test: folder with error file for code review and pr description

[yike5460]

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Description of changes:

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Description

This pull request adds a new test file test/erroneous_code_test.py to the project. The test file is designed to catch and prevent erroneous code from being introduced into the codebase. By adding this test file, we can ensure that the existing functionality remains intact and any new changes adhere to the project's coding standards and best practices.

Type of change

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

File Stats Summary

File number involved in this PR: 1, unfold to see the details:

The file changes summary is as follows:

Files	Changes	Change Summary
test/erroneous_code_test.py	87 added, 0 removed	The code contains inefficient algorithms, redundant logic, inconsistent naming conventions, and potential runtime issues related to performance, error handling, and unnecessary delays.

[github-actions]

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Actionable comments posted: 1

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Files that changed from the base of the PR and between 552578a to 5c5e370

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• test/erroneous_code_test.py (1 hunks)

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[github-actions]

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Here are my review comments on the code change:

1-87:
Avoid inefficient algorithms and unnecessary computations.

• The calculate_factorial function uses a recursive approach, which can lead to a stack overflow for large inputs (line 5-8).
• The find_largest_number function iterates through the entire list, even after finding the largest number (line 11-16).
• The inefficient_sort function uses the bubble sort algorithm, which has a time complexity of O(n^2) and is inefficient for large lists (line 18-23).
• The generate_random_numbers function generates a large number of random numbers, which can be computationally expensive and potentially unnecessary (line 46-50).

def calculate_factorial(n):
    result = 1
    for i in range(1, n+1):
        result *= i
    return result

def find_largest_number(numbers):
    largest = float('-inf')
    for num in numbers:
        largest = max(largest, num)
    return largest

def sort_list(arr):
    return sorted(arr)

27-30:
Use consistent naming conventions.

The User class follows a different naming convention (PascalCase) compared to the other functions (snake_case). Consider using a consistent naming convention throughout the codebase for better readability and maintainability.

39-43:
Simplify conditional logic.

The process_data function can be simplified using a ternary operator or a list comprehension, which can make the code more concise and readable.

def process_data(data):
    return [item * 2 if item % 2 == 0 else item * 3 for item in data]

55-55:
Handle edge cases and potential exceptions.

The calculate_average function does not handle the case where the input list is empty, which can lead to a ZeroDivisionError. Consider adding a check for the empty list case or raising an appropriate exception.

def calculate_average(numbers):
    if not numbers:
        return 0  # or raise an exception
    total = sum(numbers)
    count = len(numbers)
    average = total / count
    return average

83-83:
Avoid unnecessary delays.

The time.sleep(5) statement introduces an unnecessary delay of 5 seconds, which can negatively impact the performance and responsiveness of the application. Consider removing this delay or replacing it with a more appropriate mechanism if needed.