141 lines
5.5 KiB
Python
141 lines
5.5 KiB
Python
import json
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import pandas as pd
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import numpy as np
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from datetime import datetime, timedelta
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import dateutil.parser
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SLEEP_CODE2LEVEL = ["asleep", "restless", "awake"]
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SLEEP_INTRADAY_COLUMNS = ("device_id",
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"type_episode_id",
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"duration",
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# For "classic" type, original_level is one of {"awake", "restless", "asleep"}
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# For "stages" type, original_level is one of {"wake", "deep", "light", "rem"}
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"level",
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# one of {0, 1} where 0: nap, 1: main sleep
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"is_main_sleep",
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# one of {"classic", "stages"}
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"type",
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"local_date_time",
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"timestamp")
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def mergeLongAndShortData(data_intraday):
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long_data = pd.DataFrame(columns=["dateTime", "level"])
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short_data = pd.DataFrame(columns=["dateTime", "level"])
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window_length = 30
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for data in data_intraday["data"]:
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counter = 0
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for times in range(data["seconds"] // window_length):
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row = {"dateTime": dateutil.parser.parse(data["dateTime"])+timedelta(seconds=counter*window_length), "level": data["level"]}
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long_data = long_data.append(row, ignore_index = True)
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counter = counter + 1
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for data in data_intraday["shortData"]:
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counter = 0
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for times in range(data["seconds"] // window_length):
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row = {"dateTime": dateutil.parser.parse(data["dateTime"])+timedelta(seconds=counter*window_length), "level": data["level"]}
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short_data = short_data.append(row, ignore_index = True)
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counter = counter + 1
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long_data.set_index("dateTime",inplace=True)
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short_data.set_index("dateTime",inplace=True)
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long_data["level"] = np.where(long_data.index.isin(short_data.index) == True, "wake", long_data["level"])
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long_data.reset_index(inplace=True)
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return long_data.values.tolist()
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# Parse one record for sleep API version 1
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def parseOneRecordForV1(record, device_id, d_is_main_sleep, records_intraday, type_episode_id):
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sleep_record_type = "classic"
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d_start_datetime = datetime.strptime(record["startTime"][:18], "%Y-%m-%dT%H:%M:%S")
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d_end_datetime = datetime.strptime(record["endTime"][:18], "%Y-%m-%dT%H:%M:%S")
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# Intraday data
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start_date = d_start_datetime.date()
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end_date = d_end_datetime.date()
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is_before_midnight = True
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curr_date = start_date
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for data in record["minuteData"]:
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# For overnight episodes, use end_date once we are over midnight
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d_time = datetime.strptime(data["dateTime"], '%H:%M:%S').time()
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if is_before_midnight and d_time.hour == 0:
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curr_date = end_date
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d_datetime = datetime.combine(curr_date, d_time).strftime("%Y-%m-%d %H:%M:%S")
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# API 1.2 stores original_level as strings, so we convert original_levels of API 1 to strings too
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# (1: "asleep", 2: "restless", 3: "awake")
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d_original_level = SLEEP_CODE2LEVEL[int(data["value"])-1]
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row_intraday = (device_id, type_episode_id, 60,
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d_original_level, d_is_main_sleep, sleep_record_type,
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d_datetime, 0)
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records_intraday.append(row_intraday)
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return records_intraday
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# Parse one record for sleep API version 1.2
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def parseOneRecordForV12(record, device_id, d_is_main_sleep, records_intraday, type_episode_id):
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sleep_record_type = record['type']
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if sleep_record_type == "classic":
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for data in record["levels"]["data"]:
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d_datetime = data["dateTime"][:19].replace("T", " ")
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row_intraday = (device_id, type_episode_id, data["seconds"],
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data["level"], d_is_main_sleep, sleep_record_type,
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d_datetime, 0)
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records_intraday.append(row_intraday)
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else:
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# For sleep type "stages"
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for data in mergeLongAndShortData(record["levels"]):
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d_datetime = data[0].strftime("%Y-%m-%d %H:%M:%S")
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row_intraday = (device_id, type_episode_id, 30,
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data[1], d_is_main_sleep, sleep_record_type,
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d_datetime, 0)
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records_intraday.append(row_intraday)
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return records_intraday
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def parseSleepData(sleep_data):
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if sleep_data.empty:
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return pd.DataFrame(columns=SLEEP_INTRADAY_COLUMNS)
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device_id = sleep_data["device_id"].iloc[0]
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records_intraday = []
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type_episode_id = 0
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# Parse JSON into individual records
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for multi_record in sleep_data.json_fitbit_column:
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sleep_record = json.loads(multi_record)
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if "sleep" in sleep_record:
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for record in json.loads(multi_record)["sleep"]:
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# Whether the sleep episode is nap (0) or main sleep (1)
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d_is_main_sleep = 1 if record["isMainSleep"] else 0
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# For sleep API version 1
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if "awakeCount" in record:
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records_intraday = parseOneRecordForV1(record, device_id, d_is_main_sleep, records_intraday, type_episode_id)
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# For sleep API version 1.2
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else:
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records_intraday = parseOneRecordForV12(record, device_id, d_is_main_sleep, records_intraday, type_episode_id)
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type_episode_id = type_episode_id + 1
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parsed_data = pd.DataFrame(data=records_intraday, columns=SLEEP_INTRADAY_COLUMNS)
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return parsed_data
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def main(json_raw, stream_parameters):
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parsed_data = parseSleepData(json_raw)
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return parsed_data
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