That could be somewhat of an opinion based answer, but I would highly encourage it. ![]() conda will set up your PATH environment variable so that the new python will take precedence whenever you call python. Basically, I wouldn't bet on anyone taking this up. Yes, you get a new copy of python that can also have a different version than the one shipped with you OS. ![]() Also, other packages that build Python-version-specific variants would not be built for osx-arm64, so even if one had python=3.7, the packages wouldn't be there (at least not through Conda). 2021) was technically the final feature release, and it has now entered the maintenance-only phase (see PEP 537). I am writing because I need to import Cdo libraries in a Python script and I always get the same error: Unsupported file type (library support not. Longer term, you could try requesting that the python-feedstock include a 3.7 build for osx-arm64. # create environment from YAMLĬONDA_SUBDIR=osx-64 conda env create -n p圓7 -f p圓7.yaml Again, one still should set the environment-specific subdir option immediately after creation. With a YAML environment definition, one can use the CONDA_SUBDIR environment variable to temporarily set the platform while creating the environment. Note that MacOS will automatically recognize the architecture and run through Rosetta ( once installed) - one need not do anything special. Otherwise, the default CONDA_SUBDIR value ( osx-arm64) may be active and could result in mixing architectures in the same environment. Download Anaconda Distribution Version Release Date:Download For: High-Performance Distribution Easily install 1,000+ data science packages Package Management Manage packages. ⚠️ Important Note: Be sure to always activate this environment before installing packages. Similar to what one does for running win-32 environments on x86_64 machines, one can create osx-64 environments like # create empty environment Python 3.11 has 10-60 speed improvements over Python 3.10. ![]() Immediate alternatives for using 3.7 on Apple Silicon systems would be to emulate x86_64 with Rosetta or use a container system, e.g., Docker. Python 3.11 support will be available in the main repository, making this one of Anaconda’s biggest releases yet Python 3.11 features many user-facing and backend improvements that make it easier than ever for practitioners to get projects up and running quickly. Since Python 3.8 had been released for about a year when Apple Silicon hit the market, Python 3.7 builds for osx-arm64 were never part of the regular build matrix for Conda Forge.
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