semvec/pypi-packages huggingface dataset:
oakx-oger 0.1.6
OGER plugin for oaklib
Requires Python: >=3.9,<4.0

# oakx-oger

This is an [OGER](https://github.com/OntoGene/OGER) plugin for [`oaklib`](https://github.com/INCATools/ontology-access-kit).

**ALPHA**

## Usage

```
pip install oakx-oger
runoak -i oger:sqlite:obo:envo annotate cultured organisms polar ecosystems atmospheric gas exchange
```

## How it works

There are two possible inputs to this plugin:
1. A `.txt` file [`runoak -i oger:sqlite:obo:envo annotate --text-file text.txt`]
2. Words that need to be annotated.[`runoak -i oger:sqlite:obo:envo annotate cultured organisms polar ecosystems atmospheric gas exchange`]

Input ontologies generally used `oaklib` can be used with an `oger:` prefix.
Note: This has been tested only with `oger:sqlite:obo:*` for now.


## Acknowledgements

This [cookiecutter](https://cookiecutter.readthedocs.io/en/stable/README.html) project was developed from the [oakx-plugin-cookiecutter](https://github.com/INCATools/oakx-plugin-cookiecutter) template and will be kept up-to-date using [cruft](https://cruft.github.io/cruft/).
json-to-ndjsonify 0.1.0
A small package to convert JSON files to NDJSON (Newline Delimited JSON) format.

# JSON to NDJSONify

## Table of Contents

- [Overview](#overview)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Configuration](#configuration)
- [Running Tests](#running-tests)
- [Contributing](#contributing)
- [License](#license)

## Overview

JSON to NDJSONify is a Python package specifically engineered for converting JSON files to NDJSON (Newline Delimited JSON) format. Built for developers who are working with APIs or data platforms that require NDJSON input, this package helps streamline your workflow by automating the conversion process.

## Features

- Supports complex nested JSON structures
- Ability to filter specific nodes (e.g., `edges`)
- Highly optimized and lightweight
- Written in Python, making it highly extensible and maintainable
- Unit tests to validate NDJSON output

## Installation

Clone the repository:

```bash
git clone https://github.com/mohjak/json_to_ndjsonify.git
```

Navigate to the cloned directory and run:

```bash
pip install .
```

Or directly via pip:

```bash
pip install json-to-ndjsonify
```

## Usage

### Basic Usage

To convert a JSON file to NDJSON:

```bash
json-to-ndjsonify --input sample.json --node edges
```

This will create an NDJSON file in the same directory as the `sample.json` file, suffixed with a timestamp.

### Advanced Usage

For additional configurations, consult the inline help:

```bash
json-to-ndjsonify --help
```

## Configuration

### Command-Line Parameters

- `--input`: Specifies the path of the JSON file to be converted.
- `--node`: Specifies the node name in the JSON file. Default is 'edges'.
- `--output`: Path to the output folder.

  Example:

  ```bash
  json-to-ndjsonify --input /path/to/your/file.json --node custom_edges --output /path/to/output/folder
  ```

## Running Tests

To execute the unit tests:

```bash
export NDJSON_DIR=/path/to/your/ndjson/directory
python -m unittest tests/test_main.py
```

## Contributing

See the [CONTRIBUTING.md](CONTRIBUTING.md) file for how to contribute to this project.

## License

This package is licensed under the MIT License. See the `LICENSE.md` file for details.
ssos 1.3.5
The ssos Pipeline - Detection of Solar System Objects in astronomical images
Requires Python: >=3.6
Keywords: astronomy astrophysics solar-system data pipeline

# The _ssos_ Pipeline
---
[![Documentation Status](https://readthedocs.org/projects/ssos/badge/?version=latest)](https://ssos.readthedocs.io/en/latest/?badge=latest) <a href="http://ascl.net/1901.006"><img src="https://img.shields.io/badge/ascl-1901.006-blue.svg?colorB=262255" alt="ascl:1901.006" /></a>

Pipeline to detect, identify, and recover Solar System Objects in astronomical images.

The online documentation is available at https://ssos.readthedocs.io/en/latest/

An article describing the high-level design of the pipeline has been accepted for publication in _Astronomy&Computing_. In the meantime, if you have used the _ssos_ pipeline in your research, please reference

_Mahlke M., et al 2018, The ssos Pipeline, 1.2.1, Astrophysics Source Code Library ascl:1901.006_

Licensed under version 3 of the GNU Affero General Public License.