Virtual Environment for Python Workspace – Part 3/3 – venv

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:

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

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,

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
In the earlier post, I have discussed why and how you can share your environment made using  conda  with others. If you are using venv  or virtualenv  then you can export an environment’s state/configuration to a file, issuing the following command,

Here, the file name requirements.txt , that contains environment’s package information could be anything. But people have been using this name conventionally for a long time.

So, after exporting the environment information, you can share this file to any one who can install exact same packages in his newly created virtual environment by using the following command:

By the way, sharing environment in this way is similar if you use virtualenv

Resources
https://docs.python.org/3/tutorial/venv.html

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