A stand-alone Python 3 compatible data manager for Redis remote data structures.
The data is owned by different, configurable back-end databases and it is accessed using a light-weight Object Data Mapper (ODM). The source code and documentation are hosted at github while Downloads are available via PyPi.
|Keywords:||server, database, cache, redis, odm|
- Python 2.6 to Python 3.3. Single codebase.
- Optional Cython for faster redis protocol parser.
- You need access to a Redis server.
Key-valued pairs databases, also know as key-value stores, have many differences
from traditional relational databases,
most important being they do not use
SQL as their query language,
storage does not require a fixed table schemas and usually they do not support
Stdnet aims to accommodate a flexible schema and join type operations via a lightweight object data mapper. Importantly, it is designed with large data sets in mind. You pull data you need, nothing more, nothing less. Bandwidth and server round-trips can be reduced to the bare minimum so that your application is fast and memory efficient.
To install, download, uncompress and type:
python setup.py install
pip install python-stdnet
StdNet uses Sphinx for its documentation, and the latest is available at GitHub:
To know which version you have installed:
>>> import stdnet >>> stdnet.__version__ '0.7c2' >>> stdnet.VERSION stdnet_version(major=0, minor=7, micro=0, releaselevel='rc', serial=2)
Backend data-stores provide the backbone of the library, while the Object Data Mapper the syntactic sugar. Currently the list of back-ends is limited to
There are plans to extend it to
- Local memory (planned). For testing purposes.
- Amazon DynamoDB.
stdnet.odm module is the ODM, it maps python objects into database data
and vice-versa. It is design to be fast and safe to use:
from stdnet import odm class Base(odm.StdModel): '''An abstract model. This won't have any data in the database.''' name = odm.SymbolField(unique = True) ccy = odm.SymbolField() def __unicode__(self): return self.name class Meta: abstract = True class Instrument(Base): itype = odm.SymbolField() class Fund(Base): description = odm.CharField() class PositionDescriptor(odm.StdModel): dt = odm.DateField() size = odm.FloatField() price = odm.FloatField() position = odm.ForeignKey("Position", index=False) class Position(odm.StdModel): instrument = odm.ForeignKey(Instrument, related_name='positions') fund = odm.ForeignKey(Fund) history = odm.ListField(model = PositionDescriptor) def __unicode__(self): return '%s: %s @ %s' % (self.fund,self.instrument,self.dt)
Register models with backend:
odm.register(Instrument,'redis://localhost?db=1') odm.register(Fund,'redis://localhost?db=1') odm.register(PositionDescriptor,'redis://localhost?db=2') odm.register(Position,'redis://localhost?db=2')
And play with the API:
>>> f = Fund(name="pluto, description="The pluto fund", ccy="EUR").save() Fund: pluto
At the moment, only redis back-end is available and therefore to run tests you
need to install Redis. If you are using linux, it can be achieved simply
by downloading, uncompressing and running
make, if you are using
windows and want to save yourself a headache you can download precompiled
binaries at servicestack.
Requirements for running tests:
Note, these requirements are only needed if you are planning to run tests. To run tests open a shell and launch Redis. On another shell, from the package directory, type:
Tests are run against a local redis server on port 6379 and database 7 by default.
To change the server and database where to run tests pass the
--server option as follow:
python runtests.py --server redis://myserver.com:6450/?db=12
For more information type:
python runtests.py -h
To access coverage of tests you need to install the coverage package and run the tests using:
coverage run runtests.py
and to check out the coverage report:
- Redis simply because this library uses its awesome features.
- redis-py for the Redis Python client initial implementation which has been subsequently modified.
- hiredis-py for some parts of the C parser.
- SQLAlchemy and Django for ideas and API design.
- Armin Ronacher and Ask Solem for the celery sphinx theme used for the documentation.
Development of stdnet happens at Github: http://github.com/lsbardel/python-stdnet
We very much welcome your contribution of course. To do so, simply follow these guidelines:
- Fork python-stdnet on github
- Create a topic branch
git checkout -b my_branch
- Push to your branch
git push origin my_branch
- Create an issue at https://github.com/lsbardel/python-stdnet/issues with a link to your patch
This software is licensed under the New BSD License. See the LICENSE file in the top distribution directory for the full license text.