semvec/pypi-packages huggingface dataset:
kadoma 0.0.3
Control Daikin BRC1H units over BLE (forked from pymadoka)
Requires Python: >=3.13
Keywords: automation, ble, bluetooth, home-assistant, homeautomation, mqtt, thermostat

# Kadoma: Control for Daikin BRC1H Thermostats

Kadoma is a Python library designed to provide control over the Daikin BRC1H family thermostats. It represents an alternative approach to the original [PyMadoka](https://github.com/mduran80/pymadoka/) project.

Original [README](README.pymadoka.md] included for reference.


## Why Kadoma? The rationale behind the fork and a rewrite

The journey to Kadoma started when attempting to integrate Daikin BRC1H units into [Home Assistant](https://www.home-assistant.io/). While existing efforts, such as the [daikin_madoka integration](https://github.com/mduran80/daikin_madoka), were noted, personal experience revealed persistent challenges and inconsistencies that hindered reliable operation.

Upon deeper investigation into the underlying pyMadoka library, it became apparent that, despite its functionality, the codebase presented significant obstacles to modification and enhancement. Its intricate structure impeded efficient bug resolution, feature implementation, and overall performance improvements.

After some refactoring and rewriting substantial portions of the original code, it became clear that a simple fork and subsequent pull request would not adequately convey the scope of the modifications. Consequently, the decision was made to rebrand this endeavor as Kadoma – a distinct, yet respectful, evolution of the core concepts, aimed at delivering a more maintainable, extensible, and user-friendly experience for controlling Daikin BRC1H devices.

Ultimately, Kadoma is intended to serve as a reliable and accessible tool for developers and users seeking to integrate their Daikin BRC1H thermostats into smart home ecosystems and custom applications.


## What provides Kadoma over pyMadoka

- Cleaner high-level interface (willing to improve)
- Simplier knobs (features in pyMadoka)
- Simplified transport (BLE protocol I/O)
- Some test units


## Has Kadoma additional features?

I tried to replicate the functionality of pyMadoka, but not as 1:1.

The command line utility, kadoma, has subcommands to control the Daikin units; mqtt interface and some raw BLE stuff.

Kadoma has the [Daikin BRC1H](https://github.com/ldotlopez/ha-daikin-brc1h/) Home Assistant integration as pyMadoka has the [daikin_madoka](https://github.com/mduran80/daikin_madoka) integration.
complexitty 1.0.0
A simple Mandelbrot Set explorer for the terminal
Requires Python: >=3.10
Keywords: terminal, tui, chui, mandelbrot, fractal, maths

# Complexitty

[![Complexitty](https://raw.githubusercontent.com/davep/complexitty/refs/heads/main/.images/complexitty-social-banner.png)](https://complexitty.davep.dev/)

[![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/davep/complexitty/code-checks.yaml)](https://github.com/davep/complexitty/actions)
[![GitHub commits since latest release](https://img.shields.io/github/commits-since/davep/complexitty/latest)](https://github.com/davep/complexitty/commits/main/)
[![GitHub Issues or Pull Requests](https://img.shields.io/github/issues/davep/complexitty)](https://github.com/davep/complexitty/issues)
[![GitHub Release Date](https://img.shields.io/github/release-date/davep/complexitty)](https://github.com/davep/complexitty/releases)
[![PyPI - License](https://img.shields.io/pypi/l/complexitty)](https://github.com/davep/complexitty/blob/main/LICENSE)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/complexitty)](https://github.com/davep/complexitty/blob/main/pyproject.toml)
[![PyPI - Version](https://img.shields.io/pypi/v/complexitty)](https://pypi.org/project/complexitty/)

## Introduction

Complexitty is a simple terminal-based application that lets you explore the
classic Mandelbrot set in full character-based glory. It is the successor to
and replacement for
[`textual-mandelbrot`](https://github.com/davep/textual-mandelbrot).

## Installing

### pipx

The package can be installed using [`pipx`](https://pypa.github.io/pipx/):

```sh
$ pipx install complexitty
```

### Homebrew

The package is available via Homebrew. Use the following commands to install:

```sh
$ brew tap davep/homebrew
$ brew install complexitty
```

## Using Complexitty

Once you've installed Complexitty using one of the above methods, you can
run the application using the `complexitty` command.

The best way to get to know Complexitty is to read the help screen, once in the
main application you can see this by pressing <kbd>F1</kbd>.

![Complexitty help](https://raw.githubusercontent.com/davep/complexitty/refs/heads/main/.images/complexitty-help.png)

For more information and details on configuring Complexitty, see [the online
documentation](https://complexitty.davep.dev/).

## Getting help

If you need help, or have any ideas, please feel free to [raise an
issue](https://github.com/davep/complexitty/issues) or [start a
discussion](https://github.com/davep/complexitty/discussions).

## TODO

See [the TODO tag in
issues](https://github.com/davep/complexitty/issues?q=is%3Aissue+is%3Aopen+label%3ATODO)
to see what I'm planning.

[//]: # (README.md ends here)
bse-options 0.1.1
Unofficial Python API for fetching BSE India Option Chain data
Requires Python: >=3.12

# BSE Option Chain Scraper

This repository provides an **Unofficial Python API** to fetch **Option Chain Data** from the [BSE India](https://www.bseindia.com) website.

The scraper uses `requests` and `mthrottle` with proper headers and endpoints exposed by BSE’s API to return option chain data in a structured JSON format, similar to NSE’s option chain format.

---

## 🚀 Features
- Fetch **all available expiries** for Sensex (or other symbols by `scrip_cd`).
- Fetch option chain data for a **single expiry**.
- Fetch and merge option chain data for **all expiries at once**.
- Data is formatted with **CE (Call)** and **PE (Put)** separated, making it analysis-friendly.
- Optionally save the output to `.json` files for further processing.

---

## 📦 Installation

Clone the repo and install dependencies with uv:

```bash
git clone <reponame>
uv sync
fiatlight 0.5.0
fiatlight: shine light inside your algorithm pipelines
Requires Python: >=3.10
Keywords: python

Fiatlight: Brighten the Journey from Idea to Creation
==================================================

_Expressive Code, Instant Applications_

Fiatlight bridges the gap between code and UI, allowing you to turn ideas into fully functional applications in minutes. It automates UI generation for functions and structured data, making prototyping and fine-tuning faster and easier.
Automatically generate interactive UIs for structured data and functions.


> *For more info, [see documentation](https://pthom.github.io/fiatlight_doc)*
crowdsec-fastly-bouncer 0.4.0
CrowdSec Fastly bouncer
Requires Python: >=3.6

<p align="center">
<img src="https://github.com/crowdsecurity/cs-fastly-bouncer/raw/dev/docs/static/cs-fastly.png" alt="CrowdSec" title="CrowdSec" width="280" height="300" />
</p>
<p align="center">
<img src="https://img.shields.io/badge/build-pass-green">
<img src="https://img.shields.io/badge/tests-pass-green">
</p>
<p align="center">
&#x1F4DA; <a href="#installation/">Documentation</a>
&#x1F4A0; <a href="https://hub.crowdsec.net">Hub</a>
&#128172; <a href="https://discourse.crowdsec.net">Discourse </a>
</p>

# cs-fastly-bouncer

A bouncer that syncs the decisions made by CrowdSec with Fastly's VCL. Manages multi account, multi service setup. Supports IP, Country and AS scoped decisions.

# Documentation

Please follow [the official documentation](https://docs.crowdsec.net/docs/next/bouncers/fastly)
tuzi-mcp 0.3.3
An MCP (Model Context Protocol) server for asynchronous image generation using the Tu-zi API
Requires Python: >=3.13

# Tuzi MCP - GPT/Gemini/Seedream Image Generation Server

[中文文档](README_CN.md)

An MCP (Model Context Protocol) server for asynchronous image generation using the Tu-zi API, supporting GPT-4o, Gemini-2.5-flash, and Seedream image generation.

## MCP Configuration

```json
{
  "mcpServers": {
    "tuzi-mcp": {
      "command": "uvx",
      "args": [ "tuzi-mcp"],
      "env": {
        "TUZI_API_KEY": "your tuzi key",
        "TUZI_URL_BASE": "https://api.tu-zi.com"
      }
    }
  }
}
```

### Environment Variables

- `TUZI_API_KEY` (required): Your Tu-zi API key
- `TUZI_URL_BASE` (optional): API base URL (default: `https://api.tu-zi.com`, alternatives: `apius.tu-zi.com`, `apicdn.tu-zi.com`, `api.sydney-ai.com`)

## MCP Tools

#### `submit_gpt_image`
Submit async GPT-4o image generation task.
- `prompt` (string): Image description with aspect ratio (1:1, 3:2, or 2:3)
- `output_path` (string): Absolute save path
- `model` (string, optional): `gpt-4o-image-async` or `gpt-4o-image-vip-async`, defaults to `gpt-4o-image-async`
- `reference_image_paths` (string, optional): Comma-separated reference image paths (supports PNG, JPEG, WebP, GIF, BMP)

#### `submit_gemini_image`
Submit Gemini image generation task.
- `prompt` (string): Image description with aspect ratio (1:1, 3:2, 2:3, 16:9, 9:16, 4:5)
- `output_path` (string): Absolute save path
- `reference_image_paths` (string, optional): Comma-separated reference image paths (supports PNG, JPEG, WebP, GIF, BMP)
- `hd` (boolean, optional): HD quality, only enable when user explicitly requests, HD mode only supports .webp output
- `vip` (boolean, optional): VIP model, only use when normal model fails or user explicitly requests it

#### `submit_seedream_image`
Submit Seedream image generation/editing task. Suitable for Chinese-context tasks.
- `prompt` (string): Prompt for image generation or editing
- `output_path` (string): Absolute save path
- `size` (string, optional): Image size, supports 1024x1024, 2048x2048, 4096x4096, 2560x1440 (16:9), 1440x2560 (9:16), 2304x1728 (4:3), 1728x2304 (3:4), 2496x1664 (3:2), 1664x2496 (2:3), 3024x1296 (21:9), defaults to 1024x1024
- `quality` (string, optional): Image quality `standard` or `high`, defaults to `high`
- `n` (integer, optional): Number of images to generate (1-8), defaults to 1
- `reference_image_paths` (string, optional): Comma-separated reference image paths.

#### `wait_tasks`
Wait for all submitted tasks to complete.
- `timeout_seconds` (integer, optional): Max wait time (30-1200 seconds), defaults to 600

#### `list_tasks`
List all tasks with status.
- `status_filter` (string, optional): Filter by `pending`/`running`/`completed`/`failed`