In this article, some interesting optimization tips for Faster Python Code are discussed. These techniques help to produce result faster in a python code.
- Use builtin functions and libraries: Builtin functions like map() are implemented in C code. So the interpreter doesn’t have to execute the loop, this gives a considerable speedup.
The map() function applies a function to every member of iterable and returns the result. If there are multiple arguments, map() returns a list consisting of tuples containing the corresponding items from all iterables.
import time
start = time.clock()
s = 'geeks'
U = []
for c in s:
U.append(c.upper())
print (U)
elapsed = time.clock()
e1 = elapsed - start
print ("Time spent in function is: ", e1)
s = 'geeks'
start = time.clock()
U = map(str.upper, s)
print (U)
elapsed = time.clock()
e2 = elapsed - start
print ("Time spent in builtin function is: ", e2)
|
Output:
['G', 'E', 'E', 'K', 'S']
Time spent in function is: 0.0394747945637
['G', 'E', 'E', 'K', 'S']
Time spent in builtin function is: 0.0212335531192
The packages are platform-specific, which means that we need the appropriate package for the platform we’re using. If we are doing string operation, consider using an existing module ‘collections’ like deque which is highly optimized for our purposes.
from collections import deque
s = 'geek'
d = deque(s)
d.append('y')
d.appendleft('h')
print (d)
d.pop()
d.popleft()
print (list(reversed(d)))
|
Output:
deque(['h', 'g', 'e', 'e', 'k', 'y'])
['k', 'e', 'e', 'g']
import itertools
iter = itertools.permutations([1,2,3])
print (list(iter))
|
Output:
[(1, 2, 3), (1, 3, 2), (2, 1, 3), (2, 3, 1), (3, 1, 2), (3, 2, 1)]
- Use keys for sorts: In Python, we should use the key argument to the built-in sort instead, which is a faster way to sort.
somelist = [1, -3, 6, 11, 5]
somelist.sort()
print (somelist)
s = 'geeks'
s = sorted(s)
print (s)
|
Output:
[-3, 1, 5, 6, 11]
['e', 'e', 'g', 'k', 's']
In each case the list is sorted according to the index you select as part of the key argument. This approach works just as well with strings as it does with numbers.
- Optimizing loops: Write idiomatic code: This may sound counter-intuitive but writing idiomatic code will make your code faster in most cases. This is because Python was designed to have only one obvious/correct way to do a task.
For example (String Concatenation):
s = 'hellogeeks'
slist = ''
for i in s:
slist = slist + i
print (slist)
st = 'hellogeeks'
slist = ''.join([i for i in s])
print (slist)
evens = [ i for i in range(10) if i%2 == 0]
print (evens)
i = 0
evens = []
while i < 10:
if i %2 == 0:
evens.append(i)
i += 1
print (evens)
v = 'for'
s = 'geeks ' + v + ' geeks'
print (s)
s = 'geeks %s geeks' % v
print (s)
|
Output:
hellogeeks
[0, 2, 4, 6, 8]
geeks for geeks
Every time running a loop to s(i), Python evaluates the method. However, if you place the evaluation in a variable, the value is already known and Python can perform tasks faster.
- Try multiple coding approaches: Using precisely the same coding approach every time we create an application will almost certainly result in some situations where the application runs slower than it might.
For example (Initializing Dictionary Elements):
mydict = {'g':1,'e':1,'e':1,'k':1}
word = 'geeksforgeeks'
for w in word:
if w not in mydict:
mydict[w] = 0
mydict[w] += 1
print (mydict)
mydict = {'g':1,'e':1,'e':1,'k':1}
word = 'geeksforgeeks'
for w in word:
try:
mydict[w] += 1
except KeyError:
mydict[w] = 1
print (mydict)
|
Output:
{'e': 5, 'g': 3, 'f': 1, 'k': 3, 'o': 1, 's': 2, 'r': 1}
The output is the same in both cases. The only difference is how the output is obtained.
- Use xrange instead of range:range() – This returns a list of numbers created using range() function.
xrange() – This function returns the generator object that can be used to display numbers only by looping. Only particular range is displayed on demand and hence called “lazy evaluation”.
x = [i for i in range(0,10,2)]
print (x)
x = [i for i in range(0,10,2)]
print (x)
|
Output:
[1, 3, 5, 7, 9]
This could save you system memory because xrange() will only yield one integer element in a sequence at a time. Whereas range(), it gives you an entire list, which is unnecessary overhead for looping.
- Use Python multiple assignment to swap variables: This is elegant and faster in Python.
x = 2
y = 5
temp = x
x = y
y = temp
print (x,y)
x,y = 3,5
x, y = y, x
print (x,y)
|
Output:
5 2
5 3
- Use local variable if possible: Python is faster retrieving a local variable than retrieving a global variable. That is, avoid the “global” keyword. So if you are going to access a method often (inside a loop) consider writing it to a variable.
class Test:
def func(self,x):
print (x+x)
Obj = Test()
mytest = Obj.func
n = 2
for i in range(n):
mytest(i)
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Output:
0
2
References:
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