Development¶
When applying HydPy, you can download it from the hydpy package available on the Python package index and install it with little effort. There is a considerable amount of Python tools freely available, being of great help when trying to achieve more complex tasks like parameter calibration or regionalisation. Cherry picking from different Python packages can be a substantial time-saving. Very often it is not necessary to write a “real” Python program for the task at hand. Instead, writing a simple script utilising functionalities of different packages in the correct order often gets the job done.
There is also nothing stopping you from modifying the downloaded Python files in your favour. You are free to modify existing models, implement new ones,or change the framework’s structure in a manner that meets your personal goals and preferences.
However, if you intend to contribute to the further development of HydPy, you must abandon some parts of freedom and ease of use Python offers. First, you must become acquainted with the collaborative development of the hydpy repository, primarily taking place on GitHub. Second, you need to follow some guidelines on the development of HydPy. The Python code contributed by different developers should be as consistent as possible. Otherwise, there would be a risk of the code base becoming opaque (or even faulty), impeding future extensions of HydPy.
The following sections try to define a strategy allowing to develop HydPy as an open source project while maintaining sufficiently high quality for scientific and engineering applications. The hydrological modelling community has not made much progress in this field yet, which is why we adopted many concepts from non-hydrological open source projects like pandas. Ideas and discussions on improving the outlined strategy are welcome!