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Extending Clojure with Python - Chris Nuernberger
Chris Nuernberger explores how Clojure and Python can be seamlessly integrated for machine learning and numeric computations, bridging the gap between their strengths and achieving high performance.
- Python and Clojure can be extended to work together seamlessly
- Libpython-clj provides a way to access Python objects from Clojure without copying
- The main idea behind libpython-clj is to intermix Python and Clojure, so users can leverage the strengths of both languages
- The author’s company, Galvanize, has been working on a numeric stack that incorporates Python and Clojure
- The author extols the virtues of the REPL in both languages, saying it’s essential for language design
- Python and Clojure can be used together to extend the functionality of each language
- The author encourages users to try using Python with Clojure, especially for machine learning and numeric computations
- The author highlights the challenges of working with native libraries and the importance of understanding the language design of both Python and Clojure
- The author believes that native dependencies are the price to pay for high performance in Clojure, and that libpython-clj provides a way to make Python and Clojure interoperate seamlessly
- The author sees potential for Clojure and Python to be used together in the same system, with Clojure providing a nice REPL experience and Python providing access to high-level libraries
- The author emphasizes the importance of understanding the language model behind Python, which is based on a dictionary of attributes.
- The author also highlights the importance of Zero Copy, which allows for efficient transfer of data between Python and Clojure.