Automate Excel-to-Word Reporting with Python: A Step‑by‑Step Guide

Introduction

In a previous article we showed how to extract data from Word tables to Excel. This article demonstrates how to use Python to read data from an Excel file, process it, and automatically fill a Word document according to specific rules.

Requirements

The Excel data contains many rows, duplicates, and must be transformed and written into a Word file. The output Word filename must also follow a naming convention.

Python implementation – Excel parsing

from openpyxl import load_workbook
import os
# 获取桌面的路径
def GetDesktopPath():
    return os.path.join(os.path.expanduser("~"), 'Desktop')

path = GetDesktopPath() + '/资料/'  # 形成文件夹的路径便后续重复使用
workbook = load_workbook(filename=path + '数据.xlsx')
sheet = workbook.active  # 获取当前页
# 可以用代码获取数据范围，如果要批处理循环迭代也方便
# 获取有数据范围
print(sheet.dimensions)  # A1:W10

Using openpyxl we read cells, deduplicate values, format strings, compute totals, and build a descriptive filename.

Converting .doc to .docx (Windows)

# pip install pypiwin32
from win32com import client

def doc2docx(doc_path, docx_path):
    word = client.Dispatch("Word.Application")
    doc = word.Documents.Open(doc_path)
    doc.SaveAs(docx_path, 16)
    doc.Close()
    word.Quit()
    print('
 doc文件已转换为docx 
')

if not os.path.exists(docx_path):
    doc2docx(doc_path, docx_path)

This converts legacy .doc templates to .docx so they can be processed with python-docx.

Word filling

from docx import Document

document = Document(docx_path)
tables = document.tables
# Example of writing values
tables[0].cell(1, 1).text = SQE
tables[1].cell(1, 1).text = supplier
tables[1].cell(2, 1).text = supplier
tables[1].cell(3, 1).text = ptype
tables[1].cell(4, 1).text = info
tables[1].cell(5, 1).text = order_num
tables[1].cell(7, 1).text = time

All data must be converted to strings before writing, and table indices start at 0.

Filling a detailed table

for i in range(2, 11):
    tables[6].cell(i, 0).text = str(sheet[f'T{i}'].value)
    tables[6].cell(i, 1).text = str(sheet[f'P{i}'].value)
    tables[6].cell(i, 2).text = str(sheet[f'C{i}'].value)
    tables[6].cell(i, 4).text = str(sheet[f'V{i}'].value)
    tables[6].cell(i, 5).text = str(sheet[f'V{i}'].value)
    tables[6].cell(i, 6).text = '0'
    tables[6].cell(i, 7).text = str(sheet[f'W{i}'].value)
    tables[6].cell(i, 8).text = '0'

tables[6].cell(12, 4).text = str(total_num)
tables[6].cell(12, 5).text = str(total_num)
tables[6].cell(12, 7).text = str(box_num)

Note that merged cells or custom layouts may require index adjustments.

Saving the document

document.save(path + f'{title}.docx')
print('
文件已生成')

Key details

Convert all extracted values to strings before writing to Word.

Table structures may include merged cells; verify indices during development.

Conclusion

After populating all required tables and saving the document, the automated report is generated. Consider whether the task is repetitive enough to justify automation with Python, as manual effort may be sufficient for one‑off cases.