PyStoreDB 0.1.0

A simple NoSQL database greatly inspired by Firestore and Django Filters.

PyStoreDB

PyStoreDB is a simple NoSQL database greatly inspired by the Firebase Firestore, Django Filters, and LiteJsonDB. It is a JSON-based database that allows you to store and retrieve data in a simple and easy way.

Key Features

• Simple and easy to use: PyStoreDB is designed to be simple and easy to use.
• NoSQL database: PyStoreDB is a NoSQL database.
• JSON-based: PyStoreDB is a JSON-based database.
• Subcollections: PyStoreDB supports subcollections.
• Document CRUD operations: PyStoreDB supports document CRUD operations.
• Collection Querying operations: PyStoreDB supports collection querying operations. and where clause is inspired by Django Filters.
• Firebase Firestore-like: PyStoreDB is greatly inspired by the Firebase Firestore.

Installation

package is not yet available on PyPI, but you can install it from the source code:

git clone https://github.com/Wilfried-Tech/PyStoreDB
cd PyStoreDB
python setup.py install

Usage

Initialize the database

from PyStoreDB import PyStoreDB
from PyStoreDB.conf import PyStoreDBSettings
from PyStoreDB.engines import PyStoreDBRawEngine

# Initialize the database
# engine_class is optional, default is PyStoreDBRawEngine
# store_dir can be '' for in-memory storage
PyStoreDB.settings = PyStoreDBSettings(store_dir="data", engine_class=PyStoreDBRawEngine)
PyStoreDB.initialize()

store = PyStoreDB.get_instance(name="my_store")  # name is optional

Create a document in a collection

# Create a document

user1 = store.collection("users").add({"name": "John Doe", "age": 25})  # auto-generate id
user2 = store.collection("users").doc().set({"name": "Jane Doe", "age": 22})  # auto-generate id
user3 = store.collection("users").doc("user3").set({"name": "Alice Doe", "age": 30})

Working with documents

# Get a document reference by id
user = store.collection("users").doc('ID')
# replace the document with a new one
user.set({"name": "John Doe", "age": 26})
# update the document
user.update({"age": 27}) or user.update(age=27)
# delete the document
user.delete()  # note that delete document does not delete subcollections

Working with collections

# Get a collection reference

users = store.collection("users")
# Get all documents in a collection
all_users = users.get()

Working with subcollections

# Get a document reference
user = store.collection("users").doc('ID')
# Get a subcollection reference
posts = user.collection("posts")
# Add a document to the subcollection
post1 = posts.add({"title": "My first post", "content": "Hello, World!"})

Querying

# Get all documents in a collection with order by age
users = store.collection("users").order_by("age").get()

# Get all documents in a collection with age greater than 25
users = store.collection("users").where(age__gt=25).get()

...

Features

• Simple and easy to use
• NoSQL database
• JSON-based
• Subcollections
• Document CRUD operations
• Collection Querying operations
• Indexing
• Transactions
• multi-threading support
• multi-engine support (partially implemented)

Disclaimer

This project is still in development and should not be used in production.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Feel free to contribute to this project.