Pyenv

7 minute read Published:

A brief overview of a good Python package manager

XKCD - Python Environment

I write Python code each day, for personal and professional projects.
As I am working on multiple Python projects, old and fresh ones, I have to use different Python versions for those projects, from 2.7.2 to 3.7.0.
Also, I want to switch the Python version of my projects very easily and quickly, in case of we have to upgrade the Python version of the software.

I am a macOS user, and I use a lot HomeBrew.
Unfortunately, HomeBrew is not a great solution to keep a trace of multiple versions of a given build (especially the interpreters)…
I can take a look at each source code in python.org, download the one a want, build it, and set manually all my paths in order to retrieve the Python version I want for a given project.
But, we are in 2018, and I figured that someone already automatized this thing.

I was right.

This tool is called pyenv, and is a very simple Python package manager for UNIX-like systems.

What is pyenv

pyenv is a Python package manager, focused on the interpreter and famous Python associated tools (easy_install, pip, etc…).
pyenv was originally forked from rbenv and ruby-build for Ruby, and modified for Python.
The project is composed, principaly, by shell scripts, and totalized nearly 12,000 stars on Github on 22th of July, 2018.

Installation of pyenv

For macOS, using HomeBrew, the installation of pyenv is very simple: brew update && brew install pyenv.
That’s it.

If you are not on macOS, or if you don’t want to use HomeBrew for that, you can check the automatic installer on Github.

pyenv uses an internal system calls shims to enable the search of the Python interpreters (and associated tools), and enable autocompletion.
In order to use those binaries, you just have to enable shims and autocompletion using eval "$(pyenv init -)" (remember to add this line on your .bashrc or .zshrc).

Ok - now, pyenv is installed on the system…but there is no interpreter on your system yet.

Promises

Install a toolchain

First, you have to install a given Python ecosystem version (interpreter, and associated tools) on your system.
If you check first the versions you have installed, using pyenv versions, the output is empty.

NOTE: Along the versions option, there exists the version option. versions returns the toolchains you installed on the system, but version returns the toolchain(s) you are using on the current session.

First, let’s try to install the version 2.7.15 of Python:

~ pyenv install 2.7.15
python-build: use openssl from homebrew
python-build: use readline from homebrew
Downloading Python-2.7.15.tar.xz...
-> https://www.python.org/ftp/python/2.7.15/Python-2.7.15.tar.xz
Installing Python-2.7.15...
python-build: use readline from homebrew
Installed Python-2.7.15 to /Users/acarette/.pyenv/versions/2.7.15

As you’ve seen, pyenv will download the 2.7.15 version of Python directly from the official Python servers, and will compile and install the binary directly for your system, on your system.
If you are wondering where is the build, you can check the folder .pyenv/shims in your $HOME.

Now, let’s install the 3.4 version:

~ pyenv install 3.4
python-build: definition not found: 3.4

The following versions contain `3.4' in the name:
  3.3.4
  3.4.0
  3.4-dev
  3.4.1
  3.4.2
  3.4.3
  3.4.4
  3.4.5
  3.4.6
  3.4.7
  3.4.8
  miniconda-3.4.2
  miniconda3-3.4.2
  stackless-3.4-dev
  stackless-3.4.1
  stackless-3.4.2
  stackless-3.4.7

Oups - what the problem here?
The problem is we were not specific at all, when we asked to install the 3.4 toolchain.
Indeed, the 3.4 version is a major version of Python 3, and there exists multiple minor versions of 3.4. So, pyenv was asking to specify the minor version of the major version we asked for: pyenv install 3.4.8.

Note: If you look more closely at the error message, you can see that you can install multiple versions of anaconda via pyenv - so, the tool is not exclusive to Python builds but the Python ecosystem.

Global usage of a toolchain

If you have more than 50% of your Python projects that are using the same specific version of Python, maybe you want to use this version as a global one on your system.
pyenv can override the default Python version of your projects using the global option.

So, if you want to use the 3.4.8 version of Python as the default one, ask to pyenv to override it: pyenv global 3.4.8.

Now that Python 3 is different than Python 2 (actually, it may be a new programming language by itself…), maybe you want to override a default toolchain for Python 2 and for Python 3 too.
You can do that using pyenv global 2.7.15 3.4.8.

Using this feature, when you want to use python2, it will reach Python 2.7.15.
Also, if you want to use python3, it will reach Python 3.4.8.

You can see this behaviour on typing pyenv version (*no s at the end of version!):

~ pyenv version
2.7.15 (set by /Users/acarette/.pyenv/version)
3.4.8 (set by /Users/acarette/.pyenv/version)

Now, what happen when we want to use python?

When we asked to override the default toolchains, we gave to pyenv an order: 2.7.15 before 3.4.8.
So, using this configuration, it will reach Python 2.7.15 first.
If you want to override this behaviour, in using Python 3 instead of Python 2, you can do that switching the previous versions: pyenv global 3.4.8 2.7.15.
Using this configuration, if you launch python, it will be the 3.4.8 toolchain:

~ pyenv version
3.4.8 (set by /Users/acarette/.pyenv/version)
2.7.15 (set by /Users/acarette/.pyenv/version)

Local usage of a toolchain

The previous section explains how to define defaults toolchains in the entire system.
Now, what if you want to work using different toolchains, on different projects?

pyenv can override the default Python toolchain for a given path (or project), creating a .python-version file at the root of your Python project.
To do that, you need the local option.

So, using the local command, on a local project, each time I will want to use python, the shims will check if an overrided Python version has been done for this project.
If a .python-version file exists in the current project, pyenv will launch the toolchain described in the file. Otherwise, pyenv will execute the first default toolchain.

Ok, let’s try:

~ mkdir -p Code/pyenv_test
~ cd Code/pyenv_test
~ pyenv version
3.4.8 (set by /Users/acarette/.pyenv/version)
2.7.15 (set by /Users/acarette/.pyenv/version)
~ pyenv local 3.6.2
~ pyenv version
3.6.2 (set by /Users/acarette/Code/pyenv_test/.python-version)

NOTE: like the global option, multiple Python versions: pyenv local 2.7.15 3.4.8, with the same priorities than before.

Interactive usage of a toolchain

Python is a dynamic and interactive programming language and, sometimes, you just want to check something in the standard library, or just try to hack something on the interpreter.

Just imagine you are working on a given project, using the latest version of Python, when a colleague ask you to verify a very small piece of code using the version 3.6.2 of Python - maybe because something is struggling with the library standard of this specific version.
The code to test is so small that it would be overkill to create a virtual environment to test it, and to put in on a totest.py file.

No, you want to test the code in a Python interpreter.

Currently, using global and local, you can’t do that.
So, pyenv contributors added the shell option, in order to launch a specific version of Python in your current shell session.

~ pyenv version
3.4.8 (set by /Users/acarette/.pyenv/version)
2.7.15 (set by /Users/acarette/.pyenv/version)
~ python -V
Python 3.4.8
~ pyenv shell 3.6.2
~ python -V
Python 3.6.2

Pretty convenient, isn’t it?? :)

Conclusion

As you noticed in the Promises section, pyenv offers great features to work easily with different Python toolchains, without scratching your head on how you can install different versions of Python in your system, for a given project.
Of course, pyenv is not perfect - I still wait to install a toolchain only for a specific project, and let the tool to drop out the version if I delete the project - but it’s a very good beginning in managing your Python toolchains.