Peewee - lightweight, flexible and very fast ORM in Python

I invite all djangists / alchemists to answer a little and read a free interpretation of the introductory tutorial and partially the Peewee documentation - stand-alone ORM, which is obligatory for acquaintance to any nutritionist and, in particular, to the flasker. Little is written about her, but in vain. It is very easy to make friends with Peewee, especially if you are already familiar with some ORM on ActiveRecord. More importantly, it’s nice to be friends with her :) Well, let's begin.

pip install peewee

git clone https://github.com/coleifer/peewee.git cd peewee python setup.py install

python setup.py test

pip install flask-peewee

Definition of patterns or “smacks of junga”

from peewee import *
db = SqliteDatabase('people.db')
class Person(Model):
    name = CharField()
    birthday = DateField()
    is_relative = BooleanField()
    class Meta:
        database = db  # модель будет использовать базу данных 'people.db'

Initializing arguments

• null=False - is it possible to store null values;
• index=False - whether to create an index for a given column in the database;
• unique=False- whether to create a unique index for this column in the database. See also the chapter on composite indices ;
• verbose_name=None - a string for human-readable representation of the field;
• help_text=None - a line with auxiliary text for the field;
• db_column=None - a string that explicitly sets the name of the column in the database for this field is used, for example, when working with the legacy database;
• default=None - the default value for class fields during instantiation;
• choices=None - a list or tuple of two-element tuples, where the first element is the value for the base, the second is the displayed value (similar to jang);
• primary_key=False - whether to use this field as a primary key;
• sequence=None - the sequence for filling the field (make sure that the backend supports this functionality);

Metadata

class Pet(Model):
    owner = ForeignKeyField(Person, related_name='pets')
    name = CharField()
    animal_type = CharField()
    class Meta:
        database = db  # модель будет использовать базу данных 'people.db'

>>> Person.create_table()
>>> Pet.create_table()

Work with data

>>> from datetime import date
>>> uncle_bob = Person(name='Bob', birthday=date(1960, 1, 15), is_relative=True)
>>> uncle_bob.save()  # cохраним Боба в базе данных

>>> grandma = Person.create(name='Grandma', birthday=date(1935, 3, 1), is_relative=True)
>>> herb = Person.create(name='Herb', birthday=date(1950, 5, 5), is_relative=False)

>>> grandma.name = 'Grandma L.'
>>> grandma.save()  # обновим запись grandma

>>> bob_kitty = Pet.create(owner=uncle_bob, name='Kitty', animal_type='cat')
>>> herb_fido = Pet.create(owner=herb, name='Fido', animal_type='dog')
>>> herb_mittens = Pet.create(owner=herb, name='Mittens', animal_type='cat')
>>> herb_mittens_jr = Pet.create(owner=herb, name='Mittens Jr', animal_type='cat')

>>> herb_mittens.delete_instance()  # удачи, Варежка
1

>>> herb_fido.owner = uncle_bob
>>> herb_fido.save()
>>> bob_fido = herb_fido  # переименуем переменную для лучшего соответствия суровой реальности

Selections

Retrieve a single record

>>> grandma = Person.select().where(Person.name == 'Grandma L.').get()

>>> grandma = Person.get(Person.name == 'Grandma L.')

Retrieving Multiple Records

>>> for person in Person.select():
...     print person.name, person.is_relative
...
Bob True
Grandma L. True
Herb False

>>> for person in Person.select():
...     print person.name, person.pets.count(), 'pets'
...     for pet in person.pets:
...         print '    ', pet.name, pet.animal_type
...
Bob 2 pets
    Kitty cat
    Fido dog
Grandma L. 0 pets
Herb 1 pets
    Mittens Jr cat

>>> for pet in Pet.select().where(Pet.animal_type == 'cat'):
...     print pet.name, pet.owner.name
...
Kitty Bob
Mittens Jr Herb

# выберем всех животных Боба
>>> for pet in Pet.select().join(Person).where(Person.name == 'Bob'):
...     print pet.name
...
Kitty
Fido

>>> for pet in Pet.select().where(Pet.owner == uncle_bob):
...     print pet.name

>>> for pet in Pet.select().where(Pet.owner == uncle_bob).order_by(Pet.name):
...     print pet.name
...
Fido
Kitty

>>> for person in Person.select().order_by(Person.birthday.desc()):
...     print person.name
...
Bob
Herb
Grandma L.

• until 1940
• after 1959

>>> d1940 = date(1940, 1, 1)
>>> d1960 = date(1960, 1, 1)
>>> for person in Person.select().where((Person.birthday < d1940) | (Person.birthday > d1960)):
...     print person.name
...
Bob
Grandma L.

>>> for person in Person.select().where((Person.birthday > d1940) & (Person.birthday < d1960)):
...     print person.name
...
Herb

>>> for person in Person.select().where(fn.Lower(fn.Substr(Person.name, 1, 1)) == 'g'):
...     print person.name
...
Grandma L.

• SelectQuery.group_by()
• SelectQuery.having()
• SelectQuery.limit() and SelectQuery.offset()

Bonus

On my machine peewee has been faster than Django and SQA at most tasks, and about the same when iterating and returning Model instances.

On my computer, peewee outperformed Django and SQLAlchemy on most tasks, and showed comparable results on iterations and sample instances.

• Django: models and benchmark
• SQLAlchemy: Models and Benchmark
• Peewee: models and benchmark
• Composite bench