courlan

What it is and what it does

Courlan is a URL processing library designed to improve web crawler efficiency and document collection quality. It provides validation, normalization, filtering, and sampling functions that work together to identify high-value pages and discard low-quality content before crawling begins. The library filters out spam, tracking parameters, and platform-specific pages, and can apply language-aware heuristics to target specific locales.

The package is built on three runtime dependencies (babel, tld, urllib3) and offers both programmatic Python functions and command-line utilities. It includes specialized tools for crawl frontier management—distinguishing navigation pages from content pages, detecting non-crawlable URLs, and handling relative link resolution—making it useful for anyone building a web crawler, scraper, or bulk document collection pipeline.

Use it for:

• Filter out tracker parameters and spam domains before crawling to reduce bandwidth waste and improve document quality.
• Sample representative URLs from a large domain to avoid redundant crawling and focus on diverse content.
• Extract and prioritize links from HTML with language filtering to target content in specific locales.
• Normalize and deduplicate URLs across multiple sources to prevent re-crawling the same page.
• Identify navigation and overview pages separately from content pages to optimize crawl scheduling.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Validates, normalizes, filters, and samples URLs for web crawling and document collection, removing spam, trackers, and low-value pages while respecting language and content-type constraints.

Yes. Courlan is actively maintained, has no known vulnerabilities, and offers a focused, well-scoped toolkit for URL handling in crawling workflows. The permissive Apache-2.0 license and low install friction make it a practical choice for web scraping and document collection projects. Install it if you are building a crawler or bulk collection pipeline and need to filter, normalize, or sample URLs at scale.

Install

courlan on PyPI

pip install courlan

uv add courlan

poetry add courlan

Installing courlan

Before you install

Low install friction with three lightweight runtime dependencies (babel, tld, urllib3). Active maintenance with a recent release 74 days ago and ongoing repository activity.

License in practice

Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.

Quickstart

pip install courlan

from courlan import check_url, sample_urls, extract_links

# Validate and clean a URL
url, domain = check_url('https://example.org/page?utm_source=twitter')

# Sample URLs from a collection
sampled = sample_urls(['https://example.org/' + str(i) for i in range(100)], 10)

# Extract and filter links from HTML
links, priority_links = extract_links('<a href="/page">link</a>', 'https://example.org')

Requires Python 3.10 or higher; earlier versions (3.6–3.9) require older courlan releases.

Verify before relying

• Performance characteristics when processing large URL collections (millions of URLs).
• Accuracy of language detection and filtering heuristics across different URL patterns.
• Whether the package handles internationalized domain names (IDN) correctly.

Package facts

Evidence: courlan-1.4.0-py3-none-any.whl

Keywords: cleaner, crawler, uri, url-parsing, url-manipulation, urls, validation, webcrawling

Tags

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