Manage Python Virtual Environments with Conda

Manage Python Virtual Environments with Conda

7 most commonly used commands by Data Scientists and Python Developers

What Is a Virtual Environment?

The main purpose of a Python virtual environment is to create separate environments for each project.

Let us try to understand the need for virtual environments with an example. Assume that you are working on two projects in the same system/machine - Project_A and Project_BProject_A requires spacy=2.3.0 & Python‚ȧ3.6 and Project_B requires spacy>2.3.0 and Python>3.6. How do you handle such a situation? If you are thinking to install everything in the base environment then be assured that you will get into issues sooner or later. The best approach is to create separate virtual environments for each project and use it accordingly. This article talks about how to work with Python virtual environments.

To run these commands, use the Anaconda command prompt.

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