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A baseplate compatible fork of datastax' cqlengine library

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cqlmapper

This project is a fork of cqlengine with a number of changes to allow it to work in a baseplate application

Major changes:
  • Remove support for polymorphic models
  • Remove the query evaluator method of defining query constraints
  • Switch from using a global connection object to passing a connection object to methods that interact with the database
  • Batch queries are handled by a Connection-like Batch object that is given as the conn argument to functions rather than using the Model.batch syntax of cqlengine

Example usage:

import uuid

from cassandra.cluster import Cluster
from cqlmapper import columns, connection, models
from cqlmapper.batch import Batch
from cqlmapper.connection import Connection as CQLMapperConnection
from cqlmapper.management import sync_table

class MyFirstModel(Model):
    id = columns.UUID(primary_key=True, default=uuid.uuid4)
    body = colums.Text()

cluster = Cluster()
session = cluster.connect("example")
conn = CQLMapperConnection(session)
sync_table(conn, MyFirstModel)
model_1 = MyFirstModel.create(conn, body="Hello World")
model_2 = MyFirstModel.create(conn, body="Hola Mundo")
# Batch queries can be used as a context manager where the batch query will
# be executed when exiting the context
with Batch(conn) as batch_conn:
    MyFirstModel.create(batch_conn, body="Ciao mondo")
    MyFirstModel.create(batch_conn, body="Bonjour le monde")
# Batch queries can also be created standalone in which case execute_batch
# can be called to execute the queries.  Calls to execute will add the
# query to the batch
batch_conn = Batch(conn)
MyFirstModel.create(batch_conn, body="Hallo Welt")
MyFirstModel.create(batch_conn, body="Hei Verden")
>>> MyFirstModel.objects.count(conn)
4
>>> batch_conn.execute_batch()
>>> MyFirstModel.objects.count(conn)
6
>>> MyFirstModel.get(conn, id=model_1.id).text == model_1.text
True
>>> MyFirstModel.get(conn, id=model_2.id).text == model_1.text
False