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How to use record_summary method in autotest

Best Python code snippet using autotest_python

after_analysis2.py

Source:after_analysis2.py

...38        for row in csvReader:39            record = Record(*row)40            listOfRecords.append(record)41        return listOfRecords42def record_summary(listOfRecords):43    """44    description:45    args:46    return:47    """48    summaryRecords = defaultdict()49    count = 050    age = defaultdict(int)51    adt = 052    material = defaultdict(int)53    for record in listOfRecords:54        try:55            year = record.year56            county = record.countyCode57            yearReconstructed = record.yearReconstructed58            deck = record.deck59            adt = record.averageDailyTraffic60            structType = record.structureType61        except:62            pass63    return listOfRecords64def to_csv(output, filename):65    """66    description:67    args:68    return:69    """70    outputNew = list()71    #output = [item._asdict() for item in output]72    for item in output:73        try:74            outputNew.append(item._asdict())75        except:76            outputNew.append(None)77        output = outputNew78        fieldnames = ['year',79                      'stateCode',80                      'structureNumber',81                      'countyCode',82                      'yearBuilt',83                      'averageDailyTraffic',84                      'deck',85                      'yearReconstructed',86                      'avgDailyTruckTraffic',87                      'material',88                      'structureType'89                     ]90        with open(filename, 'w') as csvFile:91            csvWriter = csv.DictWriter(csvFile, delimiter=',', fieldnames=fieldnames)92            csvWriter.writeheader()93            for row in output:94                if row == None:95                    #NoneDict = dict(zip(fieldnames, [None]*len(fieldnames)))96                    #csvWriter.writerow(NoneDict)97                    pass98                else:99                    csvWriter.writerow(row)100def main():101    path = '../../../../data/nbi/'102    os.chdir(path)103    rfBridges = 'bridgesRf.csv'104    rfNBridges = 'bridgesRfNegative.csv'105    flBridges = 'bridgesFl.csv'106    flNBridges = 'bridgesFlNegative.csv'107    ##False Positive and false negatives108    bothFalsePositive = 'bFP.csv'109    bothFalseNegative = 'bFN.csv'110    bothTruePositive ='bTP.csv'111    bothTrueNegative ='bTN.csv'112    nbiFile = 'nebraska1992-2019.csv'113    # Read structure Number114    rfList = read_structure_numbers(rfBridges)115    rfNList = read_structure_numbers(rfNBridges)116    flList = read_structure_numbers(flBridges)117    flNList = read_structure_numbers(flNBridges)118    # read structure of false positive and negative119    bFNList = read_structure_numbers(bothFalseNegative)120    bFPList = read_structure_numbers(bothFalsePositive)121    bTPList = read_structure_numbers(bothTruePositive)122    bTNList = read_structure_numbers(bothTrueNegative)123    # read nbi records124    nbiList = read_nbi_records(nbiFile)125    # gather structure number126    structNumbers =  list()127    for nbiRecord in nbiList:128        structNumber = nbiRecord.structureNumber129        structNumbers.append(structNumber)130    # create dictionary of structure numbers131    nbiDict = defaultdict()132    for structNumber, nbiRecord in zip(structNumbers, nbiList):133        nbiDict[structNumber] = nbiRecord134    rfBridgeRecords = list()135    rfNBridgeRecords = list()136    flowBridgeRecords = list()137    flowNBridgeRecords = list()138    bFNRecords = list()139    bFPRecords = list()140    bTNRecords = list()141    bTPRecords = list()142    for structNum in rfList:143        rfBridgeRecords.append(nbiDict.get(structNum))144    for structNum in rfNList:145        rfNBridgeRecords.append(nbiDict.get(structNum))146    for structNum in flList:147        flowBridgeRecords.append(nbiDict.get(structNum))148    for structNum in flNList:149        flowNBridgeRecords.append(nbiDict.get(structNum))150    # False Positive and False Negative151    for structNum in bFNList:152        bFNRecords.append(nbiDict.get(structNum))153    for structNum in bFPList:154        bFPRecords.append(nbiDict.get(structNum))155    for structNum in bTPList:156        bTPRecords.append(nbiDict.get(structNum))157    for structNum in bTNList:158        bTNRecords.append(nbiDict.get(structNum))159    # Average random forest age, adt, adtt, year of resconstruction160    outputRf = record_summary(rfBridgeRecords)161    to_csv(outputRf, 'TrueRfFalseFl.csv')162    outputRfN = record_summary(rfNBridgeRecords)163    to_csv(outputRfN, 'TrueRfNFalseFlN.csv')164    outputFlow = record_summary(flowBridgeRecords)165    to_csv(outputFlow, 'TrueFlFalseRf.csv')166    outputFlowN = record_summary(flowNBridgeRecords)167    to_csv(outputFlowN, 'TrueFlNFalseRfN.csv')168    outputbFN = record_summary(bFNRecords)169    to_csv(outputbFN, 'bFNRecords.csv')170    outputbFP = record_summary(bFPRecords)171    to_csv(outputbFP, 'bFPRecords.csv')172    outputbTP = record_summary(bTPRecords)173    to_csv(outputbTP, 'bTPRecords.csv')174    outputbTN = record_summary(bTNRecords)175    to_csv(outputbTN, 'bTNRecords.csv')176if __name__== "__main__":...

parse_heartrate_summary_json.py

Source:parse_heartrate_summary_json.py

1import json2import pandas as pd3HR_SUMMARY_COLUMNS = ("device_id",4                        "local_date_time",5                        "timestamp",6                        "heartrate_daily_restinghr",7                        "heartrate_daily_caloriesoutofrange",8                        "heartrate_daily_caloriesfatburn",9                        "heartrate_daily_caloriescardio",10                        "heartrate_daily_caloriespeak")11def parseHeartrateSummaryData(record_summary, device_id, curr_date):12    # API Version X: not sure the exact version13    if "heartRateZones" in record_summary:14        heartrate_zones = record_summary["heartRateZones"]15        d_resting_heartrate = record_summary["value"] if "value" in record_summary else None16    # API VERSION Y: not sure the exact version17    elif "value" in record_summary:18        heartrate_zones = record_summary["value"]["heartRateZones"]19        d_resting_heartrate = record_summary["value"]["restingHeartRate"] if "restingHeartRate" in record_summary["value"] else None20    else:21        ValueError("Heartrate zone are stored in an unkown format, this could mean Fitbit's heartrate API changed")22    23    if "caloriesOut" in heartrate_zones[0]:24        d_calories_outofrange = heartrate_zones[0]["caloriesOut"]25        d_calories_fatburn = heartrate_zones[1]["caloriesOut"]26        d_calories_cardio = heartrate_zones[2]["caloriesOut"]27        d_calories_peak = heartrate_zones[3]["caloriesOut"]28    else:29        d_calories_outofrange, d_calories_fatburn, d_calories_cardio, d_calories_peak = None, None, None, None30    31    row_summary = (device_id,32                    curr_date,33                    0,34                    d_resting_heartrate,35                    d_calories_outofrange,36                    d_calories_fatburn,37                    d_calories_cardio,38                    d_calories_peak)39    return row_summary40def parseHeartrateData(heartrate_data):41    if heartrate_data.empty:42        return pd.DataFrame(columns=HR_SUMMARY_COLUMNS)43    device_id = heartrate_data["device_id"].iloc[0]44    records_summary = []45    # Parse JSON into individual records46    for record in heartrate_data.json_fitbit_column:47        record = json.loads(record)  # Parse text into JSON48        if "activities-heart" in record:49            curr_date = record["activities-heart"][0]["dateTime"] + " 00:00:00"50            record_summary = record["activities-heart"][0]51            row_summary = parseHeartrateSummaryData(record_summary, device_id, curr_date)52            records_summary.append(row_summary)53    parsed_data = pd.DataFrame(data=records_summary, columns=HR_SUMMARY_COLUMNS)54    return parsed_data55    56def main(json_raw, stream_parameters):57    parsed_data = parseHeartrateData(json_raw)...

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