Pydantic V2 Migration Guide

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Are you ready for some fun with Pydantic V2? Let’s dive in and explore the exciting world of data validation using this amazing library!

But first things first: why should we care about migrating to Pydantic V2? Well, my friend, let me tell ya it’s all about performance. With version 2, Pydantic has become faster than ever before thanks to some major under-the-hood improvements. Plus, the new syntax is more intuitive and easier to use!

So, without further ado, let’s get started with our migration guide!

Step 1: Installation
To install Pydantic V2, simply run this command in your terminal or console:

# This script installs Pydantic V2 with the dotenv extra, which allows for loading environment variables from a .env file
# The [dotenv] indicates that the extra is being installed
# The command is using the pip package manager to install Pydantic
# The install command is being run in the terminal or console


pip install pydantic[dotenv]

This will also include the dotenv package for loading environment variables. If you don’t need that, just remove it from the brackets.

Step 2: Updating your code
Now let’s take a look at some examples of how to update your existing Pydantic V1 code to work with version 2. First, let’s say we have this model in our `models.py` file:

# Importing the necessary package for loading environment variables
from pydantic import BaseModel

# Defining a User model that inherits from the BaseModel class
class User(BaseModel):
    # Defining the attributes of the User model with their respective data types
    name: str
    email: str
    age: int
    
    # Configuring the model to work with an ORM (Object Relational Mapper)
    class Config:
        # Setting the orm_mode to True to allow the model to work with an ORM
        orm_mode = True
        
    # Defining a string representation of the User model
    def __repr__(self) -> str:
        # Using f-strings to format the string representation with the model's attributes
        return f"<User({self.name}, {self.email}, {self.age})>"

To update this to Pydantic V2, we need to make a few changes. First, let’s remove the `__repr__()` method since it is no longer needed:

# Importing the necessary module
from pydantic import BaseModel

# Creating a class called User that inherits from the BaseModel class
class User(BaseModel):
    # Defining the attributes of the User class
    name: str # Name of the user, must be a string
    email: str # Email of the user, must be a string
    age: int # Age of the user, must be an integer
    
    # Creating a nested class called Config
    class Config:
        orm_mode = True # Setting the orm_mode attribute to True, which allows the class to work with ORMs (Object Relational Mappers)
        
    # Removing the __repr__() method as it is no longer needed in Pydantic V2
    # def __repr__(self) -> str:
    #     return f"<User({self.name}, {self.email}, {self.age})>"

Next, let’s update the `Config` class to use Pydantic V2 syntax instead of V1:

# Updated script with annotations

# Importing the necessary module
from pydantic import BaseModel

# Defining the User class which inherits from the BaseModel class
class User(BaseModel):
    # Defining the attributes of the User class with their respective data types
    name: str # Name of the user, data type: string
    email: str # Email of the user, data type: string
    age: int # Age of the user, data type: integer
    
    # Defining the Config class within the User class
    class Config:
        # Setting the orm_mode attribute to True, which allows the class to work with ORMs (Object Relational Mappers)
        orm_mode = True
        
        # Old syntax for validator, which is no longer supported in Pydantic V2
        # validator="my_validator"
        
        # New syntax for validator, using validate_assistant and pre parameters
        validate_assistant=True # Enables validation for the class
        pre=true # Runs the validation before the class is instantiated

Finally, let’s update any custom validation functions to use the `pre` and `post` hooks instead of the `validator` function. For example:

# Importing necessary libraries
from pydantic import BaseModel # Importing the BaseModel class from the pydantic library
import re # Importing the regular expression library

# Creating a User class that inherits from the BaseModel class
class User(BaseModel):
    name: str # Defining a name attribute of type string
    email: str # Defining an email attribute of type string
    age: int # Defining an age attribute of type integer
    
    class Config:
        orm_mode = True # Setting the orm_mode to True to enable ORM mode
        
        # Defining the new syntax for validation using pre and post hooks
        validate_assistant=True, pre=[pre_validate_email] 
        
# Defining a pre-validation function for the email attribute
def pre_validate_email(obj):
    # Using regular expressions to check if the email is in a valid format
    if not re.match("^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$", obj.email):
        raise ValueError("Invalid email address") # Raising a ValueError if the email is not in a valid format

And that’s it! Your code is now ready for Pydantic V2 goodness.

Step 3: Testing your migration
To test your migration, you can run the following command in your terminal or console:

pytest tests/unit_tests/*.py

This will execute all of your unit tests and ensure that everything is working as expected with Pydantic V2. If any issues arise, don’t worry just consult the official documentation for more information on how to fix them!

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