semvec/pypi-packages huggingface dataset:
bioma-modelling 0.0.1
Python library to streamline interaction with the BioMA APIs, providing a pythonic facade to data and service access.
License: MIT

# The BioMA services toolkit for Python Notebooks and beyond

You can get BioMA and code your own models in C# *or* you can use the online ready-made ones hosted by [AnaEE](https://anaee.eu) and [CREA](https://www.crea.gov.it/), needless to say, if you are not planning to re-invent the wheel, but you just need some quick simulation, the second option is the most straightpforard, as it removes the need for a local installation, i.e. you don't need to download, install, and configure any additional software.

## What does this do?


## Why should I use it?
Because it wraps the BioMA web APIs in a pythonic way, sparing you the hassle of writing a lot of network code.


# Setup
To use the online services, you will need an *API key*, which is free, but you'll have to register either [here](https://developer.anaee.eu) or [here](https://developer.progettoagridigit.it) to get one. 

Then you need to install *this* package into your local environment with:
```
pip install bioma-modelling
```

The BioMAtools package expects a *service key* to work, each BioMA cloud distribution allows you to register a personal key, currently public accessible instances are hosted by [AnaEE](https://developer.anaee.eu/api-details#api=biomaazuremodelexecutornetframework20200226025441) and [CREA](https://developer.progettoagridigit.it/api-details#api=model-apis).

By default, the package exptects you to store the key in a *environmental varliable* named `BIOMA_API_KEY`, however, you can hard code it into the `ModelClient` object instantiation and/or tell it to read it from a different environmental variable of your choice.

You can, of course, avoid defining an actual environmental variable by using tools such as [dotenv](https://pypi.org/project/python-dotenv/).

# Quickstart

The `ModelClient` client object allows you to communicate with the BioMA Cloud instance, to create it, just pass it the base address of your BioMA instance of choice.
```
from biomatools.clients import ModelClient

client = ModelClient('https://api.progettoagridigit.it/model/v1/')
```
The client allows you to interact with the BioMA cloud instance and to interactively build your model run request. See the attached notebooks for working examples.

## Run a model
Once you are happy with your model configuration, you can load it into the client like this:
```
client.add_model_run('test', model_run)
```
You can load as many as you like, as long as you assign them different labels, then you can run them all with the `run_all` method or one by one with the `run` method that expects the label of the model configuration you'd like to run.
```
result = client.run('test')
```
The returned object can easily be transformed into a data frame.
```
result.get_data_table('weather').to_df()
```
# Acknowledgements
This project is funded by the [Agro-Serv project](https://agroserv.eu/). The project received funding from the European Union under grant agreement No 101058020.