The problem

When you want access value by it’s key in Python dictionary instance, your program will break on KeyError if the accessed key is not contained in a dictionary.

So it’s necessary to check the presence of a key before access it.

Here is the most obvious way to check it:

def k_in_d(d, k):
  return k in d.keys()

Is this way most efficient?

It might be done better:

def k_in_d(d, k):
  return k in d

But the following one is faster:

def k_in_d(d, k):
  try:
    v = d[k]
  except KeyError:
    return False
  return True

Performance checking

By the following code it is possible to check performance and make conclusion:

import datetime as dt
import random

# *********************************************************
# dict_size = 100
# num_iterations = 1000000
dict_size = 1000000
num_iterations = 100

d = {i: i for i in range(dict_size)}

# ---------------------------------------------------------
def k_in_d_object():
    k = random.randint(0,dict_size-1)
    return k in d
# ---------------------------------------------------------
def k_in_d_keys():
    k = random.randint(0,dict_size-1)
    return k in d.keys()
# ---------------------------------------------------------
def k_in_d_except():
    k = random.randint(0,dict_size-1)
    try:
    	v = d[k]
    except KeyError:
    	return False
    return True
# ---------------------------------------------------------
def test(func):
    t = dt.datetime.utcnow()
    for i in range(num_iterations):
        func()
    print ("%s --> %1.6f sec" % 
           (func, (dt.datetime.utcnow()-t).total_seconds()))

# *********************************************************
test(k_in_d_keys)
test(k_in_d_object)
test(k_in_d_except)

Statistics on different versions of Python

The code has been tested on computer from 2015 with i5 CPU.

Python 2.7.15

dict_size = 1000000 num_iterations = 100

<function k_in_d_keys at 0x10d7f50c8> --> 2.251373 sec
<function k_in_d_object at 0x10d7f5050> --> 0.000535 sec
<function k_in_d_except at 0x10d7f5140> --> 0.000242 sec

dict_size = 100 num_iterations = 1000000

<function k_in_d_keys at 0x1014fe0c8> --> 2.959747 sec
<function k_in_d_object at 0x1014fe050> --> 2.479454 sec
<function k_in_d_except at 0x1014fe140> --> 1.402201 sec

Python 3.7.2

dict_size = 1000000 num_iterations = 100

<function k_in_d_keys at 0x10ec81598> --> 0.000792 sec
<function k_in_d_object at 0x10ec81620> --> 0.001852 sec
<function k_in_d_except at 0x10ec81510> --> 0.000638 sec

dict_size = 100 num_iterations = 1000000

<function k_in_d_keys at 0x105209598> --> 1.761158 sec
<function k_in_d_object at 0x105209620> --> 2.526102 sec
<function k_in_d_except at 0x105209510> --> 1.677804 sec

Python 3.7.4

dict_size = 1000000 num_iterations = 100

<function k_in_d_keys at 0x102a94290> --> 0.002660 sec
<function k_in_d_object at 0x102a13e60> --> 0.002838 sec 
<function k_in_d_except at 0x102a94200> --> 0.000991 sec

dict_size = 100 num_iterations = 1000000

<function k_in_d_keys at 0x103cdb290> --> 1.739541 sec 
<function k_in_d_object at 0x103c5ae60> --> 1.649423 sec 
<function k_in_d_except at 0x103cdb200> --> 1.644620 sec

Conclusion

With a time performance of Python 3 become better.

Using exceptions is the fastest way to check key existence in a dictionary.

References

Stack Overflow: Python is ‘key in dict’ different/faster than ‘key in dict.keys()’