glm-py released! 🚀¶
We're pleased to announce the first public release of glm-py on pip!
glm-py 0.1.3 provides a Python interface to the General Lake Model (GLM) that
abstracts away the complexity of building and running simulations. It is now
easier than ever to use GLM for research, education, and software development.
In the first release of glm-py we've prioritised providing functionality for
the core components of modelling a water body with GLM, i.e., writing the
.nml file, preparing the model inputs, and running GLM. The nml module of
glm-py lets you configure your model parameters without ever needing to open
a .nml file. glm-py translates parameters defined in Python dictionaries to
the format expected by GLM. The benefits of this approach include: type hints
for explicitly declaring expected parameter types, removal of .nml syntax
errors, and raising helpful error messages to enforce parameter compliance
(coming soon!). The simulation module streamlines how you prepare and run
your simulation. glm-py can automatically create a directory of your input
files that matches the structure expected by GLM. Running the model is as
simple as calling glm_run() - no need to use the command line. These features
make running GLM less complex and more accessible.
In addition to the writing .nml files and running simulations, glm-py
provides tools to automate time consuming tasks and support the development of
web applications. For example, the dimensions module lets you easily
calculate the H and A parameters for common water body morphometries.
The creation of CSV inputs is also simiplified with the inflows and
outflows modules. Meanwhile, developers can integrate GLM into web frameworks
by leveraging classes in the glm_json and simulation modules. More useful
functionality will follow in future releases and we'd love to hear your input
on how we can expand this toolkit.
Looking ahead, the development of glm-py is planning to incorporate:
- Complete error checking of model parameters
- A calibration module
- Expanded functionality for AED
We encourage you to use glm-py and engage with the project on GitHub. Be sure to browse this documentation website for a complete guide on using the package.
Happy modelling!