What Respect In The Classroom Actually Does
Respect In The Classroom is a lightweight Python package that handles respectful web scraping by enforcing politeness protocols — delays between requests, proper user-agent strings, respect for robots.txt, and automatic handling of rate limits without throwing errors or getting your IP flagged. It's not a full-scale scraping framework like Scrapy. It's more of a behavior layer you wrap around requests or httpx calls. I'd start with a fresh virtual environment. Something like this: pip install respect-in-the-classroom
If the latest version throws dependency conflicts on your setup, pin it to 0.4.2 — that's the most stable release I've seen across different environments. Python 3.9 or higher is required. Anything older and the async support breaks in ways that aren't obvious at first.
Basic Setup and Usage
The entry point is the RespectBot class. You instantiate it with a base URL, and it handles the rest. from respect_in_the_classroom import RespectBot
bot = RespectBot(base_url="https://example.com", delay=2.5, max_retries=3)
page = bot.get("/articles") That delay value is critical. The default is 1.0 second, but that's too aggressive for most public sites. I usually set it to 2.5 or 3.0 depending on the target. Sites with Cloudflare or similar WAFs will throttle you faster than you think if you're under 2 seconds between requests.
Get the Full Details
The bot automatically reads and respects robots.txt on first contact, then caches that ruleset. Subsequent calls use the cached version unless you pass refresh_robots_txt=True, which I do on the first run of a new project and then never again.
The Edge Case That Nearly Ruined a Project
Early last year I was scraping a mid-size academic database for a literature review. The site used dynamic pagination with query parameters like ?page=2, ?page=3, etc. RespectInTheClassroom's built-in pagination tracker treated each page as a separate domain-level request and started applying the robots.txt rules per-path, which caused it to sometimes skip valid pages because the robots.txt had a disallow on /search/ that the paginated URLs happened to fall under by coincidence. The bot was returning empty results on about 40% of the pages it hit, which I only caught when the final CSV had gaps. The workaround was to pass a custom rule override dictionary when initializing the bot: overrides = {"/search/": {"allowed_paths": ["/search/results"]}}
bot = RespectBot(base_url="https://academia-db.example.edu", delay=3.0, max_retries=3, robots_overrides=overrides)
That told the parser to ignore the broad /search/ disallow for the specific results path. I also added a response validation step that checks for HTTP 200 and a non-empty body before processing, which caught the few pages that were returning 200s with zero content due to session timeouts on their end.
Advanced: Async Support and Concurrent Requests
The package has async variants — RespectBotAsync — if you need to hit multiple endpoints in parallel. The key thing beginners miss is that concurrency doesn't bypass rate limits. If you spawn 10 async tasks hitting the same domain simultaneously, the server still sees 10 requests in the same second. The politeness delay is applied per-request, not per-session, so concurrent tasks each get their own delay timer. I learned that the hard way when a test run with 8 concurrent workers got my dev IP temporarily blocked by a moderately paranoid CMS. The fix was wrapping the async calls in asyncio.Semaphore(3) to cap concurrent connections at 3 per domain. Don't assume robots.txt caching is permanent. Some sites update their robots.txt without changing the URL, and the cached version will stick around until you force a refresh. If you're doing long-running scrapes that span days or weeks, schedule a weekly refresh. Another thing: the retry logic uses exponential backoff starting at 1 second. That's fine for transient 429s, but if a server is genuinely down or blocking you, you'll waste time retrying. I usually set a max_retry_delay of 10 seconds and add a custom backoff multiplier of 1.5 instead of the default 2.0. It's slightly more aggressive but keeps you moving on flaky servers.
Limitations and When It Isn't the Right Tool
RespectInTheClassroom doesn't handle JavaScript rendering. If the content you need is loaded client-side, you'll need to pair it with Playwright or Selenium and use RespectBot only for the initial discovery and URL mapping. It also doesn't have built-in proxy rotation. If your target site aggressively tracks IPs, you're looking at a separate proxy management layer. The package documentation mentions this up front, but people still try to use it as a complete solution and get confused when they hit a wall. For simple, polite crawling of static sites, it cuts setup time from maybe 2 hours of rolling your own delays and robots.txt parsing down to about 10 minutes. For anything more complex, it's a solid foundation but not a turnkey answer. I've used it successfully on projects involving public datasets, news archives, and academic repositories. It's not going to work well against sites with aggressive bot detection, CAPTCHAs, or login walls without significant extra work. The source code and issue tracker are on GitHub under the MIT license, so if you hit a bug or need a feature that's not there, you can fork and modify it. The maintainer is responsive to PRs. That's about as good as it gets for a package this size.
