RPython is a subset of Python that is used for writing high performance interpreters for dynamic languages. The most well-known product of this tooling is the PyPy interpreter. In this episode we had the pleasure of speaking with Maciej Fijalkowski about what RPython is, what it isn’t, what kinds of projects it has been used for, and what makes it so interesting.
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- We are recording today on December 17th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
- Today we are interviewing Maciej Fijalkowski on RPython
Interview with Maciej Fijalkowski
- How did you get introduced to Python? – Chris
- What is RPython and how does it differ from CPython? – Tobias
- Can you share some of the history of RPython in terms of the major improvements and design choices? – Tobias
- In the documentation it says that RPython is able to generate a Just In Time compiler for dynamic languages. Can you explain why that is significant and some of the ways that it does that? – Tobias
- The most well-known use of RPython is the PyPy interpreter for Python. Can you share some of the other languages that have been ported to the RPython runtime and how their performance has been improved or altered in the process? – Tobias
- Are there any languages that have been designed entirely for use with RPython, rather than translating an existing language to run on it? – Tobias
- Do you know of any cases where an application has been written to run directly on RPython? – Tobias
- What are the computer architecture and operating system platforms that RPython supports and do you have any plans to expand that support? – Tobias
- Are there any minimum hardware specifications that are necessary to be able to effectively run a language written against the RPython platform? – Tobias
- Is RPython similar in concept to other efforts like Parrot in the Perl world? – Chris
- Are there any particular areas of the project that you need help with and how can people get involved with the project? – Tobias