The Beginner’s Guide to Pydantic

A Python package to parse and validate data

Photo by Marc Babin on Unsplash

The topic for today is on data validation and settings management using Python type hinting. We are going to use a Python package called pydantic which enforces type hints at runtime. It provides user-friendly errors, allowing you to catch any invalid data. Based on the official documentation, Pydantic is

“… primarily a parsing library, not a validation library. Validation is a means to an end: building a model which conforms to the types and constraints provided.

In other words, pydantic guarantees the types and constraints of the output model, not the input data.”

There are three sections in this tutorial:

1. Setup
2. Implementation
3. Conclusion

Let’s proceed to the next section and start installing the necessary modules.

1. Setup

It is highly recommended to create a virtual environment before you proceed with the installation.

Basic installation

Open up a terminal and run the following command to install pydantic

pip install pydantic

Upgrade existing package

If you already have an existing package and would like to upgrade it, kindly run the following command:

pip install -U pydantic

Anaconda

For Anaconda users, you can install it as follows:

conda install pydantic -c conda-forge

Optional dependencies

pydantic comes with the following optional dependencies based on your needs:

• email-validator — Support for email validation.
• typing-extensions — Support use of Literal prior to Python 3.8.
• python-dotenv — Support for dotenv file with settings.

You can install them manually:

# install email-validator
pip install email-validator
# install typing-extensions
pip install typing_extensions