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#CONDA PYTHON VERSION CHANGE INSTALL#
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$ conda create -name ml-env scikit-learn pandas matplotlib -channel conda-forgeĮach package and its dependencies will be installed locally in ~/.conda.

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Try the following procedure to install your package(s): Commands preceded by the $ character are to be run on the command line. Angular brackets denote command line options that you should replace with a value specific to your work.

This guide presents an overview of installing Python packages and running Python scripts on the HPC clusters.

Packaging and Distributing Your Own Python Package.

Isolated Python Environments with virtualenv.

Office of Information Technology Senior Management.

Scientific Computing Administrators Meeting.

Operations Research and Financial Engineering.

Center for Statistics & Machine Learning.

Fall Break Parallel Programming Workshop 2021.

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Hardware and Software Requirements for PICSciE Workshops.

Requirements for PICSciE Virtual Workshops.

Note that I use Miniconda, not the Anaconda installer, so I have more control over base from the start. Note that some users have reported similar issues for 3.6 -> 3.7 transitions, so I believe including the minor version here is necessary.

Namely, in the env's conda-meta folder create a file, pinned and add the line python 2.7.* Direct Solution: PinningĬonda does support package pinning, and this is the more direct way to ensure you never ruin your base install again by transitioning Python 2 to 3. Or whatever Python version you actually wish to work in. 1 Software packages go into project-specific or at least development-type envs.įor example, were I doing the install shown, I would have made a new env for it conda create -n tf36 anaconda::tensorflow-gpu python=3.6 Personally, I rarely install things in base outside of infrastructure (emacs, jupyter-related things, conda, etc.). You shouldn't have accepted such a huge change in the first place, not to base.

This isn't directly solving the problem, but it will help you have a workflow that is significantly less prone to encountering such pitfalls. Preventions Avoiding Breakage through Better Practiceįirst, just a general ( opinionated) recommendation: leverage virtual envs more. Others have reported installing in other directories and being able to still use and access their envs. If all else fails you may just have to reinstall. You don't need to keep the conda-exec around. Try a new shell and see if conda is working. The -force-reinstall flag might be useful if it claims the requirement is already satisfed. Make sure that the build of Conda that is suggested corresponds to the version of Python currently installed. (Re-)Install the conda package in the base env. Option 2: Install conda for the Current Python Start a new shell and try using conda again. Identify the revision immediately before the current one (we'll denote it by here), and attempt to restore it. You should also see the pkgs folder in your base env in the package cache. The key thing to check for is that base environment: correctly identifies to where your base env is and shows it as (writable). Typically this is the anaconda3 or miniconda3 folder in this case, we'll use the path given by OP: export CONDA_ROOT_PREFIX=/home/me/anaconda2 Temporarily set CONDA_ROOT_PREFIX to the base of your install. Tar -xzOf conda-standalone-4.9.2.tar.bz2 standalone_conda/conda.exe > conda-exec

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I'm going to rename it to conda-exec anyway: # download archive

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exe it's a binary and should run when called at the shell. The actual binary will be at conda_standalone/conda.exe in the. Please report in the comments if this works or needs adjusting!ĭownload the appropriate standalone Conda for your platform (here we'll use linux-64/conda-standalone-4.9.2). You can do all the following from any directory, so maybe use a temp or wherever you put downloads. One possible route to recovery is to temporarily use a standalone build of the conda-exec to repair your base env. This sounds like something the dependency resolver is overlooking - i.e., default behavior should be to protect integrity of base environment where conda lives. It is problematic that many packages on Anaconda seem to be triggering Python version changes, but not subsequently triggering a conda package update. The Python package is necessary for Conda as a whole to function and it get's loaded whenever you try to use conda.

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The Python version change (2.7.14 -> 3.6.8) created a situation where the new python has a new site-packages which no longer contains a conda package, whereas if you only update within 2.7.x, this wouldn't be an issue.Ĭonda includes both a set of binaries (e.g., what you're invoking when you type conda in a shell) and a Python package by the same name. Changing Python versions without updating the conda package breaks Conda.

Conda python version change