220 lines
5.2 KiB
Python
220 lines
5.2 KiB
Python
from __future__ import annotations
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from contextlib import contextmanager
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import os
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from pathlib import Path
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import tempfile
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from typing import (
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IO,
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Any,
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Generator,
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)
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import uuid
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from pandas._typing import (
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BaseBuffer,
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CompressionOptions,
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FilePath,
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)
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from pandas.compat import PYPY
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from pandas.errors import ChainedAssignmentError
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from pandas import set_option
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from pandas.io.common import get_handle
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@contextmanager
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def decompress_file(
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path: FilePath | BaseBuffer, compression: CompressionOptions
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) -> Generator[IO[bytes], None, None]:
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"""
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Open a compressed file and return a file object.
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Parameters
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----------
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path : str
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The path where the file is read from.
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compression : {'gzip', 'bz2', 'zip', 'xz', 'zstd', None}
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Name of the decompression to use
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Returns
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-------
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file object
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"""
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with get_handle(path, "rb", compression=compression, is_text=False) as handle:
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yield handle.handle
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@contextmanager
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def set_timezone(tz: str) -> Generator[None, None, None]:
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"""
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Context manager for temporarily setting a timezone.
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Parameters
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----------
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tz : str
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A string representing a valid timezone.
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Examples
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--------
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>>> from datetime import datetime
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>>> from dateutil.tz import tzlocal
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>>> tzlocal().tzname(datetime(2021, 1, 1)) # doctest: +SKIP
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'IST'
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>>> with set_timezone('US/Eastern'):
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... tzlocal().tzname(datetime(2021, 1, 1))
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...
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'EST'
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"""
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import time
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def setTZ(tz) -> None:
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if tz is None:
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try:
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del os.environ["TZ"]
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except KeyError:
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pass
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else:
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os.environ["TZ"] = tz
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time.tzset()
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orig_tz = os.environ.get("TZ")
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setTZ(tz)
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try:
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yield
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finally:
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setTZ(orig_tz)
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@contextmanager
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def ensure_clean(
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filename=None, return_filelike: bool = False, **kwargs: Any
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) -> Generator[Any, None, None]:
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"""
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Gets a temporary path and agrees to remove on close.
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This implementation does not use tempfile.mkstemp to avoid having a file handle.
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If the code using the returned path wants to delete the file itself, windows
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requires that no program has a file handle to it.
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Parameters
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----------
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filename : str (optional)
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suffix of the created file.
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return_filelike : bool (default False)
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if True, returns a file-like which is *always* cleaned. Necessary for
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savefig and other functions which want to append extensions.
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**kwargs
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Additional keywords are passed to open().
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"""
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folder = Path(tempfile.gettempdir())
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if filename is None:
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filename = ""
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filename = str(uuid.uuid4()) + filename
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path = folder / filename
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path.touch()
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handle_or_str: str | IO = str(path)
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if return_filelike:
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kwargs.setdefault("mode", "w+b")
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handle_or_str = open(path, **kwargs)
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try:
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yield handle_or_str
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finally:
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if not isinstance(handle_or_str, str):
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handle_or_str.close()
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if path.is_file():
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path.unlink()
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@contextmanager
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def ensure_safe_environment_variables() -> Generator[None, None, None]:
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"""
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Get a context manager to safely set environment variables
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All changes will be undone on close, hence environment variables set
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within this contextmanager will neither persist nor change global state.
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"""
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saved_environ = dict(os.environ)
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try:
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yield
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finally:
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os.environ.clear()
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os.environ.update(saved_environ)
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@contextmanager
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def with_csv_dialect(name, **kwargs) -> Generator[None, None, None]:
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"""
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Context manager to temporarily register a CSV dialect for parsing CSV.
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Parameters
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----------
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name : str
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The name of the dialect.
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kwargs : mapping
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The parameters for the dialect.
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Raises
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------
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ValueError : the name of the dialect conflicts with a builtin one.
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See Also
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--------
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csv : Python's CSV library.
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"""
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import csv
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_BUILTIN_DIALECTS = {"excel", "excel-tab", "unix"}
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if name in _BUILTIN_DIALECTS:
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raise ValueError("Cannot override builtin dialect.")
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csv.register_dialect(name, **kwargs)
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try:
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yield
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finally:
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csv.unregister_dialect(name)
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@contextmanager
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def use_numexpr(use, min_elements=None) -> Generator[None, None, None]:
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from pandas.core.computation import expressions as expr
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if min_elements is None:
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min_elements = expr._MIN_ELEMENTS
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olduse = expr.USE_NUMEXPR
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oldmin = expr._MIN_ELEMENTS
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set_option("compute.use_numexpr", use)
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expr._MIN_ELEMENTS = min_elements
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try:
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yield
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finally:
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expr._MIN_ELEMENTS = oldmin
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set_option("compute.use_numexpr", olduse)
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def raises_chained_assignment_error():
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if PYPY:
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from contextlib import nullcontext
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return nullcontext()
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else:
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from pandas._testing import assert_produces_warning
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return assert_produces_warning(
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ChainedAssignmentError,
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match=(
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"A value is trying to be set on a copy of a DataFrame or Series "
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"through chained assignment"
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),
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)
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