Metadata-Version: 2.1
Name: ssb-datadoc
Version: 0.1.1
Summary: Document dataset metadata. For use in Statistics Norway's metadata system.
Home-page: https://github.com/statisticsnorway/datadoc
License: Apache-2.0
Author: Statistics Norway
Author-email: mmw@ssb.no
Requires-Python: >=3.8,<4.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: dash (>=2.4.1,<3.0.0)
Requires-Dist: dash-bootstrap-components (>=1.1.0,<2.0.0)
Requires-Dist: jupyter-dash (>=0.4.2,<0.5.0)
Requires-Dist: pandas (>=1.4.2,<2.0.0)
Requires-Dist: pyarrow (>=8.0.0,<9.0.0)
Requires-Dist: pydantic (>=1.9.1,<2.0.0)
Requires-Dist: requests (>=2.27.1,<3.0.0)
Requires-Dist: ssb-datadoc-model (==0.1.0)
Project-URL: Repository, https://github.com/statisticsnorway/datadoc
Description-Content-Type: text/markdown

# Datadoc

Document datasets in Statistics Norway

## Usage example

1. Run `from datadoc import main; main("./path/to/your/dataset")` to run Datadoc on a dataset of your choosing.
1. Complete metadata as you desire
1. Click `Lagre` to save a metadata document together with your dataset

### If the datadoc package is not installed

1. Clone this repo to your Jupyter instance (or local machine)
1. Open the `DataDoc.ipynb` Notebook and run the cell to see the example dataset

![DataDoc in use](./doc/change-language-example.gif)

## Contributing

### Dependency Management

Poetry is used for dependency management.

To install all required dependencies in a virtual environment run `poetry install`. To add a new dependency to the project run `poetry add <package name>`.

### Run project locally in Jupyter

To run the project locally in Jupyter run:

```bash
poetry shell
ipython kernel install --user --name="datadoc"
jupyter notebook
```

A Jupyter instance should open in your browser. Once there, open the `*.ipynb` file. Before running it, select the correct interpreter via `Kernel > Change Kernel > datadoc`.

### Run tests

1. Install dev dependencies (see [Dependency Management](#dependency-management))
1. Run `poetry shell` to open a shell in the Virtual Environment for the project
1. Run `pytest` in the root of the project

