How can I efficiently filter dictionaries based on custom conditions in Python?

Advanced Dictionary Filtering with Custom Conditions

The book's example illustrates dictionary filtering using the items() function, a process that can be streamlined for efficiency.

Dict Comprehension Method:

Python offers a powerful tool for this purpose: the dict comprehension. With it, you can create a new dictionary based on existing values while applying custom conditions. For instance, to filter a dictionary of points:

points = {'a': (3, 4), 'b': (1, 2), 'c': (5, 5), 'd': (3, 3)}

points_under_5 = {
    k: v
    for k, v in points.items()  # Iterate over (key, value) pairs
    if v[0] < 5 and v[1] < 5  # Filter based on condition
}

Python 2 Compatibility:

In Python 2 (2.7 onwards), the syntax for iterating over dictionary items is slightly different:

points_under_5 = {
    k: v
    for k, v in points.iteritems()  # Use 'iteritems()' instead of 'items()'
    if v[0] < 5 and v[1] < 5
}

Performance Considerations:

The dict comprehension approach offers superior performance compared to the manual iteration method:

import timeit

# Manual iteration
manual_time = timeit.timeit(
    """
points={'a':(3,4), 'b':(1,2), 'c':(5,5), 'd':(3,3)}
points_small={}
for item in [i for i in points.items() if i[1][0]<5 and i[1][1]<5]:
    points_small[item[0]]=item[1]
""", number=1000000
)

# Dict comprehension
dict_time = timeit.timeit(
    """
points={'a':(3,4), 'b':(1,2), 'c':(5,5), 'd':(3,3)}
points_under_5 = {k:v for k, v in points.items() if v[0]<5 and v[1]<5}
""", number=1000000
)

print("Manual iteration time:", manual_time)
print("Dict comprehension time:", dict_time)

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