How to reinstall all user packages after updating Python version in Windows?

Question

I have a Windows 7 machine running Python 3.8.5 with a very large number of physics/electronics/data analysis/simulation packages. As it turned out, I must have - for some inexplicable reason - installed the 32-bit version of Python instead of the 64-bit one despite having a 64-bit system. And I didn't notice until very recently when I was trying to install some packages that require 64-bit Python. Hence I've now downloaded and installed the latest Python version that is supported by Windows 7, which seems to be 3.8.10.

Question: What is the easiest and also fail-safe way to reinstall all the user packages - that I currently have under 3.8.5 - to 3.8.10?

For some reason, I couldn't find any "canonical" solution for this online. As it seems, Python does not come with any built-in support for updating or system migration and I'm honestly wondering why...

Anyway, my first idea was to get a list of all user (= "local"?) packages currently installed under 3.8.5, but I don't know how. Reason: Doing help('modules') inside the interpreter will list all packages and I don't see a way to "selectively apply" pip to a specific Python version, eg something like python-3.8.5 -m pip list --local is not supported.

After getting a list of the user packages, I was thinking to pack it into a batch command pip install package_1 package_2 <...> package_N , thus reinstalling everything to Python 3.8.10. And afterwards uninstalling Python 3.8.5 and removing all environment variables from system PATH.

Is this the proper way to do this?

Answer 1

Anyway, my first idea was to get a list of all user (= "local"?) packages currently installed under 3.8.5, but I don't know how.

Create a list of installed packages with pip freeze > pkglist.txt or pip list --format=freeze . If you already have one, that's great.

Then uninstall 32-bit Python 3.8.5 and clean your path for all Python related variables. Now, install 64-bit Python 3.8.10.

After reinstalling, you can install back all the packages with pip install -r pkglist.txt and it will restore the exact versions of the packages.

If you insist on having both 32-bit and 64-bit versions installed and also have the Python Launcher installed, you could invoke 32 and 64 bit versions separately with py -3.8-64 -m pip and py -3.8-32 -m pip .

I don't see a way to "selectively apply" pip to a specific Python version.

This is possible with the Python Launcher on Windows. But only between major/minor versions and not the patch versions according to its help message.

I would also recommend creating a virtual environment this time before installing the packages and leaving the root environment alone. You can create one named venv with just python -m venv venv , activate it with ./venv/Scripts/activate and proceed with the installation of packages.

Nope, doesn't work. After installing the packages with the newer Python version in PATH, eg Jupyter won't start.

If the Jupyter error persists, you could try pinning packages to their most recent patch/minor versions to update them and yet not break your code.

As a last resort, you could try installing Python 3.10 alongside your current Python installation (without uninstall or editing the PATH) and then installing the absolute latest versions of the packages in a 3.10 virtual environment to see if it works for you. You would invoke the two versions with Py Launcher, eg py -3.10 and py -3.8 .

Answer 2

One common way of handling packages in Python is via virtual environments. You can use Anaconda (conda), venv or any of several other solutions. For example, see this post:

https://towardsdatascience.com/virtual-environments-104c62d48c54#:~:text=A%20virtual%20environment%20is%20a,a%20system%2Dwide%20Python ).

The way this works in by keeping the Python interpreter separate from the virtual environment that contains all the necessary packages.

Probably the main reason Python doesn't feature migration tools (at least as part of standard library) is because pip - the main package tool - doesn't handle conflict resolution all too well. When you update a version of Python it might so happen (especially with niche packages) that some of them won't work any more and pip often won't be able to solve the dependencies. This is why it's a good idea to keep a separate venv for different Python versions and different projects.

The other tool you could use for easy migration is Docker which is a semi-virtual machine working on top of your host OS and containing usually some linux distribution, Python along with the necessary packages necessary for running and development.

It takes a bit of time to set up a container image initially but afterwards setting everythin on a new machine or in the cloud becomes a breeze.

Listing currently installed packages is done via pip freeze command, the output of which you can then pipe into a file to keep a record of project requirements, for example pip freeze > requirements.txt .

Answer 3

If I understood correctly, you have multiple packages like NumPy, pandas etc. installed on your machine, and you want to reinstall them "automatically" on a fresh installation of python.

The method (I use) to perform such an operation is by creating a file named setup.py which includes a list of all the packages. Bellow, I am attaching an example of such a file I use in one of my projects:

from setuptools import setup, find_packages

setup(
    name='surface_quality_tools',
    version='0.1',
    install_requires=["matplotlib", "psutil", "numpy", "scipy", "pandas", "trimesh", "pyglet", "networkx", "protobuf",
                      "numpy-stl", "sklearn", "opencv-python", "seaborn", "scikit-image", "flask", "tqdm", "pytest"],
    package_data={'': ['*.json']},
    packages=find_packages(include=[])
)

to run the installation you should open a command prompt from inside the project directory and run:

pip install -e .

You can find a nice example in this blog page