semvec/pypi-packages huggingface dataset:
dp-accelerator 0.1.0
Universal High-Performance Differential Privacy Accounting Engine
Requires Python: >=3.8

# DP Accelerator

Universal High-Performance Differential Privacy Accounting Engine

[![PyPI version](https://badge.fury.io/py/dp-accelerator.svg)](https://pypi.org/project/dp-accelerator/)
[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

A framework-agnostic Rust-accelerated library for computing differential privacy guarantees with **3000x+ speedup** over pure Python implementations.

## Features

- 🚀 **3000x faster** than pure Python DP accounting
- 🔧 **Framework-agnostic**: Works with JAX, PyTorch, TensorFlow
- 🦀 **Rust-powered**: Zero-cost abstractions with memory safety
- 📦 **Easy installation**: `pip install dp-accelerator`
- 🎯 **Drop-in replacement**: Compatible APIs for existing libraries

## Quick Start

```python
from dp_accelerator import DPSGDAccountant

# Initialize accountant
accountant = DPSGDAccountant(
    noise_multiplier=1.0,
    batch_size=600,
    dataset_size=60000
)

# Compute privacy guarantee
epsilon = accountant.get_epsilon(steps=10000, delta=1e-5)
print(f"Privacy guarantee: ε = {epsilon:.2f}")
```

## Framework Adapters

### JAX Privacy
```python
from dp_accelerator.jax_adapter import compute_dpsgd_epsilon

epsilon = compute_dpsgd_epsilon(
    noise_multiplier=1.0,
    batch_size=600,
    dataset_size=60000,
    num_steps=10000,
    delta=1e-5
)
```

## Performance

| Implementation | Time | Speedup |
|----------------|------|---------|
| Pure Python | 0.613s | 1x |
| **DP Accelerator** | **0.0002s** | **3000x** |

## Installation

```bash
pip install dp-accelerator
```

## Development

```bash
git clone https://github.com/yourusername/dp-accelerator
cd dp-accelerator
maturin develop
```

## Contributing

Contributions welcome! Please see our [contributing guide](CONTRIBUTING.md).

## License

Apache License 2.0
mailenv 1.0
Python client for the Mailenv API
Requires Python: >=3.8

# mailenv

Transactional email for your app. This Python client lets you send transactional and promotional email through the [Mailenv](https://mailenv.com) API so you can plug reliable, API-driven email straight into your SaaS, web app, or backend—password resets, welcome messages, notifications, and more. [API docs](https://mailenv.com/api-docs).

## Installation

```bash
pip install -e .
```

(Use your project’s normal install method if you have a `pyproject.toml` or `setup.py`.)

## Basic usage

Set `MAILENV_API_KEY` in your environment to avoid passing the key in code, or pass `api_key=` to override.

```python
from mailenv import Mailenv

client = Mailenv()  # uses MAILENV_API_KEY from env
# or: client = Mailenv(api_key="your-api-key")

result = client.send(
    to="user@example.com",
    sender="no-reply@yourdomain.com",
    subject="Hello",
    message="Hi there.",
)

# result["id"], result["status"]
```

Optional arguments include `email_type` (default `"tx"`), `sender_name`, `campaign_id`, `mailing_list_id`, `user_id`, `customer_id`, `priority`, `headers`, and `extra_data`. See the client docstrings for details.

## Errors

On API or request failure the client raises `MailenvError`:

```python
from mailenv import Mailenv, MailenvError

try:
    result = client.send(...)
except MailenvError as e:
    print(e.message, e.status_code, e.body)
```
cde-onboard 0.1.7
Interactive TUI tutorials for onboarding engineers onto ONA Environments
Requires Python: >=3.11
Keywords: cli, devcontainer, ona, onboarding, tui

# cde-onboard

Interactive TUI tutorials for onboarding engineers onto ONA Environments.

## Install

```bash
pipx install cde-onboard
```

## Usage

```bash
# Launch the interactive TUI
cde-onboard

# List lessons with progress
cde-onboard --list

# Jump to a specific lesson
cde-onboard --lesson 3

# Reset progress
cde-onboard --reset
```