Boost Your Excel Workflow: Python Automation for Contract Processing

1. Introduction

The author shares a Python automation problem raised in a community group, where a fan needed to process contract data stored in multiple Excel sheets, each representing a different product. Manually filtering each sheet was time‑consuming and error‑prone.

2. Implementation

The solution adds a conditional branch for each contract type, defining separate processing functions while keeping shared logic in a single script. The code reads the Excel file, groups rows by contract number, product code, receiving unit, and city, filters out unwanted provinces, and dispatches each group to the appropriate handler.

if __name__ == '__main__':
    df = pd.read_excel("测试数据.xlsx", sheet_name="Sheet1", usecols="B,E,F,M,Q,R,U,V,X,AC,AN:AR")
    df.columns = [c.strip() for c in df.columns]
    for (b, e, m, f), df_split in df.groupby(['合同号', '商品编号', '收货单位', "城市名"]):
        m = m.strip("*")
        # 注意这里会过滤掉特殊省位
        if any(addr in f for addr in ("广东", "安徽", "浙江", "福建", "贵州")):
            continue
        if b.startswith("合同1"):
            title = "合同1"
            hetong1(title, e)
        elif b.startswith("合同2"):
            title = "合同2"
            hetong2(title, e)
        elif b.startswith("合同3"):
            title = "合同3"
            hetong3(title, e)
        else:
            print(f"该订单{b}属于其他产品！")

After integrating the functions, the script successfully automates the fan's workflow, significantly speeding up processing and eliminating manual errors.

3. Conclusion

The article outlines a practical Python automation approach for handling contract data, providing clear code and explanations that help readers implement similar solutions in their own projects.