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As seen in: Towards Data Science
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Articles by Using PyCall

Embracing Julia: An Invitation Letter

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By Essam Wisam, Using PyCall
| Towards Data Science
Warmly Extended to Python Lovers, Scientific Computing Wizards and Data Scientists Julia is a general-purpose, dynamic, high-performance and high-level programming language that is just-in-time compiled. It’s a fairly recent language with its major 1.0 release rolled out only in 2018. In this story, we aim to demonstrate that this language is absolutely worth adding to your arsenal if you are into data science, scientific computing or are just an avid Python user.
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Julia编程04：Julia调用R和Python

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By using Pkg, Using PyCall, using RCall
| 360doc.com
参考使用homebrew管理linux和mac软件安装homebrew、mamba和Python Python环境 mamba create -y -n jlpy python=3.10 mamba activate jlpy mamba install matplotlib which python # /opt/homebrew/Caskroom/mambaforge/base/envs/jlpy/bin/python R环境 在R中运行，找到R_HOME R.home() # /Library/Frameworks/R.framework/Resources Build 在Julia中运行 using Pkg Pkg.add(["PyCall","RCall"]) ENV["PYTHON"]="/opt/homebrew/Caskroom/mambaforge/base/envs/jlpy/bin/python" Pkg.build("PyCall") ENV["R_HOME"] = "/Library/Frameworks/R.framework/Resources"...
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How To Use PyCall.jl: Python Libraries In Julia

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By Emmett Boudreau, using Pkg, Using PyCall
| Towards Data Science
A confession I must make is that I have not used the PyCall.jl package in a long time. Frankly, Julia’s ecosystem has grown dramatically since the last time I touched the package, and so has the language’s user-base.
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