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Miniconda is the small installer for conda. You get Python, the conda package manager and almost nothing else, then you add what a project needs. Full Anaconda arrives with hundreds of packages already in place, which is convenient on a desktop and wasteful on a server where you know what you're building. Conda handles the Python version itself as well as the libraries, which is the part pip cannot do, and it settles the compiled dependencies that scientific packages tend to drag behind them.
One thing worth knowing before you install it anywhere commercial: Conda is BSD licensed and free, but Miniconda points by default at Anaconda's own package repository, and Anaconda's terms ask organisations above roughly two hundred people to pay for access to it. The community channel conda-forge has no such condition at any size, and switching your default channel to it is a single line of configuration. Miniforge is the same tool shipped pointing there already. None of that is a reason to avoid conda. It is a reason to know which channel you're pulling from.
Pin the interpreter version per project, which pip and venv leave to you.
Export to environment.yml and rebuild it identically on another machine.
CUDA builds, BLAS and the rest arrive working instead of needing a compiler.
Deploy any template and certified specialists cover everything at the server level, 24/7 and in multiple languages. It's included with every plan, refined over 17 years of running infrastructure.
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