# FYI: fast.ai's "fastcore \[adds\] to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia"

**URL:** <https://discourse.julialang.org/t/fyi-fast-ais-fastcore-adds-to-python-features-inspired-by-other-languages-we-ve-loved-like-multiple-dispatch-from-julia/46794>\
**Category:** Offtopic\
**Created:** [September 17, 2020, 5:20pm UTC](https://discourse.julialang.org/t/fyi-fast-ais-fastcore-adds-to-python-features-inspired-by-other-languages-we-ve-loved-like-multiple-dispatch-from-julia/46794 "2020-09-17T17:20:22Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Palli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/palli/32/3380_2.png) [@Palli](https://discourse.julialang.org/u/Palli)\
**Post date:** [September 17, 2020, 5:20pm UTC](https://discourse.julialang.org/t/fyi-fast-ais-fastcore-adds-to-python-features-inspired-by-other-languages-we-ve-loved-like-multiple-dispatch-from-julia/46794/1 "2020-09-17T17:20:22Z")

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On their homepage:

> Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. [fastcore](https://fastcore.fast.ai) uses this flexibility to add to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and cleans up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s list type.

There is a port to replicated FastAI in Julia (incomplete?):

> **[GitHub - FluxML/FastAI.jl: Repository of best practices for deep learning in...](https://github.com/FluxML/FastAI.jl)**
>
> Repository of best practices for deep learning in Julia, inspired by fastai - GitHub - FluxML/FastAI.jl: Repository of best practices for deep learning in Julia, inspired by fastai

I’m just thinking, will we not win people over to Julia? I suppose the publicity is good, that people, are inspired by Julia.

> **[Machine Learning In Just 5 Lines Of Code: Fast.ai's New Release](https://analyticsindiamag.com/machine-learning-code-fastai-library/)**
>
> Fast.ai makes it easy to migrate from PyTorch, Ignite, or any other PyTorch-based library, or use fastai in conjunction with other libraries.

> **[fastcore: An Underrated Python Library](https://fastpages.fast.ai/fastcore/)**
>
> A unique python library that extends the python programming language and provides utilities that enhance productivity.

> **[GitHub - fastai/fastcore: Python supercharged for the fastai library](https://github.com/fastai/fastcore)**
>
> Python supercharged for the fastai library. Contribute to fastai/fastcore development by creating an account on GitHub.

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**Author:** ![ToucheSir](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/touchesir/32/14411_2.png) [@ToucheSir](https://discourse.julialang.org/u/ToucheSir)\
**Post date:** [September 17, 2020, 5:49pm UTC](https://discourse.julialang.org/t/fyi-fast-ais-fastcore-adds-to-python-features-inspired-by-other-languages-we-ve-loved-like-multiple-dispatch-from-julia/46794/2 "2020-09-17T17:49:05Z")

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In case you weren’t following the discussion on Slack, [this talk](https://www.wandb.com/podcast/jeremy-howard) may be interesting. Most of the FastAI and (Flux)ML ecosystem discussion happens on Slack and Zulip, with [https://github.com/FluxML/ML-Coordination-Tracker](https://github.com/FluxML/ML-Coordination-Tracker) as the jumping-off point.