The Orator ORM provides a simple yet beautiful ActiveRecord implementation.
It is inspired by the database part of the Laravel framework, but largely modified to be more pythonic.
The full documentation is available here: https://orator-orm.com/docs
You can install Orator in 2 different ways:
- The easier and more straightforward is to use pip
pip install orator
- Install from source using the official repository (https://github.com/sdispater/orator)
The different dbapi packages are not part of the package dependencies, so you must install them in order to connect to corresponding databases:
- Postgres:
psycopg2
- MySQL:
PyMySQL
ormysqlclient
- Sqlite: The
sqlite3
module is bundled with Python by default
All you need to get you started is the configuration describing your database connections
and passing it to a DatabaseManager
instance.
from orator import DatabaseManager, Model
config = {
'mysql': {
'driver': 'mysql',
'host': 'localhost',
'database': 'database',
'user': 'root',
'password': '',
'prefix': ''
}
}
db = DatabaseManager(config)
Model.set_connection_resolver(db)
class User(Model):
pass
Note that we did not tell the ORM which table to use for the User
model. The plural "snake case" name of the
class name will be used as the table name unless another name is explicitly specified.
In this case, the ORM will assume the User
model stores records in the users
table.
You can specify a custom table by defining a __table__
property on your model:
class User(Model):
__table__ = 'my_users'
The ORM will also assume that each table has a primary key column named id
.
You can define a __primary_key__
property to override this convention.
Likewise, you can define a __connection__
property to override the name of the database
connection that should be used when using the model.
Once a model is defined, you are ready to start retrieving and creating records in your table.
Note that you will need to place updated_at
and created_at
columns on your table by default.
If you do not wish to have these columns automatically maintained,
set the __timestamps__
property on your model to False
.
users = User.all()
user = User.find(1)
print(user.name)
users = User.where('votes', '>', 100).take(10).get()
for user in users:
print(user.name)
You can also use the query builder aggregate functions:
count = User.where('votes', '>', 100).count()
If you feel limited by the builder's fluent interface, you can use the where_raw
method:
users = User.where_raw('age > ? and votes = 100', [25]).get()
If you need to process a lot of records, you can use the chunk
method to avoid
consuming a lot of RAM:
for users in User.chunk(100):
for user in users:
# ...
You can specify which database connection to use when querying a model by using the on
method:
user = User.on('connection-name').find(1)
If you are using read / write connections, you can force the query to use the "write" connection with the following method:
user = User.on_write_connection().find(1)
When creating a new model, you pass attributes to the model constructor. These attributes are then assigned to the model via mass-assignment. Though convenient, this can be a serious security concern when passing user input into a model, since the user is then free to modify any and all of the model's attributes. For this reason, all models protect against mass-assignment by default.
To get started, set the __fillable__
or __guarded__
properties on your model.
The __fillable__
property specifies which attributes can be mass-assigned.
class User(Model):
__fillable__ = ['first_name', 'last_name', 'email']
The __guarded__
is the inverse and acts as "blacklist".
class User(Model):
__guarded__ = ['id', 'password']
You can also block all attributes from mass-assignment:
__guarded__ = ['*']
To create a new record in the database, simply create a new model instance and call the save
method.
user = User()
user.name = 'John'
user.save()
You can also use the create
method to save a model in a single line, but you will need to specify
either the __fillable__
or __guarded__
property on the model since all models are protected against
mass-assignment by default.
After saving or creating a new model with auto-incrementing IDs, you can retrieve the ID by accessing
the object's id
attribute:
inserted_id = user.id
# Create a new user in the database
user = User.create(name='John')
# Retrieve the user by attributes, or create it if it does not exist
user = User.first_or_create(name='John')
# Retrieve the user by attributes, or instantiate it if it does not exist
user = User.first_or_new(name='John')
user = User.find(1)
user.name = 'Foo'
user.save()
You can also run updates as queries against a set of models:
affected_rows = User.where('votes', '>', 100).update(status=2)
To delete a model, simply call the delete
model:
user = User.find(1)
user.delete()
User.destroy(1)
User.destroy(1, 2, 3)
You can also run a delete query on a set of models:
affected_rows = User.where('votes', '>' 100).delete()
If you want to only update the timestamps on a model, you can use the touch
method:
user.touch()
By default, the ORM will maintain the created_at
and updated_at
columns on your database table
automatically. Simply add these timestamp
columns to your table. If you do not wish for the ORM to maintain
these columns, just add the __timestamps__
property:
class User(Model):
__timestamps__ = False
If you wish to customize the format of your timestamps (the default is the ISO Format) that will be returned when using the to_dict
or the to_json
methods, you can override the get_date_format
method:
class User(Model):
def get_date_format():
return 'DD-MM-YY'
When building JSON APIs, you may often need to convert your models and relationships to dictionaries or JSON.
So, Orator includes methods for doing so. To convert a model and its loaded relationship to a dictionary,
you may use the to_dict
method:
user = User.with_('roles').first()
return user.to_dict()
Note that entire collections of models can also be converted to dictionaries:
return User.all().serailize()
To convert a model to JSON, you can use the to_json
method!
return User.find(1).to_json()
The database query builder provides a fluent interface to create and run database queries. It can be used to perform most database operations in your application, and works on all supported database systems.
users = db.table('users').get()
for user in users:
print(user['name'])
for users in db.table('users').chunk(100):
for user in users:
# ...
user = db.table('users').where('name', 'John').first()
print(user['name'])
user = db.table('users').where('name', 'John').pluck('name')
roles = db.table('roles').lists('title')
This method will return a list of role titles. It can return a dictionary if you pass an extra key parameter.
roles = db.table('roles').lists('title', 'name')
users = db.table('users').select('name', 'email').get()
users = db.table('users').distinct().get()
users = db.table('users').select('name as user_name').get()
query = db.table('users').select('name')
users = query.add_select('age').get()
users = db.table('users').where('age', '>', 25).get()
users = db.table('users').where('age', '>', 25).or_where('name', 'John').get()
users = db.table('users').where_between('age', [25, 35]).get()
users = db.table('users').where_not_between('age', [25, 35]).get()
users = db.table('users').where_in('id', [1, 2, 3]).get()
users = db.table('users').where_not_in('id', [1, 2, 3]).get()
users = db.table('users').where_null('updated_at').get()
query = db.table('users').order_by('name', 'desc')
query = query.group_by('count')
query = query.having('count', '>', 100)
users = query.get()
users = db.table('users').skip(10).take(5).get()
users = db.table('users').offset(10).limit(5).get()
The query builder can also be used to write join statements.
db.table('users') \
.join('contacts', 'users.id', '=', 'contacts.user_id') \
.join('orders', 'users.id', '=', 'orders.user_id') \
.select('users.id', 'contacts.phone', 'orders.price') \
.get()
db.table('users').left_join('posts', 'users.id', '=', 'posts.user_id').get()
You can also specify more advance join clauses:
clause = JoinClause('contacts').on('users.id', '=', 'contacts.user_id').or_on(...)
db.table('users').join(clause).get()
If you would like to use a "where" style clause on your joins,
you may use the where
and or_where
methods on a join.
Instead of comparing two columns, these methods will compare the column against a value:
clause = JoinClause('contacts').on('users.id', '=', 'contacts.user_id').where('contacts.user_id', '>', 5)
db.table('users').join(clause).get()
Sometimes you may need to create more advanced where clauses such as "where exists" or nested parameter groupings. It is pretty easy to do with the Orator query builder
db.table('users') \
.where('name', '=', 'John') \
.or_where(
db.query().where('votes', '>', 100).where('title', '!=', 'admin')
).get()
The query above will produce the following SQL:
SELECT * FROM users WHERE name = 'John' OR (votes > 100 AND title != 'Admin')
db.table('users').where_exists(
db.table('orders').select(db.raw(1)).where_raw('order.user_id = users.id')
)
The query above will produce the following SQL:
SELECT * FROM users
WHERE EXISTS (
SELECT 1 FROM orders WHERE orders.user_id = users.id
)
The query builder also provides a variety of aggregate methods, `
such as count
, max
, min
, avg
, and sum
.
users = db.table('users').count()
price = db.table('orders').max('price')
price = db.table('orders').min('price')
price = db.table('orders').avg('price')
total = db.table('users').sum('votes')
Sometimes you may need to use a raw expression in a query.
These expressions will be injected into the query as strings, so be careful not to create any SQL injection points!
To create a raw expression, you may use the raw()
method:
db.table('users') \
.select(db.raw('count(*) as user_count, status')) \
.where('status', '!=', 1) \
.group_by('status') \
.get()
db.table('users').insert(email='[email protected]', votes=0)
db.table('users').insert({
'email': '[email protected]',
'votes': 0
})
It is important to note that there is two notations available. The reason is quite simple: the dictionary notation, though a little less practical, is here to handle columns names which cannot be passed as keywords arguments.
If the table has an auto-incrementing id, use insert_get_id
to insert a record and retrieve the id:
id = db.table('users').insert_get_id({
'email': '[email protected]',
'votes': 0
})
db.table('users').insert([
{'email': '[email protected]', 'votes': 0},
{'email': '[email protected]', 'votes': 0}
])
db.table('users').where('id', 1).update(votes=1)
db.table('users').where('id', 1).update({'votes': 1})
Like the insert
statement, there is two notations available.
The reason is quite simple: the dictionary notation, though a little less practical, is here to handle
columns names which cannot be passed as keywords arguments.
db.table('users').increment('votes') # Increment the value by 1
db.table('users').increment('votes', 5) # Increment the value by 5
db.table('users').decrement('votes') # Decrement the value by 1
db.table('users').decrement('votes', 5) # Decrement the value by 5
You can also specify additional columns to update:
db.table('users').increment('votes', 1, name='John')
db.table('users').where('age', '<', 25).delete()
db.table('users').delete()
db.table('users').truncate()
The query builder provides a quick and easy way to "union" two queries:
first = db.table('users').where_null('first_name')
users = db.table('users').where_null('last_name').union(first).get()
The union_all
method is also available.
Sometimes you may wish to use one database connection for SELECT statements, and another for INSERT, UPDATE, and DELETE statements. Orator makes this easy, and the proper connections will always be used whether you use raw queries, the query builder or the actual ORM
Here is an example of how read / write connections should be configured:
config = {
'mysql': {
'read': {
'host': '192.168.1.1'
},
'write': {
'host': '192.168.1.2'
},
'driver': 'mysql',
'database': 'database',
'user': 'root',
'password': '',
'prefix': ''
}
}
Note that two keys have been added to the configuration dictionary: read
and write
.
Both of these keys have dictionary values containing a single key: host
.
The rest of the database options for the read
and write
connections
will be merged from the main mysql
dictionary. So, you only need to place items
in the read
and write
dictionaries if you wish to override the values in the main dictionary.
So, in this case, 192.168.1.1
will be used as the "read" connection, while 192.168.1.2
will be used as the "write" connection. The database credentials, prefix, character set,
and all other options in the main mysql
dictionary will be shared across both connections.
To run a set of operations within a database transaction, you can use the transaction
method
which is a context manager:
with db.transaction():
db.table('users').update({votes: 1})
db.table('posts').delete()
Note
Any exception thrown within a transaction block will cause the transaction to be rolled back automatically.
Sometimes you may need to start a transaction yourself:
db.begin_transaction()
You can rollback a transaction with the rollback
method:
db.rollback()
You can also commit a transaction via the commit
method:
db.commit()
By default, all underlying DBAPI connections are set to be in autocommit mode meaning that you don't need to explicitly commit after each operation.
When using multiple connections, you can access them via the connection()
method:
users = db.connection('foo').table('users').get()
You also can access the raw, underlying dbapi connection instance:
db.connection().get_connection()
Sometimes, you may need to reconnect to a given database:
db.reconnect('foo')
If you need to disconnect from the given database, use the disconnect
method:
db.disconnect('foo')