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I run pip3 on a Jetson Nano board which has 4 cores ARM A57 and class 1 sdcard. It is ubuntu 18.04 with nVidia repositories.

pip3 install --user pandas

Takes almost 1 hour! I have to do it multiple times because I'm building an environment over main OS and dockers. (same behavior on ubuntu and docker image)

HTOP shows that only 1 core is used at 100%; 3 others are idling.

I've thought using --user would resume "Building Wheel" process... Any option to get pip3 things go faster? Can I force Pip3 on multiple cores? It seems to be a GCC task.

Alsushi
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1 Answers1

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Download source code, run python setup.py bdist_wheel to generate a binary wheel once, upload the wheel to some internal server and install from it every time you need it:

pip install http://<internal-server>/path/to/wheels/pandas.whl

Binary wheels are installed quite fast; you only need to compile once.

Or run pip wheel pandas. Or collect all your requirements into requirements.txt and run pip wheel -r requirements.txt to build your wheelhouse. To install from it:

pip install --index-url=http://<internal-server>/path/to/wheels/ pandas
phd
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