Metadata-Version: 2.1
Name: dsp-metadata-gui
Version: 1.0.1
Summary: Python GUI tool to collect metadata for DSP projects.
Home-page: https://github.com/dasch-swiss/dsp-metadata-gui
Author: Balduin Landolt
Author-email: balduin.landolt@dasch.swiss
License: GPLv3
Description: # DSP-METADATA-GUI Metadata Module
        
        The `dsp-metadata-gui` is a GUI application written in Python for collecting project specific metadata and turn it into RDF.
        
        As part of the `dsp-tools`, its aim is to enable researchers and project managers who deposit research data on the DSP (DaSCH Service Platform), to add metadata about the project and datasets to the DSP repository. By providing metadata, the project will be searchable on the platform, which is an integral part of the FAIR principles.
        
        The metadata follows the schema defined by the [dsp-ontologies](https://github.com/dasch-swiss/dsp-ontologies).
        
        
        
        ## Install and run
        
        The module provides a command line entry point to run the GUI. The only requirement is Python 3 and PIP installed and ready to use.
        
        The application has only been tested on Python 3.9, but it might work on older versions too.
        
        __Note:__ There have been issues with `conda` installations. If this is the case, consider using a virtual environment.
        
        
        ### Installation via pip
        
        To install the application, run:
        
        ```bash
        pip install dsp-metadata-gui
        ```
        
        Or respectively:
        
        ```shell
        pip3 install dsp-metadata-gui
        ```
        
        Afterwards, the program can be started by running the command `dsp-metadata` in your terminal of choice.
        
        
        ### Installation from source
        
        Clone this repo and run `make make-and-run`. If you don't use GNU Make, run the commands specified in the `Makefile` manually.
        
        This will package the application, install it to your python environment and run the application.
        
        
        
        ## Usage
        
        The Application is divided into two windows:
        
        1. The main window lets you organize a list of projects, for which you can collect metadata. Several actions can be performed with projects, e.g. editing or exporting the project.
        
        2. When editing a project, in the project window, the actual metadata can be added, modified and saved.
        
        To add a project, you will need the project short code, which is assigned to you by the DaSCH Client Service.  
        A project is always associated with a folder on your local machine. If any files should be included with the metadata import, these files must be within that folder.
        Once all metadata are added and valid, and the overall DRF graph of the metadata set validates against the ontology, the project can be exported for upload to the DSP.
        
        All data is locally stored in the file `~/DaSCH/config/repos.data`. for more detail, see [here](https://dasch-swiss.github.io/dsp-metadata-gui/list_view/#local-data-storage).
        
        
        
        ## Development
        
        ### Development Environment
        
        #### Pipenv
        
        Use `pipenv` for a seamless development experience.  
        In order to have both dependencies and dev-dependencies installed from the `Pipfile`, set up the virtual environment running
        ```
        pipenv instal --dev
        ```
        
        `pipenv` will manage dependencies as well as a virtual environment. To install packages, use
        ```
        pipenv install <package-name>
        ```
        
        To create `requirements.txt`, run 
        ```
        pipenv lock -r > requirements.txt
        ```
        
        To bring `setup.py` up to date, run
        ```
        pipenv run pipenv-setup sync
        ```
        
        #### GNU Make
        
        `GNU Make` is used to automatize most tasks.  
        Run `make help` for info on the available targets.
        
        __Note:__ All make targets - except `make run` - should be run from within the `pipenv` shell:  
        Either by running
        ```
        pipenv run make <target-name>
        ```
        or by opening a virtual pipenv shell by running
        ```
        pipenv shell
        make <target-name>
        ...
        exit
        ```
        
        
        ### Documentation
        
        The documentation is created using `mkdocs` and `mkdocstrings` with `markdown_include.include`. To create the documentation, make sure to install all of these, using pip.
        
        To serve the documentation locally, run `make doc`. To deploy the documentation to github pages, run `make deploy-doc`.
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9.0
Description-Content-Type: text/markdown
