h#SSKJr SSKrSSKJrJr SSKJr SSK J r SSK J r SSK Jr \R"\5 SSKJr SSS5 \(a SSKJrJrJr SS KJr SS KJrJr SS KJrJr \SS S S .SSjjj5r\SS S.SSjjj5r\SS S.SSjjj5rSSSS .SSjjjr\SS S S .SSjjj5r\SS S.SSjjj5r\SS S.SSjjj5rSSSS .SSjjjrg!,(df  GN=f)) annotationsN) TYPE_CHECKINGoverload) functions)parse_into_expression) wrap_expr)parse_interval_argument)datedatetime timedelta)Literal)ExprSeries)ClosedIntervalIntoExprColumn.)closedeagercgNstartendintervalrrs [/home/james-whalen/.local/lib/python3.13/site-packages/polars/functions/range/date_range.py date_ranger )rcgrrrs rrr!rcgrrrs rrr,rbothFc[U5n[U5n[U5n[[R"XVX#55nU(a$[ R "U5R5$U$)u Generate a date range. Parameters ---------- start Lower bound of the date range. end Upper bound of the date range. interval Interval of the range periods, specified as a Python `timedelta` object or using the Polars duration string language (see "Notes" section below). Must consist of full days. closed : {'both', 'left', 'right', 'none'} Define which sides of the range are closed (inclusive). eager Evaluate immediately and return a `Series`. If set to `False` (default), return an expression instead. Returns ------- Expr or Series Column of data type :class:`Date`. See Also -------- date_ranges datetime_range Notes ----- `interval` is created according to the following string language: - 1d (1 calendar day) - 1w (1 calendar week) - 1mo (1 calendar month) - 1q (1 calendar quarter) - 1y (1 calendar year) Or combine them: "1w2d" # 1 week, 2 days By "calendar day", we mean the corresponding time on the next day (which may not be 24 hours, due to daylight savings). Similarly for "calendar week", "calendar month", "calendar quarter", and "calendar year". Examples -------- Using Polars duration string to specify the interval: >>> from datetime import date >>> pl.date_range(date(2022, 1, 1), date(2022, 3, 1), "1mo", eager=True).alias( ... "date" ... ) shape: (3,) Series: 'date' [date] [ 2022-01-01 2022-02-01 2022-03-01 ] Using `timedelta` object to specify the interval: >>> from datetime import timedelta >>> pl.date_range( ... date(1985, 1, 1), ... date(1985, 1, 10), ... timedelta(days=2), ... eager=True, ... ).alias("date") shape: (5,) Series: 'date' [date] [ 1985-01-01 1985-01-03 1985-01-05 1985-01-07 1985-01-09 ] Omit `eager=True` if you want to use `date_range` as an expression: >>> df = pl.DataFrame( ... { ... "date": [ ... date(2024, 1, 1), ... date(2024, 1, 2), ... date(2024, 1, 1), ... date(2024, 1, 3), ... ], ... "key": ["one", "one", "two", "two"], ... } ... ) >>> result = ( ... df.group_by("key") ... .agg(pl.date_range(pl.col("date").min(), pl.col("date").max())) ... .sort("key") ... ) >>> with pl.Config(fmt_str_lengths=50): ... print(result) shape: (2, 2) ┌─────┬──────────────────────────────────────┐ │ key ┆ date │ │ --- ┆ --- │ │ str ┆ list[date] │ ╞═════╪══════════════════════════════════════╡ │ one ┆ [2024-01-01, 2024-01-02] │ │ two ┆ [2024-01-01, 2024-01-02, 2024-01-03] │ └─────┴──────────────────────────────────────┘ )r rrplrrFselect to_seriesrrrrr start_pyexpr end_pyexprresults rrr7sXn'x0H(/L&s+J s~~lQ RF xx))++ Mrcgrrrs r date_rangesr.rrcgrrrs rr.r.r rcgrrrs rr.r.r"rc[U5n[U5n[U5n[[R"XVX#55nU(a$[ R "U5R5$U$)us Create a column of date ranges. Parameters ---------- start Lower bound of the date range. end Upper bound of the date range. interval Interval of the range periods, specified as a Python `timedelta` object or using the Polars duration string language (see "Notes" section below). Must consist of full days. closed : {'both', 'left', 'right', 'none'} Define which sides of the range are closed (inclusive). eager Evaluate immediately and return a `Series`. If set to `False` (default), return an expression instead. Returns ------- Expr or Series Column of data type `List(Date)`. See Also -------- date_range datetime_ranges Notes ----- `interval` is created according to the following string language: - 1d (1 calendar day) - 1w (1 calendar week) - 1mo (1 calendar month) - 1q (1 calendar quarter) - 1y (1 calendar year) Or combine them: "1w2d" # 1 week, 2 days By "calendar day", we mean the corresponding time on the next day (which may not be 24 hours, due to daylight savings). Similarly for "calendar week", "calendar month", "calendar quarter", and "calendar year". Examples -------- >>> from datetime import date >>> df = pl.DataFrame( ... { ... "start": [date(2022, 1, 1), date(2022, 1, 2)], ... "end": date(2022, 1, 3), ... } ... ) >>> with pl.Config(fmt_str_lengths=50): ... df.with_columns(date_range=pl.date_ranges("start", "end")) shape: (2, 3) ┌────────────┬────────────┬──────────────────────────────────────┐ │ start ┆ end ┆ date_range │ │ --- ┆ --- ┆ --- │ │ date ┆ date ┆ list[date] │ ╞════════════╪════════════╪══════════════════════════════════════╡ │ 2022-01-01 ┆ 2022-01-03 ┆ [2022-01-01, 2022-01-02, 2022-01-03] │ │ 2022-01-02 ┆ 2022-01-03 ┆ [2022-01-02, 2022-01-03] │ └────────────┴────────────┴──────────────────────────────────────┘ )r rrr%r.r&r'r(r)s rr.r.sXV'x0H(/L&s+J s|R SF xx))++ Mr).) r date | datetime | IntoExprColumnrr2rstr | timedeltarrrzLiteral[False]returnr) rr2rr2rr3rrrz Literal[True]r4r) rr2rr2rr3rrrboolr4z Series | Expr)1d) __future__r contextlibtypingrrpolarsrr&polars._utils.parserpolars._utils.wraprpolars.functions.range._utilsr suppress ImportError polars._plr_plrr%r r r r rrpolars._typingrrrr.rrrrCs%"*!5(A%&22#= !$ !  + )       !$ !  + )       !$ !  + )     !%@ $ @ +@ )@@  @  @@F !$ !  + )       !$ !  + )       !$ !  + )     !%T $ T +T )TT  T  TTa&%s E E