edgy

Edgy

🔥 The perfect ORM to work with complex databases 🔥

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Documentation: https://edgy.dymmond.com 📚

Source Code: https://github.com/dymmond/edgy

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Motivation

From the same author of Saffier, Edgy is also an ORM but different from its predecessor. Saffier is more of a Generic ORM for probably 99.9% of every single day application and works perfectly well with it, whereas Edgy is also that and more.

Edgy comes with batteries included thanks to Pydantic so that means your models are 100% Pydantic which also means you get all the benefits of the technology (like automatic validations...) out of the box with the need of building independent schemas to validate those fields before injest them into a database.

Was it already mentioned that Edgy is extremely fast? Well, it is!

Almost every project, in one way or another uses one (or many) databases. An ORM is simply an mapping of the top of an existing database. ORM extends for Object Relational Mapping and bridges object-oriented programs and relational databases.

Two of the most well known ORMs are from Django and SQLAlchemy. Both have their own strenghts and weaknesses and specific use cases.

This ORM is built on the top of SQLAlchemy core and aims to simplify the way the setup and queries are done into a more common and familiar interface with the power of Pydantic.

Edgy

Edgy is some sort of a fork from Saffier but rewritten at its core fully in Pydantic 🔥.

This was necessary because Saffier although serving 99.9% of the daily use cases, there was still a great need to add automatic validations and performance, so instead of rewritting Saffier and risking breaking existing use cases already in place, a brand new shiny ORM came to be 😁.

Edgy leverages the power of Pydantic while offering a friendly, familiar and easy to use interface.

This ORM was designed to be flexible and compatible with pretty much every ASGI framework, like Esmerald, Starlette, FastAPI, Sanic, Quart... With simple pluggable design thanks to its origins.

Features

While adopting a familiar interface, it offers some cool and powerful features on the top of SQLAlchemy core.

Key features

• Model inheritance - For those cases where you don't want to repeat yourself while maintaining integrity of the models.
• Abstract classes - That's right! Sometimes you simply want a model that holds common fields that doesn't need to created as a table in the database.
• Meta classes - If you are familiar with Django, this is not new to you and Edgy offers this in the same fashion.
• Managers - Versatility at its core, you can have separate managers for your models to optimise specific queries and querysets at ease.
• Filters - Filter by any field you want and need.
• Model operators - Classic operations such as update, get, get_or_none, bulk_create, bulk_update, values, values_list, only, defer and a lot more.
• Relationships made it easy - Support for OneToOne, ForeignKey and ManyToMany in the same Django style.
• Constraints - Unique constraints through meta fields.
• Indexes - Unique indexes through meta fields.
• Native test client - We all know how hard it can be to setup that client for those tests you need so we give you already one.
• Multi-tenancy - Edgy supports multi-tenancy and even offers a possible solution to be used out of the box if you don't want to waste time.

And a lot more you can do here.

Migrations

Since Edgy, like Saffier, it is built on the top of SQLAlchemy core and brings its own native migration system running on the top of Alembic but making it a lot easier to use and more pleasant for you.

Have a look at the migrations for more details.

Installation

To install Edgy, simply run:

$ pip install edgy

You can pickup your favourite database driver by yourself or you can run:

Postgres

$ pip install edgy[postgres]

MySQL/MariaDB

$ pip install edgy[mysql]

SQLite

$ pip install edgy[sqlite]

MSSQL

$ pip install edgy[mssql]

Quick Start

The following is an example how to start with Edgy and more details and examples can be found throughout the documentation.

Use ipython to run the following from the console, since it supports await.

import edgy
from edgy import Database, Registry

database = Database("sqlite:///db.sqlite")
models = Registry(database=database)


class User(edgy.Model):
    """
    The User model to be created in the database as a table
    If no name is provided the in Meta class, it will generate
    a "users" table for you.
    """

    id: int = edgy.IntegerField(primary_key=True)
    is_active: bool = edgy.BooleanField(default=False)

    class Meta:
        registry = models


# Create the db and tables
# Don't use this in production! Use Alembic or any tool to manage
# The migrations for you
await models.create_all()  # noqa

await User.query.create(is_active=False)  # noqa

user = await User.query.get(id=1)  # noqa
print(user)
# User(id=1)

As stated in the example, if no tablename is provided in the Meta class, Edgy automatically generates the name of the table for you by pluralising the class name.

Note

Edgy model declaration with typing is merely visual. The validations of the fields are not done by the typing of the attribute of the models but from the edgy fields.

Which means you don't need to worry about the wrong typing as long as you declare the correct field type.

So does that mean pydantic won't work if you don't declare the type? Absolutely not. Internally Edgy runs those validations through the declared fields and the Pydantic validations are done exactly in the same way you do a normal Pydantic model.

Nothing to worry about!

Let us see an example.

With field typing

import edgy
from edgy import Database, Registry

database = Database("sqlite:///db.sqlite")
models = Registry(database=database)


class User(edgy.Model):
    """
    The User model to be created in the database as a table
    If no name is provided the in Meta class, it will generate
    a "users" table for you.
    """

    id: int = edgy.IntegerField(primary_key=True)
    is_active: bool = edgy.BooleanField(default=False)

    class Meta:
        registry = models

Without field typing

import edgy
from edgy import Database, Registry

database = Database("sqlite:///db.sqlite")
models = Registry(database=database)


class User(edgy.Model):
    """
    The User model to be created in the database as a table
    If no name is provided the in Meta class, it will generate
    a "users" table for you.
    """

    id = edgy.IntegerField(primary_key=True)
    is_active = edgy.BooleanField(default=False)

    class Meta:
        registry = models

It does not matter if you type or not, Edgy knows what and how to validate via edgy fields like IntegerField or BooleanField or any other field.

Connect your application

Do you want to have more complex structures and connect to your favourite framework? Have a look at connections to understand how to do it properly.

Esmerald ecosystem

This does not mean that only works with Esmerald! Edgy is also framework agnostic but the author of Edgy is the same of Saffier and Esmerald which makes it nicer to integrate directly with Esmerald.

How could you integrate Edgy with Esmerald (or any other framework)?

Let us see an example. Since Edgy is fully Pydantic that means we can perform tasks directly.

from esmerald import Esmerald, Gateway, post

import edgy
from edgy.testclient import DatabaseTestClient as Database

database = Database("sqlite:///db.sqlite")
models = edgy.Registry(database=database)


class User(edgy.Model):
    id: int = edgy.IntegerField(primary_key=True)
    name: str = edgy.CharField(max_length=100)
    email: str = edgy.EmailField(max_length=100)
    language: str = edgy.CharField(max_length=200, null=True)
    description: str = edgy.TextField(max_length=5000, null=True)

    class Meta:
        registry = models


@post("/create")
async def create_user(data: User) -> User:
    """
    You can perform the same directly like this
    as the validations for the model (nulls, mandatories, @field_validators)
    already did all the necessary checks defined by you.
    """
    user = await data.save()
    return user


app = Esmerald(
    routes=[Gateway(handler=create_user)],
    on_startup=[database.connect],
    on_shutdown=[database.disconnect],
)

The response of the API /create should have a format similar to this (assuming the post with the following payload as well):

{
    "id": 1,
    "name": "Edgy",
    "email": "[e-mail]",
    "language": "EN",
    "description": "A description",
}

All the examples of this documentation will be using field typing but it is up to you if you want to use them or not.

Exciting!

In the documentation we go deeper in explanations and examples, this was just to warm up. 😁