TEEHR (pronounced "tier") is a python tool set for loading, storing, processing and visualizing hydrologic data, particularly National Water Model data, for the purpose of exploring and evaluating the datasets to assess their skill and performance.
NOTE: THIS PROJECT IS UNDER DEVELOPMENT - EXPECT TO FIND BROKEN AND INCOMPLETE CODE.
We do not currently push TEEHR to PyPI, so the easiest way to install it is directly from GitHub.
If using pip
to install TEEHR, we recommend installing TEEHR in a virtual environment.
The code below should create a new virtual environment and install TEEHR in it.
# Create directory for your code and create a new virtual environment.
mkdir teehr_examples
cd teehr_examples
python3 -m venv .venv
source .venv/bin/activate
# Install using pip.
# Starting with version 0.4.1 TEEHR is available in PyPI
pip install teehr
# Download the required JAR files for Spark to interact with AWS S3.
python -m teehr.utils.install_spark_jars
Use Docker
$ docker build -t teehr:v0.4.3 .
$ docker run -it --rm --volume $HOME:$HOME -p 8888:8888 teehr:v0.4.3 jupyter lab --ip 0.0.0.0 $HOME
For examples of how to use TEEHR, see the examples. We will maintain a basic set of example Jupyter Notebooks demonstrating how to use the TEEHR tools.
In May of 2023 we put on a workshop at the CIROH 1st Annual Training and Developers Conference. The workshop materials and presentation are available in the workshop GitHub repository: teehr-may-2023-workshop. This workshop was based on version 0.1.0.
The TEEHR project follows semantic versioning as described here: https://semver.org/. Note, per the specification, "Major version zero (0.y.z) is for initial development. Anything MAY change at any time. The public API SHOULD NOT be considered stable.". We are solidly in "major version zero" territory, and trying to move fast, so expect breaking changes often.