up until recently I have only worked with one version of Python and used virtual environments every now and then. Now, I am working with some libraries that require older version of Python. So, I am very confused. Could anyone please clear up some of my confusion?
How do I install multiple Python versions?
I initially had Python version 3.8.x but upgraded to 3.10.x last month. There is currently only that one version on my PC now.
I wanted to install one of the Python 3.8.x version and went to https://www.python.org/downloads/. It lists a lot of versions and subversions like 3.6, 3.7, 3.8 etc. etc. with 3.8.1, 3.8.2 till 3.8.13. Which one should I pick?
I actually went ahead with 3.8.12 and downloaded the Tarball on the page: https://www.python.org/downloads/release/python-3812/
I extracted the tarball (23.6MB) and it created a folder with a setup.py file.
Is Python 3.8.12 now installed? Clicking on the setup.py file simply flashes the terminal for a second.
I have a few more questions. Hopefully, they won't get me downvoted. I am just confused and couldn't find proper answers for them.
Why does Python have such heavy dependency on the exact versions of libraries and packages etc?
For example, this question
How can I run Mozilla TTS/Coqui TTS training with CUDA on a Windows system?. This seems very beginner unfriendly. Slightly mismatched package
version can prevent any program from running.
Do virtual environments copy all the files from the main Python installation to create a virtual environment and then install specific packages inside it? Isn't that a lot of wasted resources in duplication because almost all projects require there own virtual environment.
Your questions depend a bit on "all the other software". For example, as #leiyang indicated, the answer will be different if you use conda vs just pip on vanilla CPython (the standard Windows Python).
I'm also going to assume you're actually on Windows, because on Linux I would recommend looking at pyenv. There is a pyenv-win, which may be worth looking into, but I don't use it myself because it doesn't play as nice if you also want (mini)conda environments.
1. (a) How do I install multiple Python versions?
Simply download the various installers and install them in sensible locations. E.g. "C:\Program Files\Python39" for Python 3.9, or some other location where you're allowed to install software.
Don't have Python add itself to the PATH though, since that'll only find the last version to do so and can really confuse things.
Also, you probably want to use virtual environments consistently, as this ties a specific project very clearly to a specific Python version, avoiding future confusion or problems.
1. (b) "3.8.1, 3.8.2 till 3.8.13" which should I pick?
Always pick the latest 3.x.y, so if there's a 3.8.13 for Windows, but no 3.8.14, pick that. Check if the version is actually available for your operating system, sometimes there are later versions for one OS, but not for another.
The reason is that between a verion like 3.6 and 3.7, there may be major changes that change how Python works. Generally, there will be backwards compatibility, but some changes may break how some of your packages work. However, when going up a minor version, there won't be any such breaking changes, just fixes and additions that don't get in the way of what was already there. A change from 2.x to 3.x only happens if the language itself goes through a major change, and rarely happens (and perhaps never will again, depending on who you ask).
An exception to the "no minor version change problems" is of course if you run some script that very specifically relies on something that was broken in 3.8.6, but no fixed in 3.8.7+ (as an example). However, that's very bad coding, to rely on what's broken and not fixing it later, so only go along with that if you have no other recourse. Otherwise, just the latest minor version of any version you're after.
Also: make sure you pick the correct architecture. If there's no specific requirement, just pick 64-bit, but if your script needs to interact with other installed software at the binary level, it may require you to install 32-bit Python (and 32-bit packages as well). If you have no such requirement, 64-bit allows more memory access and has some other benefits on modern computers.
2. Why does Python have such heavy dependency on the exact versions of libraries and packages etc?
It's not just Python, this is true for many languages. It's just more visible to the end user for Python, because you run it as an interpreted language. It's only compiled at the very last moment, on the computer it's running on.
This has the advantage that the code can run on a variety of computers and operating systems, but the downside that you need the right environment where you're running it. For people who code in languages like C++, they have to deal with this problem when they're coding, but target a much smaller number of environments (although there's still runtimes to contend with, and DirectX versions, etc.). Other languages just roll everything up into the program that's being distributed, while a Python script by itself can be tiny. It's a design choice.
There are a lot of tools to help you automate the process though and well-written packages will make the process quite painless. If you feel Python is very shakey when it comes to this, that's probable to blame on the packages or scripts you're using, not really the language. The only fault of the language is that it makes it very easy for developers to make such a mess for you and make your life hard with getting specific requirements.
Look for alternatives, but if you can't avoid using a specific script or package, once you figure out how to install or use it, document it or better yet, automate it so you don't have to think about it again.
3. Do virtual environments copy all the files from the main Python installation to create a virtual environment and then install specific packages inside it? Isn't that a lot of wasted resources in duplication because almost all projects require there own virtual environment.
Not all of them, but quite a few of them. However, you still need the original installation to be present on the system. Also, you can't pick up a virtual environment and put it somewhere else, not even on the same PC without some careful changes (often better to just recreate it).
You're right that this is a bit wasteful - but this is a difficult choice.
Either Python would be even more complicated, having to manage many different version of packages in a single environment (Java developers will be able to tell you war stories about this, with their dependency management - or wax lyrically about it, once they get it themselves).
Or you get what we have: a bit wasteful, but in the end diskspace is a lot cheaper than your time. And unlike your time, diskspace is almost infinitely expandable.
You can share virtual environments between very similar projects though, but especially if you get your code from someone else, it's best to not have to worry and just give up a few dozen MB for the project. On the upside: you can just delete a virtual environment directory and that pretty much gets rid of the whole things. Some applications like PyCharm may remember that it was once there, but other than that, that's the virtual environment gone.
Just install them. You can have any number of Python installations side by side. Unless you need to have 2 different minor versions, for example 3.10.1 and 3.10.2, there is no need to do anything special. (And if you do need that then you don't need any advice.) Just set up separate shortcuts for each one.
Remember you have to install any 3rd-party libraries you need in each version. To do this, navigate to the Scripts folder in the version you want to do the install in, and run pip from that folder.
Python's 3rd-party libraries are open-source and come from projects that have release schedules that don't necessarily coincide with Python's. So they will not always have a version available that coincides with the latest version of Python.
Often you can get around this by downloading unofficial binaries from Christoph Gohlke's site. Google Python Gohlke.
Install Python using the windows executable installers from python.org. If the version is 3.x.y, use the highest y that has a windows executable installer. Unless your machine is very old, use the 64-bit versions. Do not have them add python to your PATH environment variable, but in only one of the installs have it install the python launcher py. That will help you in using multiple versions. See e.g. here.
Python itself does not. But some modules/libraries do. Especially those that are not purely written in Python but contain extensions written in C(++). The reason for this is that compiling programs on ms-windows can be a real PITA. Unlike UNIX-like operating systems with Linux, ms-windows doesn't come with development tools as standard. Nor does it have decent package management. Since the official Python installers are built with microsoft tools, you need to use those with C(++) extensions as well. Before 2015, you even had to use exactly the same version of the compiler that Python was built with. That is still a good idea, but no longer strictly necessary. So it is a signigicant amount of work for developers to release binary packages for each supported Python version. It is much easier for them to say "requires Python 3.x".
I'm coming to python from R, where package management is really simple. As I learn python (though a lot of googling), I see recommendations about virtual environments (which I never set up), and conda over pip for package management (I did pip because it seemed easier).
So now I've got a bunch of libraries installed globally, spyder is broken after a routine ubuntu ubdate (this problem, I think, which is solved using conda), and I am contemplating starting from scratch. But I know that lots of other system programs depend on python, so I can't just nuke it and start over like I would with R.
So:
Is my instinct correct? Should I "start fresh" with my python environment?
How do I do this in a way that won't disrupt other processes on my machine?
I know that python 2.7 exists on my machine, and I assume that it does something consequential. I use python 3 for manipulating and analyzing data. I think that this is relevant, but I am not sure how.
I just dealt with the worse bug in my entire 3 years of computer programming! It turns out that because I wanted to work with the natural language toolkit I had to install python 3.5 even though I'm using python 3.6. So I downloaded 3.5 and now my terminal is using python 3.5 by default and I can't get it back to 3.6. Because I was using python 3.5 which does not automatically order dictionaries it was throwing my program off because it relies on ordered dictionaries. It took me 4 hours to figure that out.
You want to use virtualenv and/or virtualenvwrapper. This is a utility that allows you to use multiple different environments, with different Python versions, different pip packages installed, etc.
To find the 3.5 version, run which python in your terminal to find the path to the python executable; then look at your PATH environment, and see where the location of that Python is on your PATH. Then you need to find out where that path is getting added; this will depend on your OS/Shell.
Tough times for sure, sorry to hear that.
I use pyenv to manage the different python versions on my system. This allows you to create virtual environments using whichever version you want.
EDIT to address comments.
I totally understand that setting up virtualenv or something like pyenv is not simple. However, it is unfortunately the easiest way to deal with (and avoid) situations like this. There are two essential concepts that are important here:
1) Isolation - Virtualenv takes care of this. When you install dependencies in a virtual environment, they will not affect your other environments or system python installation.
2) Multiple Python Versions - In your case, you needed to use a module that did not support 3.6. Instead of creating a virtual environment using python 3.5, you accidentally messed up your system installation of 3.6. Recovering from these types of misconfigurations can be difficult, and it is often easier to simply prevent it in the first place.
Again, I completely understand that this might be complicated, I remember thinking the same thing, but it is less complicated than troubleshooting the misconfigurations that can occur without this tooling.
I would like to ask a simple, and maybe a little bit strange, question. I wasn't able to find all answers on this site, so I hope I'm not making spam with this thread.
I installed Anaconda (Python 2.7 32-bit) in my Windows 7 (64-bit) on a different partition than my operating system. After installing Windows 8.1 (64-bit) I would like to keep all my scripts, environment, setting for Spyder etc. in new installation. I was thinking about "adding" existing Anaconda installation to Windows, to save myself from reinstalling everything and copying important files. Is it possible to be done in a simple way?
There are ways to add Python to registry (How to add Python to Windows registry) and system environment variables (How to add to the pythonpath in windows 7?) but, still, Anaconda installer does more (Start menu folders, icons etc.).
In short words: I would like to use Anaconda installer to make everything but copying new files into existing folder.
To be honest, I think there is something wrong in my way of thinking about this so I have to ask this question - how do you move your Python installation when you install new system or reinstall old one?
My first, silly answer is: install new Anaconda and then just insert old files in a place of a newly created installation. But I'm almost sure it will lead to problems with paths and working of programs - or maybe I'm too cautious and it's actually a good way to move installation to new system?
I don't think you'll be able to do everything you want in a "simple" way. Upgrading an OS is a major change. You'll just have to reinstall and reconfigure Anaconda. Then copy over your own scripts as necessary. Some applications save config files that you can use to import your systems (such as Outlook), so you could ask if that's something Anaconda supports via their support channels. If not, then you'll probably just have to reinstall.
I am not a regular Linux user so this might be completely trivial question. I am running 6.2 PUIAS version i386_64 on one of my GPU based "super" computers due to the unavailability of NVidia drivers for NetBSD. The installed version of Python is 2.6.6. I need 2.7.2 Python and newer version of scipy, numpy, matlibplot and friends. I have PUIAS and EPEL repositories enabled. However they do not have newer versions of Python. What is the "recommended" way to install newer version of Python without braking the system which depends on it. I am not interested in Python 3.2 due to the lack of libraries for scientific computing.
When the install-Python-from-source routine tells you to use make install, type make altinstall instead. This will leave the normal python executable untouched and instead create python2.7 for you to use. Install the other packages from source using this new executable. Don't forget to change the shebang line in your scripts accordingly.
I am going to answer my own question. For people who are using Python for scientific computing on RedHat clones (PUIAS for example) the easiest way to get all they need is to use rpm package manager and Enthought Python Distribution (EPD for short). EPD installs everything in a sandbox so system tools which are based on an obsolete version of Python are not massed up. However, paths have to be adjusted for system or even easier on the user base so that the using shell invokes non-system tools. One should never compile Python from source unless you are interesting in Python itself or in porting it to your favorite operating system rather than in your own research!