Amazon DynamoDB mock implementation
Project description
ddbmock – a DynamoDB mock implementation.
Presentation
DynamoDB is a minimalistic NoSQL engine provided by Amazon as a part of their AWS product.
DynamoDB allows you to store documents composed of unicode, number or binary data as well are sets. Each tables must define a hash_key and may define a range_key. All other fields are optional.
DynamoDB is really awesome but is terribly slooooow with managment tasks. This makes it completly unusable in test environements.
ddbmock brings a nice, tiny, in-memory or sqlite implementation of DynamoDB along with much better and detailed error messages. Among its niceties, it features a double entry point:
regular network based entry-point with 1:1 correspondance with stock DynamoDB
embeded entry-point with seamless boto intergration 1, ideal to avoid spinning yet another server.
ddbmock is not intended for production use. It will lose your data. you’ve been warned! I currently recommend the “boto extension” mode for unit-tests and the “server” mode for functional tests.
Installation
$ pip install ddbmock
Developing
$ hg clone ssh://hg@bitbucket.org/Ludia/dynamodb-mock $ pip install nose nosexcover coverage mock webtest boto $ python setup.py develop $ nosetests # --no-skip to run boto integration tests too
What is ddbmock not useful for ?
Do not use it in production or as a cheap DynamoDB replacement. I’ll never stress it enough.
All the focus was on simplicity/hackability and simulation quality. Nothing else.
What is ddbmock useful for ?
FAST and RELIABLE unit testing
FAST and RELIABLE functional testing
experiment with DynamoDB API.
RELIABLE throughput planification
RELIABLE disk space planification
almost any DynamoDB simulation !
ddbmock can also persist your data in SQLITE. This open another vast range of possibilities :)
Current status
pass all boto integration tests
support full table life-cycle
support full item life-cycle
support for all item limitations
accurate size, throughput reporting
no limits on concurent table operations
no limits for request/response size nor item count in these
See http://ddbmock.readthedocs.org/en/latest/pages/status.html for detailed up-to-date status.
History
v1.0.0 (*): full documentation and bugfixes
v0.4.1: schema persistence + thread safety, bugfixes
v0.4.0: sqlite backend + throughput statistics + refactoring, more documentation, more tests
v0.3.2: batchWriteItem support + pass boto integration tests
v0.3.1: accuracy in item/table sizes + full test coverage
v0.3.0: first public release. Full table lifecycle + most items operations
(?) indicates a future release. These are only ideas or “nice to have”.
Example usage
Run as Regular client-server
Ideal for test environment. For stage and production I highly recommend using DynamoDB servers. ddbmock comes with no warranty and will loose your data(tm).
Launch the server
$ pserve development.ini # launch the server on 0.0.0.0:6543
Start the client
import boto from ddbmock import connect_boto_network # Use the provided helper to connect your *own* endpoint db = connect_boto_network() # Done ! just use it wherever in your project as usual. db.list_tables() # get list of tables (empty at this stage)
Note: if you do not want to import ddbmock only for the helper, here is a reference implementation:
def connect_boto_network(host='localhost', port=6543): import boto from boto.regioninfo import RegionInfo endpoint = '{}:{}'.format(host, port) region = RegionInfo(name='ddbmock', endpoint=endpoint) return boto.connect_dynamodb(region=region, port=port, is_secure=False)
Run as a standalone library
Ideal for unit testing or small scale automated functional tests. Nice to play around with boto DynamoDB API too :)
import boto from ddbmock import connect_boto_patch # Wire-up boto and ddbmock together db = connect_boto_patch() # Done ! just use it wherever in your project as usual. db.list_tables() # get list of tables (empty at this stage)
Note, to clean patches made in boto.dynamodb.layer1, you can call clean_boto_patch() from the same module.
Requirements
Python 2.7.x
Pyramid >= 1.3
Boto >= 2.5.0 (optional)
NO AWS account :)
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