Discussion 2: Higher-Order Functions, Self Reference

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Lambda Expressions

A lambda expression evaluates to a function, called a lambda function. For example, lambda y: x + y is a lambda expression, and can be read as "a function that takes in one parameter y and returns x + y."

A lambda expression by itself evaluates to a function but does not bind it to a name. Also note that the return expression of this function is not evaluated until the lambda is called. This is similar to how defining a new function using a def statement does not execute the function’s body until it is later called.

>>> what = lambda x : x + 5
>>> what
<function <lambda> at 0xf3f490>

Unlike def statements, lambda expressions can be used as an operator or an operand to a call expression. This is because they are simply one-line expressions that evaluate to functions. In the example below, (lambda y: y + 5) is the operator and 4 is the operand.

>>> (lambda y: y + 5)(4)
9
>>> (lambda f, x: f(x))(lambda y: y + 1, 10)
11

Higher Order Functions

A higher order function (HOF) is a function that manipulates other functions by taking in functions as arguments, returning a function, or both. For example, the function compose below takes in two functions as arguments and returns a function that is the composition of the two arguments.

def composer(func1, func2):
    """Return a function f, such that f(x) = func1(func2(x))."""
    def f(x):
        return func1(func2(x))
    return f

HOFs are powerful abstraction tools that allow us to express certain general patterns as named concepts in our programs.

Q1: Make Keeper

Write a function that takes in a number n and returns a function that can take in a single parameter cond. When we pass in some condition function cond into this returned function, it will print out numbers from 1 to n where calling cond on that number returns True.

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HOFs in Environment Diagrams

An environment diagram keeps track of all the variables that have been defined and the values they are bound to. However, values are not necessarily only integers and strings. Environment diagrams can model more complex programs that utilize higher order functions.

Lambdas are represented similarly to functions in environment diagrams, but since they lack instrinsic names, the lambda symbol (λ) is used instead.

The parent of any function (including lambdas) is always the frame in which the function is defined. It is useful to include the parent in environment diagrams in order to find variables that are not defined in the current frame. In the previous example, when we call add_two (which is really the lambda function), we need to know what x is in order to compute x + y. Since x is not in the frame f2, we look at the frame’s parent, which is f1. There, we find x is bound to 2.

As illustrated above, higher order functions that return a function have their return value represented with a pointer to the function object.

Currying

One important application of HOFs is converting a function that takes multiple arguments into a chain of functions that each take a single argument. This is known as currying. For example, the function below converts the pow function into its curried form:

>>> def curried_pow(x):
        def h(y):
            return pow(x, y)
        return h

>>> curried_pow(2)(3)
8

Q2: Curry2 Diagram

Draw the environment diagram that results from executing the code below.

def curry2(h):
    def f(x):
        def g(y):
            return h(x, y)
        return g
    return f

make_adder = curry2(lambda x, y: x + y)
add_three = make_adder(3)
add_four = make_adder(4)
five = add_three(2)
Objects
Global frame
f1: [parent=]
Return value
f2: [parent=]
Return value
f3: [parent=]
Return value
f4: [parent=]
Return value
f5: [parent=]
Return value

Q3: Curry2 Lambda

Write curry2 as a lambda function.

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Self Reference

Self-reference refers to a particular design of HOF, where a function eventually returns itself. In particular, a self-referencing function will not return a function call, but rather the function object itself. As an example, take a look at the print_all function:

def print_all(x):
    print(x)
    return print_all

Self-referencing functions will often employ helper functions that reference the outer function, such as the example below, print_sums.

def print_sums(n):
    print(n)
    def next_sum(k):
        return print_sums(n + k)
    return next_sum

A call to print_sums returns next_sum. A call to next_sum will return the result of calling print_sums which will, in turn, return another function next_sum. This type of pattern is common in self-referencing functions.

Q4: Make Keeper Redux

In this question, we will build off of the make_keeper function from in Question 1.

The function make_keeper_redux is similar to make_keeper, but now the function returned by make_keeper_redux should be self-referential—i.e., the returned function should return a function with the same behavior as make_keeper_redux.

Feel free to paste and modify your code for make_keeper below.

Hint: you only need to add one line to your make_keeper solution. What is currently missing from make_keeper_redux?

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Q5: Print N

Write a function print_n that can take in an integer n and returns a repeatable print function that can print the next n parameters. After the nth parameter, it just prints "done".

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Extra Practice

Feel free to reference this section as extra practice when studying for the exam in terms of tackling more involved or challenging problems.

Q6: HOF Diagram Practice

Draw the environment diagram that results from executing the code below.

n = 7

def f(x):
    n = 8
    return x + 1

def g(x):
    n = 9
    def h():
        return x + 1
    return h

def f(f, x):
    return f(x + n)

f = f(g, n)
g = (lambda y: y())(f)
Objects
Global frame
f1: [parent=]
Return value
f2: [parent=]
Return value
f3: [parent=]
Return value
f4: [parent=]
Return value

Q7: YY Diagram

Draw the environment diagram that results from executing the code below.

Tip: Using the + operator with two strings results in the second string being appended to the first. For example "C" + "S" concatenates the two strings into one string "CS".

y = "y"
h = y
def y(y):
    h = "h"
    if y == h:
        return y + "i"
    y = lambda y: y(h)
    return lambda h: y(h)
y = y(y)(y)
Objects
Global frame
f1: [parent=]
Return value
f2: [parent=]
Return value
f3: [parent=]
Return value
f4: [parent=]
Return value

Q8: Match Maker

Implement match_k, which takes in an integer k and returns a function that takes in a variable x and returns True if all the digits in x that are k apart are the same.

For example, match_k(2) returns a one argument function that takes in x and checks if digits that are 2 away in x are the same.

match_k(2)(1010) has the value of x = 1010 and digits 1, 0, 1, 0 going from left to right. 1 == 1 and 0 == 0, so the match_k(2)(1010) results in True.

match_k(2)(2010) has the value of x = 2010 and digits 2, 0, 1, 0 going from left to right. 2 != 1 and 0 == 0, so the match_k(2)(2010) results in False.

Important: You may not use strings or indexing for this problem. You do not have to use all the lines, one staff solution does not use the line directly above the while loop.

Hint: Floor dividing by powers of 10 gets rid of the rightmost digits.

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Q9: Three Memory

A k-memory function takes in a single input, prints whether that input was seen exactly k function calls ago, and returns a new k-memory function. For example, a 2-memory function will display "Found" if its input was seen exactly two function calls ago, and otherwise will display "Not found".

Implement three_memory, which is a 3-memory function. You may assume that the value None is never given as an input to your function, and that in the first two function calls the function will display "Not found" for any valid inputs given.

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Q10: Natural Chain

For this problem, a chain_function is a higher order function that repeatedly accepts natural numbers (positive integers). The first number that is passed into the function that chain_function returns initializes a natural chain, which we define as a consecutive sequence of increasing natural numbers (i.e., 1, 2, 3). A natural chain breaks when the next input differs from the expected value of the sequence. For example, the sequence (1, 2, 3, 5) is broken because it is missing a 4.

Implement the chain_function so that it prints out the value of the expected number at each chain break as well as the number of chain breaks seen so far, including the current chain break. Each time the chain breaks, the chain restarts at the most recently input number.

For example, the sequence (1, 2, 3, 5, 6) would only print 4 and 1. We print 4 because there is a missing 4, and we print 1 because the 4 is the first number to break the chain. The 5 broke the chain and restarted the chain, so from here on out we expect to see numbers increasingly linearly from 5. See the doctests for more examples. You may assume that the higher-order function is never given numbers ≤ 0.

Important: For this problem, the starter code is a suggestion. You are welcome to add/delete/modify the starter code template, or even write your own solution that doesn’t use the starter code at all.

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