semvec/pypi-packages huggingface dataset:
aws-step-functions-pydantic 0.0.5
Pydantic models for AWS step functions
Requires Python: >=3.9

# aws-step-functions-pydantic

[![CI Status](https://github.com/lmmx/aws-step-functions-pydantic/actions/workflows/master.yml/badge.svg)](https://github.com/lmmx/aws-step-functions-pydantic/actions/workflows/master.yml)
[![Coverage](https://codecov.io/gh/lmmx/aws-step-functions-pydantic/branch/master/graph/badge.svg)](https://codecov.io/github/lmmx/aws-step-functions-pydantic)
[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

Pydantic models for AWS step functions

## Usage

### From Step Function ARN

Use the `from_arn()` class constructor

```py
from aws_sfn_pydantic import StateMachine

sfn = StateMachine.from_arn(state_machine_arn="...")
```

### From JSON

Use the `model_validate_json()` class constructor (Pydantic v2 builtin)

```py
from aws_sfn_pydantic import StateMachine

sfn = StateMachine.model_validate_json("...")
```

### To YAML

Use the `to_yaml()` class constructor, which accepts:

- `indent` (default: 2)
- `level` (default: 0)

```py
print(sfn.model_to_yaml())
```

## Requires

- Python 3.10+

## Installation

```sh
pip install aws-step-functions-pydantic
```

> _aws-step-functions-pydantic_ is available from [PyPI](https://pypi.org/project/aws-step-functions-pydantic), and
> the code is on [GitHub](https://github.com/lmmx/aws-step-functions-pydantic)
depgeist 1.0.0
A smart dependency checker for Python projects.
Requires Python: >=3.6

# 🚀 DepGeist - The Smart Dependency Manager for Python

**DepGeist** is an intelligent dependency manager that scans your Python project, detects missing or unused dependencies, and suggests updates in seconds.

## 🎯 Features  
✅ **Scans Your Project** - Detects dependencies used in your code.  
✅ **Finds Missing Dependencies** - Alerts you about packages you forgot to install.  
✅ **Detects Unused Dependencies** - Cleans up your `requirements.txt`.  
✅ **Suggests Updates** - Recommends package updates based on PyPI versions.  
✅ **Works via CLI & Python API** - Use it in scripts or the terminal.  

---

## 📦 Installation  
You can install **DepGeist** via pip:

```sh
pip install depgeist
```

---

## 🚀 Quick Start  

### **CLI Usage**  
After installation, use `depgeist` in your terminal:  

```sh
depgeist scan        # Scan the project for dependencies  
depgeist check       # Check for missing/extra dependencies  
depgeist update      # Suggest updates for outdated dependencies  
```

---

### **Python API Usage**  
DepGeist can also be used programmatically:  

```python
import depgeist

# Scan the project for dependencies
dependencies = depgeist.scan_project(".")

# Check for missing and extra dependencies
missing, extra = depgeist.check_dependencies()

# Suggest updates for outdated dependencies
outdated = depgeist.suggest_updates()
```

---

## 📜 Example Output  

```sh
$ depgeist check
🔍 Scanning project...
✅ Found dependencies: requests, numpy, pandas
⚠️ Missing dependencies: requests
🗑️ Unused dependencies: pandas
```

```sh
$ depgeist update
📌 Checking for outdated dependencies...
🔄 numpy 1.21.0 → 1.25.2  (latest)
```

---

## 🤝 Contributing  
We welcome contributions! Fork the repo, make changes, and submit a PR.  

1. Clone the repo:  
   ```sh
   git clone https://github.com/ibrahims-main/DepGeist.git
   cd depgeist
   ```

2. Open a pull request! 🚀  

---

## ⚖️ License  
DepGeist is open-source and licensed under the [MIT License](LICENSE).  

---

## ⭐ Support the Project  
If you find **DepGeist** useful, please **star** the repo and share it with others! 🌟
koopmans 1.1.0
Koopmans spectral functional calculations with python and Quantum ESPRESSO
Requires Python: >=3.10

========
koopmans
========

| |GH Actions| |Coverage Status| |GPL License| |Documentation Status|

For performing Koopmans spectral functional calculations with ``Quantum ESPRESSO``.

Installation
------------

This python package ``koopmans`` only contains a subset of the code that you will require to run Koopmans functional calculations. To install everything, download the full source code from `github <https://github.com/epfl-theos/koopmans>` and follow the installation instructions.

Running
-------
Calculations are run with the command

.. code-block:: bash

   koopmans <seed>.json

where <seed>.json is the ``koopmans`` input file. For more details, refer to the `online documentation <https://koopmans-functionals.org>`_.

Contact
-------
Written and maintained by Edward Linscott, Riccardo De Gennaro, and Nicola Colonna (2020-)

For help and feedback email edward.linscott@gmail.com

.. |GH Actions| image:: https://img.shields.io/github/actions/workflow/status/epfl-theos/koopmans/tests.yml?master&label=master&logo=github
   :target: https://github.com/epfl-theos/koopmans/actions?query=branch%3Amaster
.. |Coverage Status| image:: https://img.shields.io/codecov/c/gh/epfl-theos/koopmans/master?logo=codecov
   :target: https://codecov.io/gh/epfl-theos/koopmans
.. |GPL License| image:: https://img.shields.io/badge/license-GPL-blue
   :target: https://github.com/epfl-theos/koopmans/blob/master/LICENSE
.. |Documentation Status| image:: https://readthedocs.org/projects/koopmans/badge/?version=latest
   :target: https://koopmans-functionals.org/en/latest/?badge=latest
   :alt: Documentation Status