Update app.py

app.py

@@ -8,11 +8,20 @@ import os, re
 from collections import defaultdict
 from datetime import datetime
 
+# Hugging Face dataset + template config
 HF_DATASET_REPO = "leadingbridge/ammu"
 TEMPLATE_FILENAME = "AMMU-order-form-template.xlsx"
+# If you place the template in the Space repo, this will be used first (offline-friendly)
 LOCAL_TEMPLATE_FALLBACK = os.path.join(os.path.dirname(__file__), TEMPLATE_FILENAME)
 
+# -----------------------
+# Helpers
+# -----------------------
 def _normalize_power(val):
+    """
+    Normalize input "Product Option Value" to match template textual labels, e.g. '0.00', '-1.25'.
+    Accepts variations like 'Plano', '0', '-1', '-1.0', etc.
+    """
     if val is None:
         return None
     s = str(val).strip()
@@ -30,6 +39,10 @@ def _normalize_power(val):
     return f"{num:.2f}"
 
 def _power_to_triplet_digits(power_str: str) -> str:
+    """
+    Convert textual power to numeric triplet fallback:
+      '-1.25' -> '125', '0.00' -> '000', '-4.00' -> '400'
+    """
     if power_str is None:
         return None
     s = power_str.strip().lstrip("+").replace("-", "")
@@ -42,6 +55,10 @@ def _power_to_triplet_digits(power_str: str) -> str:
     return digits.zfill(3)
 
 def _find_header_row(ws: Worksheet, required_headers):
+    """
+    In the INPUT sheet: find a header row (top 10 rows) that contains all required headers (case-insensitive).
+    Returns (row_index, {header_lower: col_index})
+    """
     req = {h.lower() for h in required_headers}
     for r in range(1, 11):
         header_map = {}
@@ -58,6 +75,9 @@ def _find_header_row(ws: Worksheet, required_headers):
     raise ValueError(f"Could not locate a header row containing: {required_headers}")
 
 def _download_template():
+    """
+    Get the template file path, preferring a local copy, else downloading from HF dataset.
+    """
     if os.path.exists(LOCAL_TEMPLATE_FALLBACK):
         return LOCAL_TEMPLATE_FALLBACK
     return hf_hub_download(
@@ -65,7 +85,9 @@ def _download_template():
     )
 
 def _auto_fit_columns(ws: Worksheet, max_col: int, max_row: int):
-    # Width = longest string in column + small padding
+    """
+    Fit columns based on longest string length in column with small padding.
+    """
     for c in range(1, max_col + 1):
         max_len = 0
         col_letter = get_column_letter(c)
@@ -75,16 +97,19 @@ def _auto_fit_columns(ws: Worksheet, max_col: int, max_row: int):
                 max_len = max(max_len, len(str(val)))
         ws.column_dimensions[col_letter].width = max(10, max_len + 2)
 
+# -----------------------
+# Core processing
+# -----------------------
 def process(input_file):
     try:
         if input_file is None:
             return None, "Please upload an Excel file first."
 
-        # --- INPUT: detect headers by name ---
+        # --- INPUT: read and detect headers
         wb_in = load_workbook(input_file.name, data_only=True)
         ws_in = wb_in.active
 
-        # Copy ALL input (for "raw data" sheet later)
+        # For "raw data" tab later
         in_max_row = ws_in.max_row
         in_max_col = ws_in.max_column
 
@@ -97,6 +122,7 @@ def process(input_file):
 
         header_values = [ws_in.cell(row=header_row_idx, column=c).value for c in range(1, in_max_col + 1)]
 
+        # Collect entries (line-by-line) so we can keep unmatched verbatim
         entries = []
         rows_scanned = 0
         for r in range(header_row_idx + 1, ws_in.max_row + 1):
@@ -110,6 +136,7 @@ def process(input_file):
             rows_scanned += 1
 
             power = _normalize_power(pov)
+            # robust int conversion
             try:
                 q = int(qty) if qty is not None and str(qty).strip() != "" else 0
             except Exception:
@@ -125,11 +152,15 @@ def process(input_file):
                 "row_values": row_values
             })
 
-        # --- OUTPUT template ---
+        # --- OUTPUT: load the AMMU template
         template_path = _download_template()
         wb_out = load_workbook(template_path)
         ws_out = wb_out.active
 
+        # Find:
+        #   (A) "MY SKU" header to build SKU->row map (instead of "SKU")
+        #   (B) textual power labels (e.g. 0.00, -1.25)
+        #   (C) triplet labels (e.g. 000, 125) as fallback
         mysku_header_row = None
         mysku_col_idx = None
         power_label_row = None
@@ -139,12 +170,14 @@ def process(input_file):
 
         for r in range(1, 11):
             row_vals = [ws_out.cell(row=r, column=c).value for c in range(1, ws_out.max_column + 1)]
-            # "MY SKU" header
+
+            # (A) MY SKU
             for c, v in enumerate(row_vals, start=1):
                 if isinstance(v, str) and v.strip().lower() == "my sku":
                     mysku_header_row = r
                     mysku_col_idx = c
-            # textual power labels
+
+            # (B) textual powers
             labels = {}
             for c, v in enumerate(row_vals, start=1):
                 if isinstance(v, str):
@@ -154,7 +187,8 @@ def process(input_file):
             if len(labels) >= 5 and power_label_row is None:
                 power_label_row = r
                 power_col_map = labels
-            # numeric triplets
+
+            # (C) numeric triplets
             trip = {}
             for c, v in enumerate(row_vals, start=1):
                 if isinstance(v, str) and re.fullmatch(r"\d{2,3}", v.strip()):
@@ -177,28 +211,33 @@ def process(input_file):
             sku_to_row[str(val).strip()] = r
 
         # Classify entries and aggregate matches
-        agg = defaultdict(int)
-        unmatched_rows = []
+        agg = defaultdict(int)   # (sku, power) -> total qty
+        unmatched_rows = []      # verbatim rows to copy to "additional order"
 
         for rec in entries:
             sku, power, qty = rec["sku"], rec["power"], rec["qty"]
+            # Basic validation
             if not sku or qty <= 0 or power is None:
                 unmatched_rows.append(rec["row_values"])
                 continue
+
             row_idx = sku_to_row.get(sku)
             if row_idx is None:
                 unmatched_rows.append(rec["row_values"])
                 continue
+
             col_idx = power_col_map.get(power) if power_col_map else None
             if col_idx is None and triplet_col_map:
                 key = _power_to_triplet_digits(power)
                 col_idx = triplet_col_map.get(key)
+
             if col_idx is None:
                 unmatched_rows.append(rec["row_values"])
                 continue
+
             agg[(sku, power)] += qty
 
-        # Write aggregated matches
+        # Write aggregated matches to template
         written_count = 0
         for (sku, power), qty in agg.items():
             row_idx = sku_to_row.get(sku)
@@ -210,6 +249,7 @@ def process(input_file):
                 col_idx = triplet_col_map.get(key)
             if col_idx is None:
                 continue
+
             current = ws_out.cell(row=row_idx, column=col_idx).value
             try:
                 current_val = int(current) if current is not None and str(current).strip() != "" else 0
@@ -221,28 +261,37 @@ def process(input_file):
             ws_out.cell(row=row_idx, column=col_idx).value = current_val + int(qty)
             written_count += 1
 
-        # --- "additional order" tab with unmatched rows ---
+        # -----------------------
+        # "additional order" tab
+        # -----------------------
         add_name = "additional order"
         if add_name in wb_out.sheetnames:
             wb_out.remove(wb_out[add_name])
         ws_add = wb_out.create_sheet(title=add_name)
 
-        # header + rows
+        # header + unmatched rows
         for c, val in enumerate(header_values, start=1):
             ws_add.cell(row=1, column=c).value = val
         for i, row_vals in enumerate(unmatched_rows, start=2):
             for c, val in enumerate(row_vals, start=1):
                 ws_add.cell(row=i, column=c).value = val
 
-        # Auto-fit additional order
-        _auto_fit_columns(ws_add, max_col=in_max_col, max_row=len(unmatched_rows) + 1)
+        # Add custom note after the last data row
+        note_row = len(unmatched_rows) + 2  # header(1) + data(n)
+        ws_add.cell(row=note_row, column=1).value = "20片裝如無貨可以2盒10片裝代替"
+
+        # Auto-fit "additional order"
+        _auto_fit_columns(ws_add, max_col=in_max_col, max_row=max(note_row, 1))
 
-        # --- "raw data" tab with ALL input copied verbatim ---
-        raw_name = "raw data"
+        # -----------------------
+        # "Raw Data(please ignore)" tab
+        # -----------------------
+        raw_name = "Raw Data(please ignore)"
         if raw_name in wb_out.sheetnames:
             wb_out.remove(wb_out[raw_name])
         ws_raw = wb_out.create_sheet(title=raw_name)
 
+        # Copy ENTIRE input verbatim
         for r in range(1, in_max_row + 1):
             for c in range(1, in_max_col + 1):
                 ws_raw.cell(row=r, column=c).value = ws_in.cell(row=r, column=c).value
@@ -250,13 +299,16 @@ def process(input_file):
         # Auto-fit raw data
         _auto_fit_columns(ws_raw, max_col=in_max_col, max_row=in_max_row)
 
-        # --- Save output with date-based filename ---
+        # -----------------------
+        # Save output with YYMMDD suffix
+        # -----------------------
         yymmdd = datetime.now().strftime("%y%m%d")
         tmpdir = tempfile.mkdtemp()
         out_filename = f"AMMU-Order-Form-Leading-Bridge-{yymmdd}.xlsx"
         out_path = os.path.join(tmpdir, out_filename)
         wb_out.save(out_path)
 
+        # Log
         log_lines = [
             f"Rows scanned in input: {rows_scanned}",
             f"Unique matched (SKU, power) pairs aggregated: {len(agg)}",
@@ -271,14 +323,17 @@ def process(input_file):
     except Exception as e:
         return None, f"Error: {e}"
 
+# -----------------------
+# UI
+# -----------------------
 with gr.Blocks(title="AMMU Order Form Filler") as demo:
     gr.Markdown(
         "### AMMU Order Form Filler\n"
         "• Uses **MY SKU** column to map rows\n"
         "• Matches power columns (text like `-1.25` or fallback triplets like `125`)\n"
         "• Aggregates quantities for matched lines\n"
-        "• Copies **unmatched lines** to **`additional order`** (auto-fit columns)\n"
-        "• Copies **entire input** to **`raw data`** (auto-fit columns)\n"
+        "• Copies **unmatched lines** to **`additional order`** (auto-fit columns + note)\n"
+        "• Copies **entire input** to **`Raw Data(please ignore)`** (auto-fit columns)\n"
         "• Exports as **AMMU-Order-Form-Leading-Bridge-YYMMDD.xlsx**"
     )
     with gr.Row():
@@ -291,5 +346,26 @@ with gr.Blocks(title="AMMU Order Form Filler") as demo:
 
     run_btn.click(fn=process, inputs=in_file, outputs=[out_file, log_box])
 
+    # Links block at the bottom
+    gr.HTML(
+        """
+        <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> | 
+            <a href="https://huggingface.co/spaces/leadingbridge/shipping-fedex">Fedex</a> | 
+            <a href="https://huggingface.co/spaces/leadingbridge/shipping-UPS">UPS</a> | 
+            <a href="https://huggingface.co/spaces/leadingbridge/shipping-yunexpress">Yunexpress</a>
+        </div>
+        <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> | 
+            <a href="https://huggingface.co/spaces/leadingbridge/tss-order">Order Processing</a> |
+            <a href="https://huggingface.co/spaces/leadingbridge/ammu-order">Ammu Order</a>
+        </div>
+        """
+    )
+
 if __name__ == "__main__":
     demo.launch()