A minimal asynchronous database object relational mapper
Project description
A minimal asynchronous database object relational mapper that supports transaction, connection pool and migration.
Currently supports PostgreSQL with asyncpg
.
Install
Requires Python 3.10+
pip install morm
Init project
Run morm_admin init -p app
in your project directory to make some default files such as _morm_config_.py
, mgr.py
Edit morm_config.py to put the correct database credentials:
from morm.db import Pool
DB_POOL = Pool(
dsn='postgres://',
host='localhost',
port=5432,
user='user',
password='pass',
database='db_name',
min_size=10,
max_size=90,
)
This will create and open an asyncpg pool which will be automatically closed at exit.
Model
It's more than a good practice to define a Base model first:
from morm.pg_models import BaseCommon as Model
# BaseCommon defines id, created_at and updated_at fields.
# While pg_models.Base defines only id.
class Base(Model):
class Meta:
abstract = True
Then a minimal model could look like this:
from morm.fields import Field
class User(Base):
name = Field('varchar(65)')
email = Field('varchar(255)')
password = Field('varchar(255)')
Advanced models could look like this:
import random
def get_rand():
return random.randint(1, 9)
class User(Base):
class Meta:
db_table = 'myapp_user'
abstract = False # default is False
proxy = False # default is False
# ... etc...
# see morm.meta.Meta for supported meta attributes.
name = Field('varchar(65)')
email = Field('varchar(255)')
password = Field('varchar(255)')
profession = Field('varchar(255)', default='Unknown')
random = Field('integer', default=get_rand) # function can be default
class UserProfile(User):
class Meta:
proxy = True
exclude_fields_down = ('password',) # exclude sensitive fields in retrieval
# this will also exclude this field from swagger docs if you are
# using our fastAPI framework
Rules for field names
- Must not start with an underscore (
_
). You can set arbitrary variables to the model instance with names starting with underscores; normally you can not set any variable to a model instance. Names not starting with an underscore are all expected to be field names, variables or methods that are defined during class definition. _<name>_
such constructions are reserved for pre-defined overridable methods such as_pre_save_
,_post_save_
, etc..- Name
Meta
is reserved to be a class that contains configuration of the model for both model and model instance.
Initialize a model instance
keyword arguments initialize corresponding fields according to the keys.
Positional arguments must be dictionaries of keys and values.
Example:
User(name='John Doe', profession='Teacher')
User({'name': 'John Doe', 'profession': 'Teacher'})
User({'name': 'John Doe', 'profession': 'Teacher'}, age=34)
Validations
You can setup validation directly on the attribute or define a class method named _clean_fieldname
to run a validation and change the value before it is inserted or updated into the db. These two types of validations work a bit differently:
- Validation on field attribute: Can not change the value, must return True or False. It has more strict behavior than the
_clean_*
method for the attribute. This will run even when you are setting the value of an attribute by model instance, e.guser.islive = 'live'
this would throwValueError
if you set the validator asislive = Field('boolean', validator=lambda x: x is None or isinstance(x, bool))
. - Validation with
_clean_{fieldName}
method: Can change the value and must return the final value. It is only applied during insert or update using the model query handler (usingsave
orupdate
orinsert
).
Example:
class User(Base):
class Meta:
db_table = 'myapp_user'
abstract = False # default is False
proxy = False # default is False
# ... etc...
# see morm.meta.Meta for supported meta attributes.
name = Field('varchar(65)')
email = Field('varchar(255)')
# restrict your devs to things such as user.password = '1234567' # <8 chars
password = Field('varchar(255)', validator=lambda x: x is None or len(x)>=8)
profession = Field('varchar(255)', default='Unknown')
random = Field('integer', default=get_rand) # function can be default
def _clean_password(self, v: str):
if not v: return v # password can be empty (e.g for third party login)
if len(v) < 8:
raise ValueError(f"Password must be at least 8 characters long.")
if len(v) > 100:
raise ValueError(f"Password must be at most 100 characters long.")
# password should contain at least one uppercase, one lowercase, one number, and one special character
if not any(c.isupper() for c in v):
raise ValueError(f"Password must contain at least one uppercase letter.")
if not any(c.islower() for c in v):
raise ValueError(f"Password must contain at least one lowercase letter.")
if not any(c.isdigit() for c in v):
raise ValueError(f"Password must contain at least one number.")
if not any(c in '!@#$%^&*()-_=+[]{}|;:,.<>?/~' for c in v):
raise ValueError(f"Password must contain at least one special character.")
return v
Special Model Meta attribute f
:
You can access field names from ModelClass.Meta.f
.
This allows a spell-safe way to write the field names. If you
misspell the name, you will get AttributeError
.
f = User.Meta.f
my_data = {
f.name: 'John Doe', # safe from spelling mistake
f.profession: 'Teacher', # safe from spelling mistake
'hobby': 'Gardenning', # unsafe from spelling mistake
}
Model Meta attributes
db_table
(str): db table name,abstract
(bool): Whether it is an abstract model. Abstract models do not have db table and are used as base models.pk
(str): Primary key. Defaults to 'id',proxy
(bool): Whether it is a proxy model. Defaults to False. Proxy models inherit everything. This is only to have different pythonic behavior of a model. Proxy models can not define new fields and they do not have separate db table but share the same db table as their parents. Proxy setting is always inherited by child model, thus If you want to turn a child model non-proxy, set the proxy setting in its Meta class.ordering
(Tuple[str]): Ordering. Example:('name', '-price')
, where name is ascending and price is in descending order.fields_up
(Tuple[str]): These fields only will be taken to update or save data onto db. Empty tuple means no restriction.fields_down
(Tuple[str]): These fields only will be taken to select/retrieve data from db. Empty tuple means no restriction.exclude_fields_up
(Tuple[str]): Exclude these fields when updating data to db. Empty tuple means no restriction.exclude_fields_down
(Tuple[str]): Exclude these fields when retrieving data from db. Empty tuple means no restriction.exclude_values_up
(Dict[str, Tuple[Any]]): Exclude fields with these values when updating. Empty dict and empty tuple means no restriction. Example:{'': (None,), 'price': (0,)}
when field name is left empty ('') that criteria will be applied to all fields.exclude_values_down
(Dict[str, Tuple[Any]]): Exclude fields with these values when retrieving data. Empty dict and empty tuple means no restriction. Example:{'': (None,), 'price': (0,)}
when field name is left empty ('') that criteria will be applied to all fields.f
: Access field names.
CRUD
All available database operations are exposed through DB
object.
Example:
from morm.db import DB
db = DB(DB_POOL) # get a db handle.
# Create
user = User(name='John Doe', profession='Teacher')
await db.save(user)
# Read
user5 = await db(User).get(5)
# Update
user5.age = 30
await db.save(user5)
# Delete
await db.delete(user5)
Get
The get method has the signature get(*vals, col='', comp='=$1')
.
It gets the first row found by column and value. If col
is not given, it defaults to the primary key (pk
) of the model. If comparison is not given, it defaults to =$1
Example:
from morm.db import DB
db = DB(DB_POOL) # get a db handle.
# get by pk:
user5 = await db(User).get(5)
# price between 5 and 2000
user = await db(User).get(5, 2000, col='price', comp='BETWEEN $1 AND $2')
Filter
from morm.db import DB
db = DB(DB_POOL) # get a db handle.
f = User.Meta.f
user_list = await db(User).qfilter().q(f'"{f.profession}"=$1', 'Teacher').fetch()
user_list = await db(User).qfilter().qc(f.profession, '=$1', 'Teacher').fetch()
It is safer to use ${qh.c}
instead of $1
, ${qh.c+1}
instead of $2
, etc.. :
from morm.db import DB
db = DB(DB_POOL) # get a db handle.
qh = db(User)
user_list = await qh.qfilter()\
.q(f'{qh.f.profession} = ${qh.c} AND {qh.f.age} = ${qh.c+1}', 'Teacher', 30)\
.fetch()
Query
Calling db(Model)
gives you a model query handler which has several query methods to help you make queries.
Use .q(query, *args)
method to make queries with positional arguments. If you want named arguments, use the uderscored version of these methods. For example, q(query, *args)
has an underscored version q_(query, *args, **kwargs)
that can take named arguments.
You can add a long query part by part:
from morm.db import DB
db = DB(DB_POOL) # get a db handle.
qh = db(User) # get a query handle.
query, args = qh.q(f'SELECT * FROM {qh.db_table}')\
.q(f'WHERE {qh.f.profession} = ${qh.c}', 'Teacher')\
.q_(f'AND {qh.f.age} = :age', age=30)\
.getq()
print(query, args)
# fetch:
user_list = await qh.fetch()
The q
family of methods (q, qc, qu etc..
) can be used to
build a query step by step. These methods can be chained
together to break down the query building in multiple steps.
Several properties are available to get information of the model such as:
qh.db_table
: Quoted table name e.g"my_user_table"
.qh.pk
: Quoted primary key name e.g"id"
.qh.ordering
: ordering e.g"price" ASC, "quantity" DESC
.qh.f.<field_name>
: quoted field names e.g"profession"
.qh.c
: Current available position for positional argument (Instead of hardcoded$1
,$2
, usef'${qh.c}'
,f'${qh.c+1}'
).
qh.c
is a counter that gives an integer representing the
last existing argument position plus 1.
reset()
can be called to reset the query to start a new.
To execute a query, you need to run one of the execution methods
: fetch, fetchrow, fetchval, execute
.
Notable convenience methods:
qupdate(data)
: Initialize a update query for dataqfilter()
: Initialize a filter query upto WHERE clasue.get(pkval)
: Get an item by primary key.
Transaction
from morm.db import Transaction
async with Transaction(DB_POOL) as tdb:
# use tdb just like you use db
user6 = await tdb(User).get(6)
user6.age = 34
await tdb.save(user6)
user5 = await tdb(User).get(5)
user5.age = 34
await tdb.save(user5)
Indexing
You can use the index: Tuple[str] | str | None
parameter to define what type/s of indexing should be applied to the field. Examples:
class User(Base):
parent_id = Field('integer', index='hash')
username = Field('varchar(65)', index='hash,btree') # two indexes
email = Field('varchar(255)', index=('hash', 'btree')) # tuple is allowed as well
perms = Field('integer[]', index='gin:gin__int_ops')
If you want to remove the indexing, Add a -
minus sign to the specific index and then run migration. After that you can safely remove the index keyword, e.g:
--- parent_id = Field('integer', index='-hash')
===$ ./mgr makemigrations
===$ ./mgr migrate
>>> parent_id = Field('integer', index='') # now you can remove the hash
Field/Model grouping
You can group your model fields, for example, you can define groups like admin
, mod
, staff
, normal
and make your model fields organized into these groups. This will enable you to implement complex field level organized access controls. You can say, that the password
field belongs to the admin group, then subscriptions
field to mod group and then active_subscriptions
to staff group.
class UserAdmin(Base):
class Meta:
groups = ('admin',) # this model belongs to the admin group
password = Field('varchar(100)', groups=('admin',))
subscriptions = Field('integer[]', groups=('mod',))
active_subscriptions = Field('integer[]', groups=('staff',))
Sudo (Elevated access to fields)
We believe writing to certain fields or areas of your system should require elevated access.
Field
can take an argument sudo
that means elevated access required. IF sudo
is set to true for some field, you will not be able to write to this field using the ModelQuery
(direct raw query can still be performed) unless your db instance is set to have sudo=True
as well:
db = DB(DB_POOL, sudo=True)
Migration
Migration is a new feature and only forward migrations are supported as of now.
You should have created the morm_config.py and mgr.py file with morm_admin init
.
List all the models that you want migration for in mgr.py. You will know how to edit it once you open it.
Then, to make migration files, run:
python mgr.py makemigrations
This will ask you for confirmation on each changes, add -y
flag to bypass this.
run
python mgr.py migrate
to apply the migrations.
Adding data into migration
Go into migration directory after making the migration files and look for the .py
files inside queue
directory. Identify current migration files, open them for edit. You will find something similar to this:
import morm
class MigrationRunner(morm.migration.MigrationRunner):
"""Run migration with pre and after steps.
"""
migration_query = """{migration_query}"""
# async def run_before(self):
# """Run before migration
# self.tdb is the db handle (transaction)
# self.model is the model class
# """
# dbm = self.tdb(self.model)
# # # Example
# # dbm.q('SOME QUERY TO SET "column_1"=$1', 'some_value')
# # await dbm.execute()
# # # etc..
# async def run_after(self):
# """Run after migration.
# self.tdb is the db handle (transaction)
# self.model is the model class
# """
# dbm = self.tdb(self.model)
# # # Example
# # dbm.q('SOME QUERY TO SET "column_1"=$1', 'some_value')
# # await dbm.execute()
# # # etc..
As you can see, there are run_before
and run_after
hooks. You can use them to make custom queries before and after the migration query. You can even modify the migration query itself.
Example:
...
async def run_before(self):
"""Run before migration
self.tdb is the db handle (transaction)
self.model is the model class
"""
user0 = self.model(name='John Doe', profession='Software Engineer', age=45)
await self.tdb.save(user0)
...
Do not do these
- Do not delete migration files manually, use
python mgr.py delete_migration_files <start_index> <end_index>
command instead. - Do not modify mutable values in-place e.g
user.addresses.append('Some address')
, instead set the value:user.addresses = [*user.addresses, 'Some address']
so that the__setattr__
is called, on whichmorm
depends for checking changed fields for thedb.save()
and related methods.
Initialize a FastAPI project
Run init_fap app
in your project root. It will create a directory structure like this:
├── app
│ ├── core
│ │ ├── __init__.py
│ │ ├── models
│ │ │ ├── base.py
│ │ │ ├── __init__.py
│ │ │ └── user.py
│ │ ├── schemas
│ │ │ └── __init__.py
│ │ └── settings.py
│ ├── __init__.py
│ ├── main.py
│ ├── tests
│ │ ├── __init__.py
│ │ └── v1
│ │ ├── __init__.py
│ │ └── test_sample.py
│ ├── v1
│ │ ├── dependencies
│ │ │ └── __init__.py
│ │ ├── __init__.py
│ │ ├── internal
│ │ │ └── __init__.py
│ │ └── routers
│ │ ├── __init__.py
│ │ └── root.py
│ └── workers.py
├── app.service
├── .gitignore
├── gunicorn.sh
├── mgr
├── mgr.py
├── _morm_config_.py
├── nginx
│ ├── app
│ └── default
├── requirements.txt
├── run
└── vact
You can run the dev app with ./run
or the production app with ./gunicorn.sh
.
To run the production app as a service with systemctl start app
, copy the app.service to /etc/systemd/system
Notes:
- You can setup your venv path in the
vact
file. To activate the venv with all the environment vars, just run. vact
. - An environment file
.env_APP
is created in your home directory containing dev and production environments.
Pydantic support
You can get pydantic model from any morm model using the _pydantic_
method, e.g User._pydantic_()
would give you the pydantic version of your User
model. The _pydantic_()
method supports a few parameters to customize the generated pydantic model:
up=False
: Defines if the model should be for up (update into database) or down (retrieval from database).suffix=None
: You can add a suffix to the name of the generated pydantic model.include_validators=None
: Whether the validators defined in each field (with validator parameter) should be added as pydantic validators. WhenNone
(which is default) validators will be included for data update into database (i.e forup=True
). Note that, the model field validators return True or False, while pydantic validators return the value, this conversion is automatically added internally while generating the pydantic model.
If you are using our FastAPI framework, generating good docs for user data retrieval using the User model would be as simple as:
@router.get('/crud/{model}', responses=Res.schema_all(User._pydantic_())
async def get(request: Request, model: str, vals = '', col: str='', comp: str='=$1'):
if some_authentication_error:
raise Res(status=Res.Status.unauthorized, errors=['Invalid Credentials!']) # throws a correct HTTP error with additional error message
...
return Res(user)
The above will define all common response types: 200, 401, 403, etc.. and the 200 success response will show an example with correct data types from your User model and will show only the fields that are allowed to be shown (controlled with exclude_fields_down
or fields_down
in the User.Meta
).
JSON handling
It may seem tempting to add json and jsonb support with asyncpg.Connection.set_type_codec()
method, but we have not provided any option to use this method easily in morm
, as it turned out to be making the queries very very slow. If you want to handle json, better add a _clean_{field}
method in your model and do the conversion there:
class User(Base):
settings = Field('jsonb')
...
def _clean_settings(self, v):
if not isinstance(v, str):
v = json.dumps(v)
return v
If you want to have it converted to json during data retrieval from database as well, pass a validator which should return False if it is not json, and then pass a modifier in the field to do the conversion. Do note that modifier only runs if validator fails. Thus you will set and get the value as json (list or dict) and the _clean_settings
will covert it back to text during database insert or update.
class User(Base):
settings = Field('jsonb', validator=lambda x: isinstance(x, list|dict), modifier=lambda x: json.loads(x))
...
def _clean_settings(self, v):
if not isinstance(v, str):
v = json.dumps(v)
return v
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