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"""Dataframe exchange protocol tests that are specific for pandas storage format implementation."""

import pandas

import modin.pandas as pd
from modin.pandas.utils import from_dataframe
from modin.tests.pandas.utils import df_equals, test_data
from modin.tests.test_utils import warns_that_defaulting_to_pandas


def eval_df_protocol(modin_df_producer):
    internal_modin_df_producer = modin_df_producer.__dataframe__()
    # Our configuration in pytest.ini requires that we explicitly catch all
    # instances of defaulting to pandas, this one raises a warning on `.from_dataframe`
    with warns_that_defaulting_to_pandas():
        modin_df_consumer = from_dataframe(modin_df_producer)
        internal_modin_df_consumer = from_dataframe(internal_modin_df_producer)

    # TODO: the following assertions verify that `from_dataframe` doesn't return
    # the same object untouched due to optimization branching, it actually should
    # do so but the logic is not implemented yet, so the assertions are passing
    # for now. It's required to replace the producer's type with a different one
    # to consumer when we have some other implementation of the protocol as the
    # assertions may start failing shortly.
    assert modin_df_producer is not modin_df_consumer
    assert internal_modin_df_producer is not internal_modin_df_consumer
    assert (
        modin_df_producer._query_compiler._modin_frame
        is not modin_df_consumer._query_compiler._modin_frame
    )

    df_equals(modin_df_producer, modin_df_consumer)
    df_equals(modin_df_producer, internal_modin_df_consumer)


def test_simple_import():
    modin_df = pd.DataFrame(test_data["int_data"])
    eval_df_protocol(modin_df)


def test_categorical_from_dataframe():
    modin_df = pd.DataFrame(
        {"foo": pd.Series(["0", "1", "2", "3", "0", "3", "2", "3"], dtype="category")}
    )
    eval_df_protocol(modin_df)


def test_from_dataframe_with_empty_dataframe():
    modin_df = pd.DataFrame({"foo_col": pd.Series([], dtype="int64")})
    with warns_that_defaulting_to_pandas():
        eval_df_protocol(modin_df)


def test_interchange_with_pandas_string():
    modin_df = pd.DataFrame({"fips": ["01001"]})
    pandas_df = pandas.api.interchange.from_dataframe(modin_df.__dataframe__())
    df_equals(modin_df, pandas_df)
