pydantic-redis 0.1.8

This package provides a simple ORM for redis using pydantic-like models.

pydantic-redis

A simple declarative ORM for Redis

Note: For a faster ORM with similar features, consider orredis which, under the hood, is built in rust

Main Dependencies

• Python +3.6
• redis
• pydantic

Getting Started

• Install the package

  pip install pydantic-redis
  

• Import the Store, the RedisConfig and the Model classes and use accordingly

from datetime import date
from typing import Tuple, List
from pydantic_redis import RedisConfig, Model, Store


# Create models as you would create pydantic models i.e. using typings
# the _primary_key_field is mandatory for ease of data querying and updating
class Author(Model):
  _primary_key_field: str = 'name'
  name: str
  active_years: Tuple[int, int]


# Create models as you would create pydantic models i.e. using typings
# the _primary_key_field is mandatory for ease of data querying and updating
class Book(Model):
  _primary_key_field: str = 'title'
  title: str
  author: Author
  # You can even nest models. they will be automatically inserted into their own collection
  # if they don't exist. Any update to these nested models will reflect in future data; thus no stale data.
  # consider this as an actual child-parent relationship
  rating: float
  published_on: date
  tags: List[str] = []
  in_stock: bool = True


class Library(Model):
  # the _primary_key_field is mandatory
  _primary_key_field: str = 'name'
  name: str
  address: str


# Create the store and register your models
store = Store(name='some_name', redis_config=RedisConfig(db=5, host='localhost', port=6379),
              life_span_in_seconds=3600)
store.register_model(Book)
store.register_model(Library)
store.register_model(Author)

# sample authors. You can create as many as you wish anywhere in the code

authors = {
  "charles": Author(name="Charles Dickens", active_years=(1220, 1280)),
  "jane": Author(name="Jane Austen", active_years=(1580, 1640)),
}

# Sample books.
books = [
  Book(title="Oliver Twist", author=authors["charles"], published_on=date(year=1215, month=4, day=4),
       in_stock=False, rating=2, tags=["Classic"]),
  Book(title="Great Expectations", author=authors["charles"], published_on=date(year=1220, month=4, day=4),
       rating=5,
       tags=["Classic"]),
  Book(title="Jane Eyre", author=authors["charles"], published_on=date(year=1225, month=6, day=4), in_stock=False,
       rating=3.4, tags=["Classic", "Romance"]),
  Book(title="Wuthering Heights", author=authors["jane"], published_on=date(year=1600, month=4, day=4),
       rating=4.0,
       tags=["Classic", "Romance"]),
]

# Some library objects
libraries = [
  Library(name="The Grand Library", address="Kinogozi, Hoima, Uganda"),
  Library(name="Christian Library", address="Buhimba, Hoima, Uganda")
]

# Insert them into redis
Book.insert(books)  # (the associated authors will be automatically inserted)
Library.insert(libraries)

# Select all books to view them. A list of Model instances will be returned
all_books = Book.select()
print(
  all_books)  # Will print [Book(title="Oliver Twist", author="Charles Dickens", published_on=date(year=1215, month=4, day=4), in_stock=False), Book(...]

# Or select some books
some_books = Book.select(ids=["Oliver Twist", "Jane Eyre"])
print(some_books)  # Will print only those two books

# Or select some authors
some_authors = Author.select(ids=["Jane Austen"])
print(
  some_authors)  # Will print Jane Austen even though you didn't explicitly insert her in the Author's collection

# Or select some columns. THIS RETURNS DICTIONARIES not MODEL Instances
# The Dictionaries have values in string form so you might need to do some extra work
books_with_few_fields = Book.select(columns=["author", "in_stock"])
print(books_with_few_fields)  # Will print [{"author": "'Charles Dickens", "in_stock": "True"},...]

# Update any book or library
Book.update(_id="Oliver Twist", data={"author": authors["jane"]})
# You could even update a given author's details by nesting their new data in a book update
updated_jane = Author(**authors["jane"].dict())
updated_jane.active_years = (1999, 2008)
Book.update(_id="Oliver Twist", data={"author": updated_jane})
# Trying to retrieve jane directly will return her with the new details
# All other books that have Jane Austen as author will also have their data updated. (like a real relationship)
Author.select(ids=["Jane Austen"])

# Delete any number of items
Library.delete(ids=["The Grand Library"])

How to test

• Clone the repo and enter its root folder

  git clone https://github.com/sopherapps/pydantic-redis.git && cd pydantic-redis
  

• Create a virtual environment and activate it

  virtualenv -p /usr/bin/python3.6 env && source env/bin/activate
  

• Install the dependencies

  pip install -r requirements.txt
  

• Run the pre-commit installation

  pre-commit install
  

• Run the tests command

  pytest --benchmark-disable
  

• Run benchmarks

  pytest --benchmark-compare --benchmark-autosave
  

License

Copyright (c) 2020 Martin Ahindura Licensed under the MIT License

Gratitude

"There is no condemnation now for those who live in union with Christ Jesus. For the law of the Spirit, which brings us life in union with Christ Jesus, has set me free from the law of sin and death"

-- Romans 8: 1-2

All glory be to God