import pytest
import pandas as pd
import gradio as gr
from validation import validate_csv_file, validate_csv_can_be_read, validate_dataframe
from constants import REQUIRED_COLUMNS, ASSAY_LIST


class TestValidateCsvCanBeRead:
    """Test cases for validate_csv_can_be_read function"""

    def test_valid_csv_can_be_read(self, valid_csv_content):
        df = validate_csv_can_be_read(valid_csv_content)
        assert isinstance(df, pd.DataFrame)

    def test_empty_csv_raises_error(self):
        empty_csv = ""

        with pytest.raises(gr.Error) as exc_info:
            validate_csv_can_be_read(empty_csv)

        assert "empty or contains no valid data" in str(exc_info.value)

    def test_invalid_csv_format_raises_error(self):
        # Create a CSV with malformed structure that pandas cannot parse
        malformed_csv = 'column1,column2\nvalue1,"unclosed quote\nvalue4,value5'

        with pytest.raises(gr.Error) as exc_info:
            validate_csv_can_be_read(malformed_csv)

        assert "Invalid CSV format" in str(exc_info.value)

    def test_csv_with_quoted_fields_can_be_read(self):
        # Create CSV with quoted fields and enough rows
        base_row = 'test_antibody,"EVQLVESGGGLVQPGGSLRLSCAASGFTFSSYAMHWVRQAPGKGLEWVSAISGSGGSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCARDYGDGYYFDYWGQGTLVTVSS","DIQMTQSPSSLSASVGDRVTITCRASQSISSYLNWYQQKPGKAPKLLIYAASTLQSGVPSRFSGSGSGTDFTLTISSLQPEDFATYYCQQSYSTPFTFGQGTKVEIK",95.2,0.85,0.92,0.78,0.81,72.5'
        csv_content = "antibody_name,vh_protein_sequence,vl_protein_sequence,SEC %Monomer,HIC,PR_CHO,AC-SINS_pH6.0,AC-SINS_pH7.4,Tm\n"
        csv_content += "\n".join([base_row] * 10)

        df = validate_csv_can_be_read(csv_content)
        assert isinstance(df, pd.DataFrame)


class TestValidateDataframe:
    def test_valid_dataframe_passes(self, valid_input_dataframe):
        validate_dataframe(valid_input_dataframe)

    def test_missing_columns_raises_error(self, valid_input_dataframe):
        missing_column = REQUIRED_COLUMNS[0]
        df = valid_input_dataframe.copy()
        df.drop(columns=[missing_column], inplace=True)

        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(df)

        assert f"Missing required columns: {missing_column}" in str(exc_info.value)

    def test_at_least_one_assay_column_raises_error(self, valid_input_dataframe):
        df = valid_input_dataframe.copy()
        df.drop(columns=ASSAY_LIST, inplace=True, errors="ignore")
        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(df)
        assert "CSV should include at least one of the following assay columns" in str(
            exc_info.value
        )

    def test_empty_dataframe_raises_error(self, valid_input_dataframe):
        empty_df = valid_input_dataframe.head(0)

        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(empty_df)

        assert "CSV file is empty" in str(exc_info.value)

    def test_missing_antibodies_raises_error(self, valid_input_dataframe):
        df = valid_input_dataframe.head(50)
        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(df)
        assert "Missing predictions for" in str(exc_info.value)

    def test_missing_values_raises_error(self, valid_input_dataframe):
        bad_column = REQUIRED_COLUMNS[0]
        df = valid_input_dataframe.copy()
        df[bad_column] = [None] * len(df)
        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(df)

        assert f"contains {len(df)} missing values" in str(exc_info.value)

    def test_csv_with_extra_columns_passes(self, valid_input_dataframe):
        extra_column = "extra_column_1"
        df = valid_input_dataframe.copy()
        df[extra_column] = ["extra1"] * len(df)
        df[extra_column] = ["extra2"] * len(df)
        validate_dataframe(df)

    def test_duplicate_antibody_names_raises_error(self, valid_input_dataframe):
        df = valid_input_dataframe.copy()
        df = pd.concat([df, df.head(1)], ignore_index=True)
        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(df)
        assert "CSV should have only one row per antibody. Found 1 duplicates." in str(
            exc_info.value
        )

    def test_unrecognized_antibody_names_raises_error(self, valid_input_dataframe):
        df = valid_input_dataframe.copy()
        df.loc[0, "antibody_name"] = "unrecognized_antibody"
        with pytest.raises(gr.Error) as exc_info:
            validate_dataframe(df)
        assert f"Found unrecognized antibody names: {'unrecognized_antibody'}" in str(
            exc_info.value
        )


class TestValidateCsvFile:
    def test_valid_csv_passes(self, valid_csv_content):
        validate_csv_file(valid_csv_content)