data-snack 0.0.4

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Data Snack

About

Data Snack is a minimalistic framework for storing and accessing structured data.

It uses an Entity objects to define a schema for your data. Snack provides an interface for automatically serializing and storing entities in a cache database of you choice. General interface that allows you to use different backends: redis, memcached.

Install

Data Snack can be easily installed using pypi repository.

pip install data_snack

Usage

This examples shows a basic usage of defining an entity and using Snack to save and load it from the cache. More examples can be found in the Examples section.

Example 1 - Creating new entities and saving

1. Define entities

The first thing you need to do is to define an Entity. Entities are used to define a common structure of the objects stores in your database. Snack is using pydantic for type validation of entity fields.

from pydantic.dataclasses import dataclass
from typing import Text
from data_snack.entities import Entity

@dataclass
class Person(Entity):
    index: Text
    name: Text

2. Connect to Redis

Connect to you a cache database of your choice. In this example we are using Redis, but you could also use Memcached if you want.

import redis
redis_connection = redis.Redis(host='127.0.0.1', port=6379, password='')

3. Create Snack instance

In this step we create a Snack instance and connect it to our Redis database. Notice, that Redis client is wrapped in our RedisConnection class to ensure shared interface. And at least we can register all entities that will be used in our project. For each entity we specify a list of fields that will be used to define keys when saving our data.

from data_snack import Snack
from data_snack.connections.redis import RedisConnection
snack = Snack(connection=RedisConnection(redis_connection))  # create instance
snack.register_entity(Person, keys=['index'])  # register your entity

4. Save and load your entities using Snack

You are ready to save and load data using Snack.

snack.set(Person("1", "John"))
# 'Person-1'
snack.get(Person, ["1"])
# Person(index='1', name='John')
snack.set_many([Person("1", "John"), Person("2", "Anna")])
# ['Person-1', 'Person-2']
entities = snack.get_many(CarEntity, [["1"], ["2"]])
# [Person(index='1', name='John'), Person(index='2', name='Anna')]

Contact

Plugin was created by the Data Science team from Webinterpret.