nomy-data-models 0.2.9

Data model definitions for Nomy wallet analysis data processing

Nomy Data Models

This repository contains the data model definitions for Nomy wallet analysis data processing. These models are shared across multiple services:

• nomy-data-service
• nomy-data-processor
• nomy-data-ingestor

Overview

The Nomy Data Models repository serves as a single source of truth for all data structures used in the Nomy wallet analysis ecosystem. By centralizing these models, we ensure consistency across different services and reduce duplication of code.

Features

• Cross-language support: Models can be used in both Python and Rust
• Versioned releases: Proper versioning to manage dependencies
• Consistent data structures: Ensures data integrity across the entire pipeline
• Centralized schema management: Single source of truth for all data models
• SQLAlchemy ORM models: Database-ready models with full ORM support
• Automatic Rust code generation: Python SQLAlchemy models are automatically converted to Rust structs

Installation

Python

# Install from PyPI
pip install nomy-data-models

# Install from source
pip install -e .

Rust

Add to your Cargo.toml:

[dependencies]
nomy-data-models = { version = "0.1.0", git = "https://github.com/bcnmy/nomy-data-models" }

Usage

Python

from nomy_data_models.models import WalletState, ServiceState, RawTrade, EnrichedTrade, Position

# Use the models with SQLAlchemy
from sqlalchemy import create_engine
from sqlalchemy.orm import Session

engine = create_engine("sqlite:///nomy.db")
with Session(engine) as session:
    wallet_state = WalletState(
        wallet_address="0x1234567890abcdef1234567890abcdef12345678",
        chain_id=1
    )
    session.add(wallet_state)
    session.commit()

Rust

use nomy_data_models::models::{WalletState, ServiceState, RawTrade, EnrichedTrade, Position};

// Use the model
let wallet_state = WalletState {
    wallet_address: "0x1234567890abcdef1234567890abcdef12345678".to_string(),
    chain_id: 1,
    // ... other fields
};

Development Setup

Pre-commit Hooks

This repository uses pre-commit hooks to ensure code quality and consistency. After cloning the repository, install the pre-commit hooks:

# Make the script executable
chmod +x ./scripts/install-hooks.sh

# Install the hooks
./scripts/install-hooks.sh

The pre-commit hooks will automatically:

• Format code with Black
• Sort imports with isort
• Run Python tests
• Generate and verify Rust models
• Format Rust code with rustfmt
• Run Rust linting with Clippy

Important: Always ensure the pre-commit hooks are installed and up-to-date. They are essential for maintaining code quality and preventing CI failures.

Development

Prerequisites

• Python 3.8+
• Rust 1.50+
• Poetry (for Python dependency management)
• Cargo (for Rust dependency management)

Setup

1. Clone the repository
2. Install Python dependencies: poetry install
3. Build Rust package: cargo build
4. Install git hooks: ./scripts/install-hooks.sh

Git Hooks

This repository includes git hooks to automate certain tasks:

• pre-commit: Automatically generates Rust models from Python models and verifies they build correctly before each commit

To install the git hooks, run:

./scripts/install-hooks.sh

This ensures that all Rust models are kept in sync with their Python counterparts and that they build correctly.

Adding New Models

1. Add the model definition to the appropriate Python file in nomy_data_models/models/
2. Update the __init__.py files to export the new model
3. Run the code generation script: python scripts/generate_rust.py
4. Verify the generated Rust code in src/models/
5. Add tests for both Python and Rust implementations

Testing

# Run Python tests
pytest tests/python

# Run Rust tests
cargo test

Contributing

Please follow these steps when contributing:

1. Create a new branch for your feature
2. Add or modify models as needed
3. Ensure tests pass for both Python and Rust
4. Submit a pull request

Package Deployment

Preconditions

Before deploying a new version, ensure you have:

1. Updated the version number in Cargo.toml for the Rust package
2. Updated the version number in pyproject.toml for the Python package

Automated Deployment

When your changes are merged into the main branch, the CI pipeline will automatically:

1. Deploy the Python package to PyPI (https://pypi.org/)
2. Deploy the Rust package to crates.io (https://crates.io/)

The deployment process is handled automatically by the CI pipeline, so you don't need to perform any manual steps after merging to main.

Python-to-Rust Conversion

This repository includes a utility for automatically converting Python SQLAlchemy models to Rust structs. This ensures that the data models are consistent across both languages.

How it works

1. Python SQLAlchemy models are defined in the nomy_data_models/models directory
2. The nomy_data_models/py_to_rust.py module provides functions for converting these models to Rust
3. The scripts/generate_rust.py script can be used to generate Rust code from the command line

Usage

To generate Rust models from Python SQLAlchemy models:

python scripts/generate_rust.py [output_dir]

If output_dir is not specified, the default is src/models.

Testing

To test the conversion process:

python scripts/test_conversion.py

This will generate Rust code in the scripts/test_output/models directory and run various tests to ensure the conversion is working correctly.