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veranda is a place for IO related classes and operations dealing with vector and raster data.

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veranda

Build Status Coverage Status PyPi Package RTD License: MIT

Description

veranda stands for "vector and raster data access" and is a place for IO related classes and operations dealing with raster and vector data. Besides bridging the gap between rigid and complex packages like GDAL to increase user-friendliness and flexibility (similar to rasterio) it defines common ground to unite the world of raster and vector data and harmonise the entry point to access different data formats or multiple files.

veranda consist of two modules raster and vector each containing the submodules native and mosaic. native contains several classes for interacting with one file/data format, e.g. GeoTIFF or NetCDF. On the other hand, the mosaic module offers a datacube-like interface to work with multiple, structured files, which can be distributed based on a mosaic/grid in space or along a stack dimension, e.g. time, atmospheric layers, etc.

For further details we recommend to look at veranda's documentation or tests.

Installation

The package can be either installed via pip or if you want to contribute, we recommend to install it as a conda environment.

pip

To install veranda via pip in your own environment, use:

pip install veranda

ATTENTION: GDAL needs more OS support and has more dependencies then other packages and can therefore not be installed solely via pip. Please have a look at https://pypi.org/project/GDAL/ what requirements are needed. Thus, for a fresh setup, an existing environment with working a GDAL installation is expected.

conda

The packages also comes along with one conda environment conda_environment.yml. This is especially recommended if you want to contribute to the project. The following script will install miniconda and setup the environment on a UNIX like system. Miniconda will be installed into $HOME/miniconda.

wget http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
bash miniconda.sh -b -p $HOME/miniconda
export PATH="$HOME/miniconda/bin:$PATH"
conda env create -f conda_environment.yml
source activate veranda

This script adds $HOME/miniconda/bin temporarily to the PATH to do this permanently add export PATH="$HOME/miniconda/bin:$PATH" to your .bashrc or .zshrc.

For Windows, use the following setup:

  • Download the latest miniconda 3 installer for Windows
  • Click on .exe file and complete the installation.
  • Add the folder condabin folder to your environment variable PATH. You can find the condabin folder usually under: C:\Users\username\AppData\Local\Continuum\miniconda3\condabin
  • Finally, you can set up the conda environment via:
    conda env create -f conda_environment.yml
    source activate veranda
    

After that you should be able to run

python setup.py test

to run the test suite.

Contribution

We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes. If you want to contribute please follow these steps:

  • Fork the veranda repository to your account
  • Clone the veranda repository
  • Make a new feature branch from the veranda master branch
  • Add your feature
  • Please include tests for your contributions in one of the test directories. We use py.test so a simple function called test_my_feature is enough
  • Submit a pull request to our master branch

Outlook

The next major release will contain significant support for vector data including IO for SHP and LASZ files. In addition the raster module will be extended to allow for accessing ZARR or HDF data for performant time series queries.

Citation

If you use this software in a publication then please cite it using the Zenodo DOI.

Note

This project has been set up using PyScaffold 3.2.2. For details and usage information on PyScaffold see https://pyscaffold.org/.

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veranda is a place for IO related classes and operations dealing with vector and raster data.

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