Contributing¶

Welcome to the IHE WaterAccounting Report Tool (IHEWAdataanalysis) project. Here’s how we work.

Code of Conduct¶

First of all: the IHEWAdataanalysis project has a code of conduct. Please read the CODE_OF_CONDUCT.txt file, it’s important to all of us.

Rights¶

The GNU General Public License v3.0 license (see LICENSE.rst) applies to all contributions.

Issue Conventions¶

The IHEWAdataanalysis issue tracker is for actionable issues.

Questions about installation, distribution, and usage should be taken to the project’s wateraccounting.slack.com#issue. Opened issues which fall into one of these three categories may be perfunctorily closed.

Questions about development of IHEWAdataanalysis, brainstorming, requests for comment, and not-yet-actionable proposals are welcome in the project’s wateraccounting.slack.com#idea.

IHEWAdataanalysis is a relatively new project and highly active. We have bugs, both known and unknown.

Please search existing issues, open and closed, before creating a new one.

IHEWAdataanalysis employs Geospatial modules, so bug reports very often hinge on the following details:

Operating system type and version (Windows? Ubuntu 12.04? 14.04?)
The version and source of GDAL (UbuntuGIS? Homebrew?)

Dataset Objects¶

Our term for the kind of object that allows read and write access to raster data is dataset object. A dataset object might be an instance of DatasetReader or DatasetWriter. The canonical way to create a dataset object is by using the IHEWAdataanalysis.GIS.OpenAsArray() function.

This is analogous to Python’s use of file object.

Git Conventions¶

We use a variant of centralized workflow described in the Git Book. We have no 1.0 release for IHEWAdataanalysis yet and we are tagging and releasing from the master branch. Our post-1.0 workflow is to be decided.

Work on features in a new branch of the mapbox/IHEWAdataanalysis repo or in a branch on a fork. Create a GitHub pull request when the changes are ready for review. We recommend creating a pull request as early as possible to give other developers a heads up and to provide an opportunity for valuable early feedback.

Code Conventions¶

IHEWAdataanalysis supports Python 2 and Python 3 in the same code base, which is aided by an internal compatibility module named compat.py. It functions similarly to the more widely known six but we only use a small portion of the features so it eliminates a dependency.

We strongly prefer code adhering to PEP8.

Tests are mandatory for new features. We use pytest.

We aspire to 100% coverage for Python modules Coveralls.

Development Environment¶

Developing IHEWAdataanalysis requires Python 2.7 or any final release after and including 3.4. We prefer developing with the most recent version of Python but recognize this is not possible for all contributors. See the Windows install instructions in the readme for more information about building on Windows.

Initial Setup¶

First, clone IHEWAdataanalysis’s git repo:

$ git clone https://github.com/wateraccounting/ihewadataanalysis.git

Development should occur within a virtual environment to better isolate development work from custom environments.

In some cases installing a library with an accompanying executable inside a virtual environment causes the shell to initially look outside the environment for the executable. If this occurs try deactivating and reactivating the environment.

Installing GDAL¶

The GDAL library and its headers are required to build IHEWAdataanalysis. We do not have currently have guidance for any platforms other than Linux and OS X.

On Linux, GDAL and its headers should be available through your distro’s package manager. For Ubuntu the commands are:

$ sudo add-apt-repository ppa:ubuntugis/ppa
$ sudo apt-get update
$ sudo apt-get install gdal-bin libgdal-dev

On OS X, Homebrew is a reliable way to get GDAL.

$ brew install gdal

Python build requirements¶

Provision a virtualenv with IHEWAdataanalysis’s build requirements. IHEWAdataanalysis’s setup.py script will not run unless Cython and Numpy are installed, so do this first from the IHEWAdataanalysis repo directory.

Linux users may need to install some additional Numpy dependencies:

$ sudo apt-get install libatlas-dev libatlas-base-dev gfortran

then:

$ pip install -U pip
$ pip install -r requirements-dev.txt

Installing IHEWAdataanalysis¶

Installing IHEWAdataanalysis in editable mode while developing is very convenient but only affects the Python files.

$ python setup.py install

Uninstalling IHEWAdataanalysis¶

$ pip uninstall IHEWAdataanalysis

Running the tests¶

IHEWAdataanalysis’s tests live in python setup.py test and generally match the main package layout.

To run the entire suite and the code coverage report:

$ python setup.py test