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https://github.com/adewes/blitzdb
Blitz is a document-oriented database for Python that is backend-agnostic. It comes with a flat-file database for JSON documents and provides MongoDB-like querying capabilities.
https://github.com/adewes/blitzdb
Last synced: about 2 months ago
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Blitz is a document-oriented database for Python that is backend-agnostic. It comes with a flat-file database for JSON documents and provides MongoDB-like querying capabilities.
- Host: GitHub
- URL: https://github.com/adewes/blitzdb
- Owner: adewes
- License: mit
- Created: 2014-02-14T21:18:44.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2021-07-12T10:05:07.000Z (about 3 years ago)
- Last Synced: 2024-07-08T14:49:29.250Z (3 months ago)
- Language: Python
- Homepage: http://blitzdb.readthedocs.org
- Size: 1.12 MB
- Stars: 330
- Watchers: 20
- Forks: 37
- Open Issues: 26
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Blitz-DB
[](https://travis-ci.org/adewes/blitzdb)
[](https://pypi.python.org/pypi/blitzdb)
[](http://www.quantifiedcode.com/app/project/gh:adewes:blitzdb)
[](https://www.python.org/download/releases/3.0/)
**BlitzDB**, or just **Blitz** is a document-based, object-oriented, transactional database written purely in Python. Among other things, it provides a **powerful querying language**, **deep indexing of documents**, **compressed data storage** and **automatic referencing of embedded documents**. It is reasonably fast, can be easily embedded in any Python application and does not have any external dependencies (except when using a third-party backend). In addition, you can use it as a **frontend** to other database engines such as MongoDB in case you should need more power.
## [Go To Main Documentation](http://blitzdb.readthedocs.org)
## Key Features
* Document-based, object-oriented interface.
* Powerful and rich querying language.
* Deep document indexes on arbitrary fields.
* Compressed storage of documents.
* Support for multiple backends (e.g. file-based storage, MongoDB).
* Support for database transactions (currently only for the file-based backend).
## Use Cases
Blitz can be used as a standalone document store for client application. Originally blitz was designed for use with the [checkmate](https://github.com/quantifiedcode/checkmate) Python code analysis toolkit, where it stores statistical data. Since blitz stores all documents as single JSON files, it is possible to put the whole database under version-control.
## Installation
The easiest way to install Blitz is through **pip** or **easy_install**
pip install blitzdb
#or...
easy_install blitzdb
For more detailed installation instructions, have a look at the [documentation](http://blitzdb.readthedocs.org).
## Detailed Documentation
The detailed documentation for this project is hosted on [ReadTheDocs](http://blitzdb.readthedocs.org), feel free to take a look!
## Changelog
* 0.4.4: SQL backend: Do not coerce server_default values via a CAST, as this can cause incompatibilities.
* 0.4.3: Many small improvements to the SQL backend.
* 0.3.0: Fully functional SQL backend.
* 0.2.12: Added support for proper attribute iteration to `Document`.
* 0.2.11: Allow setting the `collection` parameter through a `Document.Meta` attribute.
* 0.2.10: Bugfix-Release: Fix Python 3 compatibility issue.
* 0.2.9: Bugfix-Release: Fix serialization problem with file backend.
* 0.2.8: Added `get`, `has_key` and `clear` methods to `Document` class
* 0.2.7: Fixed problem with __unicode__ function in Python 3.
* 0.2.6: Bugfix-Release: Fixed an issue with the $exists operator for the file backend.
* 0.2.5: Bugfix-Release
* 0.2.4: Added support for projections and update operations to the MongoDB backend.
* 0.2.3: Bugfix-Release: Fixed bug in transaction data caching in MongoDB backend.
* 0.2.2: Fix for slice operators in MongoDB backend.
* 0.2.1: Better tests.
* 0.2.0: Support for including additional information in DB references. Support for accessing document attributes as dictionary items.
Added $regex parameter that allows to use regular expressions in queries.
* 0.1.5: MongoDB backend now supports database transactions. Database operations are now read-isolated by default, i.e.
uncommitted operations will not affect database queries before they are committed.
* 0.1.4: Improved indexing of objects for the file backend, added support for automatic serialization/deserialization
of object attributes when adding keys to or querying an index.
* 0.1.3: Sorting of query sets is now supported (still experimental)
* 0.1.2: Small bugfixes, BlitzDB version number now contained in DB config dict
* 0.1.1: BlitzDB is now Python3 compatible (thanks to David Koblas)
## Contributors (in alphabetical order)
* @bwiessneth
* Florian Lehmann - @cashaddy
* Karskrin - @cBrauge
* Chris Mutel - @cmutel
* Cecil Woebker - @cwoebker
* Ethan Blackburn - @EthanBlackburn
* Javier Collado - @jcollado
* Jason Xie - @jxieeducation
* David Koblas - @koblas
* Stéphane Wirtel - @matrixise
* Victor Miclovich - @miclovich
* Dmytro Kyrychuk - @orgkhnargh
* Christoph Neumann - @programmdesign
* Dale - @puredistortion
* tjado - @tejado
* Thomas Ballinger - @thomasballinger
* Tyler Kennedy - @TkTech
* Toby Champion - @tobych
Thanks for all your contributions, without you BlitzDB wouldn't be what it is today :)
## Third-Party Contributions
* [Flask-BlitzDB](https://github.com/puredistortion/flask-blitzdb) Flask adapter for BlitzDB. Blitz + Flask = Awesome!
## Examples
To get an idea of what you can do with Blitz, here are some examples.
### Creating objects
```python
from blitzdb import Document
class Movie(Document):
pass
class Actor(Document):
pass
the_godfather = Movie({'name': 'The Godfather','year':1972,'pk':1L})
marlon_brando = Actor({'name':'Marlon Brando','pk':1L})
al_pacino = Actor({'name' : 'Al Pacino','pk':1L})
```
### Storing objects in the database:
```python
from blitzdb import FileBackend
backend = FileBackend("/path/to/my/db")
the_godfather.save(backend)
marlon_brando.save(backend)
al_pacino.save(backend)
```
### Retrieving objects from the database:
```python
the_godfather = backend.get(Movie,{'pk':1L})
#or...
the_godfather = backend.get(Movie,{'name' : 'The Godfather'})
```
### Filtering objects
```python
movies_from_1972 = backend.filter(Movie,{'year' : 1972})
```
### Working with transactions
```python
backend.begin()
the_godfather.director = 'Roland Emmerich' #oops...
the_godfather.save()
backend.rollback() #undo the changes...
```
### Creating nested object references
```python
the_godfather.cast = {'Don Vito Corleone' : marlon_brando, 'Michael Corleone' : al_pacino}
#Documents stored within other objects will be automatically converted to database references.
marlon_brando.performances = [the_godfather]
al_pacino.performances = [the_godfather]
marlon_brando.save(backend)
al_pacino.save(backend)
the_godfather.save(backend)
#Will store references to the movies within the documents in the DB
```
### Creation of database indexes and advanced querying
```python
backend.create_index(Actor,'performances')
#Will create an index on the 'performances' field, for fast querying
godfather_cast = backend.filter(Actor,{'movies' : the_godfather})
#Will return 'Al Pacino' and 'Marlon Brando'
```
### Arbitrary filter expressions
```python
star_wars_iv = Movie({'name' : 'Star Wars - Episode IV: A New Hope','year': 1977})
star_wars_iv.save()
movies_from_the_seventies = backend.filter(Movie,{'year': lambda year : year >= 1970 and year < 1980})
#Will return Star Wars & The Godfather (man, what a decade!)
```