scanf in python

Fredrik Lundh fredrik at pythonware.com
Fri Jul 25 13:08:38 CEST 2008


AMD wrote:

>> For reading delimited fields in Python, you can use .split string method.

> Yes, that is what I use right now, but I still have to do the conversion 
> to integers, floats, dates as several separate steps. What is nice about 
> the scanf function is that it is all done on the same step. Exactly like 
> when you use % to format a string and you pass it a dictionary, it does 
> all the conversions to string for you.

You're confusing surface syntax with processing steps.  If you want to 
do things on one line, just add a suitable helper to take care of the 
processing.  E.g. for whitespace-separated data:

 >>> def scan(s, *types):
...     return tuple(f(v) for (f, v) in zip(types, s.split()))
...
 >>> scan("1 2 3", int, int, float)
(1, 2, 3.0)

This has the additional advantage that it works with any data type that 
provides a way to convert from string to that type, not just a small 
number of built-in types.  And you can even pass in your own local 
helper, of course:

 >>> def myfactory(n):
...     return int(n) * "!"
...
 >>> scan("1 2 3", int, float, myfactory)
(1, 2.0, '!!!')

If you're reading multiple columns of the same type, you might as well 
inline the whole thing:

     data = map(int, line.split())

For other formats, replace the split with slicing or a regexp.  Or use a 
ready-made module; there's hardly every any reason to read standard CSV 
files by hand when you can just do "import csv", for example.

Also note that function *creation* is relatively cheap in Python, and 
since "def" is an executable statement, you can create them pretty much 
anywhere; if you find that need a helper somewhere in your code, just 
put it there.  The following is a perfectly valid pattern:

     def myfunc(...):

         def myhelper(...):
             ...

         myhelper(...)
         myhelper(...)

         for line in open(file):
             myhelper(...)

(I'd say knowing when and how to abstract things away into a local 
helper is an important step towards full Python fluency -- that is, the 
point where you're able to pack "a lot of action in a small amount of 
clear code" most of the time.)

</F>




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