How to use record_summary method in autotest

Best Python code snippet using autotest_python Github


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...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__":...

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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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