from __future__ import annotations

import contextlib
from typing import TYPE_CHECKING, overload

from polars import functions as F
from polars._utils.parse import parse_into_expression
from polars._utils.wrap import wrap_expr
from polars.functions.range._utils import parse_interval_argument

with contextlib.suppress(ImportError):  # Module not available when building docs
    import polars.polars as plr

if TYPE_CHECKING:
    from datetime import date, datetime, timedelta
    from typing import Literal

    from polars import Expr, Series
    from polars._typing import ClosedInterval, IntoExprColumn, TimeUnit


@overload
def datetime_range(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = ...,
    *,
    closed: ClosedInterval = ...,
    time_unit: TimeUnit | None = ...,
    time_zone: str | None = ...,
    eager: Literal[False] = ...,
) -> Expr: ...


@overload
def datetime_range(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = ...,
    *,
    closed: ClosedInterval = ...,
    time_unit: TimeUnit | None = ...,
    time_zone: str | None = ...,
    eager: Literal[True],
) -> Series: ...


@overload
def datetime_range(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = ...,
    *,
    closed: ClosedInterval = ...,
    time_unit: TimeUnit | None = ...,
    time_zone: str | None = ...,
    eager: bool,
) -> Series | Expr: ...


def datetime_range(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = "1d",
    *,
    closed: ClosedInterval = "both",
    time_unit: TimeUnit | None = None,
    time_zone: str | None = None,
    eager: bool = False,
) -> Series | Expr:
    """
    Generate a datetime range.

    Parameters
    ----------
    start
        Lower bound of the datetime range.
    end
        Upper bound of the datetime range.
    interval
        Interval of the range periods, specified as a Python `timedelta` object
        or using the Polars duration string language (see "Notes" section below).
    closed : {'both', 'left', 'right', 'none'}
        Define which sides of the range are closed (inclusive).
    time_unit : {None, 'ns', 'us', 'ms'}
        Time unit of the resulting `Datetime` data type.
    time_zone
        Time zone of the resulting `Datetime` data type.
    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:`Datetime`.

    See Also
    --------
    datetime_ranges
    date_range

    Notes
    -----
    `interval` is created according to the following string language:

    - 1ns   (1 nanosecond)
    - 1us   (1 microsecond)
    - 1ms   (1 millisecond)
    - 1s    (1 second)
    - 1m    (1 minute)
    - 1h    (1 hour)
    - 1d    (1 calendar day)
    - 1w    (1 calendar week)
    - 1mo   (1 calendar month)
    - 1q    (1 calendar quarter)
    - 1y    (1 calendar year)

    Or combine them:
    "3d12h4m25s" # 3 days, 12 hours, 4 minutes, and 25 seconds

    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 datetime
    >>> pl.datetime_range(
    ...     datetime(2022, 1, 1), datetime(2022, 3, 1), "1mo", eager=True
    ... ).alias("datetime")
    shape: (3,)
    Series: 'datetime' [datetime[μs]]
    [
        2022-01-01 00:00:00
        2022-02-01 00:00:00
        2022-03-01 00:00:00
    ]

    Using `timedelta` object to specify the interval:

    >>> from datetime import date, timedelta
    >>> pl.datetime_range(
    ...     date(1985, 1, 1),
    ...     date(1985, 1, 10),
    ...     timedelta(days=1, hours=12),
    ...     time_unit="ms",
    ...     eager=True,
    ... ).alias("datetime")
    shape: (7,)
    Series: 'datetime' [datetime[ms]]
    [
        1985-01-01 00:00:00
        1985-01-02 12:00:00
        1985-01-04 00:00:00
        1985-01-05 12:00:00
        1985-01-07 00:00:00
        1985-01-08 12:00:00
        1985-01-10 00:00:00
    ]

    Specifying a time zone:

    >>> pl.datetime_range(
    ...     datetime(2022, 1, 1),
    ...     datetime(2022, 3, 1),
    ...     "1mo",
    ...     time_zone="America/New_York",
    ...     eager=True,
    ... ).alias("datetime")
    shape: (3,)
    Series: 'datetime' [datetime[μs, America/New_York]]
    [
        2022-01-01 00:00:00 EST
        2022-02-01 00:00:00 EST
        2022-03-01 00:00:00 EST
    ]

    Omit `eager=True` if you want to use `datetime_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.datetime_range(pl.col("date").min(), pl.col("date").max()))
    ...     .sort("key")
    ... )
    >>> with pl.Config(fmt_str_lengths=70):
    ...     print(result)
    shape: (2, 2)
    ┌─────┬─────────────────────────────────────────────────────────────────┐
    │ key ┆ date                                                            │
    │ --- ┆ ---                                                             │
    │ str ┆ list[datetime[μs]]                                              │
    ╞═════╪═════════════════════════════════════════════════════════════════╡
    │ one ┆ [2024-01-01 00:00:00, 2024-01-02 00:00:00]                      │
    │ two ┆ [2024-01-01 00:00:00, 2024-01-02 00:00:00, 2024-01-03 00:00:00] │
    └─────┴─────────────────────────────────────────────────────────────────┘
    """
    interval = parse_interval_argument(interval)
    if time_unit is None and "ns" in interval:
        time_unit = "ns"

    start_pyexpr = parse_into_expression(start)
    end_pyexpr = parse_into_expression(end)
    result = wrap_expr(
        plr.datetime_range(
            start_pyexpr, end_pyexpr, interval, closed, time_unit, time_zone
        )
    )

    if eager:
        return F.select(result).to_series()

    return result


@overload
def datetime_ranges(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = ...,
    *,
    closed: ClosedInterval = ...,
    time_unit: TimeUnit | None = ...,
    time_zone: str | None = ...,
    eager: Literal[False] = ...,
) -> Expr: ...


@overload
def datetime_ranges(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = ...,
    *,
    closed: ClosedInterval = ...,
    time_unit: TimeUnit | None = ...,
    time_zone: str | None = ...,
    eager: Literal[True],
) -> Series: ...


@overload
def datetime_ranges(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = ...,
    *,
    closed: ClosedInterval = ...,
    time_unit: TimeUnit | None = ...,
    time_zone: str | None = ...,
    eager: bool,
) -> Series | Expr: ...


def datetime_ranges(
    start: datetime | date | IntoExprColumn,
    end: datetime | date | IntoExprColumn,
    interval: str | timedelta = "1d",
    *,
    closed: ClosedInterval = "both",
    time_unit: TimeUnit | None = None,
    time_zone: str | None = None,
    eager: bool = False,
) -> Series | Expr:
    """
    Create a column of datetime ranges.

    Parameters
    ----------
    start
        Lower bound of the datetime range.
    end
        Upper bound of the datetime range.
    interval
        Interval of the range periods, specified as a Python `timedelta` object
        or using the Polars duration string language (see "Notes" section below).
    closed : {'both', 'left', 'right', 'none'}
        Define which sides of the range are closed (inclusive).
    time_unit : {None, 'ns', 'us', 'ms'}
        Time unit of the resulting `Datetime` data type.
    time_zone
        Time zone of the resulting `Datetime` data type.
    eager
        Evaluate immediately and return a `Series`.
        If set to `False` (default), return an expression instead.

    Notes
    -----
    `interval` is created according to the following string language:

    - 1ns   (1 nanosecond)
    - 1us   (1 microsecond)
    - 1ms   (1 millisecond)
    - 1s    (1 second)
    - 1m    (1 minute)
    - 1h    (1 hour)
    - 1d    (1 calendar day)
    - 1w    (1 calendar week)
    - 1mo   (1 calendar month)
    - 1q    (1 calendar quarter)
    - 1y    (1 calendar year)

    Or combine them:
    "3d12h4m25s" # 3 days, 12 hours, 4 minutes, and 25 seconds

    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".

    Returns
    -------
    Expr or Series
        Column of data type `List(Datetime)`.

    See Also
    --------
    datetime_range
    date_ranges

    Examples
    --------
    >>> from datetime import datetime
    >>> df = pl.DataFrame(
    ...     {
    ...         "start": [datetime(2022, 1, 1), datetime(2022, 1, 2)],
    ...         "end": datetime(2022, 1, 3),
    ...     }
    ... )
    >>> with pl.Config(fmt_str_lengths=100):
    ...     df.select(datetime_range=pl.datetime_ranges("start", "end"))
    shape: (2, 1)
    ┌─────────────────────────────────────────────────────────────────┐
    │ datetime_range                                                  │
    │ ---                                                             │
    │ list[datetime[μs]]                                              │
    ╞═════════════════════════════════════════════════════════════════╡
    │ [2022-01-01 00:00:00, 2022-01-02 00:00:00, 2022-01-03 00:00:00] │
    │ [2022-01-02 00:00:00, 2022-01-03 00:00:00]                      │
    └─────────────────────────────────────────────────────────────────┘
    """
    interval = parse_interval_argument(interval)
    if time_unit is None and "ns" in interval:
        time_unit = "ns"

    start_pyexpr = parse_into_expression(start)
    end_pyexpr = parse_into_expression(end)

    result = wrap_expr(
        plr.datetime_ranges(
            start_pyexpr, end_pyexpr, interval, closed, time_unit, time_zone
        )
    )

    if eager:
        return F.select(result).to_series()

    return result