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146 def get_data_from_file(csv_content, files): 147 # Get description or fix from the file reference parsed in JsonToCsv class 148 data = '' 149 number_from_file = re.search('\d+', csv_content) 150 if not number_from_file: 151 return data 152 else: 153 file_number = number_from_file.group() 154 155 if file_number in files['filenames']: 156 filename = files['filenames'][file_number] 157 else: 158 return data 159 160 with open(path.join(files['path'], filename)) as file_object: 161 data = file_object.read() 162 163 return data
218 def _find_all_csv_paths(input_path, house_id, year): 219 """ 220 Returns 221 ------- 222 list of csv paths of data (with respect to a house and a particular year ) 223 """ 224 house_year_path = (input_path + '/' + 'Home' + house_id + '/' + year) 225 extension = 'csv' 226 os.chdir(house_year_path) 227 csv_names = glob.glob(house_year_path + '/*.csv') 228 229 txt_paths = glob.glob(house_year_path + '/*.txt') 230 231 paths = [] 232 # Take only those csv files which have 30 minutes as sample period 233 for txt_path in txt_paths: 234 f = open(txt_path, "r") 235 lines = f.readlines() 236 f.close() 237 if '30' in lines[-2]: 238 name_temp = lines[0].strip('\n') 239 paths.append( 240 house_year_path + 241 '/' + 242 name_temp + 243 '_' + 244 year + 245 '.csv') 246 247 return paths
10 def read_stock_csv(stock_dir): 11 for filename in os.listdir(stock_dir): 12 #logger.info("start :%s" % filename) 13 code = filename.split('.')[0] 14 d_table_name = "%s_D" % code 15 stock = CStock(code, ct.DB_INFO) 16 #logger.info("created :%s" % filename) 17 try: 18 df = pd.read_csv(os.path.join(stock_dir, filename)) 19 except pd.errors.EmptyDataError: 20 logger.info("%s:empty data" % code) 21 continue 22 df.columns = ['cdate', 'open', 'high', 'low', 'close', 'volume', 'amount'] 23 #logger.info("readcsv :%s" % filename) 24 if not stock.mysql_client.set(df, d_table_name): 25 logger.info("failed :%s" % filename) 26 succeed_list.append(filename) 27 logger.info("succeed :%s" % filename)
51 def load_csv_file(csv_file_path): 52 lines = get_lines_from_csv_file(csv_file_path) 53 54 scores = [] 55 for line in lines[1:]: 56 begin = 0 57 for strategy in STRATEGIES: 58 score = [strategy] + map(int, line[begin: begin + 4]) 59 begin += 4 60 scores.append(score) 61 62 return scores, CLASSIFICATIONS