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| import gradio as gr | |
| import pandas as pd | |
| from datetime import datetime | |
| import pytz # This library is used for timezone conversions | |
| def display_csv(file, supplier, order_number): | |
| df = pd.read_csv(file.name) | |
| # Define supplier-specific filters | |
| vendor_filters = { | |
| "Supplier 1": lambda df: df[~df['Vendor'].isin(["Seed", "EverColor", "Candy Magic", "OLENS", "Fairy", "Shobido", "Geo Medical", "Ann365", "Lenstown", "LensVery"])], | |
| "Supplier 2": lambda df: df[df['Vendor'].isin(["Candy Magic", "OLENS", "Fairy", "Shobido"])], | |
| "Supplier 3": lambda df: df[df['Vendor'].isin(["Seed", "EverColor"])], | |
| "Supplier 4": lambda df: df[df['Vendor'] == "Geo Medical", "Lenstown"], | |
| "Supplier 5": lambda df: df[df['Vendor'] == "Ann365", "LensVery"] | |
| } | |
| # Apply supplier filter if selected | |
| if supplier and supplier in vendor_filters: | |
| df = vendor_filters[supplier](df) | |
| # Filter based on order number | |
| if order_number: | |
| df = df[df['Order Number'] >= int(order_number)] | |
| # Specify columns for output | |
| columns_to_include = [ | |
| 'Order Number', 'Quantity', 'Product Title', 'Product Option Name', | |
| 'Product Option Value', 'Order Line item Properties 2 Name', | |
| 'Order Line item Properties 2 Value', 'Order Line item Properties 3 Name', | |
| 'Order Line item Properties 3 Value' | |
| ] | |
| download_df = df[columns_to_include] | |
| # Get the current date in Hong Kong Time | |
| hk_timezone = pytz.timezone("Asia/Hong_Kong") | |
| current_date_hk = datetime.now(hk_timezone).strftime("%y%m%d") | |
| # Set output file name based on the selected supplier | |
| if supplier == "Supplier 1": | |
| output_file = f"Leading Bridge Order {current_date_hk}.xlsx" | |
| elif supplier == "Supplier 2": | |
| output_file = f"Leading Bridge Order {current_date_hk}-Ammu.xlsx" | |
| else: | |
| output_file = "filtered_output.xlsx" # Default file name for other cases | |
| # Save filtered DataFrame as Excel file | |
| download_df.to_excel(output_file, index=False) | |
| return df, output_file | |
| # Define the main block for the interface | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| file_input = gr.File(label="Upload CSV") | |
| supplier_input = gr.Dropdown(choices=["", "Supplier 1", "Supplier 2", "Supplier 3", "Supplier 4", "Supplier 5"], label="Select Supplier") | |
| order_number_input = gr.Number(label="Minimum Order Number", precision=0) | |
| load_button = gr.Button("Load Data") | |
| with gr.Row(): | |
| output_df = gr.DataFrame() | |
| output_file = gr.File(label="Download Filtered CSV") | |
| # Bind the function to inputs and outputs using the button | |
| load_button.click(fn=display_csv, inputs=[file_input, supplier_input, order_number_input], outputs=[output_df, output_file]) | |
| # Run the interface | |
| demo.launch() |