Since Anaconda includes so many useful libraries and can install even more with just a few keys, the size of an Anaconda installation can be much larger than that of other competitors. Conda conda packages, created specifically for Anaconda, deal with the installation of Python packages and external third-party software requirements. Finding components, customizing them, and working with them is much easier with Anaconda than with CPython.Īnother benefit is the way Anaconda handles components from outside the Python ecosystem, if they are prioritized for a specific package. When installed, Anaconda offers a desktop application-Anaconda Navigator-that makes all aspects of the Anaconda environment available through a convenient user interface. The main use cases for Anaconda Python are mathematics, statistics, engineering, data analysis, machine learning, and related applications.Īnaconda groups together many of the most common libraries for commercial and scientific work in Python-SciPy, NumPy, Numba, and so on-and makes it much more personalized through a package management system.Īnaconda stands out from the other distributions for the way it integrates all these pieces. Anaconda was designed for Python developers who need a distribution supported by a commercial provider and with support plans for companies. But in addition to libraries for everything from GUI development to machine learning, you can also choose from a variety of tool runtimes and their libraries some runtimes may be more suited to the use case you have at hand than others.Īnaconda has versions optimized for special use cases. When choosing Python or R for software development, you choose a large language ecosystem with a wide variety of packages covering all programming needs.
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