{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Working with the Fitbit API"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First things first, all credit to [Michael Galarnyk](https://towardsdatascience.com/using-the-fitbit-web-api-with-python-f29f119621ea)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Getting the imports right for Sphinx "
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"import sys, os, pathlib\n",
"import pandas as pd\n",
"from datetime import datetime\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"ROOT_DIR = str(pathlib.Path(os.path.realpath(\"__file__\")).parents[2])\n",
"sys.path.insert(0, ROOT_DIR)\n",
"\n",
"from hfkpy.fitbit.get_data import client\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grab the tokens"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"token_path = pathlib.Path(ROOT_DIR) / \"tokens.csv\"\n",
"tokens = pd.read_csv(token_path)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Instantiate the Fitbit API client"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"auth2_client = client(tokens)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Intraday Fitbit data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The [intraday Fitbit data](https://dev.fitbit.com/build/reference/web-api/intraday/get-activity-intraday-by-date/) can be collected down to the second interval. This data includes calories | distance | elevation | floors | steps. To get multiple days of data we can pull intraday and concatenate over our date range of interest."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\"{'activities-heart': [{'dateTime': '2022-04-07', 'value': {'customHeartRateZones': [], 'heartRateZones': [{'caloriesOut': 2876.27486, 'max': 111, 'min': 30, 'minutes': 1405, 'name': 'Out of Range'}, {...\""
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"oneDate = datetime(year=2022, month=4, day=7)\n",
"\n",
"oneDayData = auth2_client.intraday_time_series(\n",
" \"activities/heart\", oneDate, detail_level=\"1min\"\n",
")\n",
"\n",
"str(oneDayData)[:200] + \"...\"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### View the data as a dataframe"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
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