Garmin HRV/sleep Plot

README.md

Garmin Connect only supports showing a maximum 4-week plot of HRV data. This script scrapes HRV and sleep data and plots it on a single graph, making it much easier to see the trend over time.

In order for the script to work, you need to provide the correct values for the Authorization and Cookie headers. To get these:

• Log in to Garmin Connect and navigate to the HRV status report
• Open the browser developer tools and select the network tab
• In the HRV status report, click to a previous period. This will cause a network request to update the report
• In the developer tools, click on the network request and look for the request header.
• Copy the values for the above headers and paste them into the script

Run the script with python main.py.

A new browser window should open with your graph.

main.py

import math
import requests
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from datetime import date, timedelta
import pandas as pd
import numpy as np

headers = {
    'DI-Backend': 'connectapi.garmin.com',
    'Authorization': '',
    'Cookie': '',
}

def request(url: str):
    r = requests.get(url, headers=headers)
    if r.status_code != 200:
        print(url)
        print(r.status_code)
        print(r.text)
        exit()
    return r

def get_dates(beg: date, end: date, period: int):
    dates = []
    cbeg = beg
    while cbeg < end:
        cend = cbeg + timedelta(days=period)
        if cend > end:
            cend = end
        dates.append([cbeg, cend])
        cbeg = cend + timedelta(days=1)
    return dates

def get_hrv_summaries(beg: date, end: date):
    print(f"Get HRV Summaries between {beg} and {end}")
    x = []
    y_hrv_last_night_avg = []
    y_hrv_weekly_avg = []
    y_hrv_blower = []
    y_hrv_bupper = []
    dates = get_dates(beg, end, 366)
    for beg, end in dates:
        url = f'https://connect.garmin.com/hrv-service/hrv/daily/{beg}/{end}'
        r = request(url)

        hrvs = r.json().get("hrvSummaries")
        for hrv in hrvs:
            x.append(hrv.get("calendarDate"))
            y_hrv_last_night_avg.append(hrv.get("lastNightAvg"))
            y_hrv_weekly_avg.append(hrv.get("weeklyAvg"))
            baseline = hrv.get("baseline")
            if baseline:
                y_hrv_blower.append(baseline.get("balancedLow"))
                y_hrv_bupper.append(baseline.get("balancedUpper"))
            else:
                y_hrv_blower.append(None)
                y_hrv_bupper.append(None)
    return x, y_hrv_last_night_avg, y_hrv_weekly_avg, y_hrv_blower, y_hrv_bupper

def get_sleep_stats(beg: date, end: date):
    print(f"Get Sleep Stats between {beg} and {end}")
    x = []
    y = []
    dates = get_dates(beg, end, 27)
    for bdate, edate in dates:
        url = f'https://connect.garmin.com/sleep-service/stats/sleep/daily/{bdate}/{edate}'
        r = request(url)

        inds = r.json().get("individualStats")
        for ind in inds:
            x.append(ind.get("calendarDate"))
            sleep = ind.get("values").get("totalSleepTimeInSeconds") / 3600
            y.append(sleep)
    return x, y

# main

beg = date.fromisoformat('2022-11-04')
end = date.today()

x1, y_hrv_last_night_avg, y_hrv, y_bl, y_bu = get_hrv_summaries(beg, end)
x2, y = get_sleep_stats(beg, end)

# Merge datasets

hrv_df = pd.DataFrame({
    'x': x1,
    'y_ln_hrv': y_hrv_last_night_avg,
    'y_hrv': y_hrv,
    'y_bl': y_bl,
    'y_bu': y_bu
})
sleep_df = pd.DataFrame({
    'x': x2,
    'y_sleep': y
})

df = pd.merge(hrv_df, sleep_df, on='x', how='outer')
df['x'] = pd.to_datetime(df['x'])
df['y_sleep_7da'] = df['y_sleep'].rolling(min_periods=3, window=7).mean()
df['color'] = np.where(df['y_sleep'] < 7, 'red', 'green')

fig = make_subplots(
    rows=3,
    cols=1,
    shared_xaxes=True,
    subplot_titles=['Last Night Average HRV', '7-day Average HRV', 'Sleep Amount (green is >= 7 hours, black=7 day average)']
)
fig.append_trace(go.Scatter(x=df['x'], y=df['y_ln_hrv'], line_color='green', name="last night average hrv", showlegend=False), 1, 1)
fig.append_trace(go.Scatter(x=df['x'], y=df['y_hrv'], line_color='blue', name="7 day average hrv", showlegend=False), 2, 1)
fig.append_trace(go.Scatter(x=df['x'], y=df['y_bl'], line_color='darkgrey', name="", showlegend=False), 2, 1)
fig.append_trace(go.Scatter(x=df['x'], y=df['y_bu'], line_color='darkgrey', name="", showlegend=False), 2, 1)
fig.append_trace(go.Bar(x=df['x'], y=df['y_sleep'], marker_color=df['color'], name="sleep in hours", showlegend=False), 3, 1)
fig.append_trace(go.Scatter(x=df['x'], y=df['y_sleep_7da'], marker_color='black', name="7 day average", showlegend=False), 3, 1)

fig.show()

requirements.txt

certifi==2023.11.17
charset-normalizer==3.3.2
idna==3.6
numpy==1.26.3
packaging==23.2
pandas==2.2.0
plotly==5.18.0
python-dateutil==2.8.2
pytz==2023.3.post1
requests==2.31.0
six==1.16.0
tenacity==8.2.3
tzdata==2023.4
urllib3==2.1.0