how to chose files to read from using nested try except?

Question

Depending on availability, I am trying to define a priority order of files to read from. I used nested Try Except and it works as expected. However, it's pretty cumbersome.

try :
    data_bachir = pd.read_table(model_data_path_1, nrows=73, infer_datetime_format = True, parse_dates = ["DATE"], sep='\s+',  engine='python') 
    Tmax_bachir = str(max(data_bachir.T2M.loc[0:23]))
except :
    try :
        data_bachir = pd.read_table(model_data_path_2, nrows=73, infer_datetime_format = True, parse_dates = ["DATE"], sep='\s+',  engine='python') 
        Tmax_bachir = str(max(data_bachir.T2M.loc[0:12])) 
    except :    
        try:
            data_bachir = pd.read_table(model_data_path_3, nrows=73, infer_datetime_format = True, parse_dates = ["DATE"], sep='\s+',  engine='python') 
            Tmax_bachir = str(max(data_bachir.T2M.loc[12:36])) 
        except : 
            data_bachir = pd.read_table(model_data_path_4, nrows=73, infer_datetime_format = True, parse_dates = ["DATE"], sep='\s+',  engine='python') 
            Tmax_bachir = str(max(data_bachir.T2M.loc[23:47]))

Is there a more elegant pythonic way to do this?

Answer 1

Another, compacter and scaleable approach, using list+loop:

import os


def find_existing_sourcefile(file_list):
  for file in file_list:
    if os.path.isfile(file):
      return file
  return None  # if loop ends without returning something, this is returned.

def do_pandas_stuff():
  file_list = ['model_data_path_1', 'model_data_path_2', 'model_data_path_3', 'model_data_path_4']
  file = find_existing_sourcefile(file_list)
  try:
    data_bachir = pd.read_table(file, nrows=73, infer_datetime_format = True, parse_dates = ["DATE"], sep='\s+',  engine='python') 
    Tmax_bachir = str(max(data_bachir.T2M.loc[0:23]))
  except:   # would be better to use named exceptions here.
    print("No valid source file found")
    
do_pandas_stuff()