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import pandas as pd
import pytest

from src.utils import filter_models, search_table, filter_queries, select_columns, update_table_long_doc, get_iso_format_timestamp, get_default_cols


@pytest.fixture
def toy_df():
    return pd.DataFrame(
        {
            "Retrieval Model": [
                "bge-m3",
                "bge-m3",
                "jina-embeddings-v2-base",
                "jina-embeddings-v2-base"
            ],
            "Reranking Model": [
                "bge-reranker-v2-m3",
                "NoReranker",
                "bge-reranker-v2-m3",
                "NoReranker"
            ],
            "Average ⬆️": [0.6, 0.4, 0.3, 0.2],
            "wiki_en": [0.8, 0.7, 0.2, 0.1],
            "wiki_zh": [0.4, 0.1, 0.4, 0.3],
            "news_en": [0.8, 0.7, 0.2, 0.1],
            "news_zh": [0.4, 0.1, 0.4, 0.3],
        }
    )


@pytest.fixture
def toy_df_long_doc():
    return pd.DataFrame(
        {
            "Retrieval Model": [
                "bge-m3",
                "bge-m3",
                "jina-embeddings-v2-base",
                "jina-embeddings-v2-base"
            ],
            "Reranking Model": [
                "bge-reranker-v2-m3",
                "NoReranker",
                "bge-reranker-v2-m3",
                "NoReranker"
            ],
            "Average ⬆️": [0.6, 0.4, 0.3, 0.2],
            "law_en_lex_files_300k_400k": [0.4, 0.1, 0.4, 0.3],
            "law_en_lex_files_400k_500k": [0.8, 0.7, 0.2, 0.1],
            "law_en_lex_files_500k_600k": [0.8, 0.7, 0.2, 0.1],
            "law_en_lex_files_600k_700k": [0.4, 0.1, 0.4, 0.3],
        }
    )
def test_filter_models(toy_df):
    df_result = filter_models(toy_df, ["bge-reranker-v2-m3", ])
    assert len(df_result) == 2
    assert df_result.iloc[0]["Reranking Model"] == "bge-reranker-v2-m3"


def test_search_table(toy_df):
    df_result = search_table(toy_df, "jina")
    assert len(df_result) == 2
    assert df_result.iloc[0]["Retrieval Model"] == "jina-embeddings-v2-base"


def test_filter_queries(toy_df):
    df_result = filter_queries("jina", toy_df)
    assert len(df_result) == 2
    assert df_result.iloc[0]["Retrieval Model"] == "jina-embeddings-v2-base"


def test_select_columns(toy_df):
    df_result = select_columns(toy_df, ['news',], ['zh',])
    assert len(df_result.columns) == 4
    assert df_result['Average ⬆️'].equals(df_result['news_zh'])


def test_update_table_long_doc(toy_df_long_doc):
    df_result = update_table_long_doc(toy_df_long_doc, ['law',], ['en',], ["bge-reranker-v2-m3", ], "jina")
    print(df_result)


def test_get_iso_format_timestamp():
    timestamp_config, timestamp_fn = get_iso_format_timestamp()
    assert len(timestamp_fn) == 14
    assert len(timestamp_config) == 20
    assert timestamp_config[-1] == "Z"


def test_get_default_cols():
    cols, types = get_default_cols("qa")
    for c, t in zip(cols, types):
        print(f"type({c}): {t}")
    assert len(frozenset(cols)) == len(cols)