accessing keys in dict

[james_027]

hi,

a_dict = {'name':'apple', 'color':'red', 'texture':'smooth',
'shape':'sphere'}

is there any difference between ..

for key in a_dict:

from

for key in a_dict.keys():


which is more preferred? any difference in performance?

THanks
james

 

[James Stroud]

hi,

a_dict = {'name':'apple', 'color':'red', 'texture':'smooth',
'shape':'sphere'}

is there any difference between ..

for key in a_dict:

from

for key in a_dict.keys():


which is more preferred?

Use the first.

any difference in performance?

It doesn't matter. Wait until later to do these types of optimizations.
Ask the list how to go about optimizing when the time comes.

James


--
James Stroud
UCLA-DOE Institute for Genomics and Proteomics
Box 951570
Los Angeles, CA 90095

http://www.jamesstroud.com/

 

[Lawrence D'Oliveiro]

is there any difference between ..

for key in a_dict:

from

for key in a_dict.keys():

I'm assuming the former is equivalent to

for key in a_dict.iterkeys() :

 

[Dustan]

In message <[email protected]>,




I'm assuming the former is equivalent to

for key in a_dict.iterkeys() :

Never assume. A better approach would be to experiment:

color
shape
name
texture color
shape
name
texture red
sphere
apple
smooth

('color', 'red')
('shape', 'sphere')
('name', 'apple')
('texture', 'smooth')

 

[Steven D'Aprano]

Never assume. A better approach would be to experiment:

I assume that you would not like it if I poked you in the eye with a
sharp stick, but perhaps I better experiment...

*wink*

More seriously, if you wish to compare dict.keys() and dict.iterkeys(),
iterating over them doesn't help you because it shows only the
similarities, not the differences. But this will:

d = {1:"one", 2:"two"}
d.keys() [1, 2]
d.iterkeys()

<dictionary-keyiterator object at 0xb7ecd280>

dict.keys() retrieves all the keys at once, up front, whether you need
them all or not. dict.iterkeys() returns an iterator which retrieves the
keys lazily, only when needed. Iterating over the dict itself is the same
as using iterkeys:
<dictionary-keyiterator object at 0xb7ecd4a0>


Performance-wise, the difference for small dicts may be trivial:

d = dict(zip(xrange(1000), xrange(1000)))
import timeit
timeit.Timer("for key in d: pass", "from __main__ import d").repeat() [71.805022954940796, 71.10006308555603, 70.985043048858643]
timeit.Timer("for key in d.keys(): pass",

.... "from __main__ import d").repeat()
[80.323757886886597, 76.463414907455444, 76.681307792663574]

A six second difference on a million iterations of the loop is probably
not worth losing sleep over. But if your dict is very big, things may be
different:
.... "from __main__ import d").repeat(number=100) # I don't have all day...
[9.2374939918518066, 8.3636147975921631, 8.3667001724243164].... "from __main__ import d").repeat(number=100)
[13.776750087738037, 12.756224155426025, 12.697851181030273]

A four second difference on a hundred iterations of the loop _is_
something worth worrying about. Fortunately, Python makes it no worry at
all: just iterate on the dict regardless of whether your dict is small or
large, and you won't go wrong.