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| import streamlit as st | |
| import pandas as pd | |
| from io import BytesIO | |
| from helper import get_res_df | |
| def to_excel(df): | |
| """ | |
| Convert a Pandas DataFrame to an Excel file in memory. | |
| Parameters: | |
| df (DataFrame): The DataFrame to be converted to Excel format. | |
| Returns: | |
| bytes: The in-memory Excel file data. | |
| """ | |
| output = BytesIO() | |
| # Use the Pandas ExcelWriter to write the DataFrame to an in-memory file | |
| with pd.ExcelWriter(output, engine='xlsxwriter') as writer: | |
| df.to_excel(writer, index=False) | |
| processed_data = output.getvalue() | |
| return processed_data | |
| def process_files(excel_file, text_file): | |
| """ | |
| Process the uploaded Excel/CSV and text files and return cleaned dataframes. | |
| Parameters: | |
| excel_file (UploadedFile): The uploaded Excel or CSV file. | |
| text_file (UploadedFile): The uploaded text file. | |
| Returns: | |
| Tuple[DataFrame, DataFrame]: A tuple containing the cleaned DataFrame from the Excel/CSV file | |
| and a DataFrame created from the text file data. | |
| """ | |
| print(excel_file, text_file) # Debugging information | |
| # Read the Excel/CSV file into a DataFrame | |
| if excel_file.name.endswith('.csv'): | |
| df_excel = pd.read_csv(excel_file) | |
| else: | |
| df_excel = pd.read_excel(excel_file) | |
| # Ensure the 'cfcf' column values are formatted as zero-padded 6-digit strings | |
| df_excel['cfcf'] = [str(number).zfill(6) for number in df_excel['cfcf']] | |
| # Read and process the text file content into a list of lines | |
| lines = text_file.read().decode('utf-8').splitlines() | |
| data = [line.strip().split(',') for line in lines] # Split each line by commas | |
| # Create a DataFrame from the parsed text file data | |
| df = pd.DataFrame(data) | |
| return df_excel, df | |
| # Streamlit UI section | |
| st.title("Fetch Employer") # Application title | |
| # File uploader widgets to allow users to upload an Excel/CSV file and a text file | |
| uploaded_excel = st.file_uploader("Upload the Master file(.xls or .csv)", type=["csv", "xls", "xlsx"]) | |
| uploaded_text = st.file_uploader("Upload your Text file(.txt)", type=["txt"]) | |
| # Check if both files are uploaded | |
| if uploaded_excel and uploaded_text: | |
| st.write("Processing the files...") # Inform the user that the files are being processed | |
| master_data, df = process_files(uploaded_excel, uploaded_text) # Process the files | |
| st.write("Final Output") # Display the result of file processing | |
| res = get_res_df(master_data, df) # Generate the result DataFrame using the helper function | |
| st.dataframe(res) # Show the result in a table format on the web app | |
| # Convert the result DataFrame to an Excel file for download | |
| excel_data = to_excel(res) | |
| # Provide a button for the user to download the result as an Excel file | |
| st.download_button(label="Download Excel", | |
| data=excel_data, | |
| file_name='Fetch_Employer_Output.xlsx', | |
| mime='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet') | |
| # import streamlit as st | |
| # import pandas as pd | |
| # from io import BytesIO | |
| # from helper import get_res_df | |
| # def to_excel(df): | |
| # output = BytesIO() | |
| # with pd.ExcelWriter(output, engine='xlsxwriter') as writer: | |
| # df.to_excel(writer, index=False) | |
| # processed_data = output.getvalue() | |
| # return processed_data | |
| # def process_files(excel_file, text_file): | |
| # print(excel_file,text_file) | |
| # if excel_file.name.endswith('.csv'): | |
| # df_excel = pd.read_csv(excel_file) | |
| # else: | |
| # df_excel = pd.read_excel(excel_file) | |
| # df_excel['cfcf']=[str(number).zfill(6) for number in df_excel['cfcf']] | |
| # lines = text_file.read().decode('utf-8').splitlines() | |
| # data = [line.strip().split(',') for line in lines] | |
| # df = pd.DataFrame(data) | |
| # return df_excel,df | |
| # st.title("Fetch Employer") | |
| # uploaded_excel = st.file_uploader("Upload the Master file(.xls or .csv)", type=["csv", "xls", "xlsx"]) | |
| # uploaded_text = st.file_uploader("Upload your Text file(.txt)", type=["txt"]) | |
| # if uploaded_excel and uploaded_text: | |
| # st.write("Processing the files...") | |
| # master_data, df = process_files(uploaded_excel, uploaded_text) | |
| # st.write("Final Output") | |
| # res = get_res_df(master_data,df) | |
| # st.dataframe(res) | |
| # excel_data = to_excel(res) | |
| # st.download_button(label="Download Excel", | |
| # data=excel_data, | |
| # file_name='Fetch_Employer_Output.xlsx', | |
| # mime='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet') | |