import pandas as pd
import gradio as gr

from helper_funcs import functions, INPUT_FILE_TYPE, OUTPUT_FILE_TYPE, get_classla_stats_df


def run_function(selected_function, file_obj, input_column, output_column, output_type):

    if 'json' in file_obj.name.lower():
        df = pd.read_json(file_obj.name)
    if any([x in file_obj.name.lower() for x in ['csv', 'txt']]):
        df = pd.read_csv(file_obj.name, encoding='utf-8')

    output_file = 'result' + output_type

    if input_column not in list(df.columns):
        raise gr.Error("Input column name: such column does not exist in dataframe!")

    funcs = functions[selected_function](df, input_column, output_column, output_file)
    return funcs


app = gr.Blocks()


with app:
    process_status = gr.State(False)
    gr.Markdown(
        """
        # Instructions
        1. Upload CSV file to process.
        2. Enter the name of the column containing the values to process.
        3. Enter the name of the column in which to save the output.
        4. Select function to process the data.
        5. Click Process.
        """
    )
    with gr.Row():
        with gr.Column():
            gr.Markdown(
                """
                # Input
                """
            )
            file_obj = gr.File(
                label="Input File",
                file_count="single",
                file_types=INPUT_FILE_TYPE
            )
            input_column = gr.Textbox(
                label="Input column name",
                info="Please enter the name of the column you want to process (as it appears in your dataset)",
                lines=1,
            )
            output_column = gr.Textbox(
                label="Output column name",
                info="Please enter the name of the column you want to save the result to",
                lines=1,
            )
            selected_function = gr.Dropdown(
                list(functions.keys()),
                label="Select processing",
                info=""
            )
            output_type = gr.Dropdown(
                list(OUTPUT_FILE_TYPE),
                label="Select the output file type",
                info=""
            )

        with gr.Column():
            gr.Markdown(
                """
                # Output
                """
            )
            output_dataframe = gr.Dataframe(
                label="Output Data"
            )
            output_csv = gr.File(
                label="Output File",
                file_types=OUTPUT_FILE_TYPE
            )

    stats_plot = gr.BarPlot(
        value = pd.DataFrame(columns=['value', 'count']),
        x = 'value',
        y = 'count'
    )

    process_button = gr.Button("Process")
    process_button.click(
        run_function,
        inputs=[selected_function, file_obj, input_column, output_column, output_type],
        outputs=[output_dataframe, output_csv],
    )
    strats_button = gr.Button("Get Stats")
    strats_button.click(get_classla_stats_df, inputs=None, outputs=stats_plot)

app.launch()