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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_p60_for_display(analysis_results_for_id):
data_to_display = {}
data_to_display["document_category"] = "income_document"
data_to_display["document_type"] = "p60"
employee_details = analysis_results_for_id.get(
"employee_details", None)
data_to_display["surname"] = employee_details.get(
"surname", None)
data_to_display["forenames_or_initials"] = employee_details.get(
"forenames_or_initials", None)
data_to_display["national_insurance_number"] = employee_details.get(
"national_insurance_number", None)
data_to_display["works_payroll_number"] = employee_details.get(
"works_payroll_number", None)
pay_and_income_tax_details = analysis_results_for_id.get(
"pay_and_income_tax_details", None)
data_to_display["previous_employments"] = pay_and_income_tax_details.get(
"previous_employments", None)
data_to_display["current_employment"] = pay_and_income_tax_details.get(
"current_employment", None)
data_to_display["total_for_year"] = pay_and_income_tax_details.get(
"total_for_year", None)
data_to_display["final_tax_code"] = pay_and_income_tax_details.get(
"final_tax_code", None)
data_to_display["national_insurance_contributions"] = analysis_results_for_id.get(
"national_insurance_contributions", None)
employer_details = analysis_results_for_id.get(
"employer_details", None)
data_to_display["employer_name_and_address"] = employer_details.get(
"employer_name_and_address", None)
data_to_display["paye_reference"] = employer_details.get(
"paye_reference", None)
return data_to_display
def display_p60(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:
dict_str = {}
for key, value in analysis_results_pruned.items():
# if key not in ['other_deductions', 'salary_components']:
dict_str[key] = value
simple_df = pd.DataFrame.from_dict(
dict_str,
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)
# st.markdown("Other Deductions")
# other_dedecutions_dict = st.session_state['tab_ocr'][
# 'values_display'][original_file]['other_deductions']
# logger.info(f"other_dedecutions_dict : {other_dedecutions_dict}")
# for other_deduc in other_dedecutions_dict:
# simple_df = pd.DataFrame.from_dict(
# other_deduc,
# orient='index', columns=['Value']).reset_index()
# simple_df.columns = ['Key', 'Value']
# simple_df = simple_df.fillna(value="Missing")
# st.dataframe(simple_df, use_container_width=True)
logger.info(f"simple_df: {simple_df}")
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