single-table-orm 0.1.0

A Django-like ORM for AWS DynamoDB using single-table design.

STORM: Single Table ORM for DynamoDB

STORM is a Python library providing a Django-like ORM interface for interacting with AWS DynamoDB, specifically designed with the single-table design paradigm in mind.

Introduction: Single-Table Design

DynamoDB is a highly scalable NoSQL database. Unlike traditional relational databases, it encourages a different approach to data modeling, often favoring a single-table design. This involves storing multiple different types of entities (e.g., Users, Orders, Products) within a single DynamoDB table.

This approach leverages DynamoDB's partition key design to efficiently query related items together in a single request, avoiding costly join operations common in SQL databases. By carefully crafting partition keys (PK) and sort keys (SK), you can model complex relationships and access patterns effectively.

Why Single-Table Design?

• Performance: Fetching related heterogeneous items often requires only a single query.
• Scalability: Aligns well with DynamoDB's horizontal scaling capabilities.
• Reduced Operational Overhead: Fewer tables to manage (monitoring, alarms, permissions).

Learn More about Single-Table Design:

• AWS Documentation: Best practices for designing and architecting with DynamoDB
• AWS Blog Post: Creating a single-table design with Amazon DynamoDB
• Alex DeBrie's Post: The What, Why, and When of Single-Table Design with DynamoDB

STORM aims to simplify working with this pattern by providing familiar ORM concepts.

Installation

Currently, STORM is not published on PyPI. To install it locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/your-username/single-table-orm.git # Replace with the actual repo URL
   cd single-table-orm
   

2. Install the package: For regular use:

   pip install .
   

   For development (installs in editable mode):

   pip install -e .
   

You will also need boto3 installed and your AWS credentials configured (e.g., via environment variables, IAM role, or ~/.aws/credentials).

pip install boto3

Future PyPI Installation:

Once the package is published on PyPI, you will be able to install it directly using pip:

# Ensure you have Python 3.x and pip installed
pip install single-table-orm # Or the final package name

Publishing to PyPI

To build and upload this package to PyPI:

1. Install build and twine:

pip install build twine

2. Build the package:

python -m build

This will create dist/ with .tar.gz and .whl files. 3. Upload to PyPI:

twine upload dist/*

You will be prompted for your PyPI credentials. For test uploads, use TestPyPI with:

twine upload --repository testpypi dist/*

For more details, see the Python Packaging User Guide.

High-Level Documentation & Usage

STORM provides several core components:

• Model: The base class for your DynamoDB entities. You define your table structure, keys, and attributes here.
• Field: Used within a Model to define attributes, their types, and whether they are part of the PK, SK, or a GSI.
• ConnectionManager (table): A singleton object managing the DynamoDB client connection and the target table name. It provides context managers for temporary changes.
• ModelManager (Model.objects): Provides methods for database interactions like get(), create(), save(), update(), delete(), and initiating queries (using()).
• QuerySet: Allows chaining of query operations like filter(), limit(), use_index(), etc., before executing the query.

Basic Example

from single_table_orm.models import Model
from single_table_orm.fields import Field

# Assumes AWS credentials and DB_TABLE_NAME env var are set

class User(Model):
    # PK field: User ID
    user_id = Field(str, pk=True)
    # SK field: Static value for User metadata item
    type = Field(str, sk=True, default="METADATA")
    email = Field(str)
    name = Field(str)
    # GSI field: Allows querying by email
    email_gsi = Field(str, gsi=True, identifier="E")

    class Meta:
        # Optional: Customize the suffix used in generated keys
        suffix = "USER"

class Order(Model):
    # PK field: User ID (same as the user this order belongs to)
    user_id = Field(str, pk=True)
    # SK field: Order ID (unique within a user's orders)
    order_id = Field(str, sk=True, identifier="O")
    amount = Field(float)
    order_date = Field(str) # Example: ISO 8601 format

    class Meta:
        suffix = "ORDER"

# --- Operations ---

# Create a User
# Note: You must provide all PK and SK fields
user = User.objects.create(user_id="user123", email="[e-mail]", name="Test User", email_gsi="[e-mail]")
# Or:
# user = User(user_id="user123", type="METADATA", email="[e-mail]", name="Test User", email_gsi="[e-mail]")
# user.save()

print(f"Created User PK: {user.get_pk()}, SK: {user.get_sk()}")
# Example Output: Created User PK: USER#U#user123#USER, SK: T#METADATA

# Create an Order for the User
order = Order.objects.create(user_id="user123", order_id="order456", amount=99.99, order_date="2024-01-01T10:00:00Z")

print(f"Created Order PK: {order.get_pk()}, SK: {order.get_sk()}")
# Example Output: Created Order PK: ORDER#U#user123#ORDER, SK: O#order456

# Get a specific User
try:
    retrieved_user = User.objects.get(user_id="user123", type="METADATA")
    print(f"Retrieved User: {retrieved_user.name}")
except User.DoesNotExist:
    print("User not found")

# Query for all orders for a user
user_orders = list(Order.objects.using(user_id="user123"))
print(f"User user123 has {len(user_orders)} orders.")

# Update a user's email (GSI field must also be updated)
retrieved_user.update(email="[e-mail]", email_gsi="[e-mail]")

# Delete an order
order.delete()

Core Concepts Diagram

classDiagram
    class Model {
        +objects: ModelManager
        +Meta
        +_fields: dict
        +_pk_attributes: list
        +_sk_attributes: list
        +_gsi_attributes: list
        +__init__(**kwargs)
        +get_pk() str
        +get_sk() str
        +get_gsi1pk() str | None
        +save()
        +update(**kwargs)
        +delete()
        +is_creatable() bool
        +to_json() dict
    }
    class Field {
        +field_type: type
        +pk: bool
        +sk: bool
        +gsi: bool
        +identifier: str
        +name: str
        +__init__(...)
        +__get__(...)
        +__set__(...)
        +__set_name__(...)
    }
    class ModelManager {
        +model: Model
        +get(**kwargs) Model
        +create(**kwargs) Model
        +get_save_query(Model) dict
        +get_update_query(Model, **kwargs) dict
        +get_delete_query(Model) dict
        +using(**kwargs) QuerySet
    }
    class QuerySet {
        +model: Model
        +using(**kwargs) QuerySet
        +use_index(bool) QuerySet
        +limit(int) QuerySet
        +filter(...) QuerySet  # Example: Add filter later
        +get_query() dict
        +__iter__()
        +__next__()
    }
    class ConnectionManager {
      +client: boto3.client
      +table_name: str
      +table_context(table_name, client)
    }
    class F {
        +query: str
        +names: dict
        +values: dict
        +__init__(field_name)
        +__add__(other) F
    }
    Model --* Field : contains >
    Model o-- ModelManager : aggregates >
    ModelManager ..> QuerySet : creates >
    QuerySet o-- Model : references >
    ModelManager ..> F : uses >
    ConnectionManager ..> ModelManager : provides_connection >

    note for ModelManager "Provides DB access methods"
    note for QuerySet "Builds and executes queries"
    note for ConnectionManager "Manages boto3 client and table name (singleton 'table')"
    note for F "For building update expressions"

License

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

Contributing

Contributions are welcome! Please see the CONTRIBUTING.md file for details.