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A minimalistic ORM with basic features.

Project description

A minimalistic ORM with basic features.

Inspired by Django ORM.

What’s the point?

MinORM was designed as minimalistic ORM, to be as simple as possible. It’s not production-ready solution, rather a proof of concept. The goal is to demonstrate example of an ORM, more-less applicable for usage, that could be created with python in a couple of days.

Usage

DB Connection

Establish connection to database by calling .connect() method of connector object, with certain db handler.

Connecting to sqlite database:

from minorm.connectors import connector
from minorm.db_specs import SQLiteSpec

connector.connect(SQLiteSpec('example.db'))

Connecting to postgresql database (requires psycopg2 to be installed):

from minorm.connectors import connector
from minorm.db_specs import PostgreSQLSpec

connection_string = "host=localhost port=5432 dbname=mydb user=admin password=secret"
connector.connect(PostgreSQLSpec(connection_string))

Close connection by calling .disconnect() method:

connector.disconnect()

Models

Create a model class that represents a single table in a database:

from minorm.models import Model
from minorm.fields import CharField, IntegerField

class Person(Model):
    name = CharField(max_length=120)
    age = IntegerField()

It’s possible to create a new table in a database:

Person.create_table()

Or to use existing one, by set table name in model meta:

class Book(Model):
    title = CharField(max_length=90)

    class Meta:
        table_name = "some_table"

It’s possible to drop a table:

Person.drop_table()

Create a new instance or update existing one in db by calling save method:

person = Person()
person.name = "John" # set field values as attributes
person.age = 33
person.save()

book = Book(title="foobar")  # or pass it in init method
book.save()

Remove a row from db by calling delete method:

person.delete()

Create a model with foreign relation by using ForeignKey field:

class Book(Model):
    title = CharField(max_length=90)
    author = ForeignKey(Person)

Pass an instance of related model when saving a new one:

book = Book(title="foobar", author=person)
book.save()

Queryset methods

Use queryset, accessible by model’s qs property, to perform db operations on multiple rows:

all():

Get all rows as a list of namedtuple objects:

persons = Person.qs.all()  # list of namedtuples

it’s possible to limit number of selected rows by using slices:

persons = Person.qs[:3].all()  # list with only three items
values(*fields):

Prepare qs to get rows as dictionaries with fields, passed to the method:

values_qs = Book.qs.values('title', 'author__name')  # dicts with this two keys
books = values_qs.all()  # this method call will actually hit db, not previous
filter(**lookups):

Filter query, result will contain only items that matches all lookups:

# user type is "member" AND age > 18
filtered_qs = Person.qs.filter(user_type='member', age__gt=18)
result = filtered_qs.all()  # hits db, performs select query

List of supported lookup expressions:

  • lt, lte - less than (or equal)

  • gt, gte - greater than (or equal)

  • neq - not equal

  • in - checks if value is between given options

  • startswith, endswith, contains - check inclusion of a string

aswell(**lookups):

Make query result to include items that also matches lookups listed in the method:

# age > 18 OR user is admin
filtered_qs = Person.qs.filter(age__gt=18).aswell(user_type="admin")
order_by(*fields):

Set ordering of queried rows. Use - prefix to reverse order:

Book.qs.order_by('created')  # for oldest to newest
Person.qs.order_by('-id')  # reverse ordering by id
exists():

Return boolean, that indicates presence of rows that match filters:

Person.qs.filter(name="mike").exists()  # True if there is such name, otherwise False
get(**lookups):

Get single row as an instance of the model class:

person = Person.qs.get(id=7)  # model instance object

raises Model.DoesNotExists if corresponding row not found in db, and MultipleQueryResult if more than one row matches query filters.

create(**field_values):

Create a new instance in db:

person = Person.qs.create(name="John", age=33)

is a shortcut for two calls:

person = Person(name="John", age=33)
person.save()
update(**field_values):

Update field values of existing rows in db:

Book.qs.filter(price__lt=200).update(price=250)
delete():

Remove all rows of queryset from db:

Product.qs.filter(created__lt=date(2020, 11, 10)).delete()
bulk_create(instances):

Create multiple instances in one db query:

Book.qs.bulk_create([
    Book(title="foo", author=1),
    Book(title="bar", author=2),
    Book(title="baz", author=1),
])  # creates all these books in one query
select_related(*fk_fields):

Prepare queryset to perform select query with join of foreign relation:

for book in Book.qs.select_related('author').all():
    author = book.author  # without select_related call, author attribute is fk ID
    print(book.title, author.name)

TODO

  • add more model fields

  • add join of 3 and more tables in select_related

  • add filter lookups over fields of foreign relations

  • test Postgresql support

  • add basic aggregation functions (SUM, COUNT, etc)

  • add transaction support

Running tests

To run tests, create virtual environment and then run:

make test

License

The MIT License (MIT)

Contributed by Campos Ilya

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