Source code for bigframes.operations.datetimes

# Copyright 2023 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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from __future__ import annotations

import datetime as dt
from typing import Optional

import bigframes_vendored.pandas.core.arrays.datetimelike as vendored_pandas_datetimelike
import bigframes_vendored.pandas.core.indexes.accessor as vendordt
import pandas

from bigframes import dataframe, dtypes, series
from bigframes.core import log_adapter
import bigframes.operations as ops

_ONE_DAY = pandas.Timedelta("1D")
_ONE_SECOND = pandas.Timedelta("1s")
_ONE_MICRO = pandas.Timedelta("1us")
_SUPPORTED_FREQS = ("Y", "Q", "M", "W", "D", "h", "min", "s", "ms", "us")


[docs] @log_adapter.class_logger class DatetimeMethods( vendordt.DatetimeProperties, vendored_pandas_datetimelike.DatelikeOps, ): __doc__ = vendordt.DatetimeProperties.__doc__
[docs] def __init__(self, data: series.Series): self._data = data
# Date accessors @property def day(self) -> series.Series: return self._data._apply_unary_op(ops.day_op) @property def dayofweek(self) -> series.Series: return self._data._apply_unary_op(ops.dayofweek_op) @property def day_of_week(self) -> series.Series: return self.dayofweek @property def weekday(self) -> series.Series: return self.dayofweek @property def dayofyear(self) -> series.Series: return self._data._apply_unary_op(ops.dayofyear_op) @property def day_of_year(self) -> series.Series: return self.dayofyear @property def date(self) -> series.Series: return self._data._apply_unary_op(ops.date_op) @property def quarter(self) -> series.Series: return self._data._apply_unary_op(ops.quarter_op) @property def year(self) -> series.Series: return self._data._apply_unary_op(ops.year_op) @property def month(self) -> series.Series: return self._data._apply_unary_op(ops.month_op)
[docs] def isocalendar(self) -> dataframe.DataFrame: iso_ops = [ops.iso_year_op, ops.iso_week_op, ops.iso_day_op] labels = pandas.Index(["year", "week", "day"]) block = self._data._block.project_exprs( [op.as_expr(self._data._value_column) for op in iso_ops], labels, drop=True ) return dataframe.DataFrame(block)
# Time accessors @property def hour(self) -> series.Series: return self._data._apply_unary_op(ops.hour_op) @property def minute(self) -> series.Series: return self._data._apply_unary_op(ops.minute_op) @property def second(self) -> series.Series: return self._data._apply_unary_op(ops.second_op) @property def time(self) -> series.Series: return self._data._apply_unary_op(ops.time_op) # Timedelta accessors @property def days(self) -> series.Series: self._check_dtype(dtypes.TIMEDELTA_DTYPE) return self._data._apply_binary_op(_ONE_DAY, ops.floordiv_op) @property def seconds(self) -> series.Series: self._check_dtype(dtypes.TIMEDELTA_DTYPE) return self._data._apply_binary_op(_ONE_DAY, ops.mod_op) // _ONE_SECOND # type: ignore @property def microseconds(self) -> series.Series: self._check_dtype(dtypes.TIMEDELTA_DTYPE) return self._data._apply_binary_op(_ONE_SECOND, ops.mod_op) // _ONE_MICRO # type: ignore
[docs] def total_seconds(self) -> series.Series: self._check_dtype(dtypes.TIMEDELTA_DTYPE) return self._data._apply_binary_op(_ONE_SECOND, ops.div_op)
def _check_dtype(self, target_dtype: dtypes.Dtype): if self._data._dtype == target_dtype: return raise TypeError(f"Expect dtype: {target_dtype}, but got {self._data._dtype}") @property def tz(self) -> Optional[dt.timezone]: # Assumption: pyarrow dtype tz_string = self._data._dtype.pyarrow_dtype.tz if tz_string == "UTC": return dt.timezone.utc elif tz_string is None: return None else: raise ValueError(f"Unexpected timezone {tz_string}") @property def unit(self) -> str: # Assumption: pyarrow dtype return self._data._dtype.pyarrow_dtype.unit
[docs] def day_name(self) -> series.Series: return self.strftime("%A")
[docs] def strftime(self, date_format: str) -> series.Series: return self._data._apply_unary_op(ops.StrftimeOp(date_format=date_format))
[docs] def normalize(self) -> series.Series: return self._data._apply_unary_op(ops.normalize_op)
[docs] def floor(self, freq: str) -> series.Series: if freq not in _SUPPORTED_FREQS: raise ValueError(f"freq must be one of {_SUPPORTED_FREQS}") return self._data._apply_unary_op(ops.FloorDtOp(freq=freq)) # type: ignore