Python defining a list of large query strings vs reading in from a file

Question

I'm curious about best practices and also performance to be gained when working with lists of large strings in python. Specifically, I have a list that contains different postgreSQL queries as strings, and I'm wondering on best practices on how to initialize the list. Consider the following 2 methods:

Method 1 - Creating the list in code:

query_load = [("SELECT val_1, COUNT(*) as frequency "
     "FROM table "
     "GROUP BY val_1 "
     "ORDER BY val_1 ASC"),

     ("SELECT val_2, COUNT(*) as frequency "
     "FROM table "
     "GROUP BY val_2 "
     "ORDER BY val_2 ASC"),

     ("SELECT val_3, COUNT(*) as frequency "
     "FROM table "
     "GROUP BY val_3 "
     "ORDER BY val_3 ASC"),

     ("SELECT val_4, COUNT(*) as frequency "
     "FROM table "
     "GROUP BY val_4 "
     "ORDER BY val_4 ASC"), 
     ... 
      ]

Method 2 - Reading queries into list from file

my_list = [line.rstrip('\n') for line in open("..Desktop/my_queries.txt")]

As far as readability and less lines of code, Method 2 appears to be the better choice, but I'd like to stay in line with best practices. Additionally, will reading a file line-by-line into a list give worse performance (by a non-trivial amount)?

Answer 1

Just use a triple-quoted string; SQL won't care about the whitespace used to make your Python source readable.

query_load = [
    """
    SELECT val_1, COUNT(*) as frequency
    FROM table
    GROUP BY val_1
    ORDER BY val_1 ASC
    """,

    """
    SELECT val_2, COUNT(*) as frequency
    FROM table
    GROUP BY val_2
    ORDER BY val_2 ASC
    """,

    # etc
]

Whether you hard-code the queries or read them from external files is really a separate question that is only marginally related to the appearance of your source code.