![]() The one exception to everything above is the conda package, which is the very infrastructure you're using to manage packages and envs. Instead, Conda makes it quite easy to create new envs, and if they have a lot of overlap with other envs, then the envs can be quite light due to sharing packages across envs via hardlinking. Every time you update an env, you risk breaking code that you've already written. Personally, I will rarely run conda update on an env once I've harden the requirements for a project. Instead, just install Miniconda and only install what you want from Conda Forge at the start. However, in my opinion, there's almost no point to installing Anaconda if you're going to switch most packages to Conda Forge anyway. ![]() ![]() It may be worth noting that people who prioritize having access to the latest versions of packages often seem to prefer Conda Forge, because it tends to have more frequent package releases. If you want the newest individual package releases and don't mind potentially working with package builds that aren't thoroughly tested for integration, then run conda update -all. In between Anaconda releases, new versions of many packages are still released on the Anaconda channel, and if you run conda update -all you're going to inevitably get ahead of the versions specified in the anaconda bundle. If you want a stable set of packages that have been tested for interoperability, then do conda update anaconda. Because this takes time to do, the Anaconda team only releases new distributions (i.e., a new anaconda version) every couple months or so. Presumably, a bunch of testing goes into verifying that all the package versions and builds are compatible with each other. Update AnacondaĪnaconda is a Python distribution that bundles together a ton of packages. In either cases, you probably want to follow one of the methods explained here.Īfter having upgraded python, you need to recreate the environment in an analogous way as it was explained for the Ubuntu case.You're not doing anything wrong per se, but it just doesn't make much sense to ever run conda update anaconda and conda update -all right after each other on the same env - they represent two completely different configurations. If you are on Windows or MacOS, probably you are using an Anaconda or conda-based python distribution. But when changing python version, and especially when upgrading it, it is recommended to reinstall manually the "top-level" packages, as stated, because a different package version (if existing) is required to work with the new python version. In general you can restore the packages through the requirements.txt file or equivalent pyproject.toml (depending on the package manager that you use). Then, you can activate the environment and install the dependencies. ![]() Then, you need to recreate an environment (virtualenv is strongly recommended!). If you want additional information about the security of the procedure, you can read this. To install a python version, you can follow one of the many guides available in the internet, like this. If you are on a Unix system (certainly Ubuntu, but I think also most of all the other Unix-bases OSs), you can have different python version installed.
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