semvec/pypi-packages huggingface dataset:
nkapi 0.2.0
A lightweight general purpose API framework. Designed to make getting started quick and easy.
Requires Python: >=3.8
Keywords: nkapi, kapi, flask, django, api framework

# NKAPI

A lightweight general-purpose API framework for Python. Designed to make getting started quick and easy, NKAPI is inspired by Flask and Django but keeps things minimal and straightforward.  

**Version:** 0.2.0

## Installation

Install NKAPI via pip (from PyPI, if published):

```python
pip install nkapi
```

Or install directly from source:

```python
git clone https://github.com/nickkipshidze/python-nkapi.git
cd python-nkapi
pip install .
```

## Quick Start

Here’s a minimal example of using NKAPI:

```python
import nkapi

server = nkapi.NKServer(
    host="127.0.0.1",
    port=8000
)

app = server.wsgi_app

def root(request: nkapi.NKRequest):
    return nkapi.NKResponse(
        headers={"Content-Type": "application/json"},
        body={
            "method": request.method,
            "path": request.path,
            "query": request.query,
            "headers": request.headers,
            "body": request.body
        }
    )

server.router.register(methods=["GET", "POST"], path="/", view=root)

if __name__ == "__main__":
    server.start()
```

Start the server and visit `http://127.0.0.1:8000/` in your browser. You will see a JSON response containing the request details.

Here's an example on how to use the WSGI app with Gunicorn:
```shell
$ gunicorn -w 4 -b 0.0.0.0 app:app --access-logfile -
```

## Logging

NKAPI logs requests to the console in the following format:

```
<client_ip> - - [timestamp] "METHOD PATH HTTP/version" STATUS -
```

## License

MIT License – see `LICENSE` file for details.
exogaia 0.0.0
Tool for analyzing Gaia epoch astrometry
Requires Python: <3.13,>=3.10

*exogaia*
==========

.. container::

    |PyPI Status| |Python Versions| |CI Status| |Docs Status| |Code Coverage| |Code Quality| |License|

*exogaia* is a tool for analyzing Gaia epoch astrometry. The package has been released on `PyPI <https://pypi.org/project/exogaia/>`_ and is actively developed and maintained on Github.

Documentation
-------------

Documentation can be found at `http://exogaia.readthedocs.io <http://exogaia.readthedocs.io>`_.

Contributing
------------

Contributions are welcome so please consider `forking <https://help.github.com/en/articles/fork-a-repo>`_ the repository and creating a `pull request <https://github.com/tomasstolker/exogaia/pulls>`_. Bug reports and feature requests can be provided by creating an `issue <https://github.com/tomasstolker/exogaia/issues>`_ on the Github page.

License
-------

Copyright 2025 Tomas Stolker

*exogaia* is distributed under the MIT License. See `LICENSE <https://github.com/tomasstolker/pycrires/blob/main/LICENSE>`_ for the terms and conditions.

.. |PyPI Status| image:: https://img.shields.io/pypi/v/exogaia
   :target: https://pypi.python.org/pypi/exogaia

.. |Python Versions| image:: https://img.shields.io/pypi/pyversions/exogaia
   :target: https://pypi.python.org/pypi/exogaia

.. |CI Status| image:: https://github.com/tomasstolker/exogaia/actions/workflows/main.yml/badge.svg
   :target: https://github.com/tomasstolker/exogaia/actions

.. |Docs Status| image:: https://img.shields.io/readthedocs/exogaia
   :target: http://exogaia.readthedocs.io

.. |Code Coverage| image:: https://codecov.io/gh/tomasstolker/exogaia/branch/main/graph/badge.svg?token=LSSCPMJ5JH
   :target: https://codecov.io/gh/tomasstolker/exogaia

.. |Code Quality| image:: https://img.shields.io/codefactor/grade/github/tomasstolker/exogaia
   :target: https://www.codefactor.io/repository/github/tomasstolker/exogaia

.. |License| image:: https://img.shields.io/github/license/tomasstolker/exogaia
   :target: https://github.com/tomasstolker/exogaia/blob/main/LICENSE
phenovector 0.1.0
Lightweight behavioural genome engine for analyzing running system processes
Requires Python: >=3.8

# PhenoVector – Behavioural Genome Engine for Running Processes

PhenoVector is a fully local, lightweight behavioural‑genome engine that derives structured “genome vectors” for running system processes. It performs safe on‑device telemetry collection using `psutil`, computes >20 behaviour‑driven gene scores, assigns risk levels, and provides an optional Streamlit dashboard for visual exploration.

All capabilities described here match the actual source code: `features.py`, `genes.py`, `genome.py`, and `app.py`.

---

## 🔍 What PhenoVector Does

### **1. Collects Runtime Behaviour Features**
From each process (`features.py`):
- CPU percentage  
- RSS memory  
- Thread count  
- Open file handles  
- Network connections  
- Executable entropy (first 200kB)  
- Lifetime & CPU time  
- System process / temp executable identification  

### **2. Computes Behavioural Gene Scores**
Each behaviour feature is normalised via `PopulationStats` and transformed into 20+ genes (`genes.py`):
- resource_abuse  
- entropy  
- impersonation  
- exfiltration  
- tracking  
- persistence  
- mutation  
- stealth  
- latency  
- syscall_diversity  
- burst_density  
- thread_intensity  
- registry_touch  
- io_intensity  
- network_activity  
- file_entropy  
- handle_abuse  
- injection_sus  
- dll_sideload  

Every gene strictly returns a float in `[0,1]`.

### **3. Produces Per‑Process Genome Objects**
`genome.py` returns a structured `ProcessGenome`:
- identity: pid, name, exe  
- behaviour features  
- gene vector (dict)  
- risk_score (0–1)  
- risk_level (`benign`, `suspicious`, `high`)  

### **4. Optional Visual Dashboard**
`app.py` provides:
- PCA/t‑SNE process clustering  
- Radar charts of gene profiles  
- IsolationForest anomaly scoring  
- PID whitelisting  
- Raw genome table & JSON export  


---

## 📦 Installation

```bash
pip install phenovector
```


---

## 🚀 Quick Usage

```python
from phenovector.genome import analyze_system

genomes = analyze_system(limit=100)
for g in genomes:
    print(g.pid, g.name, g.risk_score, g.risk_level)
    print(g.genes)
```

---

## 📊 Run the Streamlit UI

```bash
streamlit run -m phenovector.app
```


---


## 📄 License

APACHE 2.0
hhdm-apiclient-wrapper 26.1.0.0
Library that abstracts use of the HH Data Management API
Requires Python: <4.0,>=3.10

## hhdm_apiclient_wrapper

### Wrapper for use of the HH Data Management Api Client

Examples of the wrapper can be found at https://github.com/hh-development/python-api-wrapper-examples

See documentation for the API at https://hhdm-api.hh-dev.com/swagger/index.html