SQLAlchemy Mixin

A pack of framework-agnostic, easy-to-integrate for SQLAlchemy ORM.

Heavily inspired by Django ORM and Eloquent ORM

easy integration to your existing project like FastApi:

from sqlalchemy_mixins import BaseMixin

class User(Base, BaseMixin):
     pass

Table of Contents

1. Installation
2. Quick Start
   1. Framework-agnostic
   2. Usage with Flask-SQLAlchemy
3. Features
   1. Active Record
      1. CRUD
      2. Querying
   2. Eager Load
   3. Django-like queries
      1. Filter and sort by relations
      2. Automatic eager load relations
   4. All-in-one: smart_query
   5. Beauty __repr__
   6. DateMixin

Installation

Use pip

pip install SqlalchemyMixin

Quick Start

Framework-agnostic

Here's a quick demo of what our mixins can do.

bob = User.create(name='Bob')
post1 = Post.create(body='Post 1', user=bob, rating=3)
post2 = Post.create(body='long-long-long-long-long body', rating=2,
                    user=User.create(name='Bill'),
                    comments=[Comment.create(body='cool!', user=bob)])

# filter using operators like 'in' and 'contains' and relations like 'user'
# will output this beauty: <Post #1 body:'Post1' user:'Bill'>
print(Post.where(rating__in=[2, 3, 4], user___name__like='%Bi%').all())
# joinedload post and user
print(Comment.with_joined('user', 'post', 'post.comments').first())
# subqueryload posts and their comments
print(User.with_subquery('posts', 'posts.comments').first())
# sort by rating DESC, user name ASC
print(Post.sort('-rating', 'user___name').all())
# created_at, updated_at timestamps added automatically
print("Created Bob at ", bob.created_at)   
# serialize to dict, with relationships

Usage with Flask-SQLAlchemy

import sqlalchemy as sa
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy_mixins import BaseMixin

app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite://'
db = SQLAlchemy(app)

######### Models ######### 
class BaseModel(db.Model, BaseMixin):
    __abstract__ = True
    pass


class User(BaseModel):
    name = sa.Column(sa.String)

######## Initialize ########
BaseModel.set_session(db.session)

######## Create test entity ########
db.create_all()
user = User.create(name='bob')
print(user)

*** Autocommit ***

This library relies on SQLAlchemy's autocommit flag. It needs to be set to True when initializing the session i.e:

session = scoped_session(sessionmaker(bind=engine, autocommit=True))
BaseModel.set_session(session)

or with Flask-SQLAlchemy

db = SQLAlchemy(app, session_options={'autocommit': True})

Features

Main features are

• Active Record
• Eager Load
• Django-like queries
• Beauty __repr__
• Timestamps

Active Record

provided by ActiveRecordMixin

SQLAlchemy's Data Mapper pattern is cool, but Active Record pattern is easiest and more DRY.

Well, we implemented it on top of Data Mapper! All we need is to just inject session into ORM class while bootstrapping our app:

BaseModel.set_session(session)
# now we have access to BaseOrmModel.session property

CRUD

We all love SQLAlchemy, but doing CRUD is a bit tricky there.

For example, creating an object needs 3 lines of code:

bob = User(name='Bobby', age=1)
session.add(bob)
session.flush()

Well, having access to session from model, we can just write

bob = User.create(name='Bobby', age=1)

that's how it's done in Django ORM and Peewee

update and delete methods are provided as well

bob.update(name='Bob', age=21)
bob.delete()

And, as in Django and Eloquent, we can quickly retrieve object by id

User.get(1) # instead of session.query(User).get(1)

and fail if such id doesn't exist

User.get_or_abort(123987) # will raise sqlalchemy_mixins.ModelNotFoundError

Querying

As in Flask-SQLAlchemy, Peewee and Django ORM, you can quickly query some class

User.query # instead of session.query(User)

Also we can quickly retrieve first or all objects:

User.first() # instead of session.query(User).first()
User.all() # instead of session.query(User).all()

Eager load

provided by EagerLoadMixin

Nested eager load

If you use SQLAlchemy's eager loading, you may find it not very convenient, especially when we want, say, load user, all his posts and comments to every his post in the same query.

Well, now you can easily set what ORM relations you want to eager load

User.with_({
    'posts': {
        'comments': {
            'user': JOINED
        }
    }
}).all()

or we can write class properties instead of strings:

User.with_({
    User.posts: {
        Post.comments: {
            Comment.user: JOINED
        }
    }
}).all()

Subquery load

Sometimes we want to load relations in separate query, i.e. do subqueryload. For example, we load posts on page like this, and for each post we want to have user and all comments (and comment authors).

To speed up query, we load comments in separate query, but, in this separate query, join user

from sqlalchemy_mixins import JOINED, SUBQUERY
Post.with_({
    'user': JOINED, # joinedload user
    'comments': (SUBQUERY, {  # load comments in separate query
        'user': JOINED  # but, in this separate query, join user
    })
}).all()

Here, posts will be loaded on first query, and comments with users - in second one. See SQLAlchemy docs for explaining relationship loading techniques.

Quick eager load

For simple cases, when you want to just joinedload or subqueryload a few relations, we have easier syntax for you:

Comment.with_joined('user', 'post', 'post.comments').first()
User.with_subquery('posts', 'posts.comments').all()

Note that you can split relations with dot like post.comments due to this SQLAlchemy feature

Filter and sort by relations

provided by SmartQueryMixin

Django-like queries

We implement Django-like field lookups and automatic relation joins.

It means you can filter and sort dynamically by attributes defined in strings!

So, having defined Post model with Post.user relationship to User model, you can write

Post.where(rating__gt=2, user___name__like='%Bi%').all() # post rating > 2 and post user name like ...
Post.sort('-rating', 'user___name').all() # sort by rating DESC, user name ASC

(___ splits relation and attribute, __ splits attribute and operator)

If you need more flexibility, you can use low-level filter_expr method session.query(Post).filter(*Post.filter_expr(rating__gt=2, body='text')), see example.

It's like filter_by in SQLALchemy, but also allows magic operators like rating__gt.

Note: filter_expr method is very low-level and does NOT do magic Django-like joins. Use smart_query for that.

All relations used in filtering/sorting should be explicitly set, not just being a backref

In our example, Post.user relationship should be defined in Post class even if User.posts is defined too.

So, you can't type

class User(BaseModel):
    # ...
    user = sa.orm.relationship('User', backref='posts')

and skip defining Post.user relationship. You must define it anyway:

class Post(BaseModel):
    # ...
    user = sa.orm.relationship('User') # define it anyway

For DRY-ifying your code and incapsulating business logic, you can use SQLAlchemy's hybrid attributes and hybrid_methods. Using them in our filtering/sorting is straightforward (see examples and tests).

Automatic eager load relations

Well, as SmartQueryMixin does auto-joins for filtering/sorting, there's a sense to tell sqlalchemy that we already joined that relation.

So that relations are automatically set to be joinedload if they were used for filtering/sorting.

So, if we write

comments = Comment.where(post___public=True, post___user___name__like='Bi%').all()

then no additional query will be executed if we will access used relations

comments[0].post
comments[0].post.user

All-in-one: smart_query

Filter, sort and eager load in one smartest method.

provided by SmartQueryMixin

In real world, we want to filter, sort and also eager load some relations at once. Well, if we use the same, say, User.posts relation in filtering and sorting, it should not be joined twice.

That's why we combined filter, sort and eager load in one smartest method:

Comment.smart_query(
    filters={
        'post___public': True,
        'user__isnull': False
    },
    sort_attrs=['user___name', '-created_at'],
    schema={
        'post': {
            'user': JOINED
        }
    }).all()

As developers, we need to debug things with convenience. When we play in REPL, we can see this

>>> session.query(Post).all()
[<myapp.models.Post object at 0x04287A50>, <myapp.models.Post object at 0x04287A90>]

Well, using our mixin, we can have more readable output with post IDs:

>>> session.query(Post).all()
[<Post #11>, <Post #12>]

Even more, in Post model, we can define what else (except id) we want to see:

class User(BaseModel):
    __repr_attrs__ = ['name']
    # ...


class Post(BaseModel):
    __repr_attrs__ = ['user', 'body'] # body is just column, user is relationship
    # ...

Now we have

>>> session.query(Post).all()
[<Post #11 user:<User #1 'Bill'> body:'post 11'>,
 <Post #12 user:<User #2 'Bob'> body:'post 12'>]

And you can customize max __repr__ length:

class Post(BaseModel):
    # ...
    __repr_max_length__ = 25
    # ...
    
>>> long_post
<Post #2 body:'Post 2 long-long body' user:<User #1 'Bob'>>   

DateMixin

provided by DateMixin

You can view the created and updated timestamps.

bob = User(name="Bob")
session.add(bob)
session.flush()

print("Created Bob:    ", bob.created_at)
# Created Bob:     2019-03-04 03:53:53.606765

print("Pre-update Bob: ", bob.updated_at)
# Pre-update Bob:  2019-03-04 03:53:53.606769

time.sleep(2)

bob.name = "Robert"
session.commit()

print("Updated Bob:    ", bob.updated_at)
# Updated Bob:     2019-03-04 03:53:58.613044