kvlite is small library for storing documents in SQL databases. At the moment supported MySQL and SQLite. A document can be string, list/tuple or dictionary. Default serialization is based on cPickleSerializer methods but of course it is possible to define own serialization to store data in kvlite database.

A collection is a group of documents stored in kvlite, and it can be thought of as roughly the equivalent of a table in a relational database.

To install kvlite you just need to copy two files: kvlite.py and kvlite-cli.py. Second one is optional and it will be needed only if you need to have access to kvlite collections via console. Also kvlite-cli.py can be used as example how to use kvlite library.

If pip <http://www.pip-installer.org/> installed in your system, you can install kvlite via

pip install kvlite

>>> import kvlite >>> collection = open('sqlite://memory:test_collection') >>> collection <kvlite.SqliteCollection object at 0x14cb350> >>> collection.count 0 >>> collection.put('1', 'first document') >>> collection.put('2', ('second', 'document')) >>> collection.put('3', {'third': 'document'}) >>> collection.count 3 >>> collection.get('1') ('1', 'first document') >>> collection.get('2') ('2', ('second', 'document')) >>> collection.get('3') ('3', {'third': 'document'}) >>> >>> [k for k in collection.keys() ] ['1', '2', '3'] >>> collection.delete('1') >>> collection.delete('2') >>> collection.delete('3') >>> collection.count 0 >>> collection.close() >>>

• open(uri) - open collection
• remove(uri) - remove collection
• get_uuid(amount) - get list of uuid

To get started just open() function is needed.

URI format is:

• for mysql: mysql://username:password@hostname:port/database.collection_name
• for sqlite: sqlite://path-to-sqlite-file:collection_name or sqlite://memory:collection_name

In case when sqlite is in use two variants of collection is possible: in file and in memory.

The function open(uri) returns MysqlCollection or SqliteCollection object

MysqlCollection and SqliteCollection have the same methods:

• get_uuid() - in case of mysql use, this function will be working faster than for sqlite
• get(k) - if k(key) is not defined, the function get() returns the list of all documents in collection. Otherwise key/value pair is returned for defined k(key)
• put(k,v) - put key/value to storage. The key has limitation - only 40 bytes length. The value can be string, list or tuple, dictionary
• delete(k) - delete key/value pair
• keys() - returns the list of all keys in collection
• count() - returns the amount of documents in collection
• commit() - as kvlite based on transactional databases, commit() is used for commitment changes in collection
• close() - close connection to database

Sometimes it will needed to manage collections: create, check if exists, remove. For these operations you can use CollectionManager. This class has the next methods:

• parse_uri(uri) - depends on type of database, the function parse_uri() can returns deferent result based on which backend is used
• create(name) - create collection
• connection - returns refernce to database collection
• collection_class - returns class MysqlCollection or SqliteCollection depend on backend parameter in URI
• collections() - returns the list of collections in database
• remove(name) - remove collection
• close() - close connection to database

• cPickleSerializer (by default)
• CompressedJsonSerializer

Serializer can be defined via open function

def open(uri, serializer=cPickleSerializer):

''' open collection by URI, if collection does not exist kvlite will try to create it

in case of successful opening or creation new collection return Collection object

serializer: the class or module to serialize msgs with, must have methods or functions named dumps and loads, pickle is the default, use None to store messages in plain text (suitable for strings, integers, etc)

• kvlite structure <https://github.com/ownport/kvlite/blob/master/docs/kvlite.png>
• Link collection to similar projects or where the ideas were taken <https://github.com/ownport/kvlite/blob/master/docs/links.md>