oura-api-version2-example.ipynb
An example of how the Oura V2 data looks like
Some examples of the types of data that is now available through https://oura.openhumans.org.
The V1 integration remains unchanged and the data is stored in oura-data.json as it was before. Additionally there are now a number of new files with data as received from the V2 API, all prefixed oura-v2-.
Updating to V2 API: If you've been using the Oura integration before (authorized Oura before December 1st, 2022) you might have to remove the Oura authorization and reconnect it, in order to authorize the now larger scope of data that can be imported. To do so head to https://oura.openhumans.org, log-in with your Open Humans account and then select disconnect oura account on the dashboard and reconnect it afterwards.
The daily activity data is similar to the activity data provided by the original V1 API. The file contains a long list of daily activity recordings. Below is a printout of a single data point (the last in your file).
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"class_5_min": "11111111111112111111211111111111111111111111111111122221122234333444443223232222222332323233332232333333223322223233",
"score": 95,
"active_calories": 250,
"average_met_minutes": 1.5625,
"contributors": {
"meet_daily_targets": 95,
"move_every_hour": 100,
"recovery_time": 100,
"stay_active": 77,
"training_frequency": 100,
"training_volume": 100
},
"equivalent_walking_distance": 4257,
"high_activity_met_minutes": 0,
"high_activity_time": 0,
"inactivity_alerts": 0,
"low_activity_met_minutes": 47,
"low_activity_time": 5700,
"medium_activity_met_minutes": 157,
"medium_activity_time": 2160,
"met": {
"interval": 60.0,
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"timestamp": "2022-12-01T04:00:00.000+00:00"
},
"meters_to_target": 6100,
"non_wear_time": 0,
"resting_time": 17400,
"sedentary_met_minutes": 8,
"sedentary_time": 9600,
"steps": 4875,
"target_calories": 550,
"target_meters": 11000,
"total_calories": 2074,
"day": "2022-12-01",
"timestamp": "2022-12-01T04:00:00+00:00"
}
Similarly, the daily readiness records are quite similar to the V1 API records, but now also outline how the different metrics record to the daily score.
The daily sleep record is a lot briefer though, as a lot of the data has been outsourced into a different file, called oura-v2-sleep.json.
daily readiness:
{
"contributors": {
"activity_balance": 87,
"body_temperature": 100,
"hrv_balance": 88,
"previous_day_activity": 100,
"previous_night": 73,
"recovery_index": 100,
"resting_heart_rate": 100,
"sleep_balance": 74
},
"day": "2022-12-01",
"score": 86,
"temperature_deviation": -0.1,
"temperature_trend_deviation": 0.06,
"timestamp": "2022-12-01T00:00:00+00:00"
}
daily sleep:
{
"contributors": {
"deep_sleep": 94,
"efficiency": 79,
"latency": 67,
"rem_sleep": 96,
"restfulness": 77,
"timing": 47,
"total_sleep": 72
},
"day": "2022-12-01",
"score": 75,
"timestamp": "2022-12-01T00:00:00+00:00"
}
The detailed sleep records provide deeper insights, including all nightly heart rate recordings, the movement in 30 second intervals, and the time spent in different sleep phases.
heart rate:
{
"average_breath": 14.5,
"average_heart_rate": 61.125,
"average_hrv": 48,
"awake_time": 5070,
"bedtime_end": "2022-12-01T08:51:00+00:00",
"bedtime_start": "2022-12-01T00:43:00+00:00",
"day": "2022-12-01",
"deep_sleep_duration": 4770,
"efficiency": 83,
"heart_rate": {
"interval": 300.0,
"items": [
56.0,
55.0,
54.0,
54.0,
54.0,
null,
null,
null,
62.0,
53.0,
54.0,
55.0,
59.0,
58.0,
60.0,
59.0,
60.0,
59.0,
59.0,
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60.0,
63.0,
67.0,
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],
"timestamp": "2022-12-01T00:43:00.000+00:00"
},
"hrv": {
"interval": 300.0,
"items": [
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null,
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],
"timestamp": "2022-12-01T00:43:00.000+00:00"
},
"latency": 180,
"light_sleep_duration": 12510,
"low_battery_alert": false,
"lowest_heart_rate": 53,
"movement_30_sec": "3211112222111111111111111111111113233322222122122122111111344443222122111211122122111111112221321111111111111111111111121111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111132121111111111111111111111111111121111111111111122111111322111111111111111111111111111111111111111112111111111111111111111111111111111111211321111111111111111111111111111111111111111111111111111111111111111111111111111111111111111121121111111111111111111112111111111111111111111111111111111111111111111111111113211111111111111221312111111111111111111111111111111111111111111111111111111131111122111111111111111113111111111111111111111111111111111111111111111111111111121111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111211111111112111111111111111111112111111111111111113111111111111111111211111111111111121221111111111111111133222222333333332212211121212222122222222333212322322212",
"period": 1,
"readiness": {
"contributors": {
"activity_balance": 87,
"body_temperature": 100,
"hrv_balance": 88,
"previous_day_activity": 100,
"previous_night": 78,
"recovery_index": 100,
"resting_heart_rate": 100,
"sleep_balance": 74
},
"score": 86,
"temperature_deviation": -0.1,
"temperature_trend_deviation": 0.06
},
"readiness_score_delta": 0,
"rem_sleep_duration": 6930,
"restless_periods": 83,
"sleep_phase_5_min": "42244244412222111111113332442112222422223111123332222242222142222332223333333333333223222224444444",
"sleep_score_delta": 0,
"time_in_bed": 29280,
"total_sleep_duration": 24210,
"type": "long_sleep"
}
The oura-v2-heartrate.json file is another new addition and includes awake heart rate data as well:
detailed sleep:
[
{
"bpm": 90,
"source": "awake",
"timestamp": "2022-12-01T10:38:25+00:00"
},
{
"bpm": 81,
"source": "awake",
"timestamp": "2022-12-01T11:05:15+00:00"
},
{
"bpm": 73,
"source": "awake",
"timestamp": "2022-12-01T11:05:52+00:00"
},
{
"bpm": 90,
"source": "awake",
"timestamp": "2022-12-01T11:06:03+00:00"
},
{
"bpm": 60,
"source": "awake",
"timestamp": "2022-12-01T13:27:06+00:00"
},
{
"bpm": 65,
"source": "awake",
"timestamp": "2022-12-01T13:27:28+00:00"
},
{
"bpm": 60,
"source": "awake",
"timestamp": "2022-12-01T13:27:29+00:00"
},
{
"bpm": 102,
"source": "awake",
"timestamp": "2022-12-01T13:37:48+00:00"
},
{
"bpm": 101,
"source": "awake",
"timestamp": "2022-12-01T13:37:49+00:00"
},
{
"bpm": 92,
"source": "awake",
"timestamp": "2022-12-01T13:37:52+00:00"
}
]
The API now also provides access to the "tags" that you can use within the Oura mobile app to annotate how given days were, see the example below:
tags:
[
{
"day": "2022-07-20",
"text": "Covid positive in RAT just now",
"timestamp": "2022-07-20T11:36:00+02:00",
"tags": []
},
{
"day": "2022-10-09",
"text": null,
"timestamp": "2022-10-09T19:31:00+07:00",
"tags": [
"tag_generic_airplane"
]
},
{
"day": "2022-10-10",
"text": null,
"timestamp": "2022-10-10T09:01:00+07:00",
"tags": [
"tag_generic_tired",
"tag_generic_jetlag",
"tag_generic_hotel"
]
},
{
"day": "2022-10-21",
"text": null,
"timestamp": "2022-10-21T09:34:00+02:00",
"tags": [
"tag_generic_jetlag"
]
}
]
workouts:
[
{
"activity": "walking",
"calories": 52.816,
"day": "2022-10-31",
"distance": null,
"end_datetime": "2022-10-31T18:54:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-10-31T18:38:00+00:00"
},
{
"activity": "walking",
"calories": null,
"day": "2022-11-01",
"distance": null,
"end_datetime": "2022-11-01T15:58:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-01T14:42:00+00:00"
},
{
"activity": "walking",
"calories": 145.244,
"day": "2022-11-01",
"distance": null,
"end_datetime": "2022-11-01T18:24:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-01T17:40:00+00:00"
},
{
"activity": "walking",
"calories": 184.856,
"day": "2022-11-11",
"distance": null,
"end_datetime": "2022-11-11T18:50:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-11T17:54:00+00:00"
},
{
"activity": "walking",
"calories": 115.53500000000001,
"day": "2022-11-11",
"distance": null,
"end_datetime": "2022-11-11T20:44:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-11T20:09:00+00:00"
}
]
Some examples of the types of data that is now available through https://oura.openhumans.org.
The V1 integration remains unchanged and the data is stored in oura-data.json as it was before. Additionally there are now a number of new files with data as received from the V2 API, all prefixed oura-v2-.
Updating to V2 API: If you've been using the Oura integration before (authorized Oura before December 1st, 2022) you might have to remove the Oura authorization and reconnect it, in order to authorize the now larger scope of data that can be imported. To do so head to https://oura.openhumans.org, log-in with your Open Humans account and then select disconnect oura account on the dashboard and reconnect it afterwards.
The daily activity data is similar to the activity data provided by the original V1 API. The file contains a long list of daily activity recordings. Below is a printout of a single data point (the last in your file).
from ohapi import api
import os
import requests
import tempfile
user_details = api.exchange_oauth2_member(os.environ.get('OH_ACCESS_TOKEN'))
for i in user_details['data']:
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-daily_activity.json':
break
import json
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-1],indent=2))
{
"class_5_min": "11111111111112111111211111111111111111111111111111122221122234333444443223232222222332323233332232333333223322223233",
"score": 95,
"active_calories": 250,
"average_met_minutes": 1.5625,
"contributors": {
"meet_daily_targets": 95,
"move_every_hour": 100,
"recovery_time": 100,
"stay_active": 77,
"training_frequency": 100,
"training_volume": 100
},
"equivalent_walking_distance": 4257,
"high_activity_met_minutes": 0,
"high_activity_time": 0,
"inactivity_alerts": 0,
"low_activity_met_minutes": 47,
"low_activity_time": 5700,
"medium_activity_met_minutes": 157,
"medium_activity_time": 2160,
"met": {
"interval": 60.0,
"items": [
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"timestamp": "2022-12-01T04:00:00.000+00:00"
},
"meters_to_target": 6100,
"non_wear_time": 0,
"resting_time": 17400,
"sedentary_met_minutes": 8,
"sedentary_time": 9600,
"steps": 4875,
"target_calories": 550,
"target_meters": 11000,
"total_calories": 2074,
"day": "2022-12-01",
"timestamp": "2022-12-01T04:00:00+00:00"
}
Similarly, the daily readiness records are quite similar to the V1 API records, but now also outline how the different metrics record to the daily score.
The daily sleep record is a lot briefer though, as a lot of the data has been outsourced into a different file, called oura-v2-sleep.json.
for i in user_details['data']:
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-daily_readiness.json':
print('daily readiness:')
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-1],indent=2))
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-daily_sleep.json':
print('daily sleep:')
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-1],indent=2))
daily readiness:
{
"contributors": {
"activity_balance": 87,
"body_temperature": 100,
"hrv_balance": 88,
"previous_day_activity": 100,
"previous_night": 73,
"recovery_index": 100,
"resting_heart_rate": 100,
"sleep_balance": 74
},
"day": "2022-12-01",
"score": 86,
"temperature_deviation": -0.1,
"temperature_trend_deviation": 0.06,
"timestamp": "2022-12-01T00:00:00+00:00"
}
daily sleep:
{
"contributors": {
"deep_sleep": 94,
"efficiency": 79,
"latency": 67,
"rem_sleep": 96,
"restfulness": 77,
"timing": 47,
"total_sleep": 72
},
"day": "2022-12-01",
"score": 75,
"timestamp": "2022-12-01T00:00:00+00:00"
}
The detailed sleep records provide deeper insights, including all nightly heart rate recordings, the movement in 30 second intervals, and the time spent in different sleep phases.
for i in user_details['data']:
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-sleep.json':
print('heart rate:')
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-1],indent=2))
heart rate:
{
"average_breath": 14.5,
"average_heart_rate": 61.125,
"average_hrv": 48,
"awake_time": 5070,
"bedtime_end": "2022-12-01T08:51:00+00:00",
"bedtime_start": "2022-12-01T00:43:00+00:00",
"day": "2022-12-01",
"deep_sleep_duration": 4770,
"efficiency": 83,
"heart_rate": {
"interval": 300.0,
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"timestamp": "2022-12-01T00:43:00.000+00:00"
},
"hrv": {
"interval": 300.0,
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58.0,
41.0,
60.0,
57.0,
49.0,
55.0,
50.0,
47.0,
41.0,
48.0,
71.0
],
"timestamp": "2022-12-01T00:43:00.000+00:00"
},
"latency": 180,
"light_sleep_duration": 12510,
"low_battery_alert": false,
"lowest_heart_rate": 53,
"movement_30_sec": "3211112222111111111111111111111113233322222122122122111111344443222122111211122122111111112221321111111111111111111111121111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111132121111111111111111111111111111121111111111111122111111322111111111111111111111111111111111111111112111111111111111111111111111111111111211321111111111111111111111111111111111111111111111111111111111111111111111111111111111111111121121111111111111111111112111111111111111111111111111111111111111111111111111113211111111111111221312111111111111111111111111111111111111111111111111111111131111122111111111111111113111111111111111111111111111111111111111111111111111111121111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111211111111112111111111111111111112111111111111111113111111111111111111211111111111111121221111111111111111133222222333333332212211121212222122222222333212322322212",
"period": 1,
"readiness": {
"contributors": {
"activity_balance": 87,
"body_temperature": 100,
"hrv_balance": 88,
"previous_day_activity": 100,
"previous_night": 78,
"recovery_index": 100,
"resting_heart_rate": 100,
"sleep_balance": 74
},
"score": 86,
"temperature_deviation": -0.1,
"temperature_trend_deviation": 0.06
},
"readiness_score_delta": 0,
"rem_sleep_duration": 6930,
"restless_periods": 83,
"sleep_phase_5_min": "42244244412222111111113332442112222422223111123332222242222142222332223333333333333223222224444444",
"sleep_score_delta": 0,
"time_in_bed": 29280,
"total_sleep_duration": 24210,
"type": "long_sleep"
}
The oura-v2-heartrate.json file is another new addition and includes awake heart rate data as well:
for i in user_details['data']:
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-heartrate.json':
print('detailed sleep:')
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-10:],indent=2))
detailed sleep:
[
{
"bpm": 90,
"source": "awake",
"timestamp": "2022-12-01T10:38:25+00:00"
},
{
"bpm": 81,
"source": "awake",
"timestamp": "2022-12-01T11:05:15+00:00"
},
{
"bpm": 73,
"source": "awake",
"timestamp": "2022-12-01T11:05:52+00:00"
},
{
"bpm": 90,
"source": "awake",
"timestamp": "2022-12-01T11:06:03+00:00"
},
{
"bpm": 60,
"source": "awake",
"timestamp": "2022-12-01T13:27:06+00:00"
},
{
"bpm": 65,
"source": "awake",
"timestamp": "2022-12-01T13:27:28+00:00"
},
{
"bpm": 60,
"source": "awake",
"timestamp": "2022-12-01T13:27:29+00:00"
},
{
"bpm": 102,
"source": "awake",
"timestamp": "2022-12-01T13:37:48+00:00"
},
{
"bpm": 101,
"source": "awake",
"timestamp": "2022-12-01T13:37:49+00:00"
},
{
"bpm": 92,
"source": "awake",
"timestamp": "2022-12-01T13:37:52+00:00"
}
]
The API now also provides access to the "tags" that you can use within the Oura mobile app to annotate how given days were, see the example below:
for i in user_details['data']:
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-tag.json':
print('tags:')
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-4:],indent=2))
tags:
[
{
"day": "2022-07-20",
"text": "Covid positive in RAT just now",
"timestamp": "2022-07-20T11:36:00+02:00",
"tags": []
},
{
"day": "2022-10-09",
"text": null,
"timestamp": "2022-10-09T19:31:00+07:00",
"tags": [
"tag_generic_airplane"
]
},
{
"day": "2022-10-10",
"text": null,
"timestamp": "2022-10-10T09:01:00+07:00",
"tags": [
"tag_generic_tired",
"tag_generic_jetlag",
"tag_generic_hotel"
]
},
{
"day": "2022-10-21",
"text": null,
"timestamp": "2022-10-21T09:34:00+02:00",
"tags": [
"tag_generic_jetlag"
]
}
]
for i in user_details['data']:
if i['source'] == 'direct-sharing-184' and i['basename'] == 'oura-v2-workout.json':
print('workouts:')
oura = json.loads(requests.get(i['download_url']).content)
print(json.dumps(oura[-5:],indent=2))
workouts:
[
{
"activity": "walking",
"calories": 52.816,
"day": "2022-10-31",
"distance": null,
"end_datetime": "2022-10-31T18:54:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-10-31T18:38:00+00:00"
},
{
"activity": "walking",
"calories": null,
"day": "2022-11-01",
"distance": null,
"end_datetime": "2022-11-01T15:58:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-01T14:42:00+00:00"
},
{
"activity": "walking",
"calories": 145.244,
"day": "2022-11-01",
"distance": null,
"end_datetime": "2022-11-01T18:24:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-01T17:40:00+00:00"
},
{
"activity": "walking",
"calories": 184.856,
"day": "2022-11-11",
"distance": null,
"end_datetime": "2022-11-11T18:50:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-11T17:54:00+00:00"
},
{
"activity": "walking",
"calories": 115.53500000000001,
"day": "2022-11-11",
"distance": null,
"end_datetime": "2022-11-11T20:44:00+00:00",
"intensity": "moderate",
"label": null,
"source": "confirmed",
"start_datetime": "2022-11-11T20:09:00+00:00"
}
]