semvec/pypi-packages huggingface dataset:
FortniteAPIAsync 2.0.1
Asynchronous Python wrapper for Fortnite-API.com.

<div align="center">

# FortniteAPIAsync

Python wrapper for [Fortnite-API.com](https://fortnite-api.com).

[![Downloads](https://static.pepy.tech/badge/fortniteapiasync)](https://pepy.tech/project/fortniteapiasync)
[![Python](https://img.shields.io/badge/python-3.9%20%E2%80%93%203.14-blue?logo=python&logoColor=white)](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue?logo=python&logoColor=white)
[![FortniteAPIAsync Version: 2.0.0](https://img.shields.io/pypi/v/fortniteapiasync.svg)](https://pypi.org/project/fortniteapiasync/)
[![PEP-8 Compliant](https://img.shields.io/badge/PEP8-compliant-brightgreen.svg)](https://www.python.org/dev/peps/pep-0008/)
![Last Commit](https://img.shields.io/github/last-commit/xMistt/FortniteAPIAsync?logo=github)
[![Docs](https://img.shields.io/readthedocs/fortniteapiasync/latest?logo=readthedocs)](https://fortniteapiasync.readthedocs.io)

</div>


## Installation
```commandline
# windows
py -3 -m pip install -U FortniteAPIAsync

# linux/macos
python3 -m pip install -U FortniteAPIAsync
```

## Examples
### Standard example
```python
import FortniteAPIAsync
import asyncio


async def get_current_aes() -> None:
    client = FortniteAPIAsync.APIClient()
    
    aes = await client.get_aes()
    print(f'AES key for {aes.build} - {aes.main_key}')
    # outputs: AES key for ++Fortnite+Release-39.40-CL-50341043 - 67e127d5c846a0d426be...
    
    await client.close()


asyncio.run(get_current_aes())
```

### rebootpy example
```python
import rebootpy
import FortniteAPIAsync

from rebootpy.ext import commands


bot = commands.Bot(
    command_prefix='!',
    auth=rebootpy.AuthorizationCodeAuth(
        code=input('Enter authorization code: ')
    )
)


@bot.command()
async def skin(ctx: rebootpy.ext.commands.Context, *, content: str) -> None:
    try:
        async with FortniteAPIAsync.APIClient() as client:
            cosmetic = await client.get_cosmetic(
                matchMethod="contains",
                name=content,
                backendType="AthenaCharacter"
            )

        await bot.party.me.set_outfit(asset=cosmetic.id)
        await ctx.send(f'Skin set to {cosmetic.id}.')
    except FortniteAPIAsync.exceptions.NotFound:
        await ctx.send(f"Failed to find a skin with the name: {content}.")


bot.run()
```
societal-costs-pipeline-2026-02-07-0800 0.1.0
Societal costs pipeline CLI.
Requires Python: >=3.9

# societal_costs

Workspace for the societal costs study.

## Crates

- `crates/costs_core` — core domain types, aggregation, pricing, and validation.
- `crates/costs_models` — two-part, Tweedie, and log-normal models + selection tools.
- `crates/costs_matching` — matching + balance diagnostics.
- `crates/costs_cohort` — cohort assignment + diagnostics.
- `crates/costs_components` — register-derived component builders (LMDB volume so far).
- `crates/costs_population` — population files + public stats QC.
- `crates/costs_pipeline_common` — config, errors, tracing, and shared helpers.
- `crates/costs_pipeline_io` — report/Arrow/CSV/JSON writers.
- `crates/costs_registers` — register ingestion flows (BEF/LPR/LMDB/VNDS/DOD/etc).
- `crates/costs_pipeline_core` — orchestration + analysis/matching/modeling logic.
- `crates/costs_pipeline` — thin facade that re-exports common/core/io APIs.

## LMDB example

See `crates/costs_pipeline/README.md` for the LMDB ingestion example.

## Pipeline config

Start from `pipeline.example.toml` and update the register file paths to match
your local dataset layout. Most SAS7BDAT paths accept either a single file
or a directory (all `.sas7bdat` files are loaded, sorted by name). You can
also set `base_path` in the config to prefix all relative register paths.
File filtering uses `study.data_*` and optional `study.baseline_*` /
`study.followup_*` windows to avoid reading out-of-scope files.
Event registers (VNDS/DOD/DODSAARS/DODSAASG) are **not** year-filtered.
If you use contact-based SCD classification, set
`components.lpr.scd_inpatient_contact_types` (or flip
`components.lpr.scd_allow_outpatient = true` to allow outpatient contacts).

Pipeline outputs include consolidated QC under `qc_summary.csv/json`, plus
step-specific outputs such as `lpr_episode_qc.csv`, `matching_outcome_qc.csv`,
`matching_parent_qc.csv`, and `population_public_stats.csv`.

For terminal progress and timing, set:
- `pipeline.progress = true`
- `pipeline.log_level = "info"` (or `debug`)

## Additional docs

- `crates/costs_core/README.md` — core domain and aggregation usage.
- `crates/costs_models/README.md` — model APIs and examples.
- `crates/costs_models/examples/README.md` — runnable model examples.
- `crates/costs_components/README.md` — LMDB note (missing price fields).
- `crates/costs_pipeline/README.md` — pipeline usage and LMDB example.
iflow-mcp_format37-youtube_mcp 0.1.0
YouTube transcribation MCP server
Requires Python: >=3.11

# youtube_mcp
Youtube transcribation MCP server

## Demo Video

[![YouTube MCP Demo](https://img.youtube.com/vi/bS5vKuehzEE/maxresdefault.jpg)](https://youtu.be/bS5vKuehzEE)

*Click the image above to watch the demo video*

## Requirements:
* OpenAI API key
* Cookies

## Server installation
* Clone the repo:
```
git clone https://github.com/format37/youtube_mcp.git
cd youtube_mcp
nano .env
```
* Extract your cookies. See [cookies.md](./cookies.md)  
Place cookies.txt in the ./mcp/ folder.
* Generate MCP_KEY:
```
python token_generator.py
```
* Define .env:
```
CONTAINER_NAME=youtube_mcp_main
PORT=7001
MCP_KEY=YOUR-MCP-KEY
OPENAI_API_KEY=YOUR-OPENAI-KRY
```
* Provide run access
```
sudo chmod +x compose.sh
sudo chmod +x logs.sh
sudo chmod +x update.sh
```
* Run
```
./compose.sh
```
* Check that port is opened for incoming connections.

## Client configuration
3. Add Bybit server to the Claude desktop config:
Example:
```
{
    "mcpServers": {
      "youtube": {
        "command": "npx",
        "args": [
          "mcp-remote",
          "http://localhost:7001/sse",
          "--header",
          "Authorization:YOUR-TOKEN",
          "--allow-http"
        ],
        "disabled": false
      }
    }
}
```
## Client side
```
4. Restart Claude desktop
5. Check that tws tools are listed in the tools list. Ask Claude to check ibkr account
pykyfg 0.1.0
A high-level Python API for KAYA frame grabber hardware
Requires Python: >=3.8
Keywords: kaya, frame-grabber, camera, vision, coaxpress

# pykyfg

A high-level Python API for KAYA frame grabber hardware, providing easy-to-use interfaces for camera control, image acquisition, and streaming.

## ⚠️ Important Notice

**This package provides only basic functionality and does not fully support all KAYA API features.**

For complete KAYA API support and official documentation, please refer to the official [KAYA Vision Point SDK](https://kayainstruments.com/software-sdk/)

**Disclaimer**: This package is developed by a third party and is not affiliated with or endorsed by KAYA Instruments. KAYA Instruments assumes no responsibility for this package or its use.

## Overview

pykyfg is a Python wrapper around the KAYA frame grabber SDK, designed to simplify camera operations and image acquisition workflows. It provides both low-level bindings (`kyapi`) and high-level abstractions (`pykyfg`) for working with KAYA hardware.

## Installation

Install directly using pip:

```bash
pip install pykyfg
```

### Prerequisites

- Python 3.8+
- KAYA frame grabber and camera hardware
- KAYA Vision Point SDK installed and configured

### Dependencies

- `numpy` - Numerical computing
- `opencv-python` - Computer vision library

## Quick Start

```python
import pykyfg
import cv2

with pykyfg.FrameGrabber().open() as fg:
    with fg.open_camera() as cam:
        with cam.open_stream(4) as stream:
            frames = cam.capture(1)

            
for frame in frames:
    cv2.imshow("Frame", frame)
    cv2.waitKey(0)
cv2.destroyAllWindows()
```