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import streamlit as st
from utils.logger import setup_logger
import pandas as pd
from PIL import Image
import os

logger = setup_logger(__name__)


def prune_driving_license_for_display(analysis_results_for_id):
    data_to_display = {}
    data_to_display["document_category"] = "identity_verification_document"
    data_to_display["document_type"] = "driving_license"

    data_to_display["surname"] = analysis_results_for_id.get(
        "surname", None)
    data_to_display["first_name"] = analysis_results_for_id.get(
        "first_name", None)
    data_to_display["date_of_birth"] = analysis_results_for_id.get(
        "date_of_birth", None)
    data_to_display["place_of_birth"] = analysis_results_for_id.get(
        "place_of_birth", None)
    data_to_display["date_of_issue"] = analysis_results_for_id.get(
        "date_of_issue", None)
    data_to_display["date_of_expiry"] = analysis_results_for_id.get(
        "date_of_expiry", None)
    data_to_display["issuing_authority"] = analysis_results_for_id.get(
        "issuing_authority", None)
    data_to_display["driver_number"] = analysis_results_for_id.get(
        "driver_number", None)
    data_to_display["address"] = analysis_results_for_id.get(
        "address", None)
    data_to_display["entitlements"] = analysis_results_for_id.get(
        "entitlements", None)

    return data_to_display


def display_driving_license(extracted_files, analysis_results_pruned):

    col1, col2 = st.columns([2, 3])

    logger.info(f"file_path while displaying: {extracted_files}")
    st.markdown("---")

    with col1:
        if len(extracted_files) > 1:
            st.image(extracted_files, caption=[os.path.basename(
                img) for img in extracted_files], use_container_width=True)
        else:
            image = Image.open(extracted_files[0])
            st.image(image, caption=os.path.basename(
                extracted_files[0]))  # ,
            # use_container_width=True)

        logger.info(
            f"analysis_results_pruned : {analysis_results_pruned}")

    with col2:

        simple_df = pd.DataFrame.from_dict(
            analysis_results_pruned,
            orient='index', columns=['Value']).reset_index()
        simple_df.columns = ['Key', 'Value']
        simple_df = simple_df.fillna(value="Missing")
        simple_df.index += 1
        st.dataframe(simple_df, use_container_width=True)

        # logger.info(f"simple_df: {simple_df}")