Conda.io is a popular package and environment management system for data science and scientific computing. It allows users to easily install, update, and manage packages and dependencies for their projects with just a few simple commands. Conda.io supports multiple platforms and programming languages, making it a versatile tool for researchers, developers, and data scientists. With a user-friendly interface and extensive documentation, Conda.io simplifies the process of creating reproducible environments and distributing applications. Whether you are working on a small personal project or a large-scale data analysis, Conda.io provides the tools you need to succeed.

You can also have more than one environment with different packages for testing purposes. This procedure uses the Anaconda module already loaded on Discovery. Use the conda update command.rc-docs.northeastern.eduUsing a locally installed Conda virtual environment is highly recommended so that you can install the specific packages that you need.

Conda With just a few commands, you can set up a totally separate environment to run that different version of Python, while continuing to run your usual version of Python in your normal environment.docs.conda.ioIn its default configuration, conda can install and manage the thousand packages at repo.anaconda.comthat are built, reviewed and maintained by Anaconda®.

For example, to create a fresh conda environment called my-cool-project with Python 3.7 and its own pip, run the following: If you want a different version, like Python 3.6, just swap in python=3.6.sparrow.devWith Anaconda, the preferred way to use a previous version of Python is to create a separate conda environment for each project.