Tools for acquiring and analyzing Whoop API data.
WHOOP is a wearable strap for monitoring sleep, activity, and workouts. Learn more about WHOOP at https://www.whoop.com.
WHOOP API documentation can be found at https://developer.whoop.com/api.
The whoop module can be installed via pip:
pip install whoop
In order to use the WHOOP client, you must have your WHOOP email and password.
It is best practice to store these values in a .env file:
# WHOOP credentials
USERNAME="<USERNAME>"
PASSWORD="<PASSWORD>"You can use python-dotenv to load the enviroment variables for use in code:
import os
from dotenv import load_dotenv
load_dotenv()
un = os.getenv("USERNAME") or ""
pw = os.getenv("PASSWORD") or ""Once the environment variables are loaded, a WhoopClient object can be created:
from whoop import WhoopClient
# Using a traditional constructor
client = WhoopClient(username, password)
...
# Using a context manager
with WhoopClient(username, password) as client:
...The WHOOP client will authenticate the client upon construction by default. This involves fetching an access token from the API. If you don't want this request to happen automatically, pass authenticate=False into the object constructor. In order to make other requests, you will need to manually call the authenticate() method so that the other requests have the proper authorization headers:
client = WhoopClient(
client_id, client_secret, refresh_token, authenticate=False
)
client.authenticate()
...There are ten different API requests that WhoopClient can make. Full WHOOP API documentation can be found on WHOOP's website.
Get the user's basic profile.
Method: get_profile()
Payload: None
Example Response:
{
"user_id": 10129,
"email": "jsmith123@whoop.com",
"first_name": "John",
"last_name": "Smith"
}Get the user's body measurements.
Method: get_body_measurement()
Payload: None
Example Response:
{
"height_meter": 1.8288,
"weight_kilogram": 90.7185,
"max_heart_rate": 200
}Get the cycle for the specified ID.
Method: get_cycle_by_id(cycle_id: str)
Payload:
cycle_id: ID of the cycle to retrieve. Passed into the request path.
Example Response:
{
"id": 93845,
"user_id": 10129,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"start": "2022-04-24T02:25:44.774Z",
"end": "2022-04-24T10:25:44.774Z",
"timezone_offset": "-05:00",
"score_state": "SCORED",
"score": {
"strain": 5.2951527,
"kilojoule": 8288.297,
"average_heart_rate": 68,
"max_heart_rate": 141
}
}Get all physiological cycles for a user. Results are sorted by start time in descending order.
Method: get_cycle_collection(start_date: str = None, end_date: str = <today's date>)
Payload:
startDate: The earliest date for which to get data, pulled from thestart_dateparameter. Returns cycles that occurred after or during (inclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to no start date.endDate: The latest date for which to get data, pulled from theend_dateparameter. Returns cycles that intersect this time or ended before (exclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to today's date.
Example Response:
[
{
"id": 93845,
"user_id": 10129,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"start": "2022-04-24T02:25:44.774Z",
"end": "2022-04-24T10:25:44.774Z",
"timezone_offset": "-05:00",
"score_state": "SCORED",
"score": {
"strain": 5.2951527,
"kilojoule": 8288.297,
"average_heart_rate": 68,
"max_heart_rate": 141
}
},
...
]Get the recovery for a cycle
Method: get_recovery_for_cycle(cycle_id: str)
Payload:
cycle_id: ID of the cycle to retrieve. Passed into the request path.
Example Response:
{
"cycle_id": 93845,
"sleep_id": 10235,
"user_id": 10129,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"score_state": "SCORED",
"score": {
"user_calibrating": False,
"recovery_score": 44,
"resting_heart_rate": 64,
"hrv_rmssd_milli": 31.813562,
"spo2_percentage": 95.6875,
"skin_temp_celsius": 33.7
}
}Get all recoveries for a user. Results are sorted by start time of the related sleep in descending order.
Method: get_recovery_collection(start_date: str = None, end_date: str = <today's date>)
Payload:
startDate: The earliest date for which to get data, pulled from thestart_dateparameter. Returns cycles that occurred after or during (inclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to no start date.endDate: The latest date for which to get data, pulled from theend_dateparameter. Returns cycles that intersect this time or ended before (exclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to today's date.
Example Response:
[
{
"cycle_id": 93845,
"sleep_id": 10235,
"user_id": 10129,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"score_state": "SCORED",
"score": {
"user_calibrating": False,
"recovery_score": 44,
"resting_heart_rate": 64,
"hrv_rmssd_milli": 31.813562,
"spo2_percentage": 95.6875,
"skin_temp_celsius": 33.7
}
},
...
]Get the sleep for the specified ID.
Method: get_sleep_by_id(sleep_id: str)
Payload:
sleep: ID of the sleep to retrieve. Passed into the request path.
Example Response:
{
"id": 93845,
"user_id": 10129,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"start": "2022-04-24T02:25:44.774Z",
"end": "2022-04-24T10:25:44.774Z",
"timezone_offset": "-05:00",
"nap": False,
"score_state": "SCORED",
"score": {
"stage_summary": {},
"sleep_needed": {},
"respiratory_rate": 16.11328125,
"sleep_performance_percentage": 98,
"sleep_consistency_percentage": 90,
"sleep_efficiency_percentage": 91.69533848
}
}Get all sleeps for a user. Results are sorted by start time in descending order.
Method: get_sleep_collection(start_date: str = None, end_date: str = <today's date>)
Payload:
startDate: The earliest date for which to get data, pulled from thestart_dateparameter. Returns sleeps that occurred after or during (inclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to no start date.endDate: The latest date for which to get data, pulled from theend_dateparameter. Returns sleeps that intersect this time or ended before (exclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to today's date.
Example Response:
[
{
"id": 93845,
"user_id": 10129,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"start": "2022-04-24T02:25:44.774Z",
"end": "2022-04-24T10:25:44.774Z",
"timezone_offset": "-05:00",
"nap": False,
"score_state": "SCORED",
"score": {
"stage_summary": {},
"sleep_needed": {},
"respiratory_rate": 16.11328125,
"sleep_performance_percentage": 98,
"sleep_consistency_percentage": 90,
"sleep_efficiency_percentage": 91.69533848
}
},
...
]Get the workout for the specified ID.
Method: get_workout_by_id(workout_id: str)
Payload:
workout_id: ID of the workout to retrieve. Passed into the request path.
Example Response:
{
"id": 1043,
"user_id": 9012,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"start": "2022-04-24T02:25:44.774Z",
"end": "2022-04-24T10:25:44.774Z",
"timezone_offset": "-05:00",
"sport_id": 1,
"score_state": "SCORED",
"score": {
"strain": 8.2463,
"average_heart_rate": 123,
"max_heart_rate": 146,
"kilojoule": 1569.34033203125,
"percent_recorded": 100,
"distance_meter": 1772.77035916,
"altitude_gain_meter": 46.64384460449,
"altitude_change_meter": -0.781372010707855,
"zone_duration": {}
}
}Get all workouts for a user. Results are sorted by start time in descending order.
Method: get_workout_collection(start_date: str = None, end_date: str = <today's date>)
Payload:
startDate: The earliest date for which to get data, pulled from thestart_dateparameter. Returns workouts that occurred after or during (inclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to no start date.endDate: The latest date for which to get data, pulled from theend_dateparameter. Returns workouts that intersect this time or ended before (exclusive) this time. Expected in ISO 8601 format (YYYY-MM-DD HH:MM:SS). Defaults to today's date.
Example Response:
[
{
"id": 1043,
"user_id": 9012,
"created_at": "2022-04-24T11:25:44.774Z",
"updated_at": "2022-04-24T14:25:44.774Z",
"start": "2022-04-24T02:25:44.774Z",
"end": "2022-04-24T10:25:44.774Z",
"timezone_offset": "-05:00",
"sport_id": 1,
"score_state": "SCORED",
"score": {
"strain": 8.2463,
"average_heart_rate": 123,
"max_heart_rate": 146,
"kilojoule": 1569.34033203125,
"percent_recorded": 100,
"distance_meter": 1772.77035916,
"altitude_gain_meter": 46.64384460449,
"altitude_change_meter": -0.781372010707855,
"zone_duration": {}
}
},
...
]Using WHOOP API data with a Pandas DataFrame is very straightforward:
>>> import pandas as pd
>>> sleep = client.get_sleep_collection("2022-05-01", "2022-05-07")
>>> pd.json_normalize(sleep)
id user_id created_at updated_at \
0 430878903 995945 2022-05-07T14:56:28.389Z 2022-05-07T15:12:22.933Z
1 430378149 995945 2022-05-06T18:11:27.029Z 2022-05-06T18:11:29.172Z
2 429704502 995945 2022-05-05T14:31:14.954Z 2022-05-05T14:43:15.744Z
3 429055399 995945 2022-05-04T13:35:13.911Z 2022-05-04T13:35:15.758Z
4 428375477 995945 2022-05-03T12:26:02.170Z 2022-05-03T12:26:04.151Z
5 427873268 995945 2022-05-02T15:55:10.734Z 2022-05-02T15:55:13.140Z
6 427300091 995945 2022-05-01T17:06:54.808Z 2022-05-01T17:06:57.067Z
7 427069852 995945 2022-05-01T11:26:47.991Z 2022-05-01T11:26:49.684Z
start end timezone_offset nap \
0 2022-05-07T04:46:52.867Z 2022-05-07T14:40:57.427Z -04:00 False
1 2022-05-06T05:09:00.681Z 2022-05-06T15:09:12.415Z -04:00 False
2 2022-05-05T04:59:16.774Z 2022-05-05T14:29:44.886Z -04:00 False
3 2022-05-04T05:04:02.916Z 2022-05-04T13:28:57.733Z -04:00 False
4 2022-05-03T05:29:46.133Z 2022-05-03T12:14:54.861Z -04:00 False
5 2022-05-02T05:12:48.073Z 2022-05-02T15:49:36.453Z -04:00 False
6 2022-05-01T11:53:13.942Z 2022-05-01T14:51:19.894Z -04:00 True
7 2022-05-01T06:14:52.087Z 2022-05-01T09:19:14.856Z -04:00 False
score_state score.stage_summary.total_in_bed_time_milli \
0 SCORED 35643599
1 SCORED 35460907
2 SCORED 34240959
3 SCORED 30293855
4 SCORED 24307767
5 SCORED 38003623
6 SCORED 10396599
7 SCORED 11004129
score.stage_summary.total_awake_time_milli \
0 3744035
1 2064515
2 2937299
3 2769352
4 3384733
5 2235345
6 681103
7 1608235
score.stage_summary.total_no_data_time_milli \
0 0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
score.stage_summary.total_light_sleep_time_milli \
0 15384266
1 13169346
2 12210534
3 12689932
4 6655383
5 11195003
6 5900698
7 4971785
score.stage_summary.total_slow_wave_sleep_time_milli \
0 7633425
1 7874053
2 7814364
3 5554196
4 5526290
5 10101551
6 1762533
7 3008130
score.stage_summary.total_rem_sleep_time_milli \
0 8881873
1 12352993
2 11278762
3 9280375
4 8741361
5 14471724
6 2052265
7 1415979
score.stage_summary.sleep_cycle_count \
0 8
1 9
2 5
3 4
4 4
5 9
6 3
7 1
score.stage_summary.disturbance_count score.sleep_needed.baseline_milli \
0 17 27975800
1 12 27976121
2 21 27976442
3 15 27976764
4 12 27977085
5 8 27977406
6 1 27977728
7 4 27977728
score.sleep_needed.need_from_sleep_debt_milli \
0 0
1 359692
2 3237274
3 3636979
4 0
5 9792092
6 9792204
7 2098329
score.sleep_needed.need_from_recent_strain_milli \
0 367539
1 304726
2 655901
3 1812597
4 270597
5 426795
6 0
7 1463907
score.sleep_needed.need_from_recent_nap_milli score.respiratory_rate \
0 0 13.398438
1 0 13.066406
2 0 12.568359
3 0 13.164062
4 0 13.535156
5 -9715496 13.535156
6 0 14.121094
7 0 14.941406
score.sleep_performance_percentage score.sleep_consistency_percentage \
0 100.0 83.0
1 100.0 81.0
2 98.0 75.0
3 82.0 68.0
4 74.0 65.0
5 100.0 62.0
6 26.0 51.0
7 30.0 78.0
score.sleep_efficiency_percentage
0 89.857010
1 94.178050
2 91.421684
3 91.993940
4 89.586520
5 94.118080
6 93.448790
7 87.927660
[8 rows x 25 columns]