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Declarative data types using Cerberus for schemas, optimised for Redis.
This codebase is similar to Modulus, except it is far simpler and features optimisations for Redis that preserve the simple key/value nature of it - specifically selective loading and saving of fields.
$ pip install redistil
A basic example:
from redis import Redis
from redistil import Model, Field, String, Integer, Float, List
# define a model
class MyModel(Model):
string = Field(String, primary_key=True)
integer = Field(Integer)
float = Field(Float)
list = List(String)
redis = Redis()
# create an object but don't save it
obj = MyModel(string='abc', integer=123, float=1.23, list=['a', 'b'])
# create an object and immediately save it
obj = MyModel.create(redis,
string='test string',
integer=123,
float=4.56,
list=['a', 'b', 'c'],
)
# load the object using the primary key field
obj = MyModel.load(redis, 'test string')
# selectively load fields
obj = MyModel.load(redis, 'test string', MyModel.integer, MyModel.float)
# primary_key will always be loaded
print(obj.string)
print(obj.integer)
print(obj.float)
# 'list' will be None
# load fields after the fact
obj.load_fields(MyModel.list)
print(obj.list)
# update and selectively save fields
obj.list = ['d', 'e', 'f']
obj.save(redis, MyModel.list)
# determine where values are saved so we can bypass the object model if we want to
MyModel.key('test string')
# 'MyModel::test string'
MyModel.string.field()
# 'string'
MyModel.list.key(MyModel.key('test string'))
# 'MyModel::test string::list'
Properties:
Cerberus 'dict' type is not supported, instead you should flatten them into the model itself.
Field types:
All data types are specified as a sub-class of Model.
Each field is specified as a class attribute which is a Field object containing a field type.
For example:
>>> from redis import Redis
>>> from redistil import Model, Field, String, List
>>>
>>> class MyModel(Model):
... id = Field(String, primary_key=True)
... values = List(String, required=True)
...
>>> redis = Redis()
>>> mymodel = MyModel.create(redis, id='abc', values=['a', 'b', 'c'])
>>> # reload
>>> mymodel = MyModel.load(redis, 'abc')
>>> print(mymodel.data)
{'id': 'abc', 'values': ['a', 'b', 'c']}
Parameters to fields are simply passed through to the Cerberus schema. See this documentation for more Cerberus validation rules.
Selective saving of fields will only perform validation on the fields specified.
When you perform selective loading of fields, those fields' values are not loaded and may fail validation. In this case you should also perform selective saving of those same fields.
Cerberus validator rules can be added by adding a child class called "Validator" to your model definition.
from redistil import Model, Field, String
class MyModel(Model):
# default_setter is a cerberus attribute which will set the value if it is not already
# but only on save
# the value may be either a function or a string
# if the value is a string, the function must be defined in the Validator class as _normalize_default_setter_<name>
# https://docs.python-cerberus.org/en/stable/normalization-rules.html
value = Field(String, default_setter='generated_string')
class Validator(Model.Validator):
def _normalize_default_setter_generated_string(self, document):
return 'abcdefg'
Copyright (c) 2021, Adam Griffiths All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
FAQs
Declarative data types, using Cerberus and Redis
We found that redistil demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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