155 lines
4.8 KiB
Python
155 lines
4.8 KiB
Python
from __future__ import annotations
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from datetime import (
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datetime,
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time,
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)
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import numpy as np
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from pandas._libs.lib import is_list_like
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from pandas._typing import DateTimeErrorChoices
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from pandas.core.dtypes.generic import (
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ABCIndex,
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ABCSeries,
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)
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from pandas.core.dtypes.missing import notna
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def to_time(
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arg,
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format=None,
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infer_time_format: bool = False,
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errors: DateTimeErrorChoices = "raise",
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):
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"""
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Parse time strings to time objects using fixed strptime formats ("%H:%M",
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"%H%M", "%I:%M%p", "%I%M%p", "%H:%M:%S", "%H%M%S", "%I:%M:%S%p",
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"%I%M%S%p")
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Use infer_time_format if all the strings are in the same format to speed
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up conversion.
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Parameters
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----------
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arg : string in time format, datetime.time, list, tuple, 1-d array, Series
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format : str, default None
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Format used to convert arg into a time object. If None, fixed formats
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are used.
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infer_time_format: bool, default False
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Infer the time format based on the first non-NaN element. If all
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strings are in the same format, this will speed up conversion.
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errors : {'ignore', 'raise', 'coerce'}, default 'raise'
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- If 'raise', then invalid parsing will raise an exception
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- If 'coerce', then invalid parsing will be set as None
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- If 'ignore', then invalid parsing will return the input
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Returns
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-------
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datetime.time
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"""
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def _convert_listlike(arg, format):
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if isinstance(arg, (list, tuple)):
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arg = np.array(arg, dtype="O")
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elif getattr(arg, "ndim", 1) > 1:
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raise TypeError(
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"arg must be a string, datetime, list, tuple, 1-d array, or Series"
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)
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arg = np.asarray(arg, dtype="O")
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if infer_time_format and format is None:
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format = _guess_time_format_for_array(arg)
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times: list[time | None] = []
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if format is not None:
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for element in arg:
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try:
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times.append(datetime.strptime(element, format).time())
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except (ValueError, TypeError) as err:
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if errors == "raise":
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msg = (
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f"Cannot convert {element} to a time with given "
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f"format {format}"
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)
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raise ValueError(msg) from err
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if errors == "ignore":
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return arg
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else:
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times.append(None)
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else:
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formats = _time_formats[:]
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format_found = False
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for element in arg:
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time_object = None
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try:
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time_object = time.fromisoformat(element)
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except (ValueError, TypeError):
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for time_format in formats:
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try:
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time_object = datetime.strptime(element, time_format).time()
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if not format_found:
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# Put the found format in front
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fmt = formats.pop(formats.index(time_format))
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formats.insert(0, fmt)
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format_found = True
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break
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except (ValueError, TypeError):
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continue
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if time_object is not None:
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times.append(time_object)
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elif errors == "raise":
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raise ValueError(f"Cannot convert arg {arg} to a time")
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elif errors == "ignore":
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return arg
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else:
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times.append(None)
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return times
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if arg is None:
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return arg
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elif isinstance(arg, time):
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return arg
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elif isinstance(arg, ABCSeries):
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values = _convert_listlike(arg._values, format)
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return arg._constructor(values, index=arg.index, name=arg.name)
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elif isinstance(arg, ABCIndex):
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return _convert_listlike(arg, format)
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elif is_list_like(arg):
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return _convert_listlike(arg, format)
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return _convert_listlike(np.array([arg]), format)[0]
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# Fixed time formats for time parsing
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_time_formats = [
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"%H:%M",
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"%H%M",
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"%I:%M%p",
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"%I%M%p",
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"%H:%M:%S",
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"%H%M%S",
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"%I:%M:%S%p",
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"%I%M%S%p",
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]
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def _guess_time_format_for_array(arr):
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# Try to guess the format based on the first non-NaN element
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non_nan_elements = notna(arr).nonzero()[0]
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if len(non_nan_elements):
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element = arr[non_nan_elements[0]]
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for time_format in _time_formats:
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try:
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datetime.strptime(element, time_format)
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return time_format
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except ValueError:
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pass
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return None
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