In pip there is an -f
option which does the following:
-f
,--find-links
: If a url or path to an html file, then parse for links to archives. If a local path orfile://
url that's a directory, then look for archives in the directory listing.
This is the preferred way of installing PyTorch, by setting the link to their overview website, e.g.:
pip3 install torch===1.3.0 -f https://download.pytorch.org/whl/torch_stable.html
For my virtual environments I use pipenv
but I haven't found an option that does the same as -f
. In the meantime, I can just look up the direct link to the package that is relevant for my system, but that is cumbersome.
Does pipenv provide a way to do the same thing as pip's -f?
Yes, because as I said, they both just use pip . Both methods will install the packages in the same virtual environment and pipenv graph is just checking that same env. The packages will be stored in a folder under lib/pythonX.
While pip can install Python packages, Pipenv is recommended as it's a higher-level tool that simplifies dependency management for common use cases. This does a user installation to prevent breaking any system-wide packages.
Pipenv is a tool that provides all necessary means to create a virtual environment for your Python project. It automatically manages project packages through the Pipfile file as you install or uninstall packages.
Use a Pipenv projectPipenv will read the Pipfile and Pipfile. lock files for the project, create the virtual environment, and install all of the dependencies as needed.
It is possible to use environment variables recognised by pip to tweak its behaviour within pipenv
's execution. E.g.:
PIP_FIND_LINKS=https://download.pytorch.org/whl/torch_stable.html pipenv install torch==1.5.1+cu101
See:
In the new version of pipenv (I tested with version 2020.11.15), you can install packages in this way:
pipenv install https://download.pytorch.org/whl/cpu/torch-1.3.0%2Bcpu-cp36-cp36m-linux_x86_64.whl
The link can be found in the this page: https://download.pytorch.org/whl/torch_stable.html
This will be added to the Pipfile as well.
[packages]
torch = {file = "https://download.pytorch.org/whl/cpu/torch-1.3.0%2Bcpu-cp36-cp36m-linux_x86_64.whl"}
you need to manually check the link with your compute platform, os and python version.
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