Python操作Markdown格式文件的全攻略

from io import StringIO
md_text = """# 学生成绩表
| ID | Name  | Score ||----|-------|-------|| 1  | Alice | 95    || 2  | Bob   | 88    || 3  | Carol | 90    |"""
# 创建内存中文本文件对象buf = StringIO(md_text)print(buf.read())

students = [    {"id": 1, "name": "Alice", "score": 95},    {"id": 2, "name": "Bob", "score": 88},    {"id": 3, "name": "Carol", "score": 90},]

students = [    {"id": 1, "name": "Alice", "score": 95},    {"id": 2, "name": "Bob", "score": 88},    {"id": 3, "name": "Carol", "score": 90},]
# 表
头md_lines = ["| ID | Name | Score |", "|----|------|-------|"]
# 添加每一行
for s in students:    md_lines.append(f"| {s['id']} | {s['name']} | {s['score']} |")
# 写入 Markdown 文件
with open("students.md", "w", encoding="utf-8") as f:    f.write("\n".join(md_lines))
print("students.md 文件已保存。")

students = [    {"id": 1, "name": "Alice", "score": 95},    {"id": 2, "name": "Bob", "score": 88},    {"id": 3, "name": "Carol", "score": 90},]
md_lines = []
# 标题
md_lines.append("# 学生成绩分析")
# 列表
top_students = [s for s in students if s["score"] >= 90]md_lines.append("- 高分学生：")for s in top_students:    md_lines.append(f"  - {s['name']}：{s['score']}")
# 代码块
md_lines.append("\n```python")md_lines.append("print('Hello, Markdown!')")md_lines.append("```")
# 写入文件
with open("analysis.md", "w", encoding="utf-8") as f:    f.write("\n".join(md_lines))
print("analysis.md 文件已保存。")

import markdown
with open("students.md", "r", encoding="utf-8") as f:    md_content = f.read()
html_content = markdown.markdown(md_content)
# 保存 HTML 文件
with open("students.html", "w", encoding="utf-8") as f:    f.write(html_content)
print("students.html 已生成，可在浏览器中查看。")

import pandas as pd
df = pd.DataFrame(students)
# 生成 Markdown 表格md_table = df.to_markdown(index=False)print(md_table)
# 保存到文件with open("students_table.md", "w", encoding="utf-8") as f:    f.write(md_table)

import pandas as pdimport markdown
# 构造原始数据
students = [    {"id": 1, "name": "Alice", "score": 95},    {"id": 2, "name": "Bob", "score": 88},    {"id": 3, "name": "Carol", "score": 90},    {"id": 4, "name": "David", "score": 70},]
df = pd.DataFrame(students)
# 筛选高分学生
top_students = df[df["score"] >= 90]
# 生成 Markdown 表格
md_lines = ["# 高分学生表", top_students.to_markdown(index=False)]with open("top_students.md", "w", encoding="utf-8") as f:    f.write("\n".join(md_lines))
# 渲染为 HTML
with open("top_students.md", "r", encoding="utf-8") as f:    md_content = f.read()
html_content = markdown.markdown(md_content)with open("top_students.html", "w", encoding="utf-8") as f:    f.write(html_content)
print("top_students.md 与 top_students.html 已生成。")

import markdownfrom bs4 import BeautifulSoup
# 读取 Markdown 文件
with open("top_students.md", "r", encoding="utf-8") as f:    md_content = f.read()
# 渲染为 HTML
html_content = markdown.markdown(md_content)
# 使用 BeautifulSoup 解析 HTML
soup = BeautifulSoup(html_content, "html.parser")
# 提取标题
title = soup.find(["h1", "h2", "h3"])print("标题：", title.text)
# 提取表格
table = soup.find("table")rows = []for tr in table.find_all("tr"):    cells = [td.get_text(strip=True) for td in tr.find_all(["th", "td"])]    rows.append(cells)
print("表格内容：")for r in rows:    print(r)

import re
with open("top_students.md", "r", encoding="utf-8") as f:    md_content = f.read()
# 匹配 Markdown 表格行
lines = md_content.splitlines()table_rows = []
for line in lines:    if "|" in line and not re.match(r"^\s*#|^-{2,}", line):        cells = [cell.strip() for cell in line.strip("|").split("|")]        table_rows.append(cells)
print("解析表格：")for row in table_rows:    print(row)

import pandas as pdimport markdownfrom bs4 import BeautifulSoup
# 读取 Markdown 并渲染为 HTML
with open("top_students.md", "r", encoding="utf-8") as f:    md_content = f.read()
html_content = markdown.markdown(md_content)soup = BeautifulSoup(html_content, "html.parser")
# 提取表格数据
table = soup.find("table")rows = []for tr in table.find_all("tr"):    cells = [td.get_text(strip=True) for td in tr.find_all(["th", "td"])]    rows.append(cells)
# 转换为 DataFrame
df = pd.DataFrame(rows[1:], columns=rows[0])df["score"] = df["score"].astype(int)
# 统计平均分
avg_score = df["score"].mean()print(df)print(f"平均分：{avg_score:.1f}")