Scrape tech documentation for errors

Scraping tech documentation for errors involves identifying inconsistencies, outdated information, broken links, typos, or technical inaccuracies in structured or unstructured documentation across a website or set of documents. Here’s how you can approach it:

1. Define the Scope

• Target: URL(s) or repositories where the documentation is hosted (e.g., https://docs.example.com)

• Content Types: HTML pages, Markdown files, PDFs, etc.

• Error Types to Detect:

  • Broken links (404s)

  • Outdated references (e.g., deprecated functions)

  • Syntax errors (in code snippets)

  • Typos and grammatical issues

  • Inconsistent terminology or formatting

2. Choose Your Tools

Scraping Tools

• BeautifulSoup + Requests (for static HTML)

• Selenium/Playwright (for dynamic JavaScript-rendered content)

• Scrapy (for large-scale crawls)

Error Detection Tools

• Link Checkers: linkchecker, broken-link-checker

• Spell Checkers: pyspellchecker, LanguageTool

• Code Validators: linters (e.g., ESLint, Pylint, JSHint)

• Custom Rules: Regex-based rules for detecting outdated terms or deprecated APIs

3. Sample Python Workflow

python
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import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import re

def find_broken_links(base_url):
    visited = set()
    broken = []

    def crawl(url):
        if url in visited or not url.startswith(base_url):
            return
        visited.add(url)
        try:
            res = requests.get(url)
            if res.status_code != 200:
                broken.append((url, res.status_code))
                return
            soup = BeautifulSoup(res.text, 'html.parser')
            for link in soup.find_all('a', href=True):
                full_url = urljoin(url, link['href'])
                crawl(full_url)
        except requests.RequestException as e:
            broken.append((url, str(e)))

    crawl(base_url)
    return broken

# Usage
broken_links = find_broken_links("https://docs.example.com")
for url, error in broken_links:
    print(f"Broken link: {url} - Error: {error}")

4. Spell Checking

Use language_tool_python or pyspellchecker:

python
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import language_tool_python

tool = language_tool_python.LanguageTool('en-US')
text = "This is a smple sentence with a eror."
matches = tool.check(text)
for match in matches:
    print(match)

5. Code Validation

Extract code snippets using regex or DOM parsing, then run them through:

• Linters (JavaScript, Python, etc.)

• Compilers (for C/C++, Java)

• Interpreters (Python, Bash)

6. Reporting

Export issues into CSV, HTML, or integrate with tools like:

• GitHub Issues

• Notion or Jira (via API)

• Static reports using Jinja templates

If you have a specific documentation source or platform (e.g., ReadTheDocs, GitHub, or a private CMS), I can provide a tailored script or solution. Let me know the target source or your preferred language/tooling.