semvec/pypi-packages huggingface dataset:
nbdocgen 0.1.0
nbdocgen is a command line tool to generate documentation for each and every cell in a Jupyter notebook using OpenAI Chat Completion APIs.
License: MIT
Requires Python: >=3.8,<4.0

**nbdocgen** is a command line tool to generate documentation for each and every cell in a Jupyter notebook using OpenAI.

# Getting Started

## Prerequisites
- Python >=3.8
- [Poetry](https://python-poetry.org/)
- OpenAI API Key

## Installation
```
git clone https://github.com/santiadavani/nbdocgen
cd nbdocgen
poetry shell
poetry install
pip install .
```

## Usage
Set OPENAI_API_KEY environment variable. If you don't have a key please check documentation [here](https://platform.openai.com/docs/api-reference/authentication)

`export OPENAI_API_KEY=<OPENAI_API_KEY>`

You can check all the options using `--help`.
```
(nbdocgen-py3.9) bash-3.2$ nbdocgen --help
Usage: nbdocgen [OPTIONS]

Options:
  --input PATH          Input Jupyter Notebook
  --output PATH         Output Jupyter Notebook
  --temperature FLOAT   Temperature for OpenAI  [default: 0.7]
  --top_p FLOAT         Top p for OpenAI  [default: 1.0]
  --max_tokens INTEGER  Max tokens for OpenAI completion  [default: 256]
  --base_prompt TEXT    Base prompt for OpenAI completion  [default: Please
                        generate a two sentence markdown documentation for the
                        given Python code.]
  --help                Show this message and exit.
```

# Examples

## Basic Usage

`nbdocgen --input <input_notebook> --output <output_notebook>`

## Advanced Usage
In this example, we show how to use `temperature` and `base_prompt` options. 

```
nbdocgen --input ~/Downloads/input_notebook.ipynb \
--output ./output_notebook.ipynb --temperature 0.3 \
--base_prompt "Please generate 5 sentence markdown documentation for the code below"
```
moranpycess 1.1.0
Python framework for Moran Processes driven by game theory
License: MIT
Requires Python: >=3.9

The following package presents a general game-theoretical framework to carry out scientific simulations according to the Moran model. Registering distinct types of individuals together with specification of payoffs between them allows to replicate evolution of the population and observe growth dynamics.

For more information please visit project's homepage!
ckanext-envidat-validators 0.0.0
Custom CKAN validators for EnviDat.
License: MIT
Requires Python: >=3.8
Keywords: CKAN,validators,schema

# CKAN EnviDat Validators

<div align="center">
  <em>Custom CKAN validators for EnviDat.</em>
</div>
<div align="center">
  <a href="https://pypi.org/project/ckanext-envidat_validators" target="_blank">
      <img src="https://img.shields.io/pypi/v/ckanext-envidat_validators?color=%2334D058&label=pypi%20package" alt="Package version">
  </a>
  <a href="https://pypistats.org/packages/ckanext-envidat_validators" target="_blank">
      <img src="https://img.shields.io/pypi/dm/ckanext-envidat_validators.svg" alt="Downloads">
  </a>
  <a href="https://gitlabext.wsl.ch/EnviDat/ckanext-envidat_validators/-/raw/main/LICENSE" target="_blank">
      <img src="https://img.shields.io/github/license/EnviDat/ckanext-envidat_validators.svg" alt="Licence">
  </a>
</div>

---

**Source Code**: <a href="https://gitlabext.wsl.ch/EnviDat/ckanext-envidat_validators" target="_blank">https://gitlabext.wsl.ch/EnviDat/ckanext-envidat_validators</a>

---

Some basic additional validation for the CKAN schema used at EnviDat.