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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)

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