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How to use _parse_float method in localstack

Best Python code snippet using localstack_python

fetcher.py

Source:fetcher.py

...58        # Convert the US eastern time to UTC time59        trade_datetime_text = Fetcher.edt_to_utc(trade_datetime_text)60        f.trade_datetime = parse(trade_datetime_text)61        column_idx += 262        f.price = Fetcher._parse_float(data[column_idx])63        column_idx += 164        f.days_low = Fetcher._parse_float(data[column_idx])65        column_idx += 166        f.days_high = Fetcher._parse_float(data[column_idx])67        column_idx += 168        f.price_change = Fetcher._parse_float(data[column_idx])69        column_idx += 170        f.volume = Fetcher._parse_float(data[column_idx])71        column_idx += 172        f.market_cap_in_millions = Fetcher._parse_number_in_millions(data[column_idx])73        column_idx += 174        f.book_value = Fetcher._parse_float(data[column_idx])75        column_idx += 176        f.ebitda_in_millions = Fetcher._parse_number_in_millions(data[column_idx])77        column_idx += 178        f.dividend_share = Fetcher._parse_float(data[column_idx])79        column_idx += 180        f.dividend_pay_date = Fetcher._parse_date_str(data[column_idx], "%m/%d/%Y")81        column_idx += 182        f.ex_dividend_date = Fetcher._parse_date_str(data[column_idx], "%m/%d/%Y")83        column_idx += 184        f.dividend_yield = Fetcher._parse_float(data[column_idx])85        column_idx += 186        f.earning_share = Fetcher._parse_float(data[column_idx])87        column_idx += 188        f.price_book = Fetcher._parse_float(data[column_idx])89        column_idx += 190        f.price_sales = Fetcher._parse_float(data[column_idx])91        return True92    def fetch_historical(self, f, start_date, end_date, num_retries=3):93        """94        :param f: the financial object95        :type f: pyvalue.yahoofinance.financial.Financial96        :param start_date: the start date97        :type start_date: str98        :param end_date: the end data99        :type end_date: str100        :param num_retries: the number of retries101        :type num_retries: int102        :return:103        """104        stock = f.stock105        start_year, start_month, start_day = Fetcher._split_date_str(start_date)106        end_year, end_month, end_day = Fetcher._split_date_str(end_date)107        url = (r'http://ichart.finance.yahoo.com/table.csv?s={0}'108               r'&a={1}&b={2}&c={3}&d={4}&e={5}&f={6}&g=d&ignore=.csv'109               .format(stock, start_month-1, start_day, start_year, end_month-1, end_day, end_year))110        for try_idx in range(num_retries):111            try:112                response = urllib2.urlopen(url)113                csv = response.read()114                if len(csv.strip()) == 0:115                    raise YahooFinanceFetcherException("Empty response of the http request.")116                Fetcher._parse_historical_csv(csv, f)117                return True118            except Exception as err:119                traceback.print_exc()120                LogInfo.info(stock + " : " + err.message + " in the " + str((try_idx + 1)) + " time")121                if try_idx == num_retries - 1:122                    LogInfo.error('Failed to retrieve information for ' + stock)123                    return False124    @staticmethod125    def _parse_historical_csv(csv, f):126        """127        :param csv: the return csv data from Yahoo finance128        :type csv: str129        :param f: the financial object130        :type f: pyvalue.yahoofinance.financial.Financial131        :return:132        """133        lines = csv.split('\n')[1:] # skip the first line (header)134        daily_records = []135        for line in lines:136            line = line.strip()137            if len(line) == 0:138                continue139            elems = line.split(',')140            record = DailyRecord()141            column_idx = 0142            date_text = elems[column_idx]143            record.date = datetime.strptime(date_text, "%Y-%m-%d").date()144            column_idx += 1145            record.open = elems[column_idx]146            column_idx += 1147            record.high = elems[column_idx]148            column_idx += 1149            record.low = elems[column_idx]150            column_idx += 1151            record.close = elems[column_idx]152            column_idx += 1153            record.volume = elems[column_idx]154            column_idx += 1155            record.adj_close = elems[column_idx]156            daily_records.append(record)157            f.stock_historical = daily_records158        return len(f.stock_historical)159    @staticmethod160    def _parse_number_in_millions(val):161        if val is None or val == 'N/A' or val == 'n/a' or val == 'NA' or val == 'na':162            return None163        val = val.strip()164        if val.endswith("B"):165            return float(val[:-1])*1000166        elif val.endswith("M"):167            return float(val[:-1])168        elif val.endswith("K"):169            return float(val[:-1])/1000.0170        else:171            return float(val[:-1])/(1000.0*1000.0)172    @staticmethod173    def _split_date_str(date_str, format_template='%Y-%m-%d'):174        date_str = date_str.replace("'", "")175        date_str = date_str.replace("\"", "")176        if format_template == '%Y-%m-%d':177            tokens = date_str.split('-')178            year = int(tokens[0])179            month = int(tokens[1])180            day = int(tokens[2])181            return year, month, day182        elif format_template == '%m/%d/%Y':183            tokens = date_str.split('/')184            year = int(tokens[2])185            month = int(tokens[0])186            day = int(tokens[1])187            return year, month, day188        else:189            raise YahooFinanceFetcherException("Unknown format template for date parser : "+format_template)190    @staticmethod191    def _parse_date_str(date_str, format_template='%Y-%m-%d'):192        if date_str == 'N/A' or date_str == '':193            return None194        year, month, day = Fetcher._split_date_str(date_str, format_template)195        return datetime.strptime(str(year)+"-"+str(month)+"-"+str(day), "%Y-%m-%d").date()196    @staticmethod197    def _parse_float(val_str):198        if val_str == 'N/A' or val_str == 'n/a' or val_str == 'NA':199            return None200        else:201            return float(val_str)202    @staticmethod203    def edt_to_utc(date, mask='%m/%d/%Y %I:%M%p'):204        """205        Convert EDT (Eastern Daylight Time) to UTC206        :param date: EDT date string e.g. '5/26/2014 4:00pm'207        :param mask: format of input date e.g '%m/%d/%Y %I:%M%'208        :return: UTC date string e.g '2014-03-05 12:23:00'209        """210        utc = pytz.utc211        eastern = pytz.timezone('US/Eastern')...

lambda_function.py

Source:lambda_function.py

...41    # type: (dict) -> dict42    file_content = obj['Body'].read()43    json_content = json.loads(file_content)44    return json_content45def _parse_float(s):46    try:47        return float(s)48    except ValueError:49        return s50def _parse_int(s):51    try:52        return int(s)53    except ValueError:54        return s55def get_fields_parser():56    # type: () -> dict57    return {58        "lineItem_UsageAmount": (_parse_float, float),59        "lineItem_BlendedRate": (_parse_float, float),...

vasp_parse.py

Source:vasp_parse.py

1#from pymatgen.io.vasp.inputs import PotcarSingle2import pymatgen.io.vasp.inputs as vin3import re4class parse_potcar(object):5    parse_functions = {6        "LULTRA": vin._parse_bool,7        "LUNSCR": vin._parse_bool,8        "LCOR": vin._parse_bool,9        "LPAW": vin._parse_bool,10        "EATOM": vin._parse_float,11        "RPACOR": vin._parse_float,12        "POMASS": vin._parse_float,13        "ZVAL": vin._parse_float,14        "RCORE": vin._parse_float,15        "RWIGS": vin._parse_float,16        "ENMAX": vin._parse_float,17        "ENMIN": vin._parse_float,18        "EMMIN": vin._parse_float,19        "EAUG": vin._parse_float,20        "DEXC": vin._parse_float,21        "RMAX": vin._parse_float,22        "RAUG": vin._parse_float,23        "RDEP": vin._parse_float,24        "RDEPT": vin._parse_float,25        "QCUT": vin._parse_float,26        "QGAM": vin._parse_float,27        "RCLOC": vin._parse_float,28        "IUNSCR": vin._parse_int,29        "ICORE": vin._parse_int,30        "NDATA": vin._parse_int,31        "VRHFIN": vin._parse_string,32        "LEXCH": vin._parse_string,33        "TITEL": vin._parse_string,34        "STEP": vin._parse_list,35        "RRKJ": vin._parse_list,36        "GGA": vin._parse_list37    }38    def __init__(self, data):39        search_lines = re.findall(r"(?s)(parameters from PSCTR are:"40                                  r".*?END of PSCTR-controll parameters)",41                                  data)  #.group(2)42        self.all_keywords = []43        for i in range(len(search_lines)):44            keywords = {}45            for key, val in re.findall(r"(\S+)\s*=\s*(.*?)(?=;|$)",46                                       search_lines[i],47                                       flags=re.MULTILINE):48                try:49                    keywords[key] = self.parse_functions[key](val)50                except KeyError:51                    warnings.warn("Ignoring unknown variable type %s" % key)52            self.all_keywords.append(keywords)53    def get_max_enmax(self):54        max_enmax = 055        for i in range(len(self.all_keywords)):56            enmax = self.all_keywords[i]['ENMAX']57            if max_enmax < enmax:58                max_enmax = enmax59        return max_enmax60# p=PotcarSingle(file.read())...

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