Nim for Python Programmers
Abhishek Kapatker (~abhishek69) |
Ever wondered if there existed a language as expressive as Python and as efficient as C/C++? Look no further then. Nim is a statically typed, compiled language with a focus on efficiency. It is versatile and borrows much of its constructs and standard library design from Python https://nim-lang.org
As Python programmers, we are used to a language which is expressive, intuitive and versatile. Python is widely lauded for its productivity, minimalistic syntax, standard library feature set and is an inspiration to newer languages like Go, Swift, and Julia. However, there are some areas like speed, distribution, and multicore processing where it lacks a good solution. Nim is a statically typed and high-performance garbage-collected language which builds upon Python’s strengths and addresses someone its weakness in an innovative way. This talk introduces Nim to Python programmers by diving into powerful language design, syntax, data and control structures, static analysis, metaprogramming, portability/distribution and standard library features. At the end of this talk, you should have learned enough to a) get started with Nim on a project b) get familiar with Nim’s growing ecosystem c) leverage/extend existing Python skills on a Nim project.
1) Intro to Nim (10mins)
2) Language tour from Python’s point of view (20 mins)
3) Things you can do with Nim + ecosystem (5 mins)
4) Q&A (5mins)
I am a language enthusiast and a Python developer at Netflix. I’ve been learning and using Nim for over a year now and I have benefited immensely from its learnings. There is a strong correlation between Nim and Python and I would like to explain that to the audience and show them a way to think problems using Nim’s construct which I am sure will help them improve their Python skills.
I am currently using Nim to write an interpreter for ‘lox language’.
More details here https://github.com/cabhishek/nimlox
International Conference Talks:
- PyCon Ukraine 2018
Python San Sebastian 2017