Python What are the limitations of Codon, the new Python compiler?

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The MIT press release highlights the introduction of Codon, a new compiler that allows any working Python module to be compiled once and then executed over ten times faster than interpreted code, significantly enhancing Python's performance. Codon employs a specialized type checking algorithm and a novel bidirectional intermediate representation (IR) to optimize dynamic code across various domains, achieving performance levels comparable to C/C++ while maintaining high-level simplicity. However, the framework currently lacks support for certain Python features, including runtime polymorphism, reflection, and type manipulation, which may limit its applicability for some projects. Additionally, Codon faces challenges related to the extensive dependencies often required to run Python code, complicating efforts to streamline applications, particularly in environments like Docker. Future developments aim to expand Codon's compatibility with Python libraries and enhance its feature set to support more dynamic Python code.
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Python is largely an interpreted language, Codon compiles Python into fast executable images.
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This work is long overdue for Python and I'm glad its being addressed. However, there are some caveats listed in their paper conclusion mainly to do with the dynamic features of python.

One other issue with python is the need to pull in so much extra stuff to run your code. Sadly, it's very difficult to trim your code down to a minimal level. I ran into this issue while doing docker images.

https://groups.csail.mit.edu/commit/papers/2023/cc_Codon.pdf

6 Conclusion

We have introduced Codon, a domain-configurable framework for designing and rapidly implementing Pythonic DSLs. By applying a specialized type checking algorithm and novel bidirectional IR, Codon enables easy optimization of dynamic code in a variety of domains. Codon DSLs achieve considerable performance benefits over Python and can match C/C++ performance without compromising high-level simplicity. We note that Codon is already being used commercially in quantitative finance and bioinformatics.

Currently, there are several Python features that Codon does not support. They mainly consist of runtime polymorphism, runtime reflection and type manipulation (e.g., dynamic method table modification, dynamic addition of class members, metaclasses, and class decorators). There are also gaps in the standard Python library coverage. While Codon ships with Python interoperability as a workaround to some of these limitations, future work is planned to expand the amount of Pythonic code immediately compatible with the framework by adding features such as runtime polymorphism and by implementing better interoperability with the existing Python libraries. Finally, we plan to increase the standard library coverage, as well as extend syntax configurability for custom DSLs.
 
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