The glob module provides a function glob() to produce lists of files based on a wildcard search pattern that is provided as argument. The wildcard search uses Unix conventions, most of which also hold on other systems. They are as follows:

• A question mark (?) in a file name indicates any character

• A Kleene star (*) in a file name indicates any sequence of characters

• A sequence of characters between square brackets ([]) indicates any of these characters; a dash may be used to indicate a sequence that runs from the character to the left of the dash to the character to the right of the dash

For instance, the wildcard search "A[0-9]?B.*" looks for all files that start with the letter A, followed by a digit, followed by any character, followed by a B, with any extension. It depends on the operating system whether this is a case-sensitive or case-insensitive search.

Do not confuse a wildcard search pattern with a regular expression. While they have some superficial resemblance (such as an asterisk indicating “a series of any characters” in both of them), they are nothing alike. Wildcard searches only support the patterns listed above (some of which have a different meaning for regular expressions), and are only used for glob and when directly communicating with the system via the command prompt.

from glob import glob

glist = glob( "*.pdf" )
for name in glist:
    print( name )

The glob module also contains a function iglob(), which has the same functionality as glob(), but produces an iterator instead of a list.

Use glob() to list all Python files in the current directory.

statistics

The statistics module gives you access to various common statistical functions. All of these functions get as argument a sequence or iterator of numbers (integers or floats).

• mean() calculates the mean (or average) of a sequence of numbers

• median() calculates the median of a sequence of numbers, i.e., the “middle” number

• mode() calculates the mode of a sequence of numbers, i.e., the number that occurs most often

• stdev() calculates the standard deviation of a sequence of numbers

• variance() calculates the variance of a sequence of numbers

There are a few more functions in the statistics module, but these are the most-used ones. For more advanced statistical calculations, there are other modules available, which I do not discuss in this book.

These functions may raise a StatisticsError. This is particularly relevant in the case of the mode() function, as it is generated when no unique mode can be found.

from statistics import mean, median, mode, stdev, variance, \
    StatisticsError

data = [ 4, 5, 1, 1, 2, 2, 2, 3, 3, 3 ]

print( "mean:", mean( data ) )
print( "median:", median( data ) )
try:
    print( "mode:", mode( data ) )
except StatisticsError as e:
    print( e )
print( "st.dev.: {:.3f}".format( stdev( data ) ) )
print( "variance: {:.3f}".format( variance( data ) ) )

Note that for a sequence with an even number of numbers, the median is the average of the two “middle” numbers. There are different ways of calculating the median in case of an even number of numbers; if you want to use a different one, examine other functions in the statistics module.

As for the mode, in the literature you find multiple definitions of what the mode is supposed to be. The general definition is “the most common number,” but what if there are multiple of those? What if each number is unique? The version of the mode that the statistics module supports does not seem to be the most common one.