![]() I like my zombies in the movies I like them far less in my development tools.įinally, in disgust, I commented out these lines of my. Pyenv recreated the shims directory, presumably every time the shell re-evaluated my. Deleting it from the shims directory or even deleting the whole directory didn’t help. This file was taking precedence over my virtual environment. It turned out that a shell script named “jupyter” inside the pyenv shims directory was the culprit. What I often noticed is that I would try to run jupyter lab with a virtual environment activated, and I would get an error, even though I knew it was available in that environment. At the time, I had several JupyterLab environments available on my machine, with the packages installed with pip and the virtual environments managed with venv. However, the pain point that finally led me to explore Anaconda was an annoying problem with pyenv. Advertisementsīefore moving to Conda, I had used pyenv for some time and was pretty happy with it. With that file containing the correct version, you’ll use that version when you run Python from anywhere underneath that project root folder. In this respect, a helpful feature of pyenv is that you can set a version globally (let’s say you usually want 3.10), but then for the project that uses Python 3.4, you can create a file with the name, “.python_version”. For example, if you have a project on an older Python version, let’s say 3.4, but you want to experiment with the later features of 3.10, pyenv lets you switch between them. Like Conda, pyenv lets you manage multiple Python versions. The first tool I want to discuss is the one whose quirks led me to consider Conda in the first place, PyEnv. Next, we’ll go through a brief Conda tutorial that will teach you the basics of creating and using Conda environments. Although this article is heavily opinionated toward the “just use Conda” use case, I want to be as fair as possible to the alternative possibilities. In each section, we’ll give the pros and cons of the tool in contrast with Conda. To show you what I mean, we’ll first go over the tools mentioned - Pyenv, Venv, and Pip - to see how it compares to Conda. On the contrary, my experience with Conda has been that, on balance, Conda improves the work rather than degrades it. In that case, you might think that a monolithic “Swiss-army knife” tool like Conda may involve some unacceptable tradeoffs. You may be familiar with the Unix philosophy of having a collection of small tools that each do a single job well. Finally, like PyEnv, Conda can install and keep separate versions of Python, so you can work out different versions or experiment with later releases.Īs you can see, Conda’s strength is that it handles tasks that would otherwise be three different tools to accomplish.Like the Python venv module, Conda lets you create and manage isolated environments and save the dependencies for that environments with other developers.Like Pip, Conda can install packages, and as we go forward, we will discuss the pros and cons of each as a package management tool.This may seem like an unfair fight, three against one and all, but let me assure you, this match is more balanced than it looks. In the title, I told you this post would be a comparison of Conda with Pip, Venv, and Pyenv. ![]() Conda will isolate these from your “global” Python, so you won’t have to worry about conflicts. It also lets you install Python (and other tools), in addition to installing Python packages. Miniconda comes with a version of Python along with the libraries it needs to run. Incidentally, you don’t already need Python installed to do this (but it’s OK if you do). Once Miniconda is successfully installed, you should be able to run “ conda info” or “ conda -version” to verify you can see it on your path. ![]() Miniconda lets you select which of those tools you need, based on the same “conda” command line tool that Anaconda uses. The difference is that Anaconda is a massive Python distribution with a huge set of tools pre-installed. If you’re interested in trying out Conda, I recommend Miniconda unless you have a strong need to get Anaconda. “The nice thing about standards is that you have so many to choose from furthermore, if you do not like any of them, you can just wait for next year’s model.” AdvertisementsĪndrew S. ![]() ![]() Saving, Sharing, and Re-Creating Saved Environments.Creating Environments and Installing Packages.Installing Python Packages: Conda and Pip. ![]()
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