# Using Python packages in Julia

**URL:** <https://discourse.julialang.org/t/using-python-packages-in-julia/27183>\
**Category:** New to Julia\
**Created:** [August 5, 2019, 5:06pm UTC](https://discourse.julialang.org/t/using-python-packages-in-julia/27183 "2019-08-05T17:06:35Z")\
**Posts on this page:** 1\
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**Author:** ![stillyslalom](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/stillyslalom/32/45687_2.png) [@stillyslalom](https://discourse.julialang.org/u/stillyslalom)\
**Post date:** [August 5, 2019, 6:17pm UTC](https://discourse.julialang.org/t/using-python-packages-in-julia/27183/2 "2019-08-05T18:17:40Z")

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PyCall.jl is solid, and usage is [pretty straightforward](https://github.com/JuliaPy/PyCall.jl#usage). That said, using it fluidly requires fluency in both Julia and Python, since the syntax ends up midway between both. If the core of your work revolves around a large library with a Python frontend (_e.g._ Tensorflow, OpenCV), better to just write Python, but if you’re doing à la carte numerical work, give Julia a try. You can call Python as needed, but you’ll probably find that almost everything in NumPy and SciPy can be done natively with Julia packages.

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