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import PyPDF2
import pandas as pd
import os
import ast
import streamlit as st
import pandas as pd

def convert_pdf_to_excel(pdf_file):
    inputpdf = PyPDF2.PdfReader(pdf_file)
    pages_no = len(inputpdf.pages)
    whole_data = []
    for i in range(pages_no):
        inputpdf = PyPDF2.PdfReader(pdf_file)
        # output = PyPDF2.PdfWriter()
        # output.add_page(inputpdf.pages[i])
        pageObj = inputpdf.pages[i]
        page_content = pageObj.extract_text()
        for each_table in [i for i in page_content.split('Delivery Schedule Sheet') if i]:
            data = each_table.split('\n')
            each_table_data = []
            date_qty = []
            row_start_index = 0
            row_stop_index = 0
            for index in range(len(data)):
                if data[index].strip() == 'Part No.':
                    each_table_data.append(data[index+1].replace('Part Color Code',""))
                    if 'Part Name' not in data[index+2]:
                        each_table_data.append(data[index+2].replace('Part Color Code',""))
                    else:
                        each_table_data.append("")

                if 'Part Name' in data[index].strip():
                    each_table_data.append(data[index+1])
                    
                if data[index].strip() == 'ADJ':
                    row_start_index = index + 1
                    
                if data[index].strip() == 'Total':
                    row_stop_index = index
                    
            if row_start_index>0 and row_stop_index>0:
                for index in range(row_start_index,row_stop_index):
                    if '/' in data[index].strip():
                        date_qty.append([data[index].strip()[-5:].strip(),data[index+1].strip()])
            if not date_qty:
                date_qty = [["",""]]
            each_table_data.append(date_qty)
            whole_data.append(each_table_data)

    whole_data = pd.DataFrame(whole_data)
    whole_data.columns = ["Part No.","Part Color Code","Part Name",'Date Qty']
    extracted_file = "Data Extracted.xlsx"
    data_for_mapping = "Data Mapping.xlsx"
    extracted_data_for_mapping = whole_data.drop('Date Qty',axis=1)
    extracted_data_for_mapping = extracted_data_for_mapping.drop_duplicates(subset=["Part No.","Part Color Code","Part Name"])
    whole_data.to_excel(extracted_file, index=False)
    extracted_data_for_mapping.to_excel(data_for_mapping, index=False)
    return extracted_file,data_for_mapping

def map_data_to_template(excel_file, mapping_file):
    # Load Excel file and mapping file
    extracted_data = pd.read_excel(excel_file)
    mapping_data = pd.read_excel(mapping_file)
    mapping_data = mapping_data.rename(columns = {'Customer Part no as per pdf':'Part No.'})

    # Perform mapping
    extracted_data['Date Qty'] = extracted_data['Date Qty'].apply(lambda x: ast.literal_eval(x))
    extracted_data = extracted_data.explode('Date Qty')
    extracted_data[['SchDate','Qty']]= pd.DataFrame(extracted_data['Date Qty'].to_list(), index= extracted_data.index)
    extracted_data = extracted_data.drop('Date Qty',axis=1)
    mapped_data = extracted_data.merge(mapping_data, on =['Part No.'])[['Item Code','SchDate','Qty']]

    return mapped_data

def main():
    st.title("PDF to Excel Converter")
    
    # File uploader
    uploaded_file = st.file_uploader("Upload a PDF file", type=["pdf"])
    
    if uploaded_file is not None:
        st.write("Uploaded PDF file:", uploaded_file.name)
        
        # Convert PDF to Excel
        extracted_file,data_for_mapping = convert_pdf_to_excel(uploaded_file)
        
        # Download link for the Excel file
        # st.markdown(f"Download the extracted data in Excel file [here](/{excel_file})")

        if os.path.exists(data_for_mapping):
            with open(data_for_mapping, "rb") as f:
                excel_bytes = f.read()
            st.download_button(
                label="Download Excel file",
                data=excel_bytes,
                file_name=data_for_mapping,
                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
            )
        else:
            st.error("Error: Converted Excel file not found")

        
        st.markdown("## Upload the Data Master file with Item Code mapping")
        mapping_uploaded_file = st.file_uploader("Upload the Data Master file with Item Code mapping", type=["xlsx","ods"])

        if mapping_uploaded_file is not None:
            st.write("Uploaded Mapping Excel file:", mapping_uploaded_file.name)

            # Perform data mapping
            mapped_data = map_data_to_template(extracted_file, mapping_uploaded_file)

            # Provide a link to download the final Excel file after mapping
            st.markdown("### Final Excel File After Mapping")

            final_excel_file = 'Final Data.xlsx'
            mapped_data.to_excel(final_excel_file, index=False)

            if os.path.exists(final_excel_file):
                with open(final_excel_file, "rb") as f:
                    excel_bytes = f.read()
                st.download_button(
                    label="Download Excel file",
                    data=excel_bytes,
                    file_name=final_excel_file,
                    mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                )
            else:
                st.error("Error: Converted Excel file not found")

            
            
            
        
if __name__ == "__main__":
    main()