Virtual Environment for Python Workspace Part 3/3 venv

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In the earlier two posts of this series, I discussed about virtualenv and conda and their usage along with some examples. I this post I am going to introduce you guys with another package and environment manager called venv which comes with standard Python3.X by default. So, nothing to worry about its installation.

Virtual Environment for Python Workspace — Part 1⁄3 — virtualenv
Virtual Environment for Python Workspace — Part 2⁄3 — conda

Creating an Environment

For example, If you have Python3.X installed in your system and you can run it’s REPL by issuing python3 in the terminal, then you can create a virtual environment based on this Python version by issuing the following command:

python3 -m venv myvenv

This will create the myvenv directory if it doesn't exist, and also create directories inside it containing a copy of the Python interpreter, the standard library, and various supporting files. By the way, you got the idea of using different versions of Python to use its venv module for creating different environments, right? Just find out an exact Python 3.X (I showed how, in earlier posts) and use its binary/executable in the command <active python> -m venv <environment name> .

Activating the Environment

It’s similar to the previous two workarounds and again simple as below. I assumed you are inside the newly-created myvenv directory.

source bin/activate

Managing Packages with pip

As venv is native with Python, you can use pip for installing packages in your virtual environment which will pull down packages from Python's official package repository, PyPI. For example, to install our very favorite package numpy , use the following command,

pip install numpy

Also, for sure you can use commands like pip search <packagename> , pip list in each newly created virtual environment.

Did you know, you can use pip show <packagename> to see detail of an installed package in an active environment?

Sharing Environment