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_others_for_display(analysis_results_for_id):
#     data_to_display = {}

#     data_to_display["document_category"] = "income_document"
#     data_to_display["document_type"] = "payslip"

#     data_to_display["employee_name"] = analysis_results_for_id.get(
#         "employee_name", None)
#     data_to_display["employer_name"] = analysis_results_for_id.get(
#         "employer_name", None)
#     data_to_display["payslip_date"] = analysis_results_for_id.get(
#         "payslip_date", None)
#     data_to_display["pay_period_start"] = analysis_results_for_id.get(
#         "pay_period_start", None)
#     data_to_display["pay_period_end"] = analysis_results_for_id.get(
#         "pay_period_end", None)
#     data_to_display["payment_frequency"] = analysis_results_for_id.get(
#         "payment_frequency", None)
#     data_to_display["basic_pay"] = analysis_results_for_id.get(
#         "basic_pay", None)
#     data_to_display["net_pay"] = analysis_results_for_id.get(
#         "net_pay", None)
#     data_to_display["gross_pay"] = analysis_results_for_id.get(
#         "gross_pay", None)
#     data_to_display["salary_components"] = analysis_results_for_id.get(
#         "salary_components", None)
#     data_to_display["ni_contribution"] = analysis_results_for_id.get(
#         "ni_contribution", None)
#     data_to_display["tax_deduction"] = analysis_results_for_id.get(
#         "tax_deduction", None)
#     data_to_display["other_deductions"] = analysis_results_for_id.get(
#         "other_deductions", None)

#     return data_to_display


def display_others(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:

        for key, value in analysis_results_pruned.items():
            if isinstance(value, dict):
                st.write(f"**{key}:**")
                sub_data = {"Key": [], "Value": []}
                for sub_key, sub_value in value.items():
                    sub_data["Key"].append(sub_key)
                    sub_data["Value"].append(sub_value)
                sub_df = pd.DataFrame(sub_data)
                sub_df.index += 1
                st.dataframe(sub_df, use_container_width=True)
                # sub_col1, sub_col2 = st.columns(2)
                # for sub_key, sub_value in value.items():
                #     with sub_col1:
                #         st.write(f"{sub_key}",
                #                  use_container_width=True)
                #     with sub_col2:
                #         with st.container():
                #             st.write(f"{sub_value}",
                #                      use_container_width=True)
            else:
                simple_data = {"Key": [key], "Value": [value]}
                simple_df = pd.DataFrame(simple_data)
                simple_df.index += 1
                logger.info(f"simple_df['Value'] : {simple_df['Value']}")
                # simple_df["Value"] = simple_df["Value"].apply(lambda x: str(x) if not pd.isnull(x) else "")
                def safe_to_str(x):
                    try:
                        if pd.isna(x):
                            return ""
                    except:
                        pass
                    return str(x)

                simple_df["Value"] = simple_df["Value"].apply(safe_to_str)

                st.dataframe(simple_df, use_container_width=True)
                # sub_col1, sub_col2 = st.columns(2)
                # with sub_col1:
                #     st.write(f"{key}", use_container_width=True)
                # with st.container():
                #     with sub_col2:
                #         st.write(f"{value}", use_container_width=True)

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