[Python编程(第4版)].(Programming.Python.4th.Edition).Mark.Lutz.文字版

Bob Smith 10000

Sue Jones 20000

>>> [person[0][1] for person in people] # collect names

['Bob Smith', 'Sue Jones']

>>> for person in people:

print(person[0][1].split()[-1]) # get last names

person[2][1] *= 1.10 # give a 10% raise

Smith

Jones

>>> for person in people: print(person[2])

['pay', 11000.0]

['pay', 22000.0]

All we’ve really done here is add an extra level of positional indexing. To do better, we

might inspect field names in loops to find the one we want (the loop uses tuple assign-

ment here to unpack the name/value pairs):

>>> for person in people:

for (name, value) in person:

if name == 'name': print(value) # find a specific field

Bob Smith

Sue Jones

Better yet, we can code a fetcher function to do the job for us:

>>> def field(record, label):

for (fname, fvalue) in record:

if fname == label: # find any field by name

return fvalue

>>> field(bob, 'name')

'Bob Smith'

>>> field(sue, 'pay')

22000.0

>>> for rec in people:

print(field(rec, 'age')) # print all ages

42

45

If we proceed down this path, we’ll eventually wind up with a set of record interface

functions that generically map field names to field data. If you’ve done any Python

coding in the past, though, you probably already know that there is an easier way to

code this sort of association, and you can probably guess where we’re headed in the

next section.

8 | Chapter 1: A Sneak Preview

Do

wnload from Wow! eBook <www.wowebook.com>