Run-DynamoDBLocal

AWS makes DynamoDBLocal -- a service that mirrors the API of DynamoDB and runs locally -- available to their customers for testing purposes. This Python packages facilitates running that service as a subprocess of the testing harness.

Install

$ pip install 'run-dynamodblocal[boto3]'

Leave off the [boto3] if you don't intend to use this package's ability to patch boto3.

Usage

Quickstart

With thanks to ncoghlan:

import boto3_mocking
from contextlib import ExitStack
import os.path
import run_dynamodblocal
import unittest

# If patching isn't engaged when the run_dynamodblocal context is entered, an
# exception will be thrown
boto3_mocking.engage_patching()

class MyTest(unittest.TestCase):
    def setUp(self):
        with ExitStack() as resources:
            dynamodblocal_path = os.path.expanduser(
              # wherever you keep the unpacked service binaries
              '~/Downloads/dynamodb_local_latest'
            )
            resources.enter_context(
                run_dynamodblocal.rddbl.patched_into_boto3(dynamodblocal_path)
            )
            
            # Enter any other contexts for this test class...
            
            addCleanup(resources.pop_all().close)
    
    # Define test methods here

Diving Deeper

This package provides two different context managers which run the DynamoDBLocal service -- one of which integrates with boto3 to automatically redirect the dynamodb service to this DynamoDBLocal instance. The DynamoDBLocal started will use the -inMemory flag, so it does not persist on disk after the test run is over and doesn't waste testing time committing information to disk.

It also provides the run_dynamodblocal.LocalDbOps class, which supports refreshing the database schema and populated data based on a Serverless configuration and some basic JSON-type data.

Contributing

1. Fork it on GitHub (https://github.com/rtweeks/run-dynamodblocal)
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create a new Pull Request (on GitHub)