An simple async ORM with Fastapi in mind.
Project description
ORMar
The ormar
package is an async ORM for Python, with support for Postgres,
MySQL, and SQLite.
Ormar - apart form obvious ORM in name - get it's name from ormar in swedish which means snakes, and ormar(e) in italian which means cabinet. And what's a better name for python ORM than snakes cabinet :)
Ormar is built with:
SQLAlchemy core
for query building.databases
for cross-database async support.pydantic
for data validation.
Because ormar is built on SQLAlchemy core, you can use alembic
to provide
database migrations.
The goal was to create a simple ORM that can be used directly with fastapi
that bases it's data validation on pydantic.
Initial work was inspired by encode/orm
, later I found ormantic
and used it as a further inspiration.
The encode package was too simple (i.e. no ability to join two times to the same table) and used typesystem for data checks.
ormar is still under development: We recommend pinning any dependencies with ormar~=0.2.0
Note: Use ipython
to try this from the console, since it supports await
.
import databases
import ormar
import sqlalchemy
database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()
class Note(ormar.Model):
class Meta:
tablename = "notes"
database = database
metadata = metadata
# primary keys of type int by dafault are set to autoincrement
id: ormar.Integer(primary_key=True)
text: ormar.String(length=100)
completed: ormar.Boolean(default=False)
# as of ormar >=0.3.2 you can provide a list of choices that will be validated
flag: ormar.String(default='To do', choices=['To do', 'Pending', 'Done'])
# Create the database
engine = sqlalchemy.create_engine(str(database.url))
metadata.create_all(engine)
# .create()
await Note.objects.create(text="Buy the groceries.", completed=False)
await Note.objects.create(text="Call Mum.", completed=True)
await Note.objects.create(text="Send invoices.", completed=True)
# .all()
notes = await Note.objects.all()
# .filter()
notes = await Note.objects.filter(completed=True).all()
# exact, iexact, contains, icontains, lt, lte, gt, gte, in
notes = await Note.objects.filter(text__icontains="mum").all()
# exclude - from ormar >= 0.3.1
notes = await Note.objects.exclude(text__icontains="mum").all()
# startswith, istartswith, endswith, iendswith - from ormar >= 0.3.3
notes = await Note.objects.filter(text__iendswith="mum.").all()
notes = await Note.objects.filter(text__istartswith="call").all()
notes = await Note.objects.filter(text__startswith="Buy").all()
# .get()
note = await Note.objects.get(id=1)
# .update()
await note.update(completed=True)
# .delete()
await note.delete()
# 'pk' always refers to the primary key
note = await Note.objects.get(pk=2)
note.pk # 2
Ormar supports loading and filtering across foreign keys...
import databases
import ormar
import sqlalchemy
database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()
class Album(ormar.Model):
class Meta:
tablename = "album"
metadata = metadata
database = database
id: ormar.Integer(primary_key=True)
name: ormar.String(length=100)
class Track(ormar.Model):
class Meta:
tablename = "track"
metadata = metadata
database = database
id: ormar.Integer(primary_key=True)
album: ormar.ForeignKey(Album)
title: ormar.String(length=100)
position: ormar.Integer()
# Create some records to work with.
malibu = await Album.objects.create(name="Malibu")
await Track.objects.create(album=malibu, title="The Bird", position=1)
await Track.objects.create(album=malibu, title="Heart don't stand a chance", position=2)
await Track.objects.create(album=malibu, title="The Waters", position=3)
fantasies = await Album.objects.create(name="Fantasies")
await Track.objects.create(album=fantasies, title="Help I'm Alive", position=1)
await Track.objects.create(album=fantasies, title="Sick Muse", position=2)
# Fetch an instance, without loading a foreign key relationship on it.
track = await Track.objects.get(title="The Bird")
# We have an album instance, but it only has the primary key populated
print(track.album) # Album(id=1) [sparse]
print(track.album.pk) # 1
print(track.album.name) # Raises AttributeError
# Load the relationship from the database
await track.album.load()
assert track.album.name == "Malibu"
# This time, fetch an instance, loading the foreign key relationship.
track = await Track.objects.select_related("album").get(title="The Bird")
assert track.album.name == "Malibu"
# By default you also get a second side of the relation
# constructed as lowercase source model name +'s' (tracks in this case)
# you can also provide custom name with parameter related_name
album = await Album.objects.select_related("tracks").all()
assert len(album.tracks) == 3
# Fetch instances, with a filter across an FK relationship.
tracks = Track.objects.filter(album__name="Fantasies")
assert len(tracks) == 2
# Fetch instances, with a filter and operator across an FK relationship.
tracks = Track.objects.filter(album__name__iexact="fantasies")
assert len(tracks) == 2
# Limit a query
tracks = await Track.objects.limit(1).all()
assert len(tracks) == 1
Since version >=0.3 Ormar supports also many to many relationships
import databases
import ormar
import sqlalchemy
database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()
class Author(ormar.Model):
class Meta:
tablename = "authors"
database = database
metadata = metadata
id: ormar.Integer(primary_key=True)
first_name: ormar.String(max_length=80)
last_name: ormar.String(max_length=80)
class Category(ormar.Model):
class Meta:
tablename = "categories"
database = database
metadata = metadata
id: ormar.Integer(primary_key=True)
name: ormar.String(max_length=40)
class PostCategory(ormar.Model):
class Meta:
tablename = "posts_categories"
database = database
metadata = metadata
class Post(ormar.Model):
class Meta:
tablename = "posts"
database = database
metadata = metadata
id: ormar.Integer(primary_key=True)
title: ormar.String(max_length=200)
categories: ormar.ManyToMany(Category, through=PostCategory)
author: ormar.ForeignKey(Author)
guido = await Author.objects.create(first_name="Guido", last_name="Van Rossum")
post = await Post.objects.create(title="Hello, M2M", author=guido)
news = await Category.objects.create(name="News")
# Add a category to a post.
await post.categories.add(news)
# or from the other end:
await news.posts.add(post)
# Creating related object from instance:
await post.categories.create(name="Tips")
assert len(await post.categories.all()) == 2
# Many to many relation exposes a list of related models
# and an API of the Queryset:
assert news == await post.categories.get(name="News")
# with all Queryset methods - filtering, selecting related, counting etc.
await news.posts.filter(title__contains="M2M").all()
await Category.objects.filter(posts__author=guido).get()
# related models of many to many relation can be prefetched
news_posts = await news.posts.select_related("author").all()
assert news_posts[0].author == guido
# Removal of the relationship by one
await news.posts.remove(post)
# or all at once
await news.posts.clear()
Since version >=0.3.4 Ormar supports also queryset level delete and update statements, as well as get_or_create and update_or_create
import databases
import ormar
import sqlalchemy
database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()
class Book(ormar.Model):
class Meta:
tablename = "books"
metadata = metadata
database = database
id: ormar.Integer(primary_key=True)
title: ormar.String(max_length=200)
author: ormar.String(max_length=100)
genre: ormar.String(max_length=100, default='Fiction', choices=['Fiction', 'Adventure', 'Historic', 'Fantasy'])
await Book.objects.create(title='Tom Sawyer', author="Twain, Mark", genre='Adventure')
await Book.objects.create(title='War and Peace', author="Tolstoy, Leo", genre='Fiction')
await Book.objects.create(title='Anna Karenina', author="Tolstoy, Leo", genre='Fiction')
await Book.objects.create(title='Harry Potter', author="Rowling, J.K.", genre='Fantasy')
await Book.objects.create(title='Lord of the Rings', author="Tolkien, J.R.", genre='Fantasy')
# update accepts kwargs that are used to update queryset model
# all other arguments are ignored (argument names not in own model table)
await Book.objects.filter(author="Tolstoy, Leo").update(author="Lenin, Vladimir") # update all Tolstoy's books
all_books = await Book.objects.filter(author="Lenin, Vladimir").all()
assert len(all_books) == 2
# delete accepts kwargs that will be used in filter
# acting in same way as queryset.filter(**kwargs).delete()
await Book.objects.delete(genre='Fantasy') # delete all fantasy books
all_books = await Book.objects.all()
assert len(all_books) == 3
# queryset needs to be filtered before deleting to prevent accidental overwrite
# to update whole database table each=True needs to be provided as a safety switch
await Book.objects.update(each=True, genre='Fiction')
all_books = await Book.objects.filter(genre='Fiction').all()
assert len(all_books) == 3
# helper get/update or create methods of queryset
# if not exists it will be created
vol1 = await Book.objects.get_or_create(title="Volume I", author='Anonymous', genre='Fiction')
assert await Book.objects.count() == 1
# if exists it will be returned
assert await Book.objects.get_or_create(title="Volume I", author='Anonymous', genre='Fiction') == vol1
assert await Book.objects.count() == 1
# if not exist the instance will be persisted in db
vol2 = await Book.objects.update_or_create(title="Volume II", author='Anonymous', genre='Fiction')
assert await Book.objects.count() == 1
# if pk or pkname passed in kwargs (like id here) the object will be updated
assert await Book.objects.update_or_create(id=vol2.id, genre='Historic')
assert await Book.objects.count() == 1
Since version >=0.3.5 Ormar supports also bulk operations -> bulk_create and bulk_update
import databases
import ormar
import sqlalchemy
database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()
class ToDo(ormar.Model):
class Meta:
tablename = "todos"
metadata = metadata
database = database
id: ormar.Integer(primary_key=True)
text: ormar.String(max_length=500)
completed: ormar.Boolean(default=False)
# create multiple instances at once with bulk_create
await ToDo.objects.bulk_create(
[
ToDo(text="Buy the groceries."),
ToDo(text="Call Mum.", completed=True),
ToDo(text="Send invoices.", completed=True),
]
)
todoes = await ToDo.objects.all()
assert len(todoes) == 3
# update objects
for todo in todoes:
todo.completed = False
# perform update of all objects at once
# objects need to have pk column set, otherwise exception is raised
await ToDo.objects.bulk_update(todoes)
completed = await ToDo.objects.filter(completed=False).all()
assert len(completed) == 3
Data types
The following keyword arguments are supported on all field types.
primary_key: bool
nullable: bool
default: Any
server_default: Any
index: bool
unique: bool
choices: typing.Sequence
All fields are required unless one of the following is set:
nullable
- Creates a nullable column. Sets the default toNone
.default
- Set a default value for the field.server_default
- Set a default value for the field on server side (like sqlalchemy'sfunc.now()
).primary key
withautoincrement
- When a column is set to primary key and autoincrement is set on this column. Autoincrement is set by default on int primary keys.
Available Model Fields:
String(length)
Text()
Boolean()
Integer()
Float()
Date()
Time()
DateTime()
JSON()
BigInteger()
Decimal(scale, precision)
ForeignKey(to)
Many2Many(to, through)
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