Gordo
Building thousands of models with timeseries data to monitor systems.
Table of content
About
Gordo fulfills the role of inhaling config files and supplying components to the pipeline of:
- Fetching data
- Training model
- Serving model
Examples
See our example notebooks for how to develop with gordo
locally.
Install
pip install --upgrade gordo
Bleeding edge:
pip install git+https://github.com/equinor/gordo.git
Uninstall
pip uninstall gordo
Developer manual
This section will explain how to start development of Gordo.
How to prepare working environment
- install requirements
# create and activate virtualenv. Note: you should use python3.7 (project's tensorflow version is not compatible with python3.8)
# then:
pip install --upgrade pip
pip install --upgrade pip-tools
pip install -r requirements/full_requirements.txt
pip install -r requirements/test_requirements.txt
How to run tests locally
Tests system requirements
To run tests it's required for your system to has (note: commands might differ from your OS):
- running docker process;
- available 5432 port for postgres container.
Run tests
List of commands to run tests can be found here.
Running of tests takes some time, so it's faster to run tests in parallel:
# example
pytest tests/gordo/client/test_client.py --ignore benchmarks --cov-report= --no-cov -n auto -m 'not dockertest'
# or if you have multiple python versions and they're not resolved properly:
python3.7 -m pytest ...
How to run tests in debug mode
Note: this example is for Pycharm IDE to use breakpoints
in the code of the tests.
On the configuration setup for test running add to Additional arguments:
in pytest
section following string: --ignore benchmarks --cov-report= --no-cov