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A sensible orm for PostgreSQL or SQLite

Project description

An opinionated lightweight orm for PostgreSQL or SQLite.

Prom has been used in both single threaded and multi-threaded environments, including environments using Greenthreads.

1 Minute Getting Started with SQLite

First, install prom:

$ pip install prom

Set an environment variable:

$ export PROM_DSN=prom.interface.sqlite.SQLite://:memory:

Start python:

$ python

Create a prom Orm:

>>> import prom
>>> class Foo(prom.Orm):
...     table_name = "foo_table_name"
...     bar = prom.Field(int)

Now go wild and create some Foo objects:

>>> for x in range(10):
...     f = Foo.create(bar=x)

Now query them:

>>> f = Foo.query.first()
>>> for f in Foo.query.in_bar([2, 3, 4]):

Update them:

>>> for f in Foo.query:
... += 100

and get rid of them:

>>> for f in Foo.query:
...     f.delete()

Congratulations, you have now created, retrieved, updated, and deleted from your database.

Example – Create a User class

Here is how you would define a new Orm class:

# app.models (app/
from prom import Orm, Field, Index

class User(Orm):

    table_name = "user_table_name"

    username = Field(str, True, unique=True), # string field (required) with a unique index

    password = Field(str, True), # string field (required)

    email = Field(str), # string field (not required)

    index_email = Index('email') # set a normal index on email field

You can specify the connection using a prom dsn url:


So to use the builtin Postgres interface on testdb database on host localhost with username testuser and password testpw:


To use our new User class:

import prom
from app.models import User


# create a user
u = User(username='foo', password='awesome_and_secure_pw_hash', email='')

# query for our new user
u = User.query.is_username('foo').get_one()
print u.username # foo

# get the user again via the primary key:
u2 = User.query.get_pk(
print u.username # foo

# let's add a bunch more users:
for x in range(10):
    username = "foo{}".format(x)
    ut = User(username=username, password="...", email="{}".format(username))

# now let's iterate through all our new users:
for u in User.query.get():
    print u.username

Environment Configuration

Prom can be automatically configured on import by setting the environment variable PROM_DSN:

export PROM_DSN=prom.interface.postgres.PostgreSQL://testuser:testpw@localhost/testdb

If you have multiple connections, you can actually set multiple environment variables:

export PROM_DSN_1=prom.interface.postgres.PostgreSQL://testuser:testpw@localhost/testdb1#conn_1
export PROM_DSN_2=prom.interface.postgres.PostgreSQL://testuser:testpw@localhost/testdb2#conn_2

After you’ve set the environment variable, then you just need to import Prom in your code:

import prom

and Prom will take care of parsing the dsn url(s) and creating the connection(s) automatically.

The Query class

You can access the query, or table, instance for each prom.Orm child you create by calling its .query class property:

print User.query # prom.Query

Through the power of magic, everytime you call this property, a new prom.Query instance will be created.

Customize the Query class

You can also extend the default prom.Query class and let your prom.Orm child know about it

# app.models (app/

class DemoQuery(prom.Query):
    def get_by_foo(self, *foos):
        """get all demos with matching foos, ordered by last updated first"""
        return self.in_foo(*foos).desc_updated().get()

class DemoOrm(prom.Orm):
    query_class = DemoQuery

DemoOrm.query.get_by_foo(1, 2, 3) # this now works

Notice the query_class class property on the DemoOrm class. Now every instance of DemoOrm (or child that derives from it) will forever use DemoQuery.

Using the Query class

You should check the actual code for the query class in prom.query.Query for all the methods you can use to create your queries, Prom allows you to set up the query using psuedo method names in the form:


So, if you wanted to select on the foo fields, you could do:


or, if you have the name in the field as a string:

command_field(fieldname, field_value)

so, we could also select on foo this way:

query.is_field('foo', 5)

The different WHERE commands:

  • inin_field(fieldname, field_vals) – do a sql fieldname IN (field_val1, ...) query
  • ninnin_field(fieldname, field_vals) – do a sql fieldname NOT IN (field_val1, ...) query
  • isis_field(fieldname, field_val) – do a sql fieldname = field_val query
  • notnot_field(fieldname, field_val) – do a sql fieldname != field_val query
  • gtgt_field(fieldname, field_val) – do a sql fieldname > field_val query
  • gtegte_field(fieldname, field_val) – do a sql fieldname >= field_val query
  • ltlt_field(fieldname, field_val) – do a sql fieldname < field_val query
  • ltelte_field(fieldname, field_val) – do a sql fieldname <= field_val query

The different ORDER BY commands:

  • ascasc_field(fieldname) – do a sql ORDER BY fieldname ASC query
  • descdesc_field(fieldname) – do a sql ORDER BY fieldname DESC query

You can also sort by a list of values:

foos = [3, 5, 2, 1]

rows = query.select_foo().in_foo(foos).asc_foo(foos).values()
print rows # [3, 5, 2, 1]

And you can also set limit and page:

query.get(10, 1) # get 10 results for page 1 (offset 0)
query.get(10, 2) # get 10 results for page 2 (offset 10)

They can be chained together:

# SELECT * from table_name WHERE foo=10 AND bar='value 2' ORDER BY che DESC LIMIT 5
query.is_foo(10).is_bar("value 2").desc_che().get(5)

You can also write your own queries by hand:

query.raw("SELECT * FROM table_name WHERE foo = %s", [foo_val])

The prom.Query has a couple helpful query methods to make grabbing rows easy:

  • get – get(limit=None, page=None) – run the select query.

  • get_one – get_one() – run the select query with a LIMIT 1.

  • value – value() – similar to get_one() but only returns the selected field(s)

  • values – values(limit=None, page=None) – return the selected fields as a tuple, not an Orm instance

    This is really handy for when you want to get all the ids as a list:

    # get all the bar ids we want
    bar_ids = Bar.query.select_pk().values()
    # now pull out the Foo instances that correspond to the Bar ids
    foos = Foo.query.is_bar_id(bar_ids).get()
  • pk – pk() – return the selected primary key

  • pks – pks(limit=None, page=None) – return the selected primary keys

  • has – has() – return True if there is atleast one row in the db matching query

  • get_pk – get_pk(pk) – run the select query with a WHERE _id = pk

  • get_pks – get_pks([pk1, pk2,...]) – run the select query with WHERE _id IN (...)

  • raw – raw(query_str, *query_args, **query_options) – run a raw query

  • all – all() – return an iterator that can move through every row in the db matching query

  • count – count() – return an integer of how many rows match the query

NOTE, Doing custom queries using raw would be the only way to do join queries.

Specialty Queries

If you have a date or datetime field, you can pass kwargs to fine tune date queries:

import datetime

class Foo(prom.Orm):

    table_name = "foo_table"

    dt = prom.Field(datetime.datetime)

    index_dt = prom.Index('dt')

# get all the foos that have the 7th of every month
r = q.is_dt(day=7).all() # SELECT * FROM foo_table WHERE EXTRACT(DAY FROM dt) = 7

# get all the foos in 2013
r = q.is_dt(year=2013).all()

Hopefully you get the idea from the above code.

The Iterator class

the get and all query methods return a prom.query.Iterator instance. This instance has a useful attribute has_more that will be true if there are more rows in the db that match the query.

Similar to the Query class, you can customize the Iterator class by setting the iterator_class class variable:

class DemoIterator(prom.Iterator):

class DemoOrm(prom.Orm):
    iterator_class = DemoIterator

Multiple db interfaces or connections

It’s easy to have one set of prom.Orm children use one connection and another set use a different connection, the fragment part of a Prom dsn url sets the name:

import prom

class Orm1(prom.Orm):
    connection_name = "connection_1"

class Orm2(prom.Orm):
    connection_name = "connection_2"

Now, any class that extends Orm1 will use connection_1 and any orm that extends Orm2 will use connection_2.

Schema class

The Field class

You can create fields in your schema using the Field class, the field has a signature like this:

Field(field_type, field_required, **field_options)

The field_type is the python type (eg, str or int or datetime) you want the field to be.

The field_required is a boolean, it is true if the field needs to have a value, false if it doesn’t need to be in the db.

The field_options are any other settings for the fields, some possible values:

  • size – the size of the field (for a str this would be the number of characters in the string)
  • max_size – The max size of the field (for a str, the maximum number of characters, for an int, the biggest number you’re expecting)
  • min_size – The minimum size of the field (can only be used with a corresponding max_size value)
  • unique – set to True if this field value should be unique among all the fields in the db.
  • ignore_case – set to True if indexes on this field should ignore case

Foreign Keys

You can have a field reference the primary key of another field:

from prom import Orm, Field

class Orm1(Orm):
    table_name = "table_1"

    foo = Field(int)

class Orm2(Orm):
    table_name = "table_2"

    orm1_id=prom.Field(Orm1, True) # strong reference

    orm1_id_2=prom.Field(Orm1, False) # weak reference

Passing in an Orm class as the type of the field will create a foreign key reference to that Orm. If the field is required, then it will be a strong reference that deletes the row from Orm2 if the row from s1 is deleted, if the field is not required, then it is a weak reference, which will set the column to NULL in the db if the row from Orm1 is deleted.


While Prom will most likely work on other versions, these are the versions we are running it on (just for references):


$ python --version
Python 2.7.3


$ psql --version
psql (PostgreSQL) 9.3.6



If you want to use Prom with Postgres, you need psycopg2:

$ apt-get install libpq-dev python-dev
$ pip install psycopg

Green threads

If you want to use Prom with gevent, you’ll need gevent and psycogreen:

$ pip install gevent
$ pip install psycogreen

These are the versions we’re using:

$ pip install "gevent==1.0.1"
$ pip install "psycogreen==1.0"

Then you can setup Prom like this:

import gevent.monkey

import prom.gevent

Now you can use Prom in the same way you always have. If you would like to configure the threads and stuff, you can pass in some configuration options using the dsn, the three parameters are async, pool_maxconn, pool_minconn, and pool_class. The only one you’ll really care about is pool_maxconn which sets how many connections should be created.

All the options will be automatically set when prom.gevent.patch_all() is called.


Prom installs using pip:

$ pip install prom

Using for the first time

Prom takes the approach that you don’t want to be hassled with table installation while developing, so when it tries to do something and sees that the table doesn’t yet exist, it will use your defined fields for your prom.Orm child and create a table for you, that way you don’t have to remember to run a script or craft some custom db query to add your tables, Prom takes care of that for you automatically. Likewise, if you add a field (and it’s not required) then prom will go ahead and add that field to your table so you don’t have to bother with crafting ALTER queries while developing.

If you want to install the tables manually, you can create a script or something and use the install() method:


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