7/22/2023 0 Comments Where does pip3 install packages![]() This is not the same as compiling a C extension, this is just an optimization to make loading Python code faster on startup. pyc bytecode files, and store them in _pycache_ directories. Going faster (sometimes) with disabled compilationĪfter packages are downloaded (if they’re not cached locally) and installed on to the filesystem, package managers do one final step: they compile the. This saves me about 0.2-0.3s, not a very significant improvement the actual improvement probably depends on your network speed and other factors. ![]() On startup pip may check if you’re running the latest version or not, and print a warning if you’re not. Going (very slightly) faster by disabling the version check This is still not as fast as running on a dedicated machine, however: storing and loading the cache also takes time. If you’re using GitHub Actions, you can use the built-in caching support in the action used to setup Python. To work around that, most CI systems will have some way to store a cache directory at the end of the run, and then load it at the beginning of the next run. In most CI services, your cache will start out empty. On your local machine, that happens automatically. Notice that in all cases you get a speedup from having a warm cache, i.e. This example was run with 12 packages being installed with a larger number of dependencies, it’s possible that Poetry’s parallel installation would have more of an impact. Pipenv uses quite a lot of CPU compare to the other two Poetry is a bit better, but still higher than pip.Both Pipenv and Poetry use parallelism, as we can see from CPU time that is higher than wallclock time pip is currently single-threaded.Wallclock time isn’t really that different between any of them when the cache is warm, i.e.pip is the slowest by wallclock time when the cache is cold.Here’s how long each installation took, measuring both wallclock and CPU time: Tool I used the transitive dependencies for installing pandas and matplotlib, resulting in the installation of 12 different packages in total. In all cases I made sure to create the virtualenvs in advance, and for pip I made sure to use hashes in the requirements.txt, to match the hash validation that the other two package managers do by default. I therefore measured both variants: a cold cache where the package had to be downloaded, and a warm cache where the package was already available locally. Installing the already downloaded package.īy default, Python package managers will cache downloaded packages on disk, so if you install them a second time in a different virtualenv the package won’t need to be re-downloaded.Installing Python packages involves two steps: The default Python package manager is pip, but you can also use Pipenv and Poetry, both of which add additional functionality like virtualenv management. Wheels for musl-based distributions like Alpine are starting to become available, but they’re still not as common.Ĭomparing installation speed between pip, Pipenv, and Poetry Standard Linux wheels require glibc, but Alpine uses the musl C library. ![]()
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