So a working installation of, for example, Google TensorFlow will suddenly stop working when a user pip-installs a new package that needs a different version of the NumPy library.
In versions of Pip released prior to version 20.3, Pip installs all Python package dependencies required, whether or not those conflict with other packages previously installed. The big difference between Conda and the pip package manager is in how package dependencies are managed, which is a significant challenge for Python data science and the reason Conda was created. While similar Python-based cross-platform package managers (such as wheel or pip) cannot.Ī popular Conda channel for bioinformatics software is Bioconda, which provides multiple software distributions for computational biology. Conda is written in the Python programming language, but can manage projects containing code written in any language (e.g., R), including multi-language projects. Also, it allows users to switch between package versions and download and install updates from a software repository. Features Ĭonda allows users to easily install different versions of binary software packages and any required libraries appropriate for their computing platform.
The Conda package and environment manager is included in all versions of Anaconda, Miniconda, and Anaconda Repository. Īt first part of Anaconda Python distribution developed by Anaconda Inc., it ended up being useful on its own and for things other than Python, so it was spun out as a separate package, released under the BSD license. It was originally developed to solve difficult package management challenges faced by Python data scientists, and today is a popular package manager for Python and R. Conda is an open-source, cross-platform, language-agnostic package manager and environment management system.
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