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How to use handle_tr method in fMBT

Best Python code snippet using fMBT_python

Course.py

Source:Course.py

...90        for i in data:91            if first:92                first = False93                continue94            name = handle_tr(i[0]).title()95            surname = handle_tr(i[1]).title()96            student_number = str(int(float(i[2])))97            mail = i[3]98            role = 499            username = name.split()[0].lower() + surname.lower()100            password = passwordGenerator(8)101            try:102                self.execute("INSERT INTO members(PersonID, Role, Name, Surname, Username, Password, Email) "103                                     "values(%s, '%s', '%s', '%s', '%s', '%s', '%s');"104                                     % (student_number, role, name, surname, username, pas.hash_password(password), mail))105                auth.append((name + " " + surname, mail, password, username))106            except IntegrityError:107                pass108            reg.append(student_number)109        threading.Thread(target=send_mail_first_login, args=(auth, lecturer)).start()...

html2csv.py

Source:html2csv.py

...89                self.processing_table = True90            return91        if not self.table_num:92            self.processing_table = False93    def handle_tr(self, what, _tag, _attrs):94        if self.processing_table:95            if what == "start":96                self.rows.append([])97    def error(self, message):98        print(message, file=sys.stderr)99if __name__ == "__main__":...

mkDataset.py

Source:mkDataset.py

1import numpy2import csv3import cPickle4import datetime as dt5import calendar as cl6dataMonth = cPickle.load(open('data/dumpMonthly.pkl','rb'))7dataDay = cPickle.load(open('data/dumpDaily.pkl','rb'))8# get median for labelling returns9getAll = numpy.asarray([])10for key, value in dataMonth.items():11    getAll = numpy.concatenate([getAll,value.values[:,3]])12median = numpy.median(getAll)13# make dataset14handle_tr = open('data/trainData.dat', 'w')15handle_tr.write("M12,M11,M10,M9,M8,M7,M6,M5,M4,M3,M2,M1,"16                "D15,D14,D13,D12,D11,D10,D9,D8,D7,D6,D5,D4,D3,D2,D1,"17                "Jan,Label,Ticker,Month,Year\n")18handle_ts = open('data/testData.dat', 'w')19handle_ts.write("M12,M11,M10,M9,M8,M7,M6,M5,M4,M3,M2,M1,"20                "D15,D14,D13,D12,D11,D10,D9,D8,D7,D6,D5,D4,D3,D2,D1,"21                "Jan,Label,Ticker,Month,Year\n")22for key, value in dataMonth.items():23    data = []24    for k in xrange(len(dataMonth[key].values[:,3])-12):25        month =  dataMonth[key].index[k+12].month26        year = dataMonth[key].index[k+12].year27        # skip current month because insufficient data28        if month!=11 or year!=2014:29            rm = numpy.zeros(12)30            for i in xrange(k,k+12):31                rm[i-k] =  dataMonth[key].values[i,3]32            label = dataMonth[key].values[k+12,3] > median33            endday = cl.monthrange(year, month)[1]34            start = dataDay[key].index.searchsorted(dt.datetime(year, month, 1))35            end = dataDay[key].index.searchsorted(dt.datetime(year, month, endday))36            rd = dataDay[key].ix[start:end].values[:,3][-15:]37            if month==1:38                idct = 139            else:40                idct = 041            if len(rd)==15:42                datapoint = numpy.concatenate([rm, rd]).tolist()43                datapoint.append(idct)44                datapoint.append(int(label)+1)45                datapoint.append(key)46                datapoint.append(month)47                datapoint.append(year)48                data.append(datapoint)49            else:50                print "skipped",key,month,year51    train = data[:int(len(data)*0.75)]52    test = data[int(len(data)*0.75):]53    for tr in train:54        handle_tr.write(','.join([str(s) for s in tr])+'\n')55    for ts in test:56        handle_ts.write(','.join([str(s) for s in ts])+'\n')57handle_tr.close()...

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