Creating Functions (or Lambdas) in a Loop (or Comprehension)

Introduction

When working with loops or comprehensions in Python, it is common to encounter the need to create functions or lambdas within the loop. However, there is a common issue that arises when attempting to create functions inside a loop - all the functions end up being the same. This phenomenon can be confusing and frustrating, but it can be understood and resolved with a deeper understanding of how Python handles variable scoping and closures.

Understanding the Issue

In order to understand why all the functions end up being the same in the given code, we need to understand how Python handles variable scoping and closures. In Python, variables in a nested function can refer to variables in their containing function. However, these variables are not bound at the time of the nested function's creation, but at the time of its execution.

Solution 1: Using Default Arguments

One way to solve this issue is by using default arguments in the function.

            
functions = []

for i in range(3):
    def f(x=i):
        return x

    functions.append(f)

print([f() for f in functions])
# expected output: [0, 1, 2]
# actual output:   [0, 1, 2]
            
        

By providing a default argument to the function, the value of 'i' at the time of the function's definition is assigned to 'x'. This ensures that each function maintains a different value for 'x' and produces the expected output.

Solution 2: Using lambdas and a closure

An alternative solution is to use lambdas and a closure to capture the value of 'i' at each iteration.

            
functions = []

for i in range(3):
    f = (lambda x: lambda: x)(i)
    functions.append(f)

print([f() for f in functions])
# expected output: [0, 1, 2]
# actual output:   [0, 1, 2]
            
        

In this solution, a lambda function is created with an argument 'x' that is set to the value of 'i' at each iteration. This lambda function is then immediately invoked with the current value of 'i' as an argument, creating a closure that captures the value of 'x'. This ensures that each lambda function has its own unique value of 'x' and produces the expected output.

Conclusion

Creating functions or lambdas in a loop or comprehension in Python can be tricky due to variable scoping and closures. However, by using default arguments or lambdas with a closure, it is possible to overcome the issue and achieve the desired behavior. Understanding how Python handles variable scoping and closures is crucial in avoiding this common pitfall.