# pandas / Polars / etc. : if a user passes a dataframe from one of these
# libraries, it means they must already have imported the given module.
# So, we can just check sys.modules.
from __future__ import annotations

import sys
from typing import TYPE_CHECKING
from typing import Any

if TYPE_CHECKING:
    import numpy as np

    if sys.version_info >= (3, 10):
        from typing import TypeGuard
    else:
        from typing_extensions import TypeGuard
    import cudf
    import dask.dataframe as dd
    import duckdb
    import ibis
    import modin.pandas as mpd
    import pandas as pd
    import polars as pl
    import pyarrow as pa

    from narwhals.typing import IntoSeries

# We silently allow these but - given that they claim
# to be drop-in replacements for pandas - testing is
# their responsibility.
IMPORT_HOOKS = frozenset(["fireducks"])


def get_polars() -> Any:
    """Get Polars module (if already imported - else return None)."""
    return sys.modules.get("polars", None)


def get_pandas() -> Any:
    """Get pandas module (if already imported - else return None)."""
    return sys.modules.get("pandas", None)


def get_modin() -> Any:  # pragma: no cover
    """Get modin.pandas module (if already imported - else return None)."""
    if (modin := sys.modules.get("modin", None)) is not None:
        return modin.pandas
    return None


def get_cudf() -> Any:
    """Get cudf module (if already imported - else return None)."""
    return sys.modules.get("cudf", None)


def get_cupy() -> Any:
    """Get cupy module (if already imported - else return None)."""
    return sys.modules.get("cupy", None)


def get_pyarrow() -> Any:  # pragma: no cover
    """Get pyarrow module (if already imported - else return None)."""
    return sys.modules.get("pyarrow", None)


def get_numpy() -> Any:
    """Get numpy module (if already imported - else return None)."""
    return sys.modules.get("numpy", None)


def get_dask() -> Any:
    """Get dask (if already imported - else return None)."""
    return sys.modules.get("dask", None)


def get_dask_dataframe() -> Any:
    """Get dask.dataframe module (if already imported - else return None)."""
    return sys.modules.get("dask.dataframe", None)


def get_duckdb() -> Any:
    """Get duckdb module (if already imported - else return None)."""
    return sys.modules.get("duckdb", None)


def get_dask_expr() -> Any:
    """Get dask_expr module (if already imported - else return None)."""
    return sys.modules.get("dask_expr", None)


def get_ibis() -> Any:
    """Get ibis module (if already imported - else return None)."""
    return sys.modules.get("ibis", None)


def is_pandas_dataframe(df: Any) -> TypeGuard[pd.DataFrame]:
    """Check whether `df` is a pandas DataFrame without importing pandas."""
    return ((pd := get_pandas()) is not None and isinstance(df, pd.DataFrame)) or any(
        (mod := sys.modules.get(module_name, None)) is not None
        and isinstance(df, mod.pandas.DataFrame)
        for module_name in IMPORT_HOOKS
    )


def is_pandas_series(ser: Any) -> TypeGuard[pd.Series[Any]]:
    """Check whether `ser` is a pandas Series without importing pandas."""
    return ((pd := get_pandas()) is not None and isinstance(ser, pd.Series)) or any(
        (mod := sys.modules.get(module_name, None)) is not None
        and isinstance(ser, mod.pandas.Series)
        for module_name in IMPORT_HOOKS
    )


def is_pandas_index(index: Any) -> TypeGuard[pd.Index]:
    """Check whether `index` is a pandas Index without importing pandas."""
    return ((pd := get_pandas()) is not None and isinstance(index, pd.Index)) or any(
        (mod := sys.modules.get(module_name, None)) is not None
        and isinstance(index, mod.pandas.Index)
        for module_name in IMPORT_HOOKS
    )


def is_modin_dataframe(df: Any) -> TypeGuard[mpd.DataFrame]:
    """Check whether `df` is a modin DataFrame without importing modin."""
    return (mpd := get_modin()) is not None and isinstance(df, mpd.DataFrame)


def is_modin_series(ser: Any) -> TypeGuard[mpd.Series]:
    """Check whether `ser` is a modin Series without importing modin."""
    return (mpd := get_modin()) is not None and isinstance(ser, mpd.Series)


def is_modin_index(index: Any) -> TypeGuard[mpd.Index]:
    """Check whether `index` is a modin Index without importing modin."""
    return (mpd := get_modin()) is not None and isinstance(
        index, mpd.Index
    )  # pragma: no cover


def is_cudf_dataframe(df: Any) -> TypeGuard[cudf.DataFrame]:
    """Check whether `df` is a cudf DataFrame without importing cudf."""
    return (cudf := get_cudf()) is not None and isinstance(df, cudf.DataFrame)


def is_cudf_series(ser: Any) -> TypeGuard[cudf.Series[Any]]:
    """Check whether `ser` is a cudf Series without importing cudf."""
    return (cudf := get_cudf()) is not None and isinstance(ser, cudf.Series)


def is_cudf_index(index: Any) -> TypeGuard[cudf.Index]:
    """Check whether `index` is a cudf Index without importing cudf."""
    return (cudf := get_cudf()) is not None and isinstance(
        index, cudf.Index
    )  # pragma: no cover


def is_dask_dataframe(df: Any) -> TypeGuard[dd.DataFrame]:
    """Check whether `df` is a Dask DataFrame without importing Dask."""
    return (dd := get_dask_dataframe()) is not None and isinstance(df, dd.DataFrame)


def is_duckdb_relation(df: Any) -> TypeGuard[duckdb.DuckDBPyRelation]:
    """Check whether `df` is a DuckDB Relation without importing DuckDB."""
    return (duckdb := get_duckdb()) is not None and isinstance(
        df, duckdb.DuckDBPyRelation
    )


def is_ibis_table(df: Any) -> TypeGuard[ibis.Table]:
    """Check whether `df` is a Ibis Table without importing Ibis."""
    return (ibis := get_ibis()) is not None and isinstance(df, ibis.expr.types.Table)


def is_polars_dataframe(df: Any) -> TypeGuard[pl.DataFrame]:
    """Check whether `df` is a Polars DataFrame without importing Polars."""
    return (pl := get_polars()) is not None and isinstance(df, pl.DataFrame)


def is_polars_lazyframe(df: Any) -> TypeGuard[pl.LazyFrame]:
    """Check whether `df` is a Polars LazyFrame without importing Polars."""
    return (pl := get_polars()) is not None and isinstance(df, pl.LazyFrame)


def is_polars_series(ser: Any) -> TypeGuard[pl.Series]:
    """Check whether `ser` is a Polars Series without importing Polars."""
    return (pl := get_polars()) is not None and isinstance(ser, pl.Series)


def is_pyarrow_chunked_array(ser: Any) -> TypeGuard[pa.ChunkedArray]:
    """Check whether `ser` is a PyArrow ChunkedArray without importing PyArrow."""
    return (pa := get_pyarrow()) is not None and isinstance(ser, pa.ChunkedArray)


def is_pyarrow_table(df: Any) -> TypeGuard[pa.Table]:
    """Check whether `df` is a PyArrow Table without importing PyArrow."""
    return (pa := get_pyarrow()) is not None and isinstance(df, pa.Table)


def is_numpy_array(arr: Any) -> TypeGuard[np.ndarray]:
    """Check whether `arr` is a NumPy Array without importing NumPy."""
    return (np := get_numpy()) is not None and isinstance(arr, np.ndarray)


def is_pandas_like_dataframe(df: Any) -> bool:
    """Check whether `df` is a pandas-like DataFrame without doing any imports.

    By "pandas-like", we mean: pandas, Modin, cuDF.
    """
    return is_pandas_dataframe(df) or is_modin_dataframe(df) or is_cudf_dataframe(df)


def is_pandas_like_series(ser: Any) -> bool:
    """Check whether `ser` is a pandas-like Series without doing any imports.

    By "pandas-like", we mean: pandas, Modin, cuDF.
    """
    return is_pandas_series(ser) or is_modin_series(ser) or is_cudf_series(ser)


def is_pandas_like_index(index: Any) -> bool:
    """Check whether `index` is a pandas-like Index without doing any imports.

    By "pandas-like", we mean: pandas, Modin, cuDF.
    """
    return (
        is_pandas_index(index) or is_modin_index(index) or is_cudf_index(index)
    )  # pragma: no cover


def is_into_series(native_series: IntoSeries) -> bool:
    """Check whether `native_series` can be converted to a Narwhals Series.

    Arguments:
        native_series: The object to check.

    Returns:
        `True` if `native_series` can be converted to a Narwhals Series, `False` otherwise.

    Examples:
        >>> import pandas as pd
        >>> import polars as pl
        >>> import numpy as np
        >>> import narwhals as nw

        >>> s_pd = pd.Series([1, 2, 3])
        >>> s_pl = pl.Series([1, 2, 3])
        >>> np_arr = np.array([1, 2, 3])

        >>> nw.dependencies.is_into_series(s_pd)
        True
        >>> nw.dependencies.is_into_series(s_pl)
        True
        >>> nw.dependencies.is_into_series(np_arr)
        False
    """
    from narwhals.series import Series

    return (
        isinstance(native_series, Series)
        or hasattr(native_series, "__narwhals_series__")
        or is_polars_series(native_series)
        or is_pyarrow_chunked_array(native_series)
        or is_pandas_like_series(native_series)
    )


def is_into_dataframe(native_dataframe: Any) -> bool:
    """Check whether `native_dataframe` can be converted to a Narwhals DataFrame.

    Arguments:
        native_dataframe: The object to check.

    Returns:
        `True` if `native_dataframe` can be converted to a Narwhals DataFrame, `False` otherwise.

    Examples:
        >>> import pandas as pd
        >>> import polars as pl
        >>> import numpy as np
        >>> from narwhals.dependencies import is_into_dataframe

        >>> df_pd = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
        >>> df_pl = pl.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
        >>> np_arr = np.array([[1, 4], [2, 5], [3, 6]])

        >>> is_into_dataframe(df_pd)
        True
        >>> is_into_dataframe(df_pl)
        True
        >>> is_into_dataframe(np_arr)
        False
    """
    from narwhals.dataframe import DataFrame

    return (
        isinstance(native_dataframe, DataFrame)
        or hasattr(native_dataframe, "__narwhals_dataframe__")
        or is_polars_dataframe(native_dataframe)
        or is_pyarrow_table(native_dataframe)
        or is_pandas_like_dataframe(native_dataframe)
    )


__all__ = [
    "get_cudf",
    "get_ibis",
    "get_modin",
    "get_numpy",
    "get_pandas",
    "get_polars",
    "get_pyarrow",
    "is_cudf_dataframe",
    "is_cudf_series",
    "is_dask_dataframe",
    "is_ibis_table",
    "is_into_dataframe",
    "is_into_series",
    "is_modin_dataframe",
    "is_modin_series",
    "is_numpy_array",
    "is_pandas_dataframe",
    "is_pandas_index",
    "is_pandas_like_dataframe",
    "is_pandas_like_series",
    "is_pandas_series",
    "is_polars_dataframe",
    "is_polars_lazyframe",
    "is_polars_series",
    "is_pyarrow_chunked_array",
    "is_pyarrow_table",
]