semvec/pypi-packages huggingface dataset:
berry-core 0.6.13
High-performance blockchain data processing library forked from cherry-core
Requires Python: >=3.8
Keywords: blockchain, ethereum, solana, data, indexing, web3, defi

# cherry-core python bindings

## License

Licensed under either of

 * Apache License, Version 2.0
   ([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0)
 * MIT license
   ([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)

at your option.

## Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
dual licensed as above, without any additional terms or conditions.
kyg-guessing-game-kit 0.1
KYG: Guessing Game Kit – Playful Python Learning by Ashok Sir and Sathish Ramanujam
Requires Python: >=3.6
Keywords: python education game guessing tkinter induction zero2hero

# Co-Kreate Your Genius: KYG Guessing Game Kit

An interactive, gamified toolkit for learning Python fundamentals—built on a proven method by [Ashok Bakthavathsalam](https://www.ashokbakthavathsalam.com/) and created by [Sathish Ramanujam](https://professor-sathish.github.io/).

## What is KYG Guessing Game Kit?

This is a fun, hands-on way for students to experience Python’s five core constructs—**print statements, function calls, variable input, import, GUI basics**—in a real game.

* Designed for “Zero2Hero” Python induction events.
* Lets students play the classic “guess my number!” challenge.
* All logic shown in code—and explained interactively through gameplay.
* Perfect for classroom, online exercises, coding clubs, or self-learning.

## Why Use This Kit?

* Developed by Python educators for rapid onboarding and retention.
* Play, explore, then dive into code: students see the GUI first, then relate it to Python logic.
* Each step introduces a core Python concept in context.

## How to Play

* Open the game GUI, let students choose a range, and let the computer try to guess.
* Students respond with HIGHER/LOWER/YES buttons as the computer guesses their number.
* Behind the scenes: binary and linear search strategies are explained in code and gameplay.
* Replay as needed, experiment, and learn.

See the included \[readme.md] for complete instructions!

## Authors

* [Ashok Bakthavatchalam](https://www.ashokbakthavathsalam.com/)
* [Sathish Ramanujam](professor-sathish.github.io)

## Features

* Clean Tkinter GUI
* Reinforces fundamental Python constructs
* Replayable and easily customizable
* Well-documented gameplay and code

## Installation

* pip install kyg-guessing-game-kit
* **After installation, you can run the game with**

  * python -m kyg\_ggk or kyg\_ggk
pedroCLI 1.0.0
Pedro CLI — spectacular terminal AI client - Get PEDRO on your own pc
Requires Python: >=3.8

# Pedro CLI

![Pedro CLI Logo](https://gecowave.top/pedro/logo.png)

## Terminal AI Assistant

Pedro is a powerful terminal-based AI assistant created by emqnuele (gecowave). Interact with artificial intelligence directly from your terminal with a simple and intuitive interface.

## Installation

```bash
pip install pedro
```

## Usage

After installation, start Pedro by simply typing:

```bash
pedro
```

### Available Commands

Pedro supports various commands that you can use during a session:

#### Basic Commands

- `/help` - Show all available commands
- `/new` - Start a new conversation
- `/exit` - Exit Pedro
- `/clear` - Clear the screen and show the current conversation
- `/history` - Show the history of the current conversation

#### System Commands

- `/system <message>` - Set a custom system prompt
- `/config` - Show current configuration
- `/model` - Show information about the AI model being used
- `/stats` - Show conversation statistics

#### Conversation Management

- `/save <name>` - Save the current conversation with a specific name
- `/load <name>` - Load a saved conversation
- `/list` - List all saved conversations
- `/rename <old> <new>` - Rename a saved conversation
- `/delete <name>` - Delete a saved conversation

#### Interface

- `/theme` - Toggle color theme (light/dark)

## Usage Examples

### Starting a New Conversation

```
pedro
> Hello, how can I help you today?
How can I create a website with HTML and CSS?
> [Pedro responds with information about HTML and CSS...]
/new
> Started new conversation. How can I help you?
```

### Saving and Loading Conversations

```
/save web_project
> Conversation saved as 'web_project'
/new
> Started new conversation. How can I help you?
/load web_project
> Loaded conversation 'web_project'
```

### Setting a System Prompt

```
/system You are a Python programming expert and will help me write efficient code.
> System prompt set. How can I help you with Python?
```

## Features

- **Persistent Conversations**: Your conversations are saved locally
- **Intuitive Interface**: Simple interaction via terminal
- **Customization**: Set custom system prompts
- **Statistics**: Keep track of usage with detailed statistics
- **Color Themes**: Choose between light and dark theme

## System Requirements

- Python 3.8 or higher
- Active internet connection

## Additional Information

For more information, visit [gecowave.top/pedro](https://gecowave.top/pedro)

---

Created with ❤️ by emqnuele (gecowave)
gaiaflow 0.0.3
Local-first MLOps infrastructure python tool that simplifies the process of building, testing, and deploying ML workflows.
Requires Python: >=3.11

# Gaiaflow

![PyPI - Version](https://img.shields.io/pypi/v/gaiaflow)
[![Pixi Badge](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/prefix-dev/pixi/main/assets/badge/v0.json)](https://pixi.sh)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v0.json)](https://github.com/charliermarsh/ruff)
[![Docs](https://img.shields.io/badge/docs-mkdocs-blue)](https://bcdev.github.io/gaiaflow/)
![Static Badge](https://img.shields.io/badge/Airflow-3.0-8A2BE2?logo=apacheairflow)
![Static Badge](https://img.shields.io/badge/MLFlow-darkblue?logo=mlflow)
![Static Badge](https://img.shields.io/badge/MinIO-red?logo=minio)
![Static Badge](https://img.shields.io/badge/Jupyter-grey?logo=jupyter)
![Static Badge](https://img.shields.io/badge/Minikube-lightblue?logo=kubernetes)


Gaiaflow is a local-first MLOps infrastructure python package tool that simplifies the process 
of building, testing, and deploying ML workflows.
It provides an opinionated CLI for managing Airflow, MLflow, and other 
dependencies, abstracting away complex configurations, and giving you 
a smooth developer experience.

_NOTE: Currently this library is released as an experimental version. Stable 
releases will follow later_

Gaiaflow is a tool that
- provides you with a local MLOps infrastructure via a CLI tool with 
some prerequisites already installed.
- handles the complex Airflow configuration and [Xcom](https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/xcoms.html) 
handling and provides the user a simpler interface for creating DAGs.
- provides a [cookiecutter template](https://github.com/bcdev/gaiaflow-cookiecutter)
to get started with your projects with a standardized structure.

- provides tools to deploy models locally and in production (in future)
- provides clear documentation on how to setup production environment to run your 
workflows at scale (in future, private?)


Prerequisites:
- Docker
- Docker compose
- Miniforge
- Mamba/Conda

To install it, you can do it via:

`pip install gaiaflow`

Check installation:

`gaiaflow --help`

You can read the documentation [here]()