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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() |