oura-ring 0.2.0

Tools for acquiring and analyzing Oura API data.

Oura Ring for Python

Tools for acquiring and analyzing Oura API data.

Oura is a wearable ring for monitoring sleep, activity, and workouts.

Contents

• Installation
• Getting Started
• API Requests
  • Get Personal Info
  • Get Daily Sleep
  • Get Daily Activity
  • Get Daily Readiness
  • Get Heart Rate
  • Get Sleep Periods
  • Get Sessions
  • Get Tags
  • Get Workouts
• Usage With DataFrame

Installation

The oura_ring module can be installed via pip:

pip install oura-ring

Getting Started

In order to use the Oura client, you must first generate a personal_access_token for your Oura account.

It is best practice to store this value in a .env file:

# Oura credentials
PERSONAL_ACCESS_TOKEN="<PERSONAL_ACCESS_TOKEN>"

You can use python-dotenv to load the enviroment variables for use in code:

import os
from dotenv import load_dotenv

load_dotenv()

pat = os.getenv("PERSONAL_ACCESS_TOKEN") or ""

Once the environment variables are loaded, an OuraClient object can be created:

# Using a traditional constructor and destructor
import oura_ring as ou

client = ou.OuraClient(pat)

...

del client

# Using a context manager that destructs automatically
with ou.OuraClient(pat) as client:
    ...

API Requests

There are nine different API requests that OuraClient can make. Full Oura API v2 documentation can be found on Oura's website.

Get Personal Info

Method: get_personal_info()

Payload: None

Example Response:

{
    "age": 31,
    "weight": 74.8,
    "height": 1.8,
    "biological_sex": "male",
    "email": "[e-mail]"
}

Get Daily Sleep

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "contributors": {
            "deep_sleep": 57,
            "efficiency": 98,
            "latency": 81,
            "rem_sleep": 20,
            "restfulness": 54,
            "timing": 84,
            "total_sleep": 60
        },
        "day": "2022-07-14",
        "score": 63,
        "timestamp": "2022-07-14T00:00:00+00:00"
    },
    ...
]

Get Daily Activity

Method: get_daily_activity(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "class_5_min": "<long sequence of 0|1|2|3|4|5>",
        "score": 82,
        "active_calories": 1222,
        "average_met_minutes": 1.90625,
        "contributors": {
            "meet_daily_targets": 43,
            "move_every_hour": 100,
            "recovery_time": 100,
            "stay_active": 98,
            "training_frequency": 71,
            "training_volume": 98
        },
        "equivalent_walking_distance": 20122,
        "high_activity_met_minutes": 444,
        "high_activity_time": 3000,
        "inactivity_alerts": 0,
        "low_activity_met_minutes": 117,
        "low_activity_time": 10020,
        "medium_activity_met_minutes": 391,
        "medium_activity_time": 6060,
        "met": {
            "interval": 60,
            "items": [
                0.1,
                ...
            ],
            "timestamp": "2021-11-26T04:00:00.000-08:00"
        },
        "meters_to_target": -16200,
        "non_wear_time": 27480,
        "resting_time": 18840,
        "sedentary_met_minutes": 10,
        "sedentary_time": 21000,
        "steps": 18430,
        "target_calories": 350,
        "target_meters": 7000,
        "total_calories": 3446,
        "day": "2021-11-26",
        "timestamp": "2021-11-26T04:00:00-08:00"
    },
    ...
]

Get Daily Readiness

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "contributors": {
            "activity_balance": 56,
            "body_temperature": 98,
            "hrv_balance": 75,
            "previous_day_activity": null,
            "previous_night": 35,
            "recovery_index": 47,
            "resting_heart_rate": 94,
            "sleep_balance": 73
        },
        "day": "2021-10-27",
        "score": 66,
        "temperature_deviation": -0.2,
        "temperature_trend_deviation": 0.1,
        "timestamp": "2021-10-27T00:00:00+00:00"
    },
    ...
]

Get Heart Rate

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "bpm": 60,
        "source": "sleep",
        "timestamp": "2021-01-01T01:02:03+00:00"
    },
    ...
]

Get Sleep Periods

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "average_breath": 12.625,
        "average_heart_rate": 4.25,
        "average_hrv": 117,
        "awake_time": 4800,
        "bedtime_end": "2022-07-12T09:25:14-07:00",
        "bedtime_start": "2022-07-12T01:05:14-07:00",
        "day": "2022-07-12",
        "deep_sleep_duration": 4170,
        "efficiency": 84,
        "heart_rate": {
            "interval": 300,
            "items": [
                null,
                50,
                46,
                ...
            ],
            "timestamp": "2022-07-12T01:05:14.000-07:00"
        },
        "hrv": {
            "interval": 300,
            "items": [
                null,
                -102,
                -122,
                ...
            ],
            "timestamp": "2022-07-12T01:05:14.000-07:00"
        },
        "latency": 540,
        "light_sleep_duration": 18750,
        "low_battery_alert": false,
        "lowest_heart_rate": 48,
        "movement_30_sec": "<long sequence of 1|2|3>",
        "period": 0,
        "readiness_score_delta": 0,
        "rem_sleep_duration": 2280,
        "restless_periods": 415,
        "sleep_phase_5_min": "<long sequence of 1|2|3|4>",
        "sleep_score_delta": 0,
        "time_in_bed": 30000,
        "total_sleep_duration": null,
        "type": "long_sleep"
    },
    ...
]

Get Sessions

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "day": "2021-11-12",
        "start_datetime": "2021-11-12T12:32:09-08:00",
        "end_datetime": "2021-11-12T12:40:49-08:00",
        "type": "rest",
        "heart_rate": null,
        "heart_rate_variability": null,
        "mood": null,
        "motion_count": {
            "interval": 5,
            "items": [
                0
            ],
            "timestamp": "2021-11-12T12:32:09.000-08:00"
        }
    },
    ...
]

Get Tags

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "day": "2021-01-01",
        "text": "Need coffee",
        "timestamp": "2021-01-01T01:02:03-08:00",
        "tags": [
            "tag_generic_nocaffeine"
        ]
    },
    ...
]

Get Workouts

Method: get_daily_sleep(start_date: str = <end_date - 1 day>, end_date: str = <today's date>)

Payload:

• start_date: The earliest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to one day before the end_date parameter.
• end_date: The latest date for which to get data. Expected in ISO 8601 format (YYYY-MM-DD). Defaults to today's date.

Example Response:

[
    {
        "activity": "cycling",
        "calories": 300,
        "day": "2021-01-01",
        "distance": 13500.5,
        "end_datetime": "2021-01-01T01:00:00.000000+00:00",
        "intensity": "moderate",
        "label": null,
        "source": "manual",
        "start_datetime": "2021-01-01T01:30:00.000000+00:00"
    },
    ...
]

Usage With DataFrame

Using Oura API data with a Pandas DataFrame is very straightforward:

>>> import pandas as pd

>>> sleep = client.get_daily_sleep()
>>> pd.json_normalize(sleep)

          day  score                  timestamp  contributors.deep_sleep  \
0  2022-09-01     76  2022-09-01T00:00:00+00:00                       99
1  2022-09-02     81  2022-09-02T00:00:00+00:00                      100

   contributors.efficiency  contributors.latency  contributors.rem_sleep  \
0                       90                    99                      79
1                       88                    75                      95

   contributors.restfulness  contributors.timing  contributors.total_sleep
0                        55                   15                        85
1                        56                   28                        96

[2 rows x 10 columns]

>>> readiness = client.get_daily_readiness()
>>> pd.json_normalize(readiness)

          day  score  temperature_deviation  temperature_trend_deviation  \
0  2022-09-01     87                  -0.09                         0.24
1  2022-09-02     91                  -0.03                         0.11

                   timestamp  contributors.activity_balance  \
0  2022-09-01T00:00:00+00:00                             80
1  2022-09-02T00:00:00+00:00                             86

   contributors.body_temperature  contributors.hrv_balance  \
0                            100                        84
1                            100                        85

  contributors.previous_day_activity  contributors.previous_night  \
0                               None                           75
1                               None                           88

   contributors.recovery_index  contributors.resting_heart_rate  \
0                          100                              100
1                           94                               98

   contributors.sleep_balance
0                          87
1                          93

[2 rows x 13 columns]