semvec/pypi-packages huggingface dataset:
breadq 0.1.1
Multiplayer client for QBReader
Requires Python: >=3.9

# breadq

A QBReader multiplayer library.

This is meant for making clients, bots are very easy to make and boring.
(Coming soon (tm) a tui qbreader client)


Please don't use this to cheat, it really just looks bad on you.

TODO: 

    Adding the rest of the outgoing events
    Adding state
    Adding ratelimiting
    Documentation
ethereum-types 0.3.0
Types used by the Ethereum Specification.
Requires Python: >=3.10

Ethereum Types
==============

Types and utilities used by the [Ethereum Execution Layer Specification (EELS)][eels]. Includes:

- Fixed-size unsigned integers (`U256`, `U64`, etc.)
- Arbitrarily-sized unsigned integers (`Uint`.)
- Fixed-size byte sequences (`Bytes4`, `Bytes8`, etc.)
- Utilities for making/interacting with immutable dataclasses (`slotted_freezable`, `modify`.)

[eels]: https://github.com/ethereum/execution-specs
sdexe 0.2.14
Suite for Downloading, Editing & eXporting Everything — local tools for media, PDF, images, AV, file conversion, and text
Requires Python: >=3.10

# sdexe

**Suite for Downloading, Editing & eXporting Everything**

[![PyPI version](https://img.shields.io/pypi/v/sdexe)](https://pypi.org/project/sdexe/)
[![Python 3.10+](https://img.shields.io/pypi/pyversions/sdexe)](https://pypi.org/project/sdexe/)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)

Local tools for media downloads, PDF manipulation, image processing, and file conversion. Everything runs on your machine — no uploads, no accounts, no data leaves your device.

## Install

```
pipx install sdexe
```

Or with pip:

```
pip install sdexe
```

### Requirements

- Python 3.10+
- [ffmpeg](https://ffmpeg.org/) — sdexe will offer to install it automatically on first run

## Usage

```
sdexe
```

Opens `http://localhost:5001` in your browser. All processing happens locally.

## Features

### Media Downloader
Download videos and audio from YouTube, Instagram, TikTok, SoundCloud, Twitch, Vimeo, X, and 1000+ other sites.
- Formats: MP3 (128/192/320 kbps), MP4, FLAC, WAV
- Quality options: Best, 1080p, 720p, 480p for video
- Playlist and batch URL support (up to 3 concurrent downloads)
- Subtitle download for MP4
- Thumbnail embedded as album art
- Set a permanent output folder to skip manual saving
- Real-time progress with speed, ETA, and cancel button
- Desktop notifications when downloads finish
- Download history with re-fetch button

### PDF Tools
- **Merge** — combine multiple PDFs, drag to reorder
- **Split** — split by page ranges (e.g. `1-3, 5, 8-10`) or every page
- **Images to PDF** — convert JPG/PNG/WebP images into a single PDF
- **Compress** — reduce file size by compressing content streams
- **Extract Text** — pull all text to a .txt file with page markers
- **Password** — add or remove PDF password protection

### Image Tools
- **Resize** — by dimensions or percentage, with aspect ratio lock
- **Compress** — batch compression at High / Medium / Low quality
- **Convert** — convert between PNG, JPG, and WebP (batch supported)

### File Converter
- **Markdown → HTML** — live preview + styled standalone HTML output
- **CSV ↔ JSON** — bidirectional, first row as headers
- **JSON ↔ YAML** — bidirectional
- **CSV ↔ TSV** — bidirectional
- **XML → JSON**

## Development

```
git clone https://github.com/gedaliahs/sdexe.git
cd sdexe
python -m venv venv
source venv/bin/activate
pip install -e .
sdexe
```
mwin 0.1.8
Track OpenAI, Claude, Gemini and OpenAI-compatible models then give solutions to improve your agent system.
Requires Python: >=3.12

# mwin
mwin: Track OpenAI, Claude, Gemini and OpenAI-compatible models then give solutions to improve your agent system.<br/>
Our goal is to make llm application more valuable and effortlessly improve llm capabilities.

# Quickstart
You can use pip install mwin
```bash
pip install mwin
```
OR pip install from source.
```bash
git clone https://github.com/yanghui1-arch/mwin.git
cd src
pip install -e .
```
Then you need to configure mwin through CLI.
```bash
mwin configure
```
Then you just follow the instructions to configure mwin.
```
> Which deployment type do you choose?
> 1 - mwin Cloud Platform (default)
> 2 - mwin Local Platform
> Please input the choice number.>2
> Please enter your API key:
> What's your project name? mwin-demo
> Congrats to configure mwin.
```
It needs an Mwin API key. You can get the apikey after logging `http://localhost:5173`.
Finally use `@track` to track your llm input and output
```python
from mwin import track, LLMProvider
from openai import OpenAI

openai_apikey = 'YOUR API KEY'

@track(
    tags=['test', 'demo'],
    llm_provider=LLMProvider.OPENAI,    
)
def llm_classification(film_comment: str):
    prompt = "Please classify the film comment into happy, sad or others. Just tell me result. Don't output anything."
    cli = OpenAI(base_url='https://api.deepseek.com', api_key=openai_apikey)
    cli.chat.completions.create(
        messages=[{"role": "user", "content": f"{prompt}\nfilm_comment: {film_comment}"}],
        model="deepseek-chat"
    ).choices[0].message.content
    llm_counts(film_comment=film_comment)
    return "return value"

@track(
    tags=['test', 'demo', 'second_demo'],
    llm_provider=LLMProvider.OPENAI,
)
def llm_counts(film_comment: str):
    prompt = "Count the film comment words. just output word number. Don't output anything others."
    cli = OpenAI(base_url='https://api.deepseek.com', api_key=openai_apikey)
    return cli.chat.completions.create(
        messages=[{"role": "user", "content": f"{prompt}\nfilm_comment: {film_comment}"}],
        model="deepseek-chat"
    ).choices[0].message.content

llm_classification("Wow! It sucks.")
```

# Development
Mwin project package manager is uv. If you are a beginner uver, please click uv link: [uv official link](https://docs.astral.sh/uv/guides/projects/#creating-a-new-project)
```bash
uv sync
uv .venv/Script/activate
```
You can watch more detailed debug information by using `--log-level=DEBUG` or `set AT_LOG_LEVEL=DEBUG` for Windows or `export AT_LOG_LEVEL=DEBUG` for Linux and Mac.
cfn_lint_serverless 0.3.5
Serverless rules for cfn-lint
Requires Python: <4,>=3.10

# cfn-lint-serverless

Ruleset for [cfn-lint](https://github.com/aws-cloudformation/cfn-lint) to validate CloudFormation templates for serverless applications against recommended best practices.

## Installation

```bash
pip install cfn-lint cfn-lint-serverless
```

## Usage

Run cfn-lint with the serverless rules module:

```bash
cfn-lint template.yaml -a cfn_lint_serverless.rules
```

## Supported Rules

This module provides validation rules for various AWS serverless resources:

- Lambda Functions
- API Gateway
- Step Functions
- SQS
- SNS
- EventBridge
- AppSync

For a detailed list of rules, refer to the [documentation](https://awslabs.github.io/serverless-rules/rules/).

## Examples

Try it with the examples provided in the repository:

```bash
# For SAM templates
cfn-lint examples/sam/template.yaml -a cfn_lint_serverless.rules

# For Serverless Framework templates
cfn-lint examples/serverless-framework/template.yaml -a cfn_lint_serverless.rules
```

## Contributing

Contributions are welcome! Please see the [CONTRIBUTING.md](../CONTRIBUTING.md) file for guidelines.

## License

This project is licensed under the MIT-0 License. See the [LICENSE](../LICENSE) file for details.
sf-quant 0.1.23
Python package for Silver Fund quant team research and trading tools.
Requires Python: <3.14,>=3.11

# Silver Fund Quant
Python package for Silver Fund quant team research and trading tools. 

## Installation

To install run

```bash
pip install sf-quant
```

## Documentation Development

To run a local server of the sphinx documentation run

```bash
uv run sphinx-autobuild docs docs/_build/html
```

## Release Process
1. Create PR
2. Merge PR(s)
3. Increment version in pyproject.toml
4. git tag v*.*.*
5. git push origin main --tags
6. Create a release and publish release notes (github)
7. uv build
8. uv publish