Fast Python bindings for the Vedis embedded NoSQL database. Vedis is a fun, fast, embedded database modeled after Redis.
View the vedis-python documentation.
Features
Vedis features:
- Embedded, zero-conf database
- Transactional (ACID)
- Single file or in-memory database
- Key/value store
- Over 70 commands similar to standard Redis commands.
- Thread-safe
- Terabyte-sized databases
Vedis-Python features:
- Compiled library, extremely fast with minimal overhead.
- Supports key/value operations and transactions using Pythonic APIs.
- Support for executing Vedis commands.
- Write custom commands in Python.
- Python 2.x and 3.x.
Limitations:
- Not tested on Windoze.
The previous version (0.2.0) of vedis-python utilized ctypes to wrap the Vedis C library. By switching to Cython, key/value and Vedis command operations are significantly faster.
Links:
If you like Vedis, you might also want to check out UnQLite, an embedded key/value database with cursors and a cool JSON document store (python bindings: unqlite-python).
Installation
You can install vedis-python using pip.
pip install vedis
Basic usage
First you instantiate a Vedis object, passing in either the path to the database
file or the special string ':mem:' for an in-memory database.
Below is a sample interactive console session designed to show some of the basic features and functionality of the vedis-python library. Also check out the full API documentation as well as the vedis command documentation.
Key/value features
You can use Vedis like a dictionary for simple key/value lookups:
>>> from vedis import Vedis
>>> db = Vedis(':mem:') # Create an in-memory database. Alternatively you could supply a filename for an on-disk database.
>>> db['k1'] = 'v1'
>>> db['k1']
'v1'
>>> db.append('k1', 'more data') # Returns length of value after appending new data.
11
>>> db['k1']
'v1more data'
>>> del db['k1']
>>> 'k1' in db
False
>>> db['k1']
NoneYou can set and get multiple items at a time:
>>> db.mset(dict(k1='v1', k2='v2', k3='v3'))
True
>>> db.mget(['k1', 'k2', 'missing key', 'k3'])
['v1', 'v2', None, 'v3']In addition to storing string keys/values, you can also implement counters:
>>> db.incr('counter')
1
>>> db.incr('counter')
2
>>> db.incr_by('counter', 10)
12
>>> db.decr('counter')
11Hashes
Vedis supports nested key/value lookups which have the additional benefit of supporting operations to retrieve all keys, values, the number of items in the hash, and so on.
>>> h = db.Hash('some key')
>>> h['k1'] = 'v1'
>>> h.update(k2='v2', k3='v3')
>>> h
<Hash: {'k3': 'v3', 'k2': 'v2', 'k1': 'v1'}>
>>> h.to_dict()
{'k3': 'v3', 'k2': 'v2', 'k1': 'v1'}
>>> h.items()
[('k1', 'v1'), ('k3', 'v3'), ('k2', 'v2')]
>>> h.keys()
['k1', 'k3', 'k2']
>>> del h['k2']
>>> len(h)
2
>>> 'k1' in h
True
>>> [key for key in h]
['k1', 'k3']Sets
Vedis supports a set data-type which stores a unique collection of items.
>>> s = db.Set('some set')
>>> s.add('v1', 'v2', 'v3')
3
>>> len(s)
3
>>> 'v1' in s, 'v4' in s
(True, False)
>>> s.top()
'v1'
>>> s.peek()
'v3'
>>> del s['v2']
1
>>> s.add('v4', 'v5')
2
>>> s.pop()
'v5'
>>> [item for item in s]
['v1', 'v3', 'v4']
>>> s.to_set()
set(['v1', 'v3', 'v4'])
>>> s2 = db.Set('another set')
>>> s2.add('v1', 'v4', 'v5', 'v6')
4
>>> s2 & s # Intersection.
set(['v1', 'v4'])
>>> s2 - s # Difference.
set(['v5', 'v6'])Lists
Vedis also supports a list data type.
>>> l = db.List('my list')
>>> l.append('v1')
1
>>> l.extend(['v2', 'v3', 'v4'])
4
>>> len(l)
4
>>> l[1]
'v2'
>>> l.pop(), l.pop()
('v1', 'v2')
>>> len(l)
2Misc
Vedis has a somewhat quirky collection of other miscellaneous commands. Below is a sampling:
>>> db.base64('encode me')
'ZW5jb2RlIG1l'
>>> db.base64_decode('ZW5jb2RlIG1l')
'encode me'
>>> db.random_string(10)
'raurquvsnx'
>>> db.rand(1, 6)
4
>>> db.str_split('abcdefghijklmnop', 5)
['abcde', 'fghij', 'klmno', 'p']
>>> db['data'] = 'abcdefghijklmnop'
>>> db.strlen('data')
16
>>> db.strip_tags('<p>This <span>is</span> a <a href="#">test</a>.</p>')
'This is a test.'Writing your own Vedis commands
It is easy to write your own Vedis commands:
db = Vedis()
@db.register('CONCAT')
def concat(context, glue, *params):
return glue.join(params)
@db.register('TITLE')
def title(context, *params):
# The `context` can be used to access the key/value store.
for param in params:
context[param] = param.title()
return TrueHere is how you might call the custom commands:
>>> print db.execute('CONCAT | foo bar baz')
foo|bar|baz
>>> db.execute('TITLE "testing" "this is a test" "another"')
True
>>> print db['testing']
Testing
>>> print db['this is a test']
This Is A Test
>>> title('foo', 'bar') # Calling the wrapped function will go through Vedis.
True
>>> print db['foo']
Foo
>>> print db['bar']
BarThis code is based in part on buaabyl's pyUnQLite.