5.3 Using the filter() function to pass or reject data

The job of the filter() function is to use and apply a decision function called a predicate to each value in a collection. When the predicate function’s result is true, the value is passed; otherwise, the value is rejected. The itertools module includes filterfalse() as a variation on this theme. Refer to Chapter 8, The Itertools Module, to understand the usage of the itertools module’s filterfalse() function.

We might apply this to our trip data to create a subset of legs that are over 50 nautical miles long, as follows:

>>> long_legs = list( 
...     filter(lambda leg: dist(leg) >= 50, trip) 
... )

The predicate lambda will be True for long legs, which will be passed. Short legs will be rejected. The output contains the 14 legs that pass this distance test.

This kind of processing clearly segregates the filter rule (lambda leg: dist(leg) >= 50) from any other...