How To Use Print() Along With Other Operations In List Comprehension?

I have a directory of CSV data files and I load all of them in one line using pandas.read_csv() within a list comprehension statement. import glob import pandas as pd file_list = g

Solution 1:

If you want a list comprehension (understandable given the speed improvement over a for loop), you could slightly modify your solution because None is falsy:

df_list = [pd.read_csv(f) for f in file_list if not print(f)]

Alternatively make a function that does the work:

defread_and_print(f):
    print(f)
    return pd.read_csv(f)

df_list = [read_and_print(f) for f in file_list]

However, the approaches violate the Command–query separation principle that Python generally follows because the function has both a side-effect and a return value of interest. Nonetheless, I think these are quite pragmatic, particularly if you want to print() now to view the data, but later you plan to remove the print() calls.

Solution 2:

List comprehension was not designed for that. Rather, just for populating a list looping over some iterable, and (optionally) if a condition is met. Python likes to emphasise readability over lines of code.

The proper way to do what you want is to not use list comprehension at all, rather a for loop:

for f in file_list:
    print(f)
    df_list.append(pd.read_csv(f))

Solution 3:

As already noted, you should generally not use functions with side-effects in a list comprehension. However, I appreciate that for debugging purposes something like this might be useful.

One way, similar to your if condition, would be to use or, making use of the fact that the print function returns None and thus evaluating and returning the second operator:

df_list = [print(f) or pd.read_csv(f) for f in file_list]

But this might be difficult to understand and the intention not very clear. Alternatively, you could define a peek function that prints and returns the argument and use that in the comprehension:

defpeek(x, *args, **kwargs):
    print(x, *args, **kwargs)
    return x

df_list = [pd.read_csv(peek(f)) for f in file_list]

You could also make this more generic, passing the function to be applied (print in this case) as another parameter to the peek function, or first checking whether some global debug_enabled variable is actually set to True.