app.py

import PyPDF2
import pandas as pd
import os
import ast
import streamlit as st
import pandas as pd
import os
from google.oauth2.credentials import Credentials
from google.auth.transport.requests import Request
from google_auth_oauthlib.flow import InstalledAppFlow
from googleapiclient.discovery import build
from googleapiclient.http import MediaIoBaseDownload,MediaFileUpload
from google.oauth2 import service_account
import base64

def get_image_as_base64(image_path):
    with open(image_path, "rb") as img_file:
        return base64.b64encode(img_file.read()).decode()
    
# Load credentials from environment variables
SERVICE_ACCOUNT_INFO = {
  "type": "service_account",
  "project_id": os.environ.get("project_id"),
  "private_key_id": os.environ.get("private_key_id"),
  "private_key": "-----BEGIN PRIVATE KEY-----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\n2GsPiT9eCYuz6WV4+Q9RXolrhQ==\n-----END PRIVATE KEY-----\n",
  "client_email": os.environ.get("client_email"),
  "client_id": os.environ.get("client_id"),
  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
  "token_uri": os.environ.get("token_uri"),
  "auth_provider_x509_cert_url": os.environ.get("auth_provider_x509_cert_url"),
  "client_x509_cert_url": os.environ.get("client_x509_cert_url"),
  "universe_domain": "googleapis.com"
}


SCOPES = ['https://www.googleapis.com/auth/drive']


def authenticate():
    # Authenticate using service account credentials
    creds = service_account.Credentials.from_service_account_info(SERVICE_ACCOUNT_INFO, scopes=['https://www.googleapis.com/auth/drive'])

    # Build the Drive API service
    # service = build('drive', 'v3', credentials=creds)
    return creds

    # creds = service_account.Credentials.from_service_account_file(
    #     SERVICE_ACCOUNT_FILE, scopes=['https://www.googleapis.com/auth/drive'])

    # Check if token file exists
    # if os.path.exists('token.json'):
    #     creds = Credentials.from_authorized_user_file('token.json')

    # If no valid credentials available, ask the user to login
    # if not creds or not creds.valid:
    #     if creds and creds.expired and creds.refresh_token:
    #         creds.refresh(Request())
    #     else:
    #         # flow = InstalledAppFlow.from_client_secrets_file("credentials.json", SCOPES)
    #         flow = InstalledAppFlow.from_client_config(config,SCOPES)
    #         creds = flow.run_local_server(port=0)

    #     # Save the credentials for next run
    #     with open('token.json', 'w') as token:
    #         token.write(creds.to_json())


MAPPING_FILENAME = "Data Mapping with ItemCode.xlsx"

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
            year = ""
            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 data[index].strip()=='MORIROKU TECHNOLOGY':
                    try:
                        year = data[index+1].split(' ')[0].split('/')[1]
                    except Exception as e:
                        print(e)
                        year = ""

                if 'Part Name' in data[index].strip():
                    each_table_data.append(data[index+1].replace("Sched",""))
                
                if 'Inventory Category' in data[index].strip():
                    each_table_data.append(data[index+1].replace('Receive Type',""))

                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() + "/"+year,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",'Inventory Category','Date Qty']
    extracted_file = "Data Extracted.xlsx"
    data_for_mapping = "Data Mapping.xlsx"

    extracted_data_for_mapping = whole_data.drop(['Inventory Category','Date Qty'],axis=1)
    extracted_data_for_mapping = extracted_data_for_mapping.drop_duplicates(subset=["Part No.","Part Color Code","Part Name"])
    extracted_data_for_mapping.columns = ['Customer Part no as per pdf','Customer Part color  as per pdf','Customer Part name as per pdf']
    extracted_data_for_mapping['Item Code'] = ""

    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.drop_duplicates(subset=['Customer Part no as per pdf','Customer Part name as per pdf','Customer Part color  as per pdf','Item Code'])
    mapping_data.to_excel(MAPPING_FILENAME,index=False)
    save_mapping_file_to_drive()
    mapping_data = mapping_data.rename(columns = {'Customer Part no as per pdf':'Part No.','Customer Part name as per pdf':'Part Name','Customer Part color  as per pdf':'Part Color Code'})

    # 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)
    extracted_data = extracted_data[~extracted_data['SchDate'].isna()]

    mapped_data = extracted_data.merge(mapping_data, on =["Part No.","Part Name","Part Color Code"],how='outer')[['Item Code','SchDate','Qty','Inventory Category']]
    mapped_data = mapped_data[~mapped_data["SchDate"].isna()]
    mapped_data = mapped_data[~mapped_data["SchDate"].str.strip().isin(["",None])] 				

    mapped_data['SOType'] = "R"
    mapped_data['SchDate'] = mapped_data['SchDate'].astype("str")
    return mapped_data[["SchDate","SOType","Item Code","Qty","Inventory Category"]]

def save_mapping_file_to_drive():
    # creds = Credentials.from_authorized_user_info(credentials_dict)
    creds = authenticate()
    service = build('drive', 'v3', credentials=creds)
    # Authenticate with Google Drive API
    # service = build('drive', 'v3', credentials=creds)

    # List all files in the folder
    # results = service.files().list(
    #     q=f"'{folder_id}' in parents and mimeType='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'",
    #     fields="files(id, name)").execute()
    
    results = service.files().list(
        q=f"mimeType='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'",
        fields="files(id, name)").execute()
    
    files = results.get('files', [])
    files = [i for i in files if i.get('name')==MAPPING_FILENAME]

    if not files:
        print('No Excel Mapping files found in the folder.')
    else:
        for file in files:
            # Get the ID and name of the first Excel file found in the folder
            existing_file_id = file['id']
            existing_file_name = file['name']

            # Delete the existing file
            service.files().delete(fileId=existing_file_id).execute()

    file_metadata = {'name': MAPPING_FILENAME }
    media = MediaFileUpload(MAPPING_FILENAME, mimetype='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet')
    service.files().create(body=file_metadata, media_body=media, fields='id').execute()

def pull_mapping_file_from_drive():
    creds = authenticate()
    # service = build('drive', 'v3', credentials=creds)
    # creds = Credentials.from_authorized_user_info(credentials_dict)
    # Authenticate with Google Drive API
    service = build('drive', 'v3', credentials=creds)

    results = service.files().list(
        q="mimeType='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'",
        fields="files(id, name)").execute()
    files = results.get('files', [])
    files = [i for i in files if i.get('name')==MAPPING_FILENAME]    
    if files:
        file_id = files[0]['id']
        file_name = files[0]['name']
        request = service.files().get_media(fileId=file_id)
        fh = open(file_name, 'wb')
        downloader = MediaIoBaseDownload(fh, request)

        # Execute the download
        done = False
        while not done:
            status, done = downloader.next_chunk()

        fh.close()
        return 1
    
    return 0

def delete_master_file():
    creds = authenticate()
    service = build('drive', 'v3', credentials=creds)
    # Authenticate with Google Drive API
    # service = build('drive', 'v3', credentials=creds)
    folder_id = "1HBRUZePST0D0buyU9MxeYg2vQyEL4wLF"

    # List all files in the folder
    results = service.files().list(
        q=f"mimeType='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'",
        fields="files(id, name)").execute()
    files = results.get('files', [])
    files = [i for i in files if i.get('name')==MAPPING_FILENAME]

    if not files:
        print('No Excel Mapping files found in the folder.')
    else:
        for file in files:
            # Get the ID and name of the first Excel file found in the folder
            existing_file_id = file['id']
            existing_file_name = file['name']

            # Delete the existing file
            service.files().delete(fileId=existing_file_id).execute()
            print("Deleted master file")

def main():
    # Load your logo image
    logo_path = "logo.jpeg"
    logo_base64 = get_image_as_base64(logo_path)
    logo_html = f"""
    <div style="display: flex; justify-content: center; align-items: center; height: 100px;">
        <img src="data:image/jpeg;base64,{logo_base64}" style="width: 100px; height: 100px;">
    </div>
    """

    # Display the logo HTML
    st.markdown(logo_html, unsafe_allow_html=True)
    st.markdown("<h1 style='text-align: center;'>PDF to Excel Converter</h1>", unsafe_allow_html=True)
    
    
    # File uploader
    st.markdown("### STEP 1")
    st.markdown("#### Upload a PDF File")
    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)
        
        file_present = pull_mapping_file_from_drive()

        if file_present:
            try:
                mapping_data_from_drive = pd.read_excel(MAPPING_FILENAME)
                extracted_data_for_mapping = pd.read_excel(data_for_mapping)
                extracted_data_for_mapping.columns = [i.strip() for i in extracted_data_for_mapping.columns]
                mapping_data_from_drive.columns = [i.strip() for i in mapping_data_from_drive.columns if "inventory category" not in i.lower()]
                mapping_data_from_drive = mapping_data_from_drive.drop_duplicates(subset=['Customer Part no as per pdf','Customer Part name as per pdf','Customer Part color  as per pdf','Item Code'])

                extracted_data_for_mapping = extracted_data_for_mapping[['Customer Part no as per pdf','Customer Part name as per pdf','Customer Part color  as per pdf']].merge(mapping_data_from_drive, on = ['Customer Part no as per pdf','Customer Part name as per pdf','Customer Part color  as per pdf'], how='outer')
                extracted_data_for_mapping.to_excel(data_for_mapping,index=False)
            except Exception as e:
                st.error("Error in the Mapping Master file on Cloud. " + str(e))
                st.error("Please reupload the Data Master file with Item Code mapping")
                delete_master_file()
                file_present = None


        # 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("##### Click the button below if you want to upload a new mapping file")
        if st.button("Delete Mapping file in Cloud", key="delete"):
            delete_master_file()
            file_present = pull_mapping_file_from_drive()

        st.markdown("### STEP 2")
        mapping_uploaded_file = None
        if not file_present:
            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"])
        else:
            mapping_data = pd.read_excel(MAPPING_FILENAME)
            # mapping_data = mapping_data.rename(columns = {'Customer Part no as per pdf':'Part No.'})
            data_for_mapping = "Data Mapping.xlsx"
            extracted_data_for_mapping = pd.read_excel(data_for_mapping)
            if 'Item Code' not in extracted_data_for_mapping.columns:
                extracted_data_for_mapping['Item Code'] = ""
            
            extracted_data_for_mapping = extracted_data_for_mapping[extracted_data_for_mapping['Item Code'].isna()]
            unmapped_part_no = extracted_data_for_mapping['Customer Part no as per pdf'].nunique()
            if unmapped_part_no>0:
                st.markdown("There are {} Part No. with No ItemCode present. Upload a new file after mapping them".format(unmapped_part_no))
                st.markdown("Do you want to skip this or Upload a new Mapping File")

                if 'button_pressed' not in st.session_state:
                    st.session_state.button_pressed = None
                
                # placeholder = st.empty()  # Create a placeholder

                if st.session_state.button_pressed is None:
                    if st.button("Skip"):
                        st.session_state.button_pressed = "Skip"
                        # placeholder.empty()  # Clear the placeholder content

                    if st.button("Upload a new Master Mapping"):
                        st.session_state.button_pressed = "Upload a new Master Mapping"
                        # placeholder.empty()  # Clear the placeholder content
                        
                        
                if st.session_state.button_pressed is not None:
                    # Common block of code that uses the variable

                    if st.session_state.button_pressed == "Skip":
                        mapping_uploaded_file =  MAPPING_FILENAME
                        # Add your code that runs when Yes is pressed

                    elif st.session_state.button_pressed == "Upload a new Master Mapping":
                        mapping_uploaded_file = st.file_uploader("Upload the Data Master file with Item Code mapping", type=["xlsx","ods"])
                        # Add your code that runs when No is pressed

            else:
                st.markdown("All Part No. are mapped with ItemCode so using the Mapping file available in Google Drive")
                mapping_uploaded_file =  MAPPING_FILENAME

        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 DOWNLOAD")
            st.markdown("Final Excel File After Mapping")

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

            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")

            st.session_state.button_pressed = None
            
 
if __name__ == "__main__":
    main()