A simple-to-use, in-memory JSON database
Many small to medium sized database applications require the use of a database for persistent storage of a small amount of data (up to a few gigabytes). While tools like Redis provide simple O(1) key value stores, larger applications easily become overly complicated due to the flat nature of key value stores along with JSON being a second class citizen. Ruko aims to solve this problem by being a fast, in-memory JSON database where all requests are O(1) (or O(n) if it has to build an index). Learn more about it below.
Start ruko server process:
ruko-server
Example Python code:
from ruko import RDict
db = RDict.client()
notes = db['notes']
def get_notes():
return notes.get()
def create_note(title, note):
notes.append({
'title': title,
'note': note
})
return notes[-1]()
def get_note_by_title(title):
return notes.by('title')[title]()
If you are using Flask, checkout Flask-Ruko.
Ruko consists of a json database backend and a native feeling Python interface. Requests consist of a key location and a request type. Requests are only performed via one of the following:
.get()
: This immediately performs a request, returning the default value orNone
as expected in Python()
: Calling an index performs the request.append()
,.keys()
,len(x)
,y in x
, etc. Performing an operation on anRDict
performs a request['key'] = ...
Item assignment performs a request
For example, each of these lines performs one request:
db['users']['abc'].get('name', 'john')
abc_user = db['users']['abc']()
db['users']['abc']['devices'].append({'name': 'def'})
db['users']['abc'] = {'devices': {'name': 'def'}}
Difference between .get()
and ()
:
When using .get
, it returns a default value if no vaue is present. ()
, however,
raises KeyError
(or the default error class) if the value is not present.
Additionally, you can search for a value inside a list or a dictionary based on its attributes:
users = db['users']
users[()] = [
{'name': 'John', 'email': 'john325@gmail.com'},
{'name': 'Sam', 'email': 'sam151@yahoo.com'},
{'name': 'Kelly', 'email': 'kelly12@gmail.com'}
] # Assign the current object via [()] = ...
users.by('name')['Sam']() # {'name': 'Sam', 'email': 'sam151@yahoo.com'}
Sometimes various objects that reside in different locations need to be aggregated and searched. This is where mappings come into play. For example:
users = db['users']
users.append({
'name': 'John',
'email': 'john325@gmail.com',
'devices': [
{'id': 'abc', 'name': "John's first device"},
{'id': 'def', 'name': "John's second device"}
]
})
users.append({
'name': 'Sam',
'email': 'sam151@yahoo.com',
'devices': [
{'id': 'ghi', 'name': "Sam's first device"},
{'id': 'jkl', 'name': "Sam's second device"}
]
})
devices = db.create_mapping('devices', 'users.*.devices.*')
devices.by('id')['ghi'].get() # {'id': 'ghi', 'name': "Sam's first device"}
- Compile and install ruko-server
- Install the
ruko
python package:
pip install ruko
Ruko is in active development and encourages contributions from anyone.