Maximum Subsequence Score

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from queue import PriorityQueue

class Solution:
    def maxScore(self, speed: List[int], efficiency: List[int], k: int) -> int:
        total_speed = 0
        result = 0
        min_heap = []

        for current_speed, current_efficiency in sorted(list(zip(speed, efficiency)), key=lambda se: -se[1]):
            heappush(min_heap, current_speed)
            total_speed += current_speed

            if len(min_heap) > k:
                total_speed -= heappop(min_heap)

            if len(min_heap) == k:
                result = max(result, total_speed * current_efficiency)

        return result

Problem Classification

Language Agnostic Coding Drills

This code is solving a problem using a combination of sorting, priority queue, heap operations, and list manipulation. Here’s the breakdown into smallest units of learning:

1. Variable Declaration and Initialization: Understand the basics of declaring and initializing variables in your language of choice.

2. Arrays and Lists: Learn how to create and manipulate lists (or arrays) in your language of choice. This includes accessing elements, iterating over elements, etc.

3. Tuples and the zip function: Understanding what a tuple is, how to create and access its elements, and how to use the zip function to combine two lists into a list of tuples.

4. List Sorting: Learn how to sort a list of numbers, strings, or even tuples using custom comparison functions. In this case, it involves sorting the tuples by the second element in descending order.

5. Heap Operations: Understand the concepts of a heap and priority queue, and how to use heap operations like push and pop. This includes understanding how a min heap operates, as that’s what’s being used in this code.

6. Prefix Sum Computation: Understand the concept of prefix sums and how they can be used to optimize certain types of computations.

7. Conditional Statements and Loops: Master the use of conditional statements (like if-else) and loops (like for loop) to control the flow of the program.

8. Functions and Methods: Understand how to define and use functions or methods in your language of choice. This includes understanding the structure of a class and how to define methods within it.

9. Lambda Functions: Learn how to use lambda functions or other means of creating small, unnamed functions for simple operations. In Python, the itemgetter function from the operator module is used, which could be considered a form of a lambda function.

10. List Slicing and Accessing Elements: Learn how to access specific elements in a list, including accessing the last element and slicing the list to get a new list with only a specific range of elements.

Each of these units of learning can be used independently and combined to form the final solution.

Targeted Drills in Python

1. Variable Declaration and Initialization

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a = 5
b = 10
print(a, b)

2. Arrays and Lists

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my_list = [1, 2, 3, 4, 5]
for i in my_list:
    print(i)

3. Tuples and the zip function

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list1 = [1, 2, 3]
list2 = ['a', 'b', 'c']
for item in zip(list1, list2):
    print(item)

4. List Sorting

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my_list = [(2, 'b'), (1, 'a'), (3, 'c')]
my_list.sort(key=lambda x: x[1])
print(my_list)

5. Heap Operations

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import heapq

heap = []
heapq.heappush(heap, 5)
heapq.heappush(heap, 2)
heapq.heappush(heap, 4)
print(heapq.heappop(heap))

6. Prefix Sum Computation

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arr = [1, 2, 3, 4, 5]
prefix_sum = [0] * len(arr)
prefix_sum[0] = arr[0]

for i in range(1, len(arr)):
    prefix_sum[i] = prefix_sum[i - 1] + arr[i]

print(prefix_sum)

7. Conditional Statements and Loops

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for i in range(10):
    if i % 2 == 0:
        print(f"{i} is even")
    else:
        print(f"{i} is odd")

8. Functions and Methods

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class MyClass:
    def say_hello(self):
        print("Hello, world!")

obj = MyClass()
obj.say_hello()

9. Lambda Functions

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from operator import itemgetter

my_list = [(2, 'b'), (1, 'a'), (3, 'c')]
my_list.sort(key=itemgetter(1))
print(my_list)

10. List Slicing and Accessing Elements

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my_list = [1, 2, 3, 4, 5]
print(my_list[2])       # Single element
print(my_list[-1])      # Last element
print(my_list[1:3])     # Slicing

Finally, once all these concepts are understood and practiced, they can be integrated to write the final solution.