Python 定义大型查询字符串列表与从文件中读取

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

我很好奇在 python 中处理大字符串列表时的最佳实践和性能。具体来说,我有一个列表,其中包含不同的 postgreSQL 查询作为字符串,我想知道如何初始化列表的最佳实践。考虑以下两种方法:

方法 1 - 在代码中创建列表:

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"), 
     ... 
      ]

方法 2 - 从文件中将查询读入列表

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

就可读性和代码行数而言,方法 2 似乎是更好的选择,但我希望与最佳实践保持一致。此外,将文件逐行读取到列表中会导致性能变差(非常小的数量)吗?

只需使用一个triple-quoted字符串; SQL 不会关心用于使您的 Python 源代码可读的空格。

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
]

您是 hard-code 查询还是从外部文件中读取它们实际上是一个单独的问题,与源代码的外观仅略有相关。