31 lines
1.4 KiB
Python
31 lines
1.4 KiB
Python
import json
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import pandas as pd
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from datetime import datetime
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CALORIES_INTRADAY_COLUMNS = ("device_id", "level", "mets", "value", "local_date_time", "timestamp")
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def parseCaloriesData(calories_data):
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if calories_data.empty:
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return pd.DataFrame(columns=CALORIES_INTRADAY_COLUMNS)
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device_id = calories_data["device_id"].iloc[0]
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records_intraday = []
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# Parse JSON into individual records
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for record in calories_data.json_fitbit_column:
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record = json.loads(record) # Parse text into JSON
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if "activities-calories" in record and "activities-calories-intraday" in record:
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curr_date = datetime.strptime(record["activities-calories"][0]["dateTime"], "%Y-%m-%d")
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dataset = record["activities-calories-intraday"]["dataset"]
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for data in dataset:
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d_time = datetime.strptime(data["time"], '%H:%M:%S').time()
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d_datetime = datetime.combine(curr_date, d_time).strftime("%Y-%m-%d %H:%M:%S")
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row_intraday = (device_id, data["level"], data["mets"], data["value"], d_datetime, 0)
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records_intraday.append(row_intraday)
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return pd.DataFrame(data=records_intraday, columns=CALORIES_INTRADAY_COLUMNS)
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def main(json_raw, stream_parameters):
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parsed_data = parseCaloriesData(json_raw)
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parsed_data["mets"] = parsed_data["mets"] / 10
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return parsed_data
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