Wearipedia provides a one-stop shop for accessing and extracting data from wearable devices.

Data from these devices may be used for:

• Clinical research
• Personal health monitoring
• Health coaching
• Health product development
• Wearable device development

Wearipedia is developed and maintained by the Snyder Lab at the Stanford University.

The data from these devices is accessed using an easy-to-use API. In order to use this API, you will need to import the wearipedia module:

import wearipedia

Once you have imported the wearipedia module, accessing data from any wearable device is as easy as:

device = wearipedia.get_device("whoop/whoop_4")
device.authenticate({"email": "[email protected]", "password": "foobar"})

# data is a DataFrame
data = device.get_data("metrics")

If you don't have access to your device, or need to demo data from a device without revealing your sensitive data or getting a device yourself, you can generate synthetic data, as shown below:

device = wearipedia.get_device("whoop/whoop_4")

# data is an automatically generated DataFrame
data = device.get_data("metrics")

and you're done!

The easiest way to install wearipedia is to use pip:

pip install wearipedia

We currently support Python 3.7, 3.8, and 3.9.

Wearipedia supports the following devices:

For more information on how to use wearipedia, please refer to our documentation.

A paper is in progress!

This project is currently in alpha. This means that test coverage is limited, and the codebase is still really a prototype. Moreover, the API is unstable, as we are still rapidly iterating on it. Expect for most things to work, but also small bugs, rough edges, and sparse documentation.

As Wearipedia is still at an early stage, we are not yet accepting contributions from the broader community. Once Wearipedia reaches its first stable release, we will begin accepting contributions.

Wearipedia is released under the MIT license.

This project was generated with python-package-template