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Python library for extrating geospatial extent of files and directories with multiple data formats

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o2r-project/geoextent

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geoextent

Python package Build Status PyPI version Binder Project Status: Active – The project has reached a stable, usable state and is being actively developed. DOI SWH SWH

Python library for extracting geospatial extent of files and directories with multiple data formats. Read a notebook-based article about the library published at EarthCube 2021.

This project is developed as part of the DFG-funded research project Opening Reproducible Research (o2r, https://o2r.info).

Installation

System requirements

Python: 3.x

The package relies on common system libraries for reading geospatial datasets, such as GDAL and NetCDF. On Debian systems, the UbuntuGIS project offers easy installation of up to date versions of those libraries.

See the packages list in travis.yml for a full list of dependencies on Linux.

Install from PyPI

You must install a suitable version of pygdal manually first, see instructions and this related SO thread with different helpful answers. We use pygdal for better compatibility with virtual environments.

pip install pygdal=="`gdal-config --version`.*"
pip install geoextent

Source installation

git clone https://github.com/o2r-project/geoextent
cd geoextent
pip install -r requirements.txt

pip install -e .

Use

Run

geoextent --help

to see usage instructions.

Showcases

Binder

To run the showcase notebooks, install JupyterLab or the classic Jupyter Notebook and then start a local server as shown below. If your IDE has support for the Jupyter format, installing ipykernel might be enough. We recommend running the below commands in a virtual environment as described here. The notebook must be trusted and python-markdown extension must be installed so that variables within Markdown text can be shown.

cd showcase
pip install -r requirements.txt
pip install -r showcase/requirements.txt
pip install -e .

jupyter trust showcase/SG_01_Exploring_Research_Data_Repositories_with_geoextent.ipynb
jupyter lab

Then open the local Jupyter Notebook server using the displayed link and open the notebook (*.ipynb files) in the showcase/ directory. Consult the documentation on paired notebooks based on Jupytext before editing selected notebooks.

Supported data formats

  • GeoJSON (.geojson)
  • Tabular data (.csv)
  • Shapefile (.shp)
  • GeoTIFF (.geotiff, .tif)

Contribute

All help is welcome: asking questions, providing documentation, testing, or even development.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

See CONTRIBUTING.md for details.

How to cite

Nüst, Daniel; Garzón, Sebastian and Qamaz, Yousef. (2021, May 14). o2r-project/geoextent (Version v0.7.1). Zenodo. https://zenodo.org/record/4762205

See also the CITATION.cff and codemeta.json files in this repository, which can possibly be imported in the reference manager of your choice.

License

geoextent is licensed under MIT license, see file LICENSE.

Copyright (C) 2020 - o2r project.