Pydantic-v2-crashcourse

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Pydantic-v2-crashcourse

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# Overview of Pydantic v2

This repository provides an in-depth overview of the `pydantic` library, version `2.3.0`. Pydantic is a crucial data validation and settings management library for Python, enabling the early identification and rectification of errors.

## Table of Contents

1. [Models](#models)
2. [Nested Models](#nested-models)
3. [Fields](#fields)
4. [Field Validators](#field-validators)
5. [Model Validators](#model-validators)
6. [Computed Fields](#computed-fields)
7. [Integration with Dataclasses](#integration-with-dataclasses)
8. [Settings for Environment Variables](#settings-for-environment-variables)

## Models

Models in Pydantic are classes that inherit from `BaseModel`. They define the data structure using type annotations and offer avenues for data validation and conversion.

## Nested Models

Nested Models allow you to represent complex, nested data structures by defining models within models.

## Fields

Fields are the individual variables defined within a model. They can have additional configurations and validations beyond the basic type annotations.

## Field Validators

Field Validators are functions used to apply additional validations or transformations to fields before they are set in the model.

## Model Validators

Model Validators allow for validation at the model level, occurring after all the Field Validators have been executed. They can be performed both pre and post-field validation.

## Computed Fields

Computed Fields are fields whose values are dynamically computed from the values of other fields.

## Integration with Dataclasses

Pydantic offers integrations with Python Dataclasses to simplify type safety and data validation.

## Settings for Environment Variables

Pydantic enables the loading and validation of settings from environment variables, simplifying the configuration of your applications.

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