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Introduction to Python Virtualenv

Python virtual environment of venv module provides developers the capability of creating a quite lightweight virtual environment with its standalone directory. This directory can be a different one as well from the system directory; that is, it can be optionally isolated as well. Each Python virtual environment can have its Python binary and can have its standalone Python packages as well installed in its site directory. If in case we have different projects to work on and require to keep their dependencies separately, then Python virtual environments can be used. The Python virtualenv makes it the most widely used feature in Python.

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Syntax:

python3 -m venv /path/to/new/virtual/environment

This command will not provide any output but will perform the below operations in the background:

It creates a target directory.

It also creates parent directories, even if they do not exist before

It places a Python environment file inside the directory. The file is – pyvenv.cfg

It also creates a subdirectory that contains Python binaries.

Why do We Need Virtual Environments in Python?

Consider a scenario wherein you are working on two different projects and one of them uses Django 1.9, and the other one requires Django1.10

In such cases, virtual environments work like a charm to maintain the dependencies of multiple projects. Alternate commands that can be invoked over Windows as well:

How Does Virtual Environment Creation Work?

Here we discuss the working of virtual environment creation with Different Arguments Pass.

Positional Arguments

These arguments are order-specific when passed while calling a function.

ENV_DIR: It is a positional argument that creates the directory n the environment we are working.

Optional Arguments

These arguments can be skipped as well. In a nutshell, as the name specifies, these are not compulsory ones.

-h or –help: This optional argument displays the help message during the virtual env creation and exits.

–system-site-packages: This optional argument provides access to the site-packages directory to the virtual env being created.

–symlinks: This optional argument prefers using symlinks instead of using copies.

–copies: This optional argument prefers using copies instead of using symlinks.

Example:

Let’s take an example to understand creating the env directory while creating the Python virtual env:

## Python program to understand how virtual env works in python def create(self, env_dir): ## Function to create a virtualized python directory ##Target directory is the env_dir env_dir = os.path.abspath(env_dir) context = self.ensure_directories(env_dir) self.create_configuration(context) self.setup_python(context) self.setup_scripts(context) self.post_setup(context)

Eventually, this program will not provide any output but will run several processes at the backend.

ensure_directories(env_dir): This function eventually creates all of the required directories. This returns a context object as soon as this function is called

The directories may exist previously as well

create_configuration(context): This function will create a configuration file. The fine name is pyvenv.cfg

setup_python(context): For the Python executable files residing in the environment, This function creates a copy of the symlink

setup_scripts(context): There needs to be an activation script for each virtual environment, and this is what this function creates.

post_setup(context): It comes up with a placeholder method to pre-install the packages.

How We Can Manage Python virtualenv?

The simplest way of reproducing the same work is to incorporate a requirements file inside the root directory of our project.

Example

Let’s take an example to understand this in detail:

numpy==1.15.3

Output:

To implement the same, we have run pip freeze:

This indeed provides the list of all the third-party packages installed along with their version numbers

The output of this command, that is, the list of all the third-party packages installed along with their version numbers, is written to a file called – requirements.txt

Moreover, we can utilize the same command in order to rewrite the requirements file whensoever we install a new package or update the one

Code:

Output:

Now if we share this project and try to run this in another virtual environment, then we will be able to do the same with quite ease.

How We Can Duplicate Python Virtualenv?

To run a project created on one machine, on some other,

All we need to do is create a virtual env inside the project root directory.

python3 -m venv venv/

Then we need to install the project dependencies inside the active virtual env utilizing the below command:

pip install -r requirements.txt

This creates a replication of the project environment, which eventually makes us run the project on the other virtual env as well.

Activate the Virtual Environment

In order to activate the multiple virtual environments that you have created in for taking care of multiple projects, all you need to do is use the ‘activate’ command.

mypythonScriptsactivate

Deactivate the Virtual Environment

In order to deactivate the multiple virtual environments that you have created for taking care of multiple projects, all you need to do is use the ‘deactivate’ command.

deactivate

It is quite useful to have more than one Python environment configured in order to test multiple libraries or to take care of multiple dependencies of different projects that you have been working on. This makes it the most widely used feature in Python.

Conclusion

A virtual env is simply a copy of the original Python version installed on your machine with an option available to inherit the existing Python libraries/packages.

Moreover, you can install variant libraries with even different versions of the same libraries/packages as per your needs.

It’s quite useful when it comes to a shared system. As it provides each user the capability to create their own virtual env

It indeed creates a folder that contains all of the necessary directories required to initiate the same.