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Simple Firestore collection definitions and queries using pydantic schemas and Firestore query API.

Project description

Firestore Collections

Simple Firestore collection definitions and queries using pydantic schemas and Firestore query API.

A quick and easy way to make use of the NoSQL document database solution Firestore available in Google Cloud Platform (GCP).

Requirements

  • Python 3.6+
  • GCP project with Firestore enabled

Features

  • Schema definition and validation: Define collection schemas using pydantic and built-in type hinting (typing).
  • Automatic IDs: Automatic ID generation using 12-byte hexadecimal (bson.ObjectId).
  • Simple queries: Query collections using a simple interface.
  • Auxiliary timestamps: Automatically added timestamps to objects like created_at and updated_at.

Example

Define users collection and perform different queries:

from typing import Optional

from pydantic import EmailStr, SecretStr
from firestore_collections import Collection, Schema


class User(Schema):
    __collection_name__ = 'users'
    __unique_keys__ = ['email']

    email: EmailStr
    full_name: str = None
    password: Optional[SecretStr]


# Initialize firestore collection
collection = Collection(schema=User)

# Initialize user object
user = User(
    email='john@doe.com',
    full_name='John')

# Insert
user = collection.insert(user)

# Get object from db
user = collection.get(user.id)

# Update
user.full_name = 'John Doe'
collection.update(user)

# Get by attribute
user = collection.get_by_attribute('email', 'john@doe.com')

# Get all objects
users = collection.get_all()

# Delete object
collection.delete(id=user.id)

GCP credentials

NOTE: The package assumes a valid GCP credentials file is available and its path defined in the environment variable GOOGLE_APPLICATION_CREDENTIALS.

License

This project is licensed under the terms of the MIT license.

Project details


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