data-analytics

Welcome to the Tidepool Data Analytics Repository. This is the home for the code we use to download, clean, and analyze data for the Tidepool Big Data Donation project.

About our use of Python & R

We use the Anaconda distribution of Python & R. You are welcome to install the full Anaconda installer, but will only need Miniconda to get started.

Getting started

Project Setup

1. Install Miniconda for your platform.
2. In a terminal, navigate to the data-analytics directory where the environment.yml is located.
3. Run conda env create. This will download all of the package dependencies and install them in a virtual environment named tidepool-analytics. PLEASE NOTE: this may take close to 30 minutes to complete.

To list the Virtual Environments

Run conda env list

To use the Virtual Environment

In Bash run source activate tidepool-analytics, or in the Anaconda Prompt run conda activate tidepool-analytics to start the environment.

Run deactivate to stop the environment.

Testing

This project uses the testing framework named pyTest. https://docs.pytest.org/en/latest/

After following the project setup instructions, including creating and activating the virtual environment, you can simply run your tests within Bash

# Run tests via  
pytest 

Running Tests with Test Coverage

This project uses pytest-cov (https://pytest-cov.readthedocs.io/en/latest/) to run test and produce code test coverage.

To execute a basic test coverage report, run the following from within the virtual environment created during project setup . This will give the output directly in the Terminal.

# Run tests via  
pytest --cov 

To execute a detailed test coverage report, run the following command from within the virtual environment created during the project setup. This will create an htmlcov directory containing an index.html page with coverage details.

# Run tests via  
pytest --cov --cov-report html