Question 1

How do I find the best Common Lisp library for web development?

Accepted Answer

Browse the 'Web frameworks' and 'HTTP Servers' sections in Awesome Common Lisp, which list options like Hunchentoot and Clack. Look for community-standard marks (⭐) or recommendations (👍) to identify stable, popular choices, and check if libraries support your needs like PostgreSQL or websockets.

Question 2

What are the top Common Lisp libraries for machine learning?

Accepted Answer

Awesome Common Lisp highlights MGL for neural networks and clml for general ML, both with noted real-world use cases. The README also mentions newer tools like llama.cl for LLM inference, so review the AI section for updates and community endorsements to gauge suitability.

Question 3

Awesome Common Lisp vs other Lisp resource lists like Awesome Lisp?

Accepted Answer

Awesome Common Lisp focuses exclusively on Common Lisp with curated, quality-filtered entries and active maintenance, while broader lists might include Scheme or Clojure with less depth. For Common Lisp-specific discovery, this list is more comprehensive and practical, but check multiple sources for niche topics.

Question 4

How to contribute a library to Awesome Common Lisp?

Accepted Answer

Follow the contributing guidelines in the README, which typically involve submitting a pull request on GitHub. Ensure your library is available via Quicklisp and includes a clear description, as the maintainers prioritize production-ready tools with community relevance.

Question 5

Is there a search function for Awesome Common Lisp?

Accepted Answer

No built-in search exists; you must use GitHub's text search or browse the table of contents manually. This static format can make finding specific libraries tedious, so consider using browser find tools or external indexes for efficiency.

Question 6

How often is Awesome Common Lisp updated?

Accepted Answer

The README notes regular updates with new contributions, but frequency depends on community activity. Check the GitHub commit history for recent changes, as updates can be sporadic in less active periods, potentially missing cutting-edge developments.

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