34 ms·

Yeah but do you really need a separate copy of numpy/matplotlib/scipy/etc. for every single project? I don't have infinite disk space...

• zahlman 2y ago
  If your projects are using different versions of the library and/or different Python versions, then yes. Especially for libraries like NumPy/SciPy that rely on compiled code. It must be re-compiled against the API of a specific Python minor version, for many reasons (e.g., the bytecode format changes with almost every minor version). If your projects can get away with having the same exact set of libraries installed, then no - just reuse the same virtual environment. In between is, I would argue, mostly Pip's fault. There's no facility for installing via symlinks, or hard links, or `.pth` files, even though all of those would work fine in Python. Granted, using `.pth` files causes `sys.path` to blow up at startup, which some people claim is a performance issue (it's searched linearly) - but it's honestly probably not a meaningful problem in remotely normal cases (especially considering that module imports are cached in `sys.modules`). Pip also unpacks wheels, even though Python could theoretically import from them directly (they're renamed zip files). This is partly for performance reasons but largely because it allows installed packages to read their own data files using relative paths and the ordinary file I/O API. For packages that don't need to do that, the egg format implemented a `zip_safe` flag, but for whatever reason, wheels don't have this.