Learn and practice the Cyclic Sort and Topological Sort patterns to solve coding interview problems.

Speedrun the Netflix Coding Interview: Top Problems in Python

This module will focus on two advanced sorting algorithms, Cyclic Sort and Topological Sort. These are often used in coding interviews as a way to distinguish between average and outstanding candidates. Cyclic Sort may only be used if the input list meets certain criteria, and in those situations, it’s the most efficient sorting algorithm possible. Topological Sort utilizes graph-based algorithms to deal with partially ordered elements. This module teaches us to recognize whether either of these advanced sorting techniques is applicable, as well as how to use them to solve the given problem.

Advanced Sorting Techniques

# Statement

Given an unsorted integer array, `nums`, return the smallest missing positive integer. 
Create an algorithm that runs with an $O(n)$ time complexity and utilizes a constant amount of space.

> **Note:** The smallest missing positive isn't the first positive number that's missing in the range of elements in the input, but the first positive number that’s missing if we start from $1$.


**Constraints:**

- $1 \leq$ `nums.length` $\leq 10^5$

- $-2^{31} \leq$ `nums[i]` $\leq 2^{31} - 1$


## Understand the problem

Let’s take a moment to make sure you’ve correctly understood the problem. The quiz below helps you check if you’re solving the correct problem:

What is the output if the following array is given as input?

[7, 8, 9, 11, 12]

What is the output if the following array is given as input?
[7, 8, 9, 11, 12]

What is the output if the following array is given as input?

[-1, -2, -3, -4, -5]

What is the output if the following array is given as input?
[-1, -2, -3, -4, -5]

Find the Smallest Missing Positive Number

Find the Smallest Missing Positive Number

# How to perform cyclic sort on an array

def cyclic_sort(nums):
 for i in range(len(nums)): # Traversing the array from the first index to the last index
 # Determining what position the specific element should be at
 correct_spot = nums[i] - 1
 while 1 <= nums[i] <= len(nums) and nums[i] != nums[correct_spot]:
 nums[i], nums[correct_spot] = nums[correct_spot], nums[i]
 correct_spot = nums[i] - 1

Help me debug only the function First Missing Positive . . I don't need the corrected code.I don't want explanations or code review. Just provide me the exact and to-the-point error that helps me run the code successfully on the test cases provided.

Please help me understand why this code failed for the last failed test case. Don't give me the corrected code. . If yes, then Just provide me the exact and to-the-point error that helps me run the code successfully on the test cases provided.

Your current task is to review only the smallest_missing_positive_integer function and the other function(s) invoked in it/them. Do not review extra/helper files or functions not invoked in the solution function smallest_missing_positive_integer. Do not review the code of data structures objects instantiated like a binary tree, linked list, trie, union find, etc., in the solution functions. Just review the solution/algorithm function of the problem. Also, Answer the following questions: Is the Cyclic Sort pattern used? Take your time and review the code.

Please provide a brief time complexity analysis of the function smallest_missing_positive_integer. While calculating time complexity, include the time complexity of built-in Python functions invoked by the code. The Answer should be to the point and in a few lines.

Please provide a brief Space complexity analysis of the function smallest_missing_positive_integer. While calculating space complexity, include the space complexity of built-in Python functions invoked by the code. Do not include the space used for the input parameters and the space used for just returning an output(not used as a scratch space). The Answer should be to the point and in a few lines

def evaluate_results(self) -> object:
 """
 self.__inputs is the list of inputs that are passed as input to function
 self.__actual_output is a list of outputs that is produced by the learner's code
 return : self.__edu__result object
 """
 # multiple outputs will be added at each index respectively for a single test_case
 expected_outputs = [] 
 # store the 1st expected output that should be displayed to the user 
 expected_outputs.append(smallest_missing_positive_integer(self.__inputs[0]))

 if json.dumps(smallest_missing_positive_integer(self.__inputs[0])) == json.dumps(self.__actual_outputs[0]):
 self.__edu_result.store_result(expected_outputs, TestCaseResult.PASS)
 else:
 self.__edu_result.store_result(expected_outputs, TestCaseResult.FAIL)

 return self.__edu_result

def smallest_missing_positive_integer(nums):
 i = 0
 while i < len(nums):
 correct_spot = nums[i] - 1
 if 0 <= correct_spot < len(nums) and nums[i] != nums[correct_spot]:
 nums[i], nums[correct_spot] = nums[correct_spot], nums[i]
 else:
 i += 1

 for i in range(len(nums)):
 if i + 1 != nums[i]:
 return i + 1
 return len(nums) + 1

def smallest_missing_positive_integer(nums):

    # Replace this placeholder return statement with your code
    return -1

PrivateTestCases.yaml

testcases:
  - name: "testcase 1"
    inputs:
    - 1 : [1, 2, 3, 5]
    output: 
    - 1 : 4
  - name: "testcase 2"
    inputs:
    - 1: [2, 3, 4, 5, 6]
    output:
    - 1 : 1
  - name: "testcase 3"
    inputs:
    - 1 : [-1, -2, -3, -4]
    output: 
    - 1 : 1
  - name: "testcase 4"
    inputs:
    - 1: [55, 22, 52, 100, 1, 3, -5]
    output:
    - 1 : 2
  - name: "testcase 5"
    inputs:
    - 1: [0, -1, -2, -3, 5]
    output:
    - 1 : 1

def sum(input_1, input_2):
    return input_1+input_2

def validate_inputs(self) -> None:
 """
 self.__inputs is the list of inputs that are passed as input to function
 store the result using the self.store_result(error_msg, status)
 return : void
 """
 nums= self.__inputs[0]
 def is_valid_1d_array(arr):
 if not isinstance(arr, list):
 return False # Not a valid 1D array if it's not a list
 
 return all(isinstance(elem, int) and not isinstance(elem, bool) for elem in arr)
 
 if not is_valid_1d_array(nums):
 self.store_result(("Invalid test case."), ValidationFunction.FAIL)
 elif len(nums) < 1 or len(nums) > 10**5 :
 self.store_result ("Input length should be between 1 and 10^5", ValidationFunction.FAIL)
 elif any(value < -2**31 or value >= 2**31 for value in nums):
 self.store_result("All elements in the input set should be between -2^31 and 2^31 - 1", ValidationFunction.FAIL)
 else:
 self.store_result("", ValidationFunction.PASS)

Try to solve the First Missing Positive problem.

Cyclic Sort

Topological Sort

Conclusion

First Missing Positive

Statement

Examples

Understand the problem

Figure it out!

Try it yourself