Modern data science utilities library with type safety and extensibility
Project description
DSPU
Modern data science utilities library with type safety, extensibility, and async-first design.
Features
- Type-Safe: Full type hints with runtime validation using Pydantic
- Async-First: Modern async APIs with sync wrappers when needed
- Extensible: Plugin architecture for easy customization
- Zero Bloat: Minimal dependencies, optional extras for features
- Fast: Built with UV, 10-100x faster package management
- Batteries Included: Config, I/O, async utils, security, ML, observability
Installation
# Install core package
uv pip install dspu
# Install with extras
uv pip install dspu[io,async,security]
# Install everything
uv pip install dspu[all]
Quick Start
from pydantic import BaseModel
from dspu.config import Config, ConfigSource
from dspu.io import Storage
from dspu.observability import get_logger
# Type-safe configuration
class AppConfig(BaseModel):
database_url: str
max_workers: int = 4
config = Config.load(
AppConfig,
sources=[
ConfigSource.file("config.yaml"),
ConfigSource.env(prefix="APP_"),
]
)
# Unified storage interface
storage = Storage.from_uri("s3://my-bucket/data")
data = await storage.read("file.json")
# Structured logging
logger = get_logger(__name__)
logger.info("processing_started", count=len(data))
Development
# Clone and setup
git clone https://github.com/yourorg/dspu
cd dspu
uv sync --all-extras
# Run tests
uv run pytest
# Run linting
uv run ruff check .
# Type check
uv run pyrefly check src/dspu
Documentation
Requirements
- Python 3.11+
- UV (recommended) or pip
Status
Current Version: 0.1.0 (Alpha)
Project details
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