How to use pip and create venv virtual environment in Python: A complete guide

Dependency Management and Virtual Environments in Python: pip, venv, virtualenv, pipenv (Updated for 2025)

Python has established itself as a powerful and flexible tool for developing projects of varying complexity. One of the key advantages of this programming language is its extensive ecosystem of libraries and tools. To effectively manage these libraries, it is necessary to master working with pip and virtual environments. In this article, we will explore in detail how to use pip to install packages and how to create isolated virtual environments using venv, virtualenv, and pipenv, which will optimize the development process and avoid dependency conflicts.

Using pip to Manage Python Packages

pip (Python Package Installer) is the standard package manager in Python, designed to install and manage third-party libraries available in the official PyPI (Python Package Index) repository. It allows you to easily add, update, and remove packages needed for your project.

Checking pip Installation

To make sure pip is installed on your system, open a terminal or command prompt and run the following command:

pip --version

If pip is installed, you will see information about its version and location. For example:

pip 24.0 from /usr/local/lib/python3.12/site-packages/pip

If pip is not present, you can install it by running the following command:

python -m ensurepip --upgrade

Basic pip Commands

Installing a Package:

pip install package_name

Example:

pip install requests

This command will install the latest version of the requests package from PyPI.

Installing a Specific Version of a Package:

pip install package_name==version_number

Example:

pip install pandas==2.2.0

This command will install version 2.2.0 of the pandas library.

Updating a Package to the Latest Version:

pip install --upgrade package_name

Example:

pip install --upgrade numpy

This command will update the numpy package to the newest version.

Uninstalling a Package:

pip uninstall package_name

Example:

pip uninstall matplotlib

This command will remove the matplotlib package from your system.

Viewing Installed Packages:

pip list

This command will display a list of all installed packages in your current Python environment.

Installing Multiple Packages at Once

To install multiple packages simultaneously, it is convenient to use a requirements.txt file, which lists all the necessary libraries and their versions.

Create a requirements.txt file with the following format:

requests==2.32.0
flask==3.0.0
pandas==2.2.0

Then execute the command:

pip install -r requirements.txt

This command will install all the packages specified in the requirements.txt file.

Saving a List of Installed Packages

To fix the current dependencies of the project, you can create a requirements.txt file with a list of all installed packages and their versions:

pip freeze > requirements.txt

Subsequently, to restore the environment, you can use this file:

pip install -r requirements.txt

Creating and Using Virtual Environments (venv)

Using virtual environments is a recommended practice when developing in Python. Virtual environments allow you to isolate the dependencies of different projects from each other, which prevents library version conflicts.

What is a Virtual Environment?

A virtual environment is an isolated environment that contains its own copy of the Python interpreter and a set of installed packages. This means that packages installed in the virtual environment do not affect the global Python installation or other projects.

Creating a Virtual Environment with venv

venv is a built-in Python module designed to create virtual environments.

Navigate to the project directory:

cd /path/to/project

Create a virtual environment:

python -m venv venv

Here, venv is the name of the folder where the virtual environment files will be stored. You can use any other name, but venv is commonly used.

Activating the Virtual Environment:

On Windows:

venv\Scripts\activate

On macOS and Linux:

source venv/bin/activate

After activation, a prefix with the environment name will appear in the command line:

(venv) user@machine:~/project$

This means that all packages will now be installed only in this environment.

Installing Packages in the Virtual Environment:

pip install flask

Checking Installed Packages in the Environment:

pip list

Deactivating the Virtual Environment

To exit the virtual environment, execute the command:

deactivate

After that, you will return to the system Python interpreter.

Benefits of Using Virtual Environments

• Project Isolation: Different projects may require different versions of libraries. Virtual environments prevent conflicts between these versions.
• Dependency Management: Using requirements.txt and virtual environments simplifies the portability of projects between different machines.
• Security: You can experiment with new libraries without risking damage to the global Python installation.

Tips for Working with Virtual Environments

• Create a virtual environment immediately after creating a new project.
• Store the requirements.txt file in the root directory of the project.
• Use .gitignore to exclude the venv folder from the version control system (for example, Git).
• In the IDE (for example, VS Code, PyCharm), configure automatic use of the virtual environment in the project.

Alternative Tools: virtualenv and pipenv

In addition to the built-in venv module, there are other tools for managing virtual environments and dependencies: virtualenv and pipenv.

Using virtualenv

What is virtualenv?

virtualenv is a third-party library that provides advanced features for creating and managing virtual environments. Unlike venv, virtualenv can be used with older versions of Python (before 3.3).

Installing virtualenv

pip install virtualenv

Creating a Virtual Environment

virtualenv env_name

Example:

virtualenv venv

Activating the Environment

On Windows:

venv\Scripts\activate

On macOS and Linux:

source venv/bin/activate

Deactivating the Environment

deactivate

Difference Between venv and virtualenv

virtualenv is often used in older projects or when needing support for different Python versions.

Using pipenv

What is pipenv?

pipenv is a tool that combines the management of virtual environments and dependencies. It automatically creates a virtual environment and uses the Pipfile and Pipfile.lock files to fix dependencies, making the project more structured and manageable.

Installing pipenv

pip install pipenv

Creating an Environment and Installing a Package

pipenv install requests

This command will automatically create a virtual environment and install the requests library.

Activating the Environment

pipenv shell

Exiting the Environment

exit

Removing the Environment

pipenv --rm

Benefits of Using pipenv

• Dependency management through a convenient and readable Pipfile.
• Secure fixation of dependency versions through Pipfile.lock.
• Automatic creation of virtual environments.
• Support for the pipenv check command to search for known vulnerabilities in dependencies.

Pipfile Example

[[source]]
name = "pypi"
url = "https://pypi.org/simple"
verify_ssl = true

[packages]
requests = "*"
flask = "==3.0.0"

[dev-packages]
pytest = "*"

[requires]
python_version = "3.12"

For team development:

pipenv install

All dependencies will be installed automatically in the required versions.

Which Tool to Choose?

• For small projects without complex dependency management, use venv.
• For old projects or supporting multiple Python versions, choose virtualenv.
• For modern projects with team development, pipenv is ideal.

Conclusion

Effective environment and dependency management is an important skill for every Python developer.

Key points to remember:

• Use pip to install packages and manage dependencies.
• Create virtual environments with venv, virtualenv, or pipenv to isolate projects and avoid library conflicts.
• When working in a team, use pipenv.