *
-71
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@@ -1,71 +0,0 @@
# -*- coding: utf-8 -*-
"""
This module offers general convenience and utility functions for dealing with
datetimes.
.. versionadded:: 2.7.0
"""
from __future__ import unicode_literals
from datetime import datetime, time
def today(tzinfo=None):
"""
Returns a :py:class:`datetime` representing the current day at midnight
:param tzinfo:
The time zone to attach (also used to determine the current day).
:return:
A :py:class:`datetime.datetime` object representing the current day
at midnight.
"""
dt = datetime.now(tzinfo)
return datetime.combine(dt.date(), time(0, tzinfo=tzinfo))
def default_tzinfo(dt, tzinfo):
"""
Sets the ``tzinfo`` parameter on naive datetimes only
This is useful for example when you are provided a datetime that may have
either an implicit or explicit time zone, such as when parsing a time zone
string.
.. doctest::
>>> from dateutil.tz import tzoffset
>>> from dateutil.parser import parse
>>> from dateutil.utils import default_tzinfo
>>> dflt_tz = tzoffset("EST", -18000)
>>> print(default_tzinfo(parse('2014-01-01 12:30 UTC'), dflt_tz))
2014-01-01 12:30:00+00:00
>>> print(default_tzinfo(parse('2014-01-01 12:30'), dflt_tz))
2014-01-01 12:30:00-05:00
:param dt:
The datetime on which to replace the time zone
:param tzinfo:
The :py:class:`datetime.tzinfo` subclass instance to assign to
``dt`` if (and only if) it is naive.
:return:
Returns an aware :py:class:`datetime.datetime`.
"""
if dt.tzinfo is not None:
return dt
else:
return dt.replace(tzinfo=tzinfo)
def within_delta(dt1, dt2, delta):
"""
Useful for comparing two datetimes that may have a negligible difference
to be considered equal.
"""
delta = abs(delta)
difference = dt1 - dt2
return -delta <= difference <= delta
@@ -1,167 +0,0 @@
# -*- coding: utf-8 -*-
import warnings
import json
from tarfile import TarFile
from pkgutil import get_data
from io import BytesIO
from dateutil.tz import tzfile as _tzfile
__all__ = ["get_zonefile_instance", "gettz", "gettz_db_metadata"]
ZONEFILENAME = "dateutil-zoneinfo.tar.gz"
METADATA_FN = 'METADATA'
class tzfile(_tzfile):
def __reduce__(self):
return (gettz, (self._filename,))
def getzoneinfofile_stream():
try:
return BytesIO(get_data(__name__, ZONEFILENAME))
except IOError as e: # TODO switch to FileNotFoundError?
warnings.warn("I/O error({0}): {1}".format(e.errno, e.strerror))
return None
class ZoneInfoFile(object):
def __init__(self, zonefile_stream=None):
if zonefile_stream is not None:
with TarFile.open(fileobj=zonefile_stream) as tf:
self.zones = {zf.name: tzfile(tf.extractfile(zf), filename=zf.name)
for zf in tf.getmembers()
if zf.isfile() and zf.name != METADATA_FN}
# deal with links: They'll point to their parent object. Less
# waste of memory
links = {zl.name: self.zones[zl.linkname]
for zl in tf.getmembers() if
zl.islnk() or zl.issym()}
self.zones.update(links)
try:
metadata_json = tf.extractfile(tf.getmember(METADATA_FN))
metadata_str = metadata_json.read().decode('UTF-8')
self.metadata = json.loads(metadata_str)
except KeyError:
# no metadata in tar file
self.metadata = None
else:
self.zones = {}
self.metadata = None
def get(self, name, default=None):
"""
Wrapper for :func:`ZoneInfoFile.zones.get`. This is a convenience method
for retrieving zones from the zone dictionary.
:param name:
The name of the zone to retrieve. (Generally IANA zone names)
:param default:
The value to return in the event of a missing key.
.. versionadded:: 2.6.0
"""
return self.zones.get(name, default)
# The current API has gettz as a module function, although in fact it taps into
# a stateful class. So as a workaround for now, without changing the API, we
# will create a new "global" class instance the first time a user requests a
# timezone. Ugly, but adheres to the api.
#
# TODO: Remove after deprecation period.
_CLASS_ZONE_INSTANCE = []
def get_zonefile_instance(new_instance=False):
"""
This is a convenience function which provides a :class:`ZoneInfoFile`
instance using the data provided by the ``dateutil`` package. By default, it
caches a single instance of the ZoneInfoFile object and returns that.
:param new_instance:
If ``True``, a new instance of :class:`ZoneInfoFile` is instantiated and
used as the cached instance for the next call. Otherwise, new instances
are created only as necessary.
:return:
Returns a :class:`ZoneInfoFile` object.
.. versionadded:: 2.6
"""
if new_instance:
zif = None
else:
zif = getattr(get_zonefile_instance, '_cached_instance', None)
if zif is None:
zif = ZoneInfoFile(getzoneinfofile_stream())
get_zonefile_instance._cached_instance = zif
return zif
def gettz(name):
"""
This retrieves a time zone from the local zoneinfo tarball that is packaged
with dateutil.
:param name:
An IANA-style time zone name, as found in the zoneinfo file.
:return:
Returns a :class:`dateutil.tz.tzfile` time zone object.
.. warning::
It is generally inadvisable to use this function, and it is only
provided for API compatibility with earlier versions. This is *not*
equivalent to ``dateutil.tz.gettz()``, which selects an appropriate
time zone based on the inputs, favoring system zoneinfo. This is ONLY
for accessing the dateutil-specific zoneinfo (which may be out of
date compared to the system zoneinfo).
.. deprecated:: 2.6
If you need to use a specific zoneinfofile over the system zoneinfo,
instantiate a :class:`dateutil.zoneinfo.ZoneInfoFile` object and call
:func:`dateutil.zoneinfo.ZoneInfoFile.get(name)` instead.
Use :func:`get_zonefile_instance` to retrieve an instance of the
dateutil-provided zoneinfo.
"""
warnings.warn("zoneinfo.gettz() will be removed in future versions, "
"to use the dateutil-provided zoneinfo files, instantiate a "
"ZoneInfoFile object and use ZoneInfoFile.zones.get() "
"instead. See the documentation for details.",
DeprecationWarning)
if len(_CLASS_ZONE_INSTANCE) == 0:
_CLASS_ZONE_INSTANCE.append(ZoneInfoFile(getzoneinfofile_stream()))
return _CLASS_ZONE_INSTANCE[0].zones.get(name)
def gettz_db_metadata():
""" Get the zonefile metadata
See `zonefile_metadata`_
:returns:
A dictionary with the database metadata
.. deprecated:: 2.6
See deprecation warning in :func:`zoneinfo.gettz`. To get metadata,
query the attribute ``zoneinfo.ZoneInfoFile.metadata``.
"""
warnings.warn("zoneinfo.gettz_db_metadata() will be removed in future "
"versions, to use the dateutil-provided zoneinfo files, "
"ZoneInfoFile object and query the 'metadata' attribute "
"instead. See the documentation for details.",
DeprecationWarning)
if len(_CLASS_ZONE_INSTANCE) == 0:
_CLASS_ZONE_INSTANCE.append(ZoneInfoFile(getzoneinfofile_stream()))
return _CLASS_ZONE_INSTANCE[0].metadata
@@ -1,75 +0,0 @@
import logging
import os
import tempfile
import shutil
import json
from subprocess import check_call, check_output
from tarfile import TarFile
from dateutil.zoneinfo import METADATA_FN, ZONEFILENAME
def rebuild(filename, tag=None, format="gz", zonegroups=[], metadata=None):
"""Rebuild the internal timezone info in dateutil/zoneinfo/zoneinfo*tar*
filename is the timezone tarball from ``ftp.iana.org/tz``.
"""
tmpdir = tempfile.mkdtemp()
zonedir = os.path.join(tmpdir, "zoneinfo")
moduledir = os.path.dirname(__file__)
try:
with TarFile.open(filename) as tf:
for name in zonegroups:
tf.extract(name, tmpdir)
filepaths = [os.path.join(tmpdir, n) for n in zonegroups]
_run_zic(zonedir, filepaths)
# write metadata file
with open(os.path.join(zonedir, METADATA_FN), 'w') as f:
json.dump(metadata, f, indent=4, sort_keys=True)
target = os.path.join(moduledir, ZONEFILENAME)
with TarFile.open(target, "w:%s" % format) as tf:
for entry in os.listdir(zonedir):
entrypath = os.path.join(zonedir, entry)
tf.add(entrypath, entry)
finally:
shutil.rmtree(tmpdir)
def _run_zic(zonedir, filepaths):
"""Calls the ``zic`` compiler in a compatible way to get a "fat" binary.
Recent versions of ``zic`` default to ``-b slim``, while older versions
don't even have the ``-b`` option (but default to "fat" binaries). The
current version of dateutil does not support Version 2+ TZif files, which
causes problems when used in conjunction with "slim" binaries, so this
function is used to ensure that we always get a "fat" binary.
"""
try:
help_text = check_output(["zic", "--help"])
except OSError as e:
_print_on_nosuchfile(e)
raise
if b"-b " in help_text:
bloat_args = ["-b", "fat"]
else:
bloat_args = []
check_call(["zic"] + bloat_args + ["-d", zonedir] + filepaths)
def _print_on_nosuchfile(e):
"""Print helpful troubleshooting message
e is an exception raised by subprocess.check_call()
"""
if e.errno == 2:
logging.error(
"Could not find zic. Perhaps you need to install "
"libc-bin or some other package that provides it, "
"or it's not in your PATH?")
@@ -1,2 +0,0 @@
Version: 1.11.1
Arguments: ['C:\\Users\\runneradmin\\AppData\\Local\\Temp\\cibw-run-5t0hy_xh\\cp313-win_amd64\\build\\venv\\Scripts\\delvewheel', 'repair', '--add-path', 'D:/a/numpy-release/numpy-release/.openblas/lib', '-w', 'C:\\Users\\runneradmin\\AppData\\Local\\Temp\\cibw-run-5t0hy_xh\\cp313-win_amd64\\repaired_wheel', 'C:\\Users\\runneradmin\\AppData\\Local\\Temp\\cibw-run-5t0hy_xh\\cp313-win_amd64\\built_wheel\\numpy-2.3.3-cp313-cp313-win_amd64.whl']
@@ -1 +0,0 @@
pip
@@ -1,950 +0,0 @@
Copyright (c) 2005-2025, NumPy Developers.
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 of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above
copyright notice, this list of conditions and the following
disclaimer in the documentation and/or other materials provided
with the distribution.
* Neither the name of the NumPy Developers nor the names of any
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
----
The NumPy repository and source distributions bundle several libraries that are
compatibly licensed. We list these here.
Name: lapack-lite
Files: numpy/linalg/lapack_lite/*
License: BSD-3-Clause
For details, see numpy/linalg/lapack_lite/LICENSE.txt
Name: dragon4
Files: numpy/_core/src/multiarray/dragon4.c
License: MIT
For license text, see numpy/_core/src/multiarray/dragon4.c
Name: libdivide
Files: numpy/_core/include/numpy/libdivide/*
License: Zlib
For license text, see numpy/_core/include/numpy/libdivide/LICENSE.txt
Note that the following files are vendored in the repository and sdist but not
installed in built numpy packages:
Name: Meson
Files: vendored-meson/meson/*
License: Apache 2.0
For license text, see vendored-meson/meson/COPYING
Name: spin
Files: .spin/cmds.py
License: BSD-3
For license text, see .spin/LICENSE
Name: tempita
Files: numpy/_build_utils/tempita/*
License: MIT
For details, see numpy/_build_utils/tempita/LICENCE.txt
----
This binary distribution of NumPy also bundles the following software:
Name: OpenBLAS
Files: numpy.libs\libscipy_openblas*.dll
Description: bundled as a dynamically linked library
Availability: https://github.com/OpenMathLib/OpenBLAS/
License: BSD-3-Clause
Copyright (c) 2011-2014, The OpenBLAS Project
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the
distribution.
3. Neither the name of the OpenBLAS project nor the names of
its contributors may be used to endorse or promote products
derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE
USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Name: LAPACK
Files: numpy.libs\libscipy_openblas*.dll
Description: bundled in OpenBLAS
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under version 3 of the GNU Affero General Public License into a single
combined work, and to convey the resulting work. The terms of this
License will continue to apply to the part which is the covered work,
but the special requirements of the GNU Affero General Public License,
section 13, concerning interaction through a network will apply to the
combination as such.
14. Revised Versions of this License.
The Free Software Foundation may publish revised and/or new versions of
the GNU General Public License from time to time. Such new versions will
be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU General
Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the
GNU General Public License, you may choose any version ever published
by the Free Software Foundation.
If the Program specifies that a proxy can decide which future
versions of the GNU General Public License can be used, that proxy's
public statement of acceptance of a version permanently authorizes you
to choose that version for the Program.
Later license versions may give you additional or different
permissions. However, no additional obligations are imposed on any
author or copyright holder as a result of your choosing to follow a
later version.
15. Disclaimer of Warranty.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
<program> Copyright (C) <year> <name of author>
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<https://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<https://www.gnu.org/licenses/why-not-lgpl.html>.
File diff suppressed because it is too large Load Diff
File diff suppressed because it is too large Load Diff
@@ -1,4 +0,0 @@
Wheel-Version: 1.0
Generator: meson
Root-Is-Purelib: false
Tag: cp313-cp313-win_amd64
@@ -1,13 +0,0 @@
[pkg_config]
numpy = numpy._core.lib.pkgconfig
[array_api]
numpy = numpy
[pyinstaller40]
hook-dirs = numpy:_pyinstaller_hooks_dir
[console_scripts]
f2py = numpy.f2py.f2py2e:main
numpy-config = numpy._configtool:main
-170
View File
@@ -1,170 +0,0 @@
# This file is generated by numpy's build process
# It contains system_info results at the time of building this package.
from enum import Enum
from numpy._core._multiarray_umath import (
__cpu_features__,
__cpu_baseline__,
__cpu_dispatch__,
)
__all__ = ["show_config"]
_built_with_meson = True
class DisplayModes(Enum):
stdout = "stdout"
dicts = "dicts"
def _cleanup(d):
"""
Removes empty values in a `dict` recursively
This ensures we remove values that Meson could not provide to CONFIG
"""
if isinstance(d, dict):
return {k: _cleanup(v) for k, v in d.items() if v and _cleanup(v)}
else:
return d
CONFIG = _cleanup(
{
"Compilers": {
"c": {
"name": "msvc",
"linker": r"link",
"version": "19.44.35215",
"commands": r"cl",
"args": r"",
"linker args": r"",
},
"cython": {
"name": "cython",
"linker": r"cython",
"version": "3.1.3",
"commands": r"cython",
"args": r"",
"linker args": r"",
},
"c++": {
"name": "msvc",
"linker": r"link",
"version": "19.44.35215",
"commands": r"cl",
"args": r"",
"linker args": r"",
},
},
"Machine Information": {
"host": {
"cpu": "x86_64",
"family": "x86_64",
"endian": "little",
"system": "windows",
},
"build": {
"cpu": "x86_64",
"family": "x86_64",
"endian": "little",
"system": "windows",
},
"cross-compiled": bool("False".lower().replace("false", "")),
},
"Build Dependencies": {
"blas": {
"name": "scipy-openblas",
"found": bool("True".lower().replace("false", "")),
"version": "0.3.30",
"detection method": "pkgconfig",
"include directory": r"C:/Users/runneradmin/AppData/Local/Temp/cibw-run-5t0hy_xh/cp313-win_amd64/build/venv/Lib/site-packages/scipy_openblas64/include",
"lib directory": r"C:/Users/runneradmin/AppData/Local/Temp/cibw-run-5t0hy_xh/cp313-win_amd64/build/venv/Lib/site-packages/scipy_openblas64/lib",
"openblas configuration": r"OpenBLAS 0.3.30 USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell MAX_THREADS=24",
"pc file directory": r"D:/a/numpy-release/numpy-release/.openblas",
},
"lapack": {
"name": "scipy-openblas",
"found": bool("True".lower().replace("false", "")),
"version": "0.3.30",
"detection method": "pkgconfig",
"include directory": r"C:/Users/runneradmin/AppData/Local/Temp/cibw-run-5t0hy_xh/cp313-win_amd64/build/venv/Lib/site-packages/scipy_openblas64/include",
"lib directory": r"C:/Users/runneradmin/AppData/Local/Temp/cibw-run-5t0hy_xh/cp313-win_amd64/build/venv/Lib/site-packages/scipy_openblas64/lib",
"openblas configuration": r"OpenBLAS 0.3.30 USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell MAX_THREADS=24",
"pc file directory": r"D:/a/numpy-release/numpy-release/.openblas",
},
},
"Python Information": {
"path": r"C:\Users\runneradmin\AppData\Local\Temp\build-env-q3zde7n4\Scripts\python.exe",
"version": "3.13",
},
"SIMD Extensions": {
"baseline": __cpu_baseline__,
"found": [
feature for feature in __cpu_dispatch__ if __cpu_features__[feature]
],
"not found": [
feature for feature in __cpu_dispatch__ if not __cpu_features__[feature]
],
},
}
)
def _check_pyyaml():
import yaml
return yaml
def show(mode=DisplayModes.stdout.value):
"""
Show libraries and system information on which NumPy was built
and is being used
Parameters
----------
mode : {`'stdout'`, `'dicts'`}, optional.
Indicates how to display the config information.
`'stdout'` prints to console, `'dicts'` returns a dictionary
of the configuration.
Returns
-------
out : {`dict`, `None`}
If mode is `'dicts'`, a dict is returned, else None
See Also
--------
get_include : Returns the directory containing NumPy C
header files.
Notes
-----
1. The `'stdout'` mode will give more readable
output if ``pyyaml`` is installed
"""
if mode == DisplayModes.stdout.value:
try: # Non-standard library, check import
yaml = _check_pyyaml()
print(yaml.dump(CONFIG))
except ModuleNotFoundError:
import warnings
import json
warnings.warn("Install `pyyaml` for better output", stacklevel=1)
print(json.dumps(CONFIG, indent=2))
elif mode == DisplayModes.dicts.value:
return CONFIG
else:
raise AttributeError(
f"Invalid `mode`, use one of: {', '.join([e.value for e in DisplayModes])}"
)
def show_config(mode=DisplayModes.stdout.value):
return show(mode)
show_config.__doc__ = show.__doc__
show_config.__module__ = "numpy"
@@ -1,102 +0,0 @@
from enum import Enum
from types import ModuleType
from typing import Final, NotRequired, TypedDict, overload, type_check_only
from typing import Literal as L
_CompilerConfigDictValue = TypedDict(
"_CompilerConfigDictValue",
{
"name": str,
"linker": str,
"version": str,
"commands": str,
"args": str,
"linker args": str,
},
)
_CompilerConfigDict = TypedDict(
"_CompilerConfigDict",
{
"c": _CompilerConfigDictValue,
"cython": _CompilerConfigDictValue,
"c++": _CompilerConfigDictValue,
},
)
_MachineInformationDict = TypedDict(
"_MachineInformationDict",
{
"host": _MachineInformationDictValue,
"build": _MachineInformationDictValue,
"cross-compiled": NotRequired[L[True]],
},
)
@type_check_only
class _MachineInformationDictValue(TypedDict):
cpu: str
family: str
endian: L["little", "big"]
system: str
_BuildDependenciesDictValue = TypedDict(
"_BuildDependenciesDictValue",
{
"name": str,
"found": NotRequired[L[True]],
"version": str,
"include directory": str,
"lib directory": str,
"openblas configuration": str,
"pc file directory": str,
},
)
class _BuildDependenciesDict(TypedDict):
blas: _BuildDependenciesDictValue
lapack: _BuildDependenciesDictValue
class _PythonInformationDict(TypedDict):
path: str
version: str
_SIMDExtensionsDict = TypedDict(
"_SIMDExtensionsDict",
{
"baseline": list[str],
"found": list[str],
"not found": list[str],
},
)
_ConfigDict = TypedDict(
"_ConfigDict",
{
"Compilers": _CompilerConfigDict,
"Machine Information": _MachineInformationDict,
"Build Dependencies": _BuildDependenciesDict,
"Python Information": _PythonInformationDict,
"SIMD Extensions": _SIMDExtensionsDict,
},
)
###
__all__ = ["show_config"]
CONFIG: Final[_ConfigDict] = ...
class DisplayModes(Enum):
stdout = "stdout"
dicts = "dicts"
def _check_pyyaml() -> ModuleType: ...
@overload
def show(mode: L["stdout"] = "stdout") -> None: ...
@overload
def show(mode: L["dicts"]) -> _ConfigDict: ...
@overload
def show_config(mode: L["stdout"] = "stdout") -> None: ...
@overload
def show_config(mode: L["dicts"]) -> _ConfigDict: ...
File diff suppressed because it is too large Load Diff
File diff suppressed because it is too large Load Diff
-941
View File
@@ -1,941 +0,0 @@
"""
NumPy
=====
Provides
1. An array object of arbitrary homogeneous items
2. Fast mathematical operations over arrays
3. Linear Algebra, Fourier Transforms, Random Number Generation
How to use the documentation
----------------------------
Documentation is available in two forms: docstrings provided
with the code, and a loose standing reference guide, available from
`the NumPy homepage <https://numpy.org>`_.
We recommend exploring the docstrings using
`IPython <https://ipython.org>`_, an advanced Python shell with
TAB-completion and introspection capabilities. See below for further
instructions.
The docstring examples assume that `numpy` has been imported as ``np``::
>>> import numpy as np
Code snippets are indicated by three greater-than signs::
>>> x = 42
>>> x = x + 1
Use the built-in ``help`` function to view a function's docstring::
>>> help(np.sort)
... # doctest: +SKIP
For some objects, ``np.info(obj)`` may provide additional help. This is
particularly true if you see the line "Help on ufunc object:" at the top
of the help() page. Ufuncs are implemented in C, not Python, for speed.
The native Python help() does not know how to view their help, but our
np.info() function does.
Available subpackages
---------------------
lib
Basic functions used by several sub-packages.
random
Core Random Tools
linalg
Core Linear Algebra Tools
fft
Core FFT routines
polynomial
Polynomial tools
testing
NumPy testing tools
distutils
Enhancements to distutils with support for
Fortran compilers support and more (for Python <= 3.11)
Utilities
---------
test
Run numpy unittests
show_config
Show numpy build configuration
__version__
NumPy version string
Viewing documentation using IPython
-----------------------------------
Start IPython and import `numpy` usually under the alias ``np``: `import
numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste
examples into the shell. To see which functions are available in `numpy`,
type ``np.<TAB>`` (where ``<TAB>`` refers to the TAB key), or use
``np.*cos*?<ENTER>`` (where ``<ENTER>`` refers to the ENTER key) to narrow
down the list. To view the docstring for a function, use
``np.cos?<ENTER>`` (to view the docstring) and ``np.cos??<ENTER>`` (to view
the source code).
Copies vs. in-place operation
-----------------------------
Most of the functions in `numpy` return a copy of the array argument
(e.g., `np.sort`). In-place versions of these functions are often
available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.
Exceptions to this rule are documented.
"""
# start delvewheel patch
def _delvewheel_patch_1_11_1():
import os
if os.path.isdir(libs_dir := os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, 'numpy.libs'))):
os.add_dll_directory(libs_dir)
_delvewheel_patch_1_11_1()
del _delvewheel_patch_1_11_1
# end delvewheel patch
import os
import sys
import warnings
# If a version with git hash was stored, use that instead
from . import version
from ._expired_attrs_2_0 import __expired_attributes__
from ._globals import _CopyMode, _NoValue
from .version import __version__
# We first need to detect if we're being called as part of the numpy setup
# procedure itself in a reliable manner.
try:
__NUMPY_SETUP__ # noqa: B018
except NameError:
__NUMPY_SETUP__ = False
if __NUMPY_SETUP__:
sys.stderr.write('Running from numpy source directory.\n')
else:
# Allow distributors to run custom init code before importing numpy._core
from . import _distributor_init
try:
from numpy.__config__ import show_config
except ImportError as e:
msg = """Error importing numpy: you should not try to import numpy from
its source directory; please exit the numpy source tree, and relaunch
your python interpreter from there."""
raise ImportError(msg) from e
from . import _core
from ._core import (
False_,
ScalarType,
True_,
abs,
absolute,
acos,
acosh,
add,
all,
allclose,
amax,
amin,
any,
arange,
arccos,
arccosh,
arcsin,
arcsinh,
arctan,
arctan2,
arctanh,
argmax,
argmin,
argpartition,
argsort,
argwhere,
around,
array,
array2string,
array_equal,
array_equiv,
array_repr,
array_str,
asanyarray,
asarray,
ascontiguousarray,
asfortranarray,
asin,
asinh,
astype,
atan,
atan2,
atanh,
atleast_1d,
atleast_2d,
atleast_3d,
base_repr,
binary_repr,
bitwise_and,
bitwise_count,
bitwise_invert,
bitwise_left_shift,
bitwise_not,
bitwise_or,
bitwise_right_shift,
bitwise_xor,
block,
bool,
bool_,
broadcast,
busday_count,
busday_offset,
busdaycalendar,
byte,
bytes_,
can_cast,
cbrt,
cdouble,
ceil,
character,
choose,
clip,
clongdouble,
complex64,
complex128,
complexfloating,
compress,
concat,
concatenate,
conj,
conjugate,
convolve,
copysign,
copyto,
correlate,
cos,
cosh,
count_nonzero,
cross,
csingle,
cumprod,
cumsum,
cumulative_prod,
cumulative_sum,
datetime64,
datetime_as_string,
datetime_data,
deg2rad,
degrees,
diagonal,
divide,
divmod,
dot,
double,
dtype,
e,
einsum,
einsum_path,
empty,
empty_like,
equal,
errstate,
euler_gamma,
exp,
exp2,
expm1,
fabs,
finfo,
flatiter,
flatnonzero,
flexible,
float16,
float32,
float64,
float_power,
floating,
floor,
floor_divide,
fmax,
fmin,
fmod,
format_float_positional,
format_float_scientific,
frexp,
from_dlpack,
frombuffer,
fromfile,
fromfunction,
fromiter,
frompyfunc,
fromstring,
full,
full_like,
gcd,
generic,
geomspace,
get_printoptions,
getbufsize,
geterr,
geterrcall,
greater,
greater_equal,
half,
heaviside,
hstack,
hypot,
identity,
iinfo,
indices,
inexact,
inf,
inner,
int8,
int16,
int32,
int64,
int_,
intc,
integer,
intp,
invert,
is_busday,
isclose,
isdtype,
isfinite,
isfortran,
isinf,
isnan,
isnat,
isscalar,
issubdtype,
lcm,
ldexp,
left_shift,
less,
less_equal,
lexsort,
linspace,
little_endian,
log,
log1p,
log2,
log10,
logaddexp,
logaddexp2,
logical_and,
logical_not,
logical_or,
logical_xor,
logspace,
long,
longdouble,
longlong,
matmul,
matrix_transpose,
matvec,
max,
maximum,
may_share_memory,
mean,
memmap,
min,
min_scalar_type,
minimum,
mod,
modf,
moveaxis,
multiply,
nan,
ndarray,
ndim,
nditer,
negative,
nested_iters,
newaxis,
nextafter,
nonzero,
not_equal,
number,
object_,
ones,
ones_like,
outer,
partition,
permute_dims,
pi,
positive,
pow,
power,
printoptions,
prod,
promote_types,
ptp,
put,
putmask,
rad2deg,
radians,
ravel,
recarray,
reciprocal,
record,
remainder,
repeat,
require,
reshape,
resize,
result_type,
right_shift,
rint,
roll,
rollaxis,
round,
sctypeDict,
searchsorted,
set_printoptions,
setbufsize,
seterr,
seterrcall,
shape,
shares_memory,
short,
sign,
signbit,
signedinteger,
sin,
single,
sinh,
size,
sort,
spacing,
sqrt,
square,
squeeze,
stack,
std,
str_,
subtract,
sum,
swapaxes,
take,
tan,
tanh,
tensordot,
timedelta64,
trace,
transpose,
true_divide,
trunc,
typecodes,
ubyte,
ufunc,
uint,
uint8,
uint16,
uint32,
uint64,
uintc,
uintp,
ulong,
ulonglong,
unsignedinteger,
unstack,
ushort,
var,
vdot,
vecdot,
vecmat,
void,
vstack,
where,
zeros,
zeros_like,
)
# NOTE: It's still under discussion whether these aliases
# should be removed.
for ta in ["float96", "float128", "complex192", "complex256"]:
try:
globals()[ta] = getattr(_core, ta)
except AttributeError:
pass
del ta
from . import lib
from . import matrixlib as _mat
from .lib import scimath as emath
from .lib._arraypad_impl import pad
from .lib._arraysetops_impl import (
ediff1d,
in1d,
intersect1d,
isin,
setdiff1d,
setxor1d,
union1d,
unique,
unique_all,
unique_counts,
unique_inverse,
unique_values,
)
from .lib._function_base_impl import (
angle,
append,
asarray_chkfinite,
average,
bartlett,
bincount,
blackman,
copy,
corrcoef,
cov,
delete,
diff,
digitize,
extract,
flip,
gradient,
hamming,
hanning,
i0,
insert,
interp,
iterable,
kaiser,
median,
meshgrid,
percentile,
piecewise,
place,
quantile,
rot90,
select,
sinc,
sort_complex,
trapezoid,
trapz,
trim_zeros,
unwrap,
vectorize,
)
from .lib._histograms_impl import histogram, histogram_bin_edges, histogramdd
from .lib._index_tricks_impl import (
c_,
diag_indices,
diag_indices_from,
fill_diagonal,
index_exp,
ix_,
mgrid,
ndenumerate,
ndindex,
ogrid,
r_,
ravel_multi_index,
s_,
unravel_index,
)
from .lib._nanfunctions_impl import (
nanargmax,
nanargmin,
nancumprod,
nancumsum,
nanmax,
nanmean,
nanmedian,
nanmin,
nanpercentile,
nanprod,
nanquantile,
nanstd,
nansum,
nanvar,
)
from .lib._npyio_impl import (
fromregex,
genfromtxt,
load,
loadtxt,
packbits,
save,
savetxt,
savez,
savez_compressed,
unpackbits,
)
from .lib._polynomial_impl import (
poly,
poly1d,
polyadd,
polyder,
polydiv,
polyfit,
polyint,
polymul,
polysub,
polyval,
roots,
)
from .lib._shape_base_impl import (
apply_along_axis,
apply_over_axes,
array_split,
column_stack,
dsplit,
dstack,
expand_dims,
hsplit,
kron,
put_along_axis,
row_stack,
split,
take_along_axis,
tile,
vsplit,
)
from .lib._stride_tricks_impl import (
broadcast_arrays,
broadcast_shapes,
broadcast_to,
)
from .lib._twodim_base_impl import (
diag,
diagflat,
eye,
fliplr,
flipud,
histogram2d,
mask_indices,
tri,
tril,
tril_indices,
tril_indices_from,
triu,
triu_indices,
triu_indices_from,
vander,
)
from .lib._type_check_impl import (
common_type,
imag,
iscomplex,
iscomplexobj,
isreal,
isrealobj,
mintypecode,
nan_to_num,
real,
real_if_close,
typename,
)
from .lib._ufunclike_impl import fix, isneginf, isposinf
from .lib._utils_impl import get_include, info, show_runtime
from .matrixlib import asmatrix, bmat, matrix
# public submodules are imported lazily, therefore are accessible from
# __getattr__. Note that `distutils` (deprecated) and `array_api`
# (experimental label) are not added here, because `from numpy import *`
# must not raise any warnings - that's too disruptive.
__numpy_submodules__ = {
"linalg", "fft", "dtypes", "random", "polynomial", "ma",
"exceptions", "lib", "ctypeslib", "testing", "typing",
"f2py", "test", "rec", "char", "core", "strings",
}
# We build warning messages for former attributes
_msg = (
"module 'numpy' has no attribute '{n}'.\n"
"`np.{n}` was a deprecated alias for the builtin `{n}`. "
"To avoid this error in existing code, use `{n}` by itself. "
"Doing this will not modify any behavior and is safe. {extended_msg}\n"
"The aliases was originally deprecated in NumPy 1.20; for more "
"details and guidance see the original release note at:\n"
" https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations")
_specific_msg = (
"If you specifically wanted the numpy scalar type, use `np.{}` here.")
_int_extended_msg = (
"When replacing `np.{}`, you may wish to use e.g. `np.int64` "
"or `np.int32` to specify the precision. If you wish to review "
"your current use, check the release note link for "
"additional information.")
_type_info = [
("object", ""), # The NumPy scalar only exists by name.
("float", _specific_msg.format("float64")),
("complex", _specific_msg.format("complex128")),
("str", _specific_msg.format("str_")),
("int", _int_extended_msg.format("int"))]
__former_attrs__ = {
n: _msg.format(n=n, extended_msg=extended_msg)
for n, extended_msg in _type_info
}
# Some of these could be defined right away, but most were aliases to
# the Python objects and only removed in NumPy 1.24. Defining them should
# probably wait for NumPy 1.26 or 2.0.
# When defined, these should possibly not be added to `__all__` to avoid
# import with `from numpy import *`.
__future_scalars__ = {"str", "bytes", "object"}
__array_api_version__ = "2024.12"
from ._array_api_info import __array_namespace_info__
# now that numpy core module is imported, can initialize limits
_core.getlimits._register_known_types()
__all__ = list(
__numpy_submodules__ |
set(_core.__all__) |
set(_mat.__all__) |
set(lib._histograms_impl.__all__) |
set(lib._nanfunctions_impl.__all__) |
set(lib._function_base_impl.__all__) |
set(lib._twodim_base_impl.__all__) |
set(lib._shape_base_impl.__all__) |
set(lib._type_check_impl.__all__) |
set(lib._arraysetops_impl.__all__) |
set(lib._ufunclike_impl.__all__) |
set(lib._arraypad_impl.__all__) |
set(lib._utils_impl.__all__) |
set(lib._stride_tricks_impl.__all__) |
set(lib._polynomial_impl.__all__) |
set(lib._npyio_impl.__all__) |
set(lib._index_tricks_impl.__all__) |
{"emath", "show_config", "__version__", "__array_namespace_info__"}
)
# Filter out Cython harmless warnings
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
warnings.filterwarnings("ignore", message="numpy.ndarray size changed")
def __getattr__(attr):
# Warn for expired attributes
import warnings
if attr == "linalg":
import numpy.linalg as linalg
return linalg
elif attr == "fft":
import numpy.fft as fft
return fft
elif attr == "dtypes":
import numpy.dtypes as dtypes
return dtypes
elif attr == "random":
import numpy.random as random
return random
elif attr == "polynomial":
import numpy.polynomial as polynomial
return polynomial
elif attr == "ma":
import numpy.ma as ma
return ma
elif attr == "ctypeslib":
import numpy.ctypeslib as ctypeslib
return ctypeslib
elif attr == "exceptions":
import numpy.exceptions as exceptions
return exceptions
elif attr == "testing":
import numpy.testing as testing
return testing
elif attr == "matlib":
import numpy.matlib as matlib
return matlib
elif attr == "f2py":
import numpy.f2py as f2py
return f2py
elif attr == "typing":
import numpy.typing as typing
return typing
elif attr == "rec":
import numpy.rec as rec
return rec
elif attr == "char":
import numpy.char as char
return char
elif attr == "array_api":
raise AttributeError("`numpy.array_api` is not available from "
"numpy 2.0 onwards", name=None)
elif attr == "core":
import numpy.core as core
return core
elif attr == "strings":
import numpy.strings as strings
return strings
elif attr == "distutils":
if 'distutils' in __numpy_submodules__:
import numpy.distutils as distutils
return distutils
else:
raise AttributeError("`numpy.distutils` is not available from "
"Python 3.12 onwards", name=None)
if attr in __future_scalars__:
# And future warnings for those that will change, but also give
# the AttributeError
warnings.warn(
f"In the future `np.{attr}` will be defined as the "
"corresponding NumPy scalar.", FutureWarning, stacklevel=2)
if attr in __former_attrs__:
raise AttributeError(__former_attrs__[attr], name=None)
if attr in __expired_attributes__:
raise AttributeError(
f"`np.{attr}` was removed in the NumPy 2.0 release. "
f"{__expired_attributes__[attr]}",
name=None
)
if attr == "chararray":
warnings.warn(
"`np.chararray` is deprecated and will be removed from "
"the main namespace in the future. Use an array with a string "
"or bytes dtype instead.", DeprecationWarning, stacklevel=2)
import numpy.char as char
return char.chararray
raise AttributeError(f"module {__name__!r} has no attribute {attr!r}")
def __dir__():
public_symbols = (
globals().keys() | __numpy_submodules__
)
public_symbols -= {
"matrixlib", "matlib", "tests", "conftest", "version",
"distutils", "array_api"
}
return list(public_symbols)
# Pytest testing
from numpy._pytesttester import PytestTester
test = PytestTester(__name__)
del PytestTester
def _sanity_check():
"""
Quick sanity checks for common bugs caused by environment.
There are some cases e.g. with wrong BLAS ABI that cause wrong
results under specific runtime conditions that are not necessarily
achieved during test suite runs, and it is useful to catch those early.
See https://github.com/numpy/numpy/issues/8577 and other
similar bug reports.
"""
try:
x = ones(2, dtype=float32)
if not abs(x.dot(x) - float32(2.0)) < 1e-5:
raise AssertionError
except AssertionError:
msg = ("The current Numpy installation ({!r}) fails to "
"pass simple sanity checks. This can be caused for example "
"by incorrect BLAS library being linked in, or by mixing "
"package managers (pip, conda, apt, ...). Search closed "
"numpy issues for similar problems.")
raise RuntimeError(msg.format(__file__)) from None
_sanity_check()
del _sanity_check
def _mac_os_check():
"""
Quick Sanity check for Mac OS look for accelerate build bugs.
Testing numpy polyfit calls init_dgelsd(LAPACK)
"""
try:
c = array([3., 2., 1.])
x = linspace(0, 2, 5)
y = polyval(c, x)
_ = polyfit(x, y, 2, cov=True)
except ValueError:
pass
if sys.platform == "darwin":
from . import exceptions
with warnings.catch_warnings(record=True) as w:
_mac_os_check()
# Throw runtime error, if the test failed
# Check for warning and report the error_message
if len(w) > 0:
for _wn in w:
if _wn.category is exceptions.RankWarning:
# Ignore other warnings, they may not be relevant (see gh-25433)
error_message = (
f"{_wn.category.__name__}: {_wn.message}"
)
msg = (
"Polyfit sanity test emitted a warning, most likely due "
"to using a buggy Accelerate backend."
"\nIf you compiled yourself, more information is available at:" # noqa: E501
"\nhttps://numpy.org/devdocs/building/index.html"
"\nOtherwise report this to the vendor "
f"that provided NumPy.\n\n{error_message}\n")
raise RuntimeError(msg)
del _wn
del w
del _mac_os_check
def hugepage_setup():
"""
We usually use madvise hugepages support, but on some old kernels it
is slow and thus better avoided. Specifically kernel version 4.6
had a bug fix which probably fixed this:
https://github.com/torvalds/linux/commit/7cf91a98e607c2f935dbcc177d70011e95b8faff
"""
use_hugepage = os.environ.get("NUMPY_MADVISE_HUGEPAGE", None)
if sys.platform == "linux" and use_hugepage is None:
# If there is an issue with parsing the kernel version,
# set use_hugepage to 0. Usage of LooseVersion will handle
# the kernel version parsing better, but avoided since it
# will increase the import time.
# See: #16679 for related discussion.
try:
use_hugepage = 1
kernel_version = os.uname().release.split(".")[:2]
kernel_version = tuple(int(v) for v in kernel_version)
if kernel_version < (4, 6):
use_hugepage = 0
except ValueError:
use_hugepage = 0
elif use_hugepage is None:
# This is not Linux, so it should not matter, just enable anyway
use_hugepage = 1
else:
use_hugepage = int(use_hugepage)
return use_hugepage
# Note that this will currently only make a difference on Linux
_core.multiarray._set_madvise_hugepage(hugepage_setup())
del hugepage_setup
# Give a warning if NumPy is reloaded or imported on a sub-interpreter
# We do this from python, since the C-module may not be reloaded and
# it is tidier organized.
_core.multiarray._multiarray_umath._reload_guard()
# TODO: Remove the environment variable entirely now that it is "weak"
if (os.environ.get("NPY_PROMOTION_STATE", "weak") != "weak"):
warnings.warn(
"NPY_PROMOTION_STATE was a temporary feature for NumPy 2.0 "
"transition and is ignored after NumPy 2.2.",
UserWarning, stacklevel=2)
# Tell PyInstaller where to find hook-numpy.py
def _pyinstaller_hooks_dir():
from pathlib import Path
return [str(Path(__file__).with_name("_pyinstaller").resolve())]
# Remove symbols imported for internal use
del os, sys, warnings
File diff suppressed because it is too large Load Diff
@@ -1,346 +0,0 @@
"""
Array API Inspection namespace
This is the namespace for inspection functions as defined by the array API
standard. See
https://data-apis.org/array-api/latest/API_specification/inspection.html for
more details.
"""
from numpy._core import (
bool,
complex64,
complex128,
dtype,
float32,
float64,
int8,
int16,
int32,
int64,
intp,
uint8,
uint16,
uint32,
uint64,
)
class __array_namespace_info__:
"""
Get the array API inspection namespace for NumPy.
The array API inspection namespace defines the following functions:
- capabilities()
- default_device()
- default_dtypes()
- dtypes()
- devices()
See
https://data-apis.org/array-api/latest/API_specification/inspection.html
for more details.
Returns
-------
info : ModuleType
The array API inspection namespace for NumPy.
Examples
--------
>>> info = np.__array_namespace_info__()
>>> info.default_dtypes()
{'real floating': numpy.float64,
'complex floating': numpy.complex128,
'integral': numpy.int64,
'indexing': numpy.int64}
"""
__module__ = 'numpy'
def capabilities(self):
"""
Return a dictionary of array API library capabilities.
The resulting dictionary has the following keys:
- **"boolean indexing"**: boolean indicating whether an array library
supports boolean indexing. Always ``True`` for NumPy.
- **"data-dependent shapes"**: boolean indicating whether an array
library supports data-dependent output shapes. Always ``True`` for
NumPy.
See
https://data-apis.org/array-api/latest/API_specification/generated/array_api.info.capabilities.html
for more details.
See Also
--------
__array_namespace_info__.default_device,
__array_namespace_info__.default_dtypes,
__array_namespace_info__.dtypes,
__array_namespace_info__.devices
Returns
-------
capabilities : dict
A dictionary of array API library capabilities.
Examples
--------
>>> info = np.__array_namespace_info__()
>>> info.capabilities()
{'boolean indexing': True,
'data-dependent shapes': True,
'max dimensions': 64}
"""
return {
"boolean indexing": True,
"data-dependent shapes": True,
"max dimensions": 64,
}
def default_device(self):
"""
The default device used for new NumPy arrays.
For NumPy, this always returns ``'cpu'``.
See Also
--------
__array_namespace_info__.capabilities,
__array_namespace_info__.default_dtypes,
__array_namespace_info__.dtypes,
__array_namespace_info__.devices
Returns
-------
device : str
The default device used for new NumPy arrays.
Examples
--------
>>> info = np.__array_namespace_info__()
>>> info.default_device()
'cpu'
"""
return "cpu"
def default_dtypes(self, *, device=None):
"""
The default data types used for new NumPy arrays.
For NumPy, this always returns the following dictionary:
- **"real floating"**: ``numpy.float64``
- **"complex floating"**: ``numpy.complex128``
- **"integral"**: ``numpy.intp``
- **"indexing"**: ``numpy.intp``
Parameters
----------
device : str, optional
The device to get the default data types for. For NumPy, only
``'cpu'`` is allowed.
Returns
-------
dtypes : dict
A dictionary describing the default data types used for new NumPy
arrays.
See Also
--------
__array_namespace_info__.capabilities,
__array_namespace_info__.default_device,
__array_namespace_info__.dtypes,
__array_namespace_info__.devices
Examples
--------
>>> info = np.__array_namespace_info__()
>>> info.default_dtypes()
{'real floating': numpy.float64,
'complex floating': numpy.complex128,
'integral': numpy.int64,
'indexing': numpy.int64}
"""
if device not in ["cpu", None]:
raise ValueError(
'Device not understood. Only "cpu" is allowed, but received:'
f' {device}'
)
return {
"real floating": dtype(float64),
"complex floating": dtype(complex128),
"integral": dtype(intp),
"indexing": dtype(intp),
}
def dtypes(self, *, device=None, kind=None):
"""
The array API data types supported by NumPy.
Note that this function only returns data types that are defined by
the array API.
Parameters
----------
device : str, optional
The device to get the data types for. For NumPy, only ``'cpu'`` is
allowed.
kind : str or tuple of str, optional
The kind of data types to return. If ``None``, all data types are
returned. If a string, only data types of that kind are returned.
If a tuple, a dictionary containing the union of the given kinds
is returned. The following kinds are supported:
- ``'bool'``: boolean data types (i.e., ``bool``).
- ``'signed integer'``: signed integer data types (i.e., ``int8``,
``int16``, ``int32``, ``int64``).
- ``'unsigned integer'``: unsigned integer data types (i.e.,
``uint8``, ``uint16``, ``uint32``, ``uint64``).
- ``'integral'``: integer data types. Shorthand for ``('signed
integer', 'unsigned integer')``.
- ``'real floating'``: real-valued floating-point data types
(i.e., ``float32``, ``float64``).
- ``'complex floating'``: complex floating-point data types (i.e.,
``complex64``, ``complex128``).
- ``'numeric'``: numeric data types. Shorthand for ``('integral',
'real floating', 'complex floating')``.
Returns
-------
dtypes : dict
A dictionary mapping the names of data types to the corresponding
NumPy data types.
See Also
--------
__array_namespace_info__.capabilities,
__array_namespace_info__.default_device,
__array_namespace_info__.default_dtypes,
__array_namespace_info__.devices
Examples
--------
>>> info = np.__array_namespace_info__()
>>> info.dtypes(kind='signed integer')
{'int8': numpy.int8,
'int16': numpy.int16,
'int32': numpy.int32,
'int64': numpy.int64}
"""
if device not in ["cpu", None]:
raise ValueError(
'Device not understood. Only "cpu" is allowed, but received:'
f' {device}'
)
if kind is None:
return {
"bool": dtype(bool),
"int8": dtype(int8),
"int16": dtype(int16),
"int32": dtype(int32),
"int64": dtype(int64),
"uint8": dtype(uint8),
"uint16": dtype(uint16),
"uint32": dtype(uint32),
"uint64": dtype(uint64),
"float32": dtype(float32),
"float64": dtype(float64),
"complex64": dtype(complex64),
"complex128": dtype(complex128),
}
if kind == "bool":
return {"bool": bool}
if kind == "signed integer":
return {
"int8": dtype(int8),
"int16": dtype(int16),
"int32": dtype(int32),
"int64": dtype(int64),
}
if kind == "unsigned integer":
return {
"uint8": dtype(uint8),
"uint16": dtype(uint16),
"uint32": dtype(uint32),
"uint64": dtype(uint64),
}
if kind == "integral":
return {
"int8": dtype(int8),
"int16": dtype(int16),
"int32": dtype(int32),
"int64": dtype(int64),
"uint8": dtype(uint8),
"uint16": dtype(uint16),
"uint32": dtype(uint32),
"uint64": dtype(uint64),
}
if kind == "real floating":
return {
"float32": dtype(float32),
"float64": dtype(float64),
}
if kind == "complex floating":
return {
"complex64": dtype(complex64),
"complex128": dtype(complex128),
}
if kind == "numeric":
return {
"int8": dtype(int8),
"int16": dtype(int16),
"int32": dtype(int32),
"int64": dtype(int64),
"uint8": dtype(uint8),
"uint16": dtype(uint16),
"uint32": dtype(uint32),
"uint64": dtype(uint64),
"float32": dtype(float32),
"float64": dtype(float64),
"complex64": dtype(complex64),
"complex128": dtype(complex128),
}
if isinstance(kind, tuple):
res = {}
for k in kind:
res.update(self.dtypes(kind=k))
return res
raise ValueError(f"unsupported kind: {kind!r}")
def devices(self):
"""
The devices supported by NumPy.
For NumPy, this always returns ``['cpu']``.
Returns
-------
devices : list of str
The devices supported by NumPy.
See Also
--------
__array_namespace_info__.capabilities,
__array_namespace_info__.default_device,
__array_namespace_info__.default_dtypes,
__array_namespace_info__.dtypes
Examples
--------
>>> info = np.__array_namespace_info__()
>>> info.devices()
['cpu']
"""
return ["cpu"]
@@ -1,207 +0,0 @@
from typing import (
ClassVar,
Literal,
Never,
TypeAlias,
TypedDict,
TypeVar,
final,
overload,
type_check_only,
)
import numpy as np
_Device: TypeAlias = Literal["cpu"]
_DeviceLike: TypeAlias = _Device | None
_Capabilities = TypedDict(
"_Capabilities",
{
"boolean indexing": Literal[True],
"data-dependent shapes": Literal[True],
},
)
_DefaultDTypes = TypedDict(
"_DefaultDTypes",
{
"real floating": np.dtype[np.float64],
"complex floating": np.dtype[np.complex128],
"integral": np.dtype[np.intp],
"indexing": np.dtype[np.intp],
},
)
_KindBool: TypeAlias = Literal["bool"]
_KindInt: TypeAlias = Literal["signed integer"]
_KindUInt: TypeAlias = Literal["unsigned integer"]
_KindInteger: TypeAlias = Literal["integral"]
_KindFloat: TypeAlias = Literal["real floating"]
_KindComplex: TypeAlias = Literal["complex floating"]
_KindNumber: TypeAlias = Literal["numeric"]
_Kind: TypeAlias = (
_KindBool
| _KindInt
| _KindUInt
| _KindInteger
| _KindFloat
| _KindComplex
| _KindNumber
)
_T1 = TypeVar("_T1")
_T2 = TypeVar("_T2")
_T3 = TypeVar("_T3")
_Permute1: TypeAlias = _T1 | tuple[_T1]
_Permute2: TypeAlias = tuple[_T1, _T2] | tuple[_T2, _T1]
_Permute3: TypeAlias = (
tuple[_T1, _T2, _T3] | tuple[_T1, _T3, _T2]
| tuple[_T2, _T1, _T3] | tuple[_T2, _T3, _T1]
| tuple[_T3, _T1, _T2] | tuple[_T3, _T2, _T1]
)
@type_check_only
class _DTypesBool(TypedDict):
bool: np.dtype[np.bool]
@type_check_only
class _DTypesInt(TypedDict):
int8: np.dtype[np.int8]
int16: np.dtype[np.int16]
int32: np.dtype[np.int32]
int64: np.dtype[np.int64]
@type_check_only
class _DTypesUInt(TypedDict):
uint8: np.dtype[np.uint8]
uint16: np.dtype[np.uint16]
uint32: np.dtype[np.uint32]
uint64: np.dtype[np.uint64]
@type_check_only
class _DTypesInteger(_DTypesInt, _DTypesUInt): ...
@type_check_only
class _DTypesFloat(TypedDict):
float32: np.dtype[np.float32]
float64: np.dtype[np.float64]
@type_check_only
class _DTypesComplex(TypedDict):
complex64: np.dtype[np.complex64]
complex128: np.dtype[np.complex128]
@type_check_only
class _DTypesNumber(_DTypesInteger, _DTypesFloat, _DTypesComplex): ...
@type_check_only
class _DTypes(_DTypesBool, _DTypesNumber): ...
@type_check_only
class _DTypesUnion(TypedDict, total=False):
bool: np.dtype[np.bool]
int8: np.dtype[np.int8]
int16: np.dtype[np.int16]
int32: np.dtype[np.int32]
int64: np.dtype[np.int64]
uint8: np.dtype[np.uint8]
uint16: np.dtype[np.uint16]
uint32: np.dtype[np.uint32]
uint64: np.dtype[np.uint64]
float32: np.dtype[np.float32]
float64: np.dtype[np.float64]
complex64: np.dtype[np.complex64]
complex128: np.dtype[np.complex128]
_EmptyDict: TypeAlias = dict[Never, Never]
@final
class __array_namespace_info__:
__module__: ClassVar[Literal['numpy']]
def capabilities(self) -> _Capabilities: ...
def default_device(self) -> _Device: ...
def default_dtypes(
self,
*,
device: _DeviceLike = ...,
) -> _DefaultDTypes: ...
def devices(self) -> list[_Device]: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: None = ...,
) -> _DTypes: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: _Permute1[_KindBool],
) -> _DTypesBool: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: _Permute1[_KindInt],
) -> _DTypesInt: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: _Permute1[_KindUInt],
) -> _DTypesUInt: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: _Permute1[_KindFloat],
) -> _DTypesFloat: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: _Permute1[_KindComplex],
) -> _DTypesComplex: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: (
_Permute1[_KindInteger]
| _Permute2[_KindInt, _KindUInt]
),
) -> _DTypesInteger: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: (
_Permute1[_KindNumber]
| _Permute3[_KindInteger, _KindFloat, _KindComplex]
),
) -> _DTypesNumber: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: tuple[()],
) -> _EmptyDict: ...
@overload
def dtypes(
self,
*,
device: _DeviceLike = ...,
kind: tuple[_Kind, ...],
) -> _DTypesUnion: ...
@@ -1,39 +0,0 @@
import argparse
import sys
from pathlib import Path
from .lib._utils_impl import get_include
from .version import __version__
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument(
"--version",
action="version",
version=__version__,
help="Print the version and exit.",
)
parser.add_argument(
"--cflags",
action="store_true",
help="Compile flag needed when using the NumPy headers.",
)
parser.add_argument(
"--pkgconfigdir",
action="store_true",
help=("Print the pkgconfig directory in which `numpy.pc` is stored "
"(useful for setting $PKG_CONFIG_PATH)."),
)
args = parser.parse_args()
if not sys.argv[1:]:
parser.print_help()
if args.cflags:
print("-I" + get_include())
if args.pkgconfigdir:
_path = Path(get_include()) / '..' / 'lib' / 'pkgconfig'
print(_path.resolve())
if __name__ == "__main__":
main()
@@ -1 +0,0 @@
def main() -> None: ...
@@ -1,186 +0,0 @@
"""
Contains the core of NumPy: ndarray, ufuncs, dtypes, etc.
Please note that this module is private. All functions and objects
are available in the main ``numpy`` namespace - use that instead.
"""
import os
from numpy.version import version as __version__
# disables OpenBLAS affinity setting of the main thread that limits
# python threads or processes to one core
env_added = []
for envkey in ['OPENBLAS_MAIN_FREE', 'GOTOBLAS_MAIN_FREE']:
if envkey not in os.environ:
os.environ[envkey] = '1'
env_added.append(envkey)
try:
from . import multiarray
except ImportError as exc:
import sys
msg = """
IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
Importing the numpy C-extensions failed. This error can happen for
many reasons, often due to issues with your setup or how NumPy was
installed.
We have compiled some common reasons and troubleshooting tips at:
https://numpy.org/devdocs/user/troubleshooting-importerror.html
Please note and check the following:
* The Python version is: Python%d.%d from "%s"
* The NumPy version is: "%s"
and make sure that they are the versions you expect.
Please carefully study the documentation linked above for further help.
Original error was: %s
""" % (sys.version_info[0], sys.version_info[1], sys.executable,
__version__, exc)
raise ImportError(msg) from exc
finally:
for envkey in env_added:
del os.environ[envkey]
del envkey
del env_added
del os
from . import umath
# Check that multiarray,umath are pure python modules wrapping
# _multiarray_umath and not either of the old c-extension modules
if not (hasattr(multiarray, '_multiarray_umath') and
hasattr(umath, '_multiarray_umath')):
import sys
path = sys.modules['numpy'].__path__
msg = ("Something is wrong with the numpy installation. "
"While importing we detected an older version of "
"numpy in {}. One method of fixing this is to repeatedly uninstall "
"numpy until none is found, then reinstall this version.")
raise ImportError(msg.format(path))
from . import numerictypes as nt
from .numerictypes import sctypeDict, sctypes
multiarray.set_typeDict(nt.sctypeDict)
from . import (
_machar,
einsumfunc,
fromnumeric,
function_base,
getlimits,
numeric,
shape_base,
)
from .einsumfunc import *
from .fromnumeric import *
from .function_base import *
from .getlimits import *
# Note: module name memmap is overwritten by a class with same name
from .memmap import *
from .numeric import *
from .records import recarray, record
from .shape_base import *
del nt
# do this after everything else, to minimize the chance of this misleadingly
# appearing in an import-time traceback
# add these for module-freeze analysis (like PyInstaller)
from . import (
_add_newdocs,
_add_newdocs_scalars,
_dtype,
_dtype_ctypes,
_internal,
_methods,
)
from .numeric import absolute as abs
acos = numeric.arccos
acosh = numeric.arccosh
asin = numeric.arcsin
asinh = numeric.arcsinh
atan = numeric.arctan
atanh = numeric.arctanh
atan2 = numeric.arctan2
concat = numeric.concatenate
bitwise_left_shift = numeric.left_shift
bitwise_invert = numeric.invert
bitwise_right_shift = numeric.right_shift
permute_dims = numeric.transpose
pow = numeric.power
__all__ = [
"abs", "acos", "acosh", "asin", "asinh", "atan", "atanh", "atan2",
"bitwise_invert", "bitwise_left_shift", "bitwise_right_shift", "concat",
"pow", "permute_dims", "memmap", "sctypeDict", "record", "recarray"
]
__all__ += numeric.__all__
__all__ += function_base.__all__
__all__ += getlimits.__all__
__all__ += shape_base.__all__
__all__ += einsumfunc.__all__
def _ufunc_reduce(func):
# Report the `__name__`. pickle will try to find the module. Note that
# pickle supports for this `__name__` to be a `__qualname__`. It may
# make sense to add a `__qualname__` to ufuncs, to allow this more
# explicitly (Numba has ufuncs as attributes).
# See also: https://github.com/dask/distributed/issues/3450
return func.__name__
def _DType_reconstruct(scalar_type):
# This is a work-around to pickle type(np.dtype(np.float64)), etc.
# and it should eventually be replaced with a better solution, e.g. when
# DTypes become HeapTypes.
return type(dtype(scalar_type))
def _DType_reduce(DType):
# As types/classes, most DTypes can simply be pickled by their name:
if not DType._legacy or DType.__module__ == "numpy.dtypes":
return DType.__name__
# However, user defined legacy dtypes (like rational) do not end up in
# `numpy.dtypes` as module and do not have a public class at all.
# For these, we pickle them by reconstructing them from the scalar type:
scalar_type = DType.type
return _DType_reconstruct, (scalar_type,)
def __getattr__(name):
# Deprecated 2022-11-22, NumPy 1.25.
if name == "MachAr":
import warnings
warnings.warn(
"The `np._core.MachAr` is considered private API (NumPy 1.24)",
DeprecationWarning, stacklevel=2,
)
return _machar.MachAr
raise AttributeError(f"Module {__name__!r} has no attribute {name!r}")
import copyreg
copyreg.pickle(ufunc, _ufunc_reduce)
copyreg.pickle(type(dtype), _DType_reduce, _DType_reconstruct)
# Unclutter namespace (must keep _*_reconstruct for unpickling)
del copyreg, _ufunc_reduce, _DType_reduce
from numpy._pytesttester import PytestTester
test = PytestTester(__name__)
del PytestTester
@@ -1,2 +0,0 @@
# NOTE: The `np._core` namespace is deliberately kept empty due to it
# being private

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