Update app.py

app.py

@@ -16,7 +16,7 @@ def process_file(file):
     except Exception as e:
         return f"Error reading file: {e}", None
 
-    # Output headers
+    # New output headers as requested
     output_headers = [
         "CustomerOrderNo.", "RoutingCode", "Trackingnumber", "AdditionalServices",
         "ShipmentProtectionPlusService", "SignatureService", "VatNumber", "EoriNumber",
@@ -34,22 +34,23 @@ def process_file(file):
         "PaymentTransactionNumber"
     ]
 
+    # Initialize empty output DataFrame
     output_df = pd.DataFrame("", index=range(len(df)), columns=output_headers)
 
     # 1. Order Number → CustomerOrderNo. (prefix "LB")
     if "Order Number" in df.columns:
         output_df["CustomerOrderNo."] = "LB" + df["Order Number"].astype(str)
 
-    # 2. Name
-    if {"Shipping First Name","Shipping Last Name","Shipping Company"}.issubset(df.columns):
+    # 2. Name mapping: First + Last + Company → Name
+    if {"Shipping First Name", "Shipping Last Name", "Shipping Company"}.issubset(df.columns):
         first = df["Shipping First Name"].fillna("").astype(str).str.strip()
         last  = df["Shipping Last Name"].fillna("").astype(str).str.strip()
         comp  = df["Shipping Company"].fillna("").astype(str).str.strip()
         output_df["Name"] = (first + " " + last + " " + comp).str.strip()
 
-    # 3. Street
-    addr1 = df.get("Shipping Address 1", pd.Series([""]*len(df))).fillna("").astype(str).str.strip()
-    addr2 = df.get("Shipping Address 2", pd.Series([""]*len(df))).fillna("").astype(str).str.strip()
+    # 3. Street: Address 1 + Address 2 → Street
+    addr1 = df.get("Shipping Address 1", pd.Series([""] * len(df))).fillna("").astype(str).str.strip()
+    addr2 = df.get("Shipping Address 2", pd.Series([""] * len(df))).fillna("").astype(str).str.strip()
     output_df["Street"] = (addr1 + " " + addr2).str.strip()
 
     # 4. City
@@ -62,74 +63,74 @@ def process_file(file):
 
     # 6. ZipCode
     if "Shipping ZIP" in df.columns:
-        output_df["ZipCode"] = df["Shipping ZIP"].astype(str)
+        output_df["ZipCode"] = df["Shipping ZIP"]
 
     # 7. CountryCode
     if "Shipping Country Code" in df.columns:
         output_df["CountryCode"] = df["Shipping Country Code"]
 
-    # 8. Pad US 4-digit Zips with leading apostrophe
-    zip_str = output_df["ZipCode"].fillna("")
-    mask_us = (output_df.get("CountryCode","") == "US") & zip_str.str.match(r'^\d{4}$')
-    output_df.loc[mask_us, "ZipCode"] = "'" + zip_str.str.zfill(5)
-
-    # 9. phone
+    # 8. phone
     if "Shipping Address Phone" in df.columns:
         output_df["phone"] = df["Shipping Address Phone"]
 
-    # 10. PackageWeight (kg)
+    # 9. PackageWeight: Total Weight (g) → kg
     if "Total Weight" in df.columns:
         output_df["PackageWeight"] = df["Total Weight"] / 1000
 
-    # 11. DeclaredQuantity1
+    # 10. DeclaredQuantity1: sum of Quantity per Order Number
     if "Order Number" in df.columns and "Quantity" in df.columns:
         output_df["DeclaredQuantity1"] = df.groupby("Order Number")["Quantity"].transform("sum")
 
-    # 12. Defaults & RoutingCode
-    mask = output_df["CustomerOrderNo."].astype(bool)
-    mask_no = mask & (output_df["CountryCode"] == "NO")
-    mask_oth= mask & (output_df["CountryCode"] != "NO")
-    output_df.loc[mask_oth, "RoutingCode"] = "HKTHZXR"
-    output_df.loc[mask_no,  "RoutingCode"] = "HK-ASS-PF"
-
-    defaults = {
-        "UnitPrice1":2, "CurrencyCode":"USD",
-        "ItemDescription1":"Eye Cosmetic Accessories",
-        "UnitWeight1":0.02,
-        "ForeignItemDescription1":"Eye Cosmetic Accessories"
-    }
-    for col,val in defaults.items():
-        output_df.loc[mask, col] = val
-
-    # 13. AdditionalServices for EU
-    EU = {"AT","BE","BG","CY","CZ","DE","DK","EE","ES","FI",
-          "FR","HR","HU","IE","IT","LT","LU","LV","MT","NL",
-          "PL","PT","RO","SE","SI","SK","GR"}
-    mask_eu = mask & output_df["CountryCode"].isin(EU)
-    output_df.loc[mask_eu, "AdditionalServices"] = "v1"
-
-    # Remove duplicates
+    # 11. Fixed defaults and conditional RoutingCode
+    mask = output_df["CustomerOrderNo."].notna() & (output_df["CustomerOrderNo."] != "")
+    # Norway code
+    mask_norway = mask & (output_df["CountryCode"] == "NO")
+    mask_other  = mask & (output_df["CountryCode"] != "NO")
+    # RoutingCode assignments
+    output_df.loc[mask_other, "RoutingCode"] = "HKTHZXR"
+    output_df.loc[mask_norway, "RoutingCode"] = "HK-ASS-PF"
+    # Other fixed values
+    output_df.loc[mask, "UnitPrice1"]              = 2
+    output_df.loc[mask, "CurrencyCode"]            = "USD"
+    output_df.loc[mask, "ItemDescription1"]        = "Eye Cosmetic Accessories"
+    output_df.loc[mask, "UnitWeight1"]             = 0.02
+    # ForeignItemDescription1
+    output_df.loc[mask, "ForeignItemDescription1"] = "Eye Cosmetic Accessories"
+    # EU AdditionalServices
+    EU_COUNTRIES = {"AT","BE","BG","CY","CZ","DE","DK","EE","ES","FI",
+                    "FR","HR","HU","IE","IT","LT","LU","LV","MT","NL",
+                    "PL","PT","RO","SE","SI","SK","GR"}
+    mask_eu = mask & output_df["CountryCode"].isin(EU_COUNTRIES)
+    output_df.loc[mask_eu, "AdditionalServices"]    = "v1"
+
+    # 12. Remove duplicate rows based on CustomerOrderNo.
     output_df = output_df.drop_duplicates(subset=["CustomerOrderNo."], keep="first")
 
-    # Save file
-    hk = pytz.timezone("Asia/Hong_Kong")
-    date = datetime.now(hk).strftime("%y%m%d")
-    name = f"yunexpress {date}.xlsx"
-    output_df.to_excel(name, index=False)
-    return output_df, name
+    # 13. Generate output filename using HK date
+    hk_tz = pytz.timezone("Asia/Hong_Kong")
+    today_hk = datetime.now(hk_tz).strftime("%y%m%d")
+    output_file_name = f"yunexpress {today_hk}.xlsx"
+
+    # Save to Excel
+    output_df.to_excel(output_file_name, index=False)
+
+    return output_df, output_file_name
 
-# Interface
-demo = gr.Blocks()
-with demo:
+# Gradio interface
+with gr.Blocks(title="Shipping - YunExpress") as demo:
     gr.Markdown("# Shipping - YunExpress")
-    file_input = gr.File(label="Upload Excel File with a YunExpress sheet")
-    btn = gr.Button("Process Data")
-    out_table = gr.DataFrame()
-    out_file  = gr.File(label="Download Processed File")
-    btn.click(process_file, [file_input], [out_table, out_file])
+    with gr.Row():
+        file_input = gr.File(label="Upload Excel File with a YunExpress sheet")
+        process_button = gr.Button("Process Data")
+    with gr.Row():
+        output_data = gr.DataFrame()
+        output_file_component = gr.File(label="Download Processed File")
+    process_button.click(fn=process_file, inputs=[file_input], outputs=[output_data, output_file_component])
+
+    # Restored original hyperlinks + Yunexpress link
     gr.HTML(
         """
-        <div style="text-align:center;font-size:16px;margin-top:20px;">
+        <div style="text-align: center; font-size: 16px; margin-top: 20px;">
             <h3>Shipping Tools</h3>
             <a href="https://huggingface.co/spaces/leadingbridge/shipping-dhl-e-commerce">DHL</a> | 
             <a href="https://huggingface.co/spaces/leadingbridge/shipping-ec-ship">EC-Ship</a> | 
@@ -137,7 +138,7 @@ with demo:
             <a href="https://huggingface.co/spaces/leadingbridge/shipping-UPS">UPS</a><br>
             <a href="https://huggingface.co/spaces/leadingbridge/shipping-yunexpress">Yunexpress</a>
         </div>
-        <div style="text-align:center;font-size:16px;margin-top:20px;">
+        <div style="text-align: center; font-size: 16px; margin-top: 20px;">
             <h3>Administration Tools</h3>
             <a href="https://huggingface.co/spaces/leadingbridge/email-template">Email Template</a> | 
             <a href="https://huggingface.co/spaces/leadingbridge/product-feed">Google Merchant</a> | 
@@ -146,4 +147,4 @@ with demo:
         """
     )
 
-demo.launch()
+demo.launch()