Skip to main content

Storing state in a Python function

This one blew me away. You can store state in a function, just like you would any object. These are called function attributes. As an aside, I also learned that using a try: except clause is ever slightly so faster than an if.

def foo(a):
  try:
    foo.b += a
  except AttributeError:
    foo.b = a
  return foo.b

def foo2(a):
  if hasattr(foo2, 'b'):
    foo2.b += a
  else:
    foo2.b = a
  return foo2.b

if __name__ == '__main__':
  print [foo(x) for x in range(10)]
  print [foo2(x) for x in range(10)]

"""
python -mtimeit -s'import test' '[test.foo(x) for x in range(100)]'
python -mtimeit -s'import test' '[test.foo2(x) for x in range(100)]'
"""

Giving us:

python test.py
[0, 1, 3, 6, 10, 15, 21, 28, 36, 45]
[0, 1, 3, 6, 10, 15, 21, 28, 36, 45]

python -mtimeit -s'import test' '[test.foo(x) for x in range(100)]'  ->  10000 loops, best of 3: 29.4 usec per loop
python -mtimeit -s'import test' '[test.foo2(x) for x in range(100)]' -> 10000 loops, best of 3: 39.1 usec per loop

Comments

Popular posts from this blog

Flowing text in inkscape (Poster making)

You can flow text into arbitrary shapes in inkscape. (From a hint here).

You simply create a text box, type your text into it, create a frame with some drawing tool, select both the text box and the frame (click and shift) and then go to text->flow into frame.

UPDATE:

The omnipresent anonymous asked:
Trying to enter sentence so that text forms the number three...any ideas?
The solution:
Type '3' using the text toolConvert to path using object->pathSize as necessaryRemove fillUngroupType in actual text in new text boxSelect the text and the '3' pathFlow the text

Pandas panel = collection of tables/data frames aligned by index and column

Pandas panel provides a nice way to collect related data frames together while maintaining correspondence between the index and column values:


import pandas as pd, pylab #Full dimensions of a slice of our panel index = ['1','2','3','4'] #major_index columns = ['a','b','c'] #minor_index df = pd.DataFrame(pylab.randn(4,3),columns=columns,index=index) #A full slice of the panel df2 = pd.DataFrame(pylab.randn(3,2),columns=['a','c'],index=['1','3','4']) #A partial slice df3 = pd.DataFrame(pylab.randn(2,2),columns=['a','b'],index=['2','4']) #Another partial slice df4 = pd.DataFrame(pylab.randn(2,2),columns=['d','e'],index=['5','6']) #Partial slice with a new column and index pn = pd.Panel({'A': df}) pn['B'] = df2 pn['C'] = df3 pn['D'] = df4 for key in pn.items: print pn[key] -> output …

Python: Multiprocessing: passing multiple arguments to a function

Write a wrapper function to unpack the arguments before calling the real function. Lambda won't work, for some strange un-Pythonic reason.


import multiprocessing as mp def myfun(a,b): print a + b def mf_wrap(args): return myfun(*args) p = mp.Pool(4) fl = [(a,b) for a in range(3) for b in range(2)] #mf_wrap = lambda args: myfun(*args) -> this sucker, though more pythonic and compact, won't work p.map(mf_wrap, fl)