![]() ![]() ![]() To avoid that we can use pyenv-virtualenv to create virtualenvs for the tools. Eventually I will probably settle on poetry by at the moment I need both.Īlso, I rely a lot on jupyter notebooks, for quick data analysis tasks and ipython as a fancy Python interpreter.Īgain, I don't want to pollute the global installation. Installing the toolsįor dependency management I use two different tools, pipenv, and more recently poetry. ![]() PY_VERSIONS=( $PY_DEFAULT 3.7.8 3.6.11 2.7.18 )įor py_version in " do echo -e "Installing Python $py_version.\n\n" # Install specific Python version Once that's done, you can restart your shell by either closing and opening a new window or running: exec $SHELL Installing all Python versions I need. The variable WORKON_HOME tells pipenv where to place your virtual environments. # Initialize pyenv if command -v pyenv 1>/dev/null 2>&1 then eval " $(pyenv init -)" fi # Initialize pyenv-virtualenv eval " $(pyenv virtualenv-init -)" # pyenv config # Set virtualenv dir export WORKON_HOME=~/.ve ![]() Once the folder is created I add the path to my ~/.zshrc (for bash users, add it to ~/.bashrc): cat > ~/.zshrc I keep all my virtualenvs under the $HOME/.ve directory. This way we can work on more than one project at a time without introducing conflicts in their dependencies. brew install pyenvĮach project should have each own virtual environment associated with. So, the following steps are OS agnostic for me. Since last year, I've been using Homebrew both on macOS and Linux. In addition to pyenv, I also use the pyenv-virtualenv plugin to manage my virtual environments. Supports pypy, anaconda, CPython, Stackless-Python and others!.This means no risk of messing up the default Python installation. Everything is installed in the $HOME directory.Provides support for per-project Python versions.Lets you change the global Python version on a per-user basis.To install multiple versions and being able to switch between them, I use pyenv. Installing and configuring multiple Python versions Dependency tools I use - pipenv and poetry - must work with all Python 3+ versions.I must be able to fire up a ipython using the default python version I specified.I must be able to switch between versions easily.Python 3.8 must be the default version.It must have Python 2.7+, Python 3.6, Python 3.7, and Python 3.8 installed.Define your requirementsīefore getting into the actual configuration, you must take some time to define what your optimal setup looks like. So, without further ado, here's how I setup my Python workspace: Step 1. Also, I use zsh as my default shell, but this guide applies to bash as well. In fact, I have a MacBook at work and follow the same steps to configure my workspace with little modifications. This guide will focus on Linux, but you can easily adapt to macOS. Fortunately, there are a couple of tools that can help us have seamless experience handling different Python versions. As a matter of fact, it’s worse.įor instance, there are libraries that only work with Python 2, despite not being supported anymore. When it comes to Python, it’s no different. Regardless of the language you use, having projects targeting at distinct versions can be a nightmare. One thing that has always been very common is having multiple projects in different Python versions. In the beginning academically and as a hobby, then professionally. I’ve been working with Python for the last 6 years. You can also install pip in the environment and then use pip to install packages.TL DR: In this tutorial, I’ll teach you what I do to have multiple Python versions and tools installed without conflicts. Install package using the following command line: conda install package_name To deactivate, simply run the following command and Anaconda Prompt will switch back to the default environment: conda deactivate Install packages The above command line activate virtual environment named p圓7. You can use conda activate $environment_name to activate environments. The above command lines create three environments named p圓7, p圓8 and p圓9 with python versions 3.7, 3.8 and 3.9 respectively. The following commands create three environments with different Python versions: conda create -n p圓7 python=3.7 Once installed, open CMD.exe Prompt from the navigator. You can install the individual edition from this website. This article shows you the simple guide of creating different environments. This can be very handy when certain package only supports certain Python versions. With Anaconda, we can create virtual environments with different Python versions. ![]()
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