semvec/pypi-packages huggingface dataset:
onyxcloud 1.12.9
Python package for the OnyxCloud CTF challenge. Part 1
License: MIT
Requires Python: >=3.10

# CTF Challenge: OnyxCloud - NOMI's Signal Decryption

Welcome to the **OnyxCloud** CTF challenge! Your mission begins with an intriguing introduction from NOMI, the Neural Operations & Multilingual Interface. Prepare to decode cryptic signals and uncover the secrets hidden within the OnyxCloud fleet's transmissions.

## Introduction

Upon starting the challenge, you'll be greeted with the following message:

```
--------------------------------------------------
 Welcome aboard, Inspector!

 I am NOMI, your Neural Operations & Multilingual Interface
   here to bridge communication with the OnyxCloud fleet.

 Advisory: Subspace linguistic algorithms are in preliminary phases.
   Translations are severely hindered due to alien signal complexity!
--------------------------------------------------
```

### What Does This Mean?

NOMI is your AI guide, designed to assist in decoding alien transmissions. However, the system's **linguistic algorithms** are still experimental, making the translation process challenging. You'll need to apply your analytical skills to extract meaningful data from fragmented signals.

## Objective

Your goal is to:

- Analyze NOMI's output for clues hidden in the text.
- Identify patterns, ciphers, or encoded messages.
- Decipher the alien signals to reveal the next steps in the challenge.

## Hints

- Pay close attention to formatting, symbols, and color-coded text.
- NOMI's messages may contain encoded strings, hexadecimal data, or subtle clues in the dialogue.
- Be mindful of the "advisory" notice â€” garbled data may require multiple approaches to decode.


Good luck, Inspector!
SPTpython 1.0.4
A Python package for processing and analyzing single-particle tracking (SPT) data
License: MIT
Requires Python: <=3.9.17

# SPTpython

This package enables simple processing for single-particle tracking data. Currently a command-line interface is supported for processing results, but a GUI is planned to be added later. For details on what commands are supported by the CLI, refer to CLI.py.

This is intended to be used when taking large amounts of similar data in the form of .tif files. Functionality allows for easy comparison between datasets, using SPTpython.compare

## Installation
This project was built on Python 3.8.3, so install it [here](https://www.python.org/downloads/release/python-383/). I am not planning to add support for more recent versions.

Install python as normal, then make sure your pip and setuptools are upgraded:

`python -m pip install --upgrade pip ` 

`pip install --upgrade setuptools`

`pip install SPTpython`

(last updated v1.0.1)