一個 Python 腳本，把供應商或舊商店的商品檔案轉成可直接匯入 Shopify 的 CSV

How it is run

python merge_sales.py --month 2026-10

2026-11-02 09:14:03 INFO  Folder: sales/2026-10, 9 files found
2026-11-02 09:14:03 INFO  shop-01.csv: 1,284 rows
2026-11-02 09:14:04 INFO  shop-02.xlsx: 967 rows
2026-11-02 09:14:04 WARN  shop-07.csv: 3 rows without a price skipped (lines 88, 412, 913)
2026-11-02 09:14:05 INFO  Done: 10,412 rows -> report-2026-10.xlsx (sheets "Sales" and "Totals")

Settings, not code

The column names of each shop live in settings.ini, so a new shop or a renamed column is a line there:

[columns]
date = Date, Sale date, Day
product = Product, Item, Name
quantity = Qty, Quantity, Pcs
price = Price, Unit price

A part of the code

def read_shop_file(path: Path, columns: dict[str, list[str]]) -> pd.DataFrame:
    """Reads one shop's file and gives it the report's column names."""
    table = pd.read_excel(path) if path.suffix == ".xlsx" else pd.read_csv(path, encoding="utf-8-sig")
    renamed = {}
    for name, variants in columns.items():
        found = next((c for c in table.columns if c.strip() in variants), None)
        if found is None:
            raise ReportError(f"{path.name}: no column for '{name}' (looked for {', '.join(variants)})")
        renamed[found] = name
    table = table.rename(columns=renamed)[list(columns)]
    table["shop"] = path.stem
    return table

Files: a ZIP archive with merge_sales.py (310 lines), settings.ini, requirements.txt and a README with installing Python, running the script and what each message in the log means. The client runs it on their own computer.