semvec/pypi-packages huggingface dataset:
iceflow-engine-cli 0.0.2
This is an Ice Flow Engine CLI tool for creating workflow executions.

# Ice Flow CLI

Ice Flow CLI is a command-line tool designed to streamline workflow templates, step templates and executions creation.

## Features
- Automate CREATE, RECREATE, GET, UPDATE, DELETE of workflow templates, step templates and executions.
- Supports JSON and YAML processing with `jq` and `yq`.
- Work in different environment. Set ENV to dev or local.

---

## Installation Instructions

### Prerequisites
Before installing the **Ice Flow CLI**, ensure the following dependencies are installed on your system:

- `yq`
- `jq`
- `curl`
- `envsubst`

---

### Install the CLI via pip
Once dependencies are installed, you can install the Ice Flow CLI using `pip`:

```bash
pip install iceflow-engine-cli
```

---

## Dependency Installation Guide

#### **macOS**
Use Homebrew to install dependencies:
```bash
brew install yq jq curl gettext
```

#### **Debian/Ubuntu**
```bash
sudo apt update
sudo apt install -y jq curl gettext
```
For `yq`, install via Snap:
```bash
sudo snap install yq
```

#### **Red Hat/CentOS**
```bash
sudo yum install -y jq curl gettext
```

#### **Windows (WSL)**
For Windows users running WSL (Ubuntu-based), install dependencies using:
```bash
sudo apt update
sudo apt install -y jq curl gettext
snap install yq
```

---

## Verify Installation
After installing the dependencies and the CLI package, verify that everything is set up correctly:

```bash
iceflow --help
```

If you encounter any issues, ensure all required dependencies are installed by running:

```bash
which yq jq curl envsubst
```

---

## Usage

Run the CLI with:
```bash
iceflow <KIND> <COMMAND> <ARG>
```

For example:
```bash
iceflow_engine_cli wft create demo-simple/inline-steps/workflow_demo.yaml
```
```bash
iceflow_engine_cli exec create demo-simple/inline-steps/execution.yaml --start
```

---

## Uninstalling the CLI
To remove the CLI from your system, run:
```bash
pip uninstall iceflow-engine-cli
```
curriculumagent 1.1.0
CurriculumAgent is a cleanup and improved version of the NeurIPS 2020 Competition Agent by Binbinchen.The agent is build to extract action sets of the Grid2Op Environment and then use rule-based agent to train a Reinforcement Learning agent.

CurriculumAgent
===============
[![CI](https://github.com/FraunhoferIEE/CurriculumAgent/actions/workflows/main.yml/badge.svg)](https://github.com/FraunhoferIEE/CurriculumAgent/actions/workflows/main.yml)
[![Documentation Status](https://readthedocs.org/projects/curriculumagent/badge/?version=latest)](https://curriculumagent.readthedocs.io/en/latest/?badge=latest)
[![PyPI version](https://badge.fury.io/py/curriculumagent.svg)](https://badge.fury.io/py/curriculumagent)

CurriculumAgent is a cleanup and improved version of the
[NeurIPS 2020 Competition Agent by binbinchen](https://github.com/AsprinChina/L2RPN_NIPS_2020_a_PPO_Solution).
The agent is build to extract action sets of the Grid2Op Environment and then use rule-based agent to train
a Reinforcement Learning agent. We explain each step in more detail in our paper. 

When using the CurriculumAgent, please cite our paper with.
```
@article{lehna_managing_2023,
	title = {Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents},
	issn = {2666-5468},
	url = {https://www.sciencedirect.com/science/article/pii/S2666546823000484},
	doi = {https://doi.org/10.1016/j.egyai.2023.100276},
	pages = {100276},
	journaltitle = {Energy and {AI}},
	author = {Lehna, Malte and Viebahn, Jan and Marot, Antoine and Tomforde, Sven and Scholz, Christoph},
	date = {2023},
}
```
The code of the paper can be found under `/paper_data_MPGTTA`.

Setup
-----

All requirements are listed in `requirements.txt`.

Installing the package should already give you all needed requirements.

Usage/Documentation
-------------------

Please take a look at our [sphinx documentation](https://curriculumagent.readthedocs.io/en/latest/) on how to use the package.

We also provide several jupyter notebooks in `./jupyter_notebooks` to get you started quickly.



License
-------

```
Copyright (c) 2022 EI Innovation Lab, Huawei Cloud, Huawei Technologies and Fraunhofer IEE
The code is subject to the terms of Mozilla Public License (MPL) v2.0.
Commercial use is NOT allowed.
```

Please take a look at the LICENSE file for a full copy of the MPL license.