name: python-automation description: "Full-stack Python automation toolkit for file processing, data extraction, PDF manipulation, Excel/workbook automation, web scraping, and system tasks. Use when the user needs to: (1) Process/rename/organize files in bulk, (2) Extract data from PDFs, CSVs, or web pages, (3) Generate or modify Excel reports, (4) Automate repetitive system tasks (cron, file watching), (5) Build quick CLI tools for data processing."

Python Automation

Core Libraries Quick Reference

Common Patterns

1. Batch File Processing

from pathlib import Path

for f in Path(".").glob("**/*.txt"):
    content = f.read_text()
    # transform content
    f.write_text(content)

2. CSV Read/Write

import csv
with open("input.csv", newline="") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row["column_name"])

with open("output.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerow(["col1", "col2"])
    writer.writerow(["val1", "val2"])

3. Excel Generation

from openpyxl import Workbook
wb = Workbook()
ws = wb.active
ws["A1"] = "Hello"
ws["B1"] = 42
wb.save("output.xlsx")

4. Web Scraping

import requests
from bs4 import BeautifulSoup

resp = requests.get("https://example.com", timeout=10)
soup = BeautifulSoup(resp.text, "html.parser")
for link in soup.select("a[href]"):
    print(link["href"], link.text.strip())

Scripts

更多技能请访问小葱技能站7w4.net。

See scripts/ for ready-to-use automation scripts: - rename_batch.py — Batch rename files with pattern matching - csv_to_excel.py — Convert CSV files to Excel workbooks

Reference Files

• references/pandas.md — Advanced data analysis with pandas
• references/pdf.md — PDF extraction patterns

这个Skill质量较好，内容全面且实用，适合日常Python自动化任务。代码示例丰富、可直接运行，脚本拿来就能用。不足之处是某些边界情况（如文件损坏、编码错误）缺少处理指引，部分高级功能尚有欠缺，对新手不太友好。总体而言是一个实用的工具包，但使用时要留意自行处理异常情况。