Third-party libraries and pip

Third-party libraries are everything that's not part of Python's standard distribution: web frameworks, data-science libraries, ML toolkits, parsers, and thousands more. You install them with pip, the standard Python package manager.

What are third-party libraries?

Third-party libraries are Python modules that are not part of the standard library and are developed by independent developers or organizations.

What is pip?

pip (Package Installer for Python) is a package management system used to install and manage software packages written in Python. It downloads packages from the Python Package Index (PyPI) and can also update, remove, and pin project dependencies.

Installing and using pip

Usually pip is already installed along with Python. You can check the presence and version of pip like this:


pip --version

Expected result:


pip 23.1.2 from /usr/local/lib/python3.11/site-packages/pip (python 3.11)

Basic pip commands

Installing a package


pip install requests

Expected result:


Collecting requests
  Downloading requests-2.31.0-py3-none-any.whl (62 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 62.6/62.6 kB 1.2 MB/s eta 0:00:00
Installing collected packages: requests
Successfully installed requests-2.31.0

Installing a specific version


pip install requests==2.25.1

Expected result:


Collecting requests==2.25.1
  Downloading requests-2.25.1-py2.py3-none-any.whl (61 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 61.2/61.2 kB 1.8 MB/s eta 0:00:00
Installing collected packages: requests
Successfully installed requests-2.25.1

List of installed packages


pip list

Expected result:


Package    Version
---------- ---------
certifi    2023.5.7
charset-normalizer 3.1.0
idna       3.4
pip        23.1.2
requests   2.31.0
setuptools 67.8.0
urllib3    2.0.3

Removing a package


pip uninstall requests -y

Expected result:


Found existing installation: requests 2.31.0
Uninstalling requests-2.31.0:
  Successfully uninstalled requests-2.31.0

Popular third-party libraries

Python has a huge number of third-party libraries for a wide variety of tasks. Here are some of the most popular and useful:

Library	Description	Main application	Link
Requests	Convenient handling of HTTP requests	Interaction with web resources, APIs	Documentation
Pandas	Powerful tool for data analysis	Processing and analyzing tabular data	Documentation
NumPy	Working with arrays and mathematical calculations	Scientific computing, array operations	Documentation
Matplotlib	Data visualization	Creating plots and charts	Documentation
Seaborn	Statistical data visualization	Beautiful statistical graphics	Documentation
scikit-learn	Machine learning	Building and training machine learning models	Documentation
TensorFlow	Deep learning and neural networks	Complex deep learning models	Documentation
PyTorch	Deep learning with dynamic computational graphs	Research in deep learning	Documentation
Flask	Micro-framework for web development	Creating web applications and APIs	Documentation
Django	Full-featured web framework	Large web projects	Documentation
Beautiful Soup	Parsing HTML and XML	Extracting data from web pages	Documentation
Pillow	Image processing	Editing and analyzing images	Documentation
SQLAlchemy	ORM for working with databases	Interaction with SQL databases	Documentation
Pygame	Creating games and multimedia applications	2D game development	Documentation
PyQt	Creating desktop applications	Graphical user interfaces (GUI)	Documentation

The choice of library depends on the specific task you want to solve. The Python community is very active, and ready-made solutions already exist for most practical tasks, which can be installed via pip.

Example of installing a popular library:


# Installing pandas for data analysis
pip install pandas

# Installing Flask for web development
pip install flask

Virtual environments

If you install every library into your system Python, sooner or later you'll hit a conflict: one project needs django 3.0, another needs django 4.2, but only one version can be installed. The standard practice is to create a separate virtual environment for each project.

A virtual environment (venv) is an isolated Python environment where you can install packages without affecting other projects or the system Python.

Two projects, each with its own venv holding its own package versions: django 3.0 + requests 2.20 in project A, django 4.2 + requests 2.31 in project B

Creating a virtual environment


# Creating a virtual environment
python -m venv myenv

# Activating the virtual environment
# On Windows:
myenv\Scripts\activate

# On macOS/Linux:
source myenv/bin/activate

# After activation, the environment name will appear at the beginning of the command prompt
(myenv) $

Installing packages in a virtual environment


# Installing packages in the activated virtual environment
pip install pandas matplotlib

Saving and installing dependencies


# Saving the list of installed packages
pip freeze > requirements.txt

# The contents of the requirements.txt file will look something like this:
# matplotlib==3.7.2
# numpy==1.25.2
# pandas==2.0.3
# ...

# Installing packages from the requirements.txt file
pip install -r requirements.txt

Understanding Check

Let's check how well you've learned about third-party libraries and pip:

Which command will correctly install pandas version 1.5.0?