Building Asynchronous Python Applications with ORM

Are you looking for a powerful and flexible tool to manage your database operations in Python? Look no further than the orm package. This async ORM for Python provides an intuitive and efficient way to interact with databases and build high-performance, scalable, and secure applications. Whether you’re working with Postgres, MySQL, or SQLite, the orm package has got you covered.

At its core, the orm package leverages SQLAlchemy core for query building. This means you can take advantage of SQLAlchemy’s powerful query capabilities while enjoying the benefits of an asynchronous ORM. But that’s not all. The orm package also integrates seamlessly with the databases library, providing cross-database async support. This allows you to work with different database backends without worrying about compatibility issues.

Data validation is an essential part of any application, and the orm package understands that. That’s why it integrates with the typesystem library, which provides robust data validation capabilities. With typesystem, you can ensure that the data you store in your database meets the desired criteria, reducing the risk of data integrity issues.

One of the key features of the orm package is its compatibility with Alembic. With Alembic, you can easily manage database migrations, making it a breeze to evolve your database schema as your application grows and changes. Say goodbye to manual database schema management and let the orm package handle it for you.

Getting started with the orm package is easy. Simply install it using pip and include the required database driver for your chosen database backend. Whether it’s Postgres, MySQL, or SQLite, the orm package has the necessary drivers to ensure smooth integration.

To illustrate the power of the orm package, let’s walk through a quick example. In this example, we’ll create a simple Note model with three fields: id, text, and completed. We’ll use SQLite as our database backend, but feel free to use the database of your choice. Once we have our model defined, we can create the necessary tables using the create_all method. From there, we can start interacting with our database, whether it’s creating new notes, retrieving existing ones, or updating their properties.

“`python
import databases
import orm

database = databases.Database(“sqlite:///db.sqlite”)
models = orm.ModelRegistry(database=database)

class Note(orm.Model):
tablename = “notes”
registry = models
fields = {
“id”: orm.Integer(primary_key=True),
“text”: orm.String(max_length=100),
“completed”: orm.Boolean(default=False),
}

Create the tables

await models.create_all()

await Note.objects.create(text=”Buy the groceries.”, completed=False)

note = await Note.objects.get(id=1)
print(note)

Note(id=1)

“`

With just a few lines of code, we’ve set up our database, defined our model, created the necessary tables, and interacted with our data. Thanks to the power of the orm package, managing your database operations in your Python applications has never been easier.

In conclusion, the orm package is a versatile and powerful tool for building asynchronous Python applications. Whether you’re working with Postgres, MySQL, or SQLite, the orm package provides a consistent and efficient way to interact with your database. With its integration with SQLAlchemy core, the databases library, and the typesystem library, you can build highly performant and scalable applications while ensuring data integrity and validation. Don’t forget to leverage the power of Alembic for smooth database migrations. So, why wait? Give the orm package a try and experience the joy of building robust and efficient applications with ease.

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Please note that the orm package is BSD licensed and has been designed and built in Brighton, England.*

References:
– ORM Documentation
– SQLAlchemy Core Documentation
– Databases Library
– Typesystem Library
– Asyncpg
– Aiomysql
– Aiosqlite