Implement Linear Search Algorithm
Description
Implement the linear() method in the Search class (search.py). This method should use the linear search algorithm to find an element in a list based on a custom comparator function.
Requirements
Method Signature:
@staticmethod
def linear(data: List[Any], target: Any, comparator: Callable[[Any, Any], bool]) -> Any
Parameters:
data: A list of elements to search throughtarget: The element to findcomparator: A function that takes two elements and returns True if they match
Returns:
- The index of the found element
Raises:
NotFoundError if the target is not found in the list
Algorithm Details
Linear search works by:
- Iterating through each element in the list
- Using the comparator to check if the current element matches the target
- Returning the index immediately when found
- Raising
NotFoundError if the entire list is searched without finding the target
Time Complexity:
- Best case: O(1) - element is first
- Average: O(n/2)
- Worst case: O(n) - element is last or not present
Space Complexity: O(1)
Performance Requirements
Your implementation must pass the performance test with the following criteria:
- Dataset size: 100,000 elements
- Target position: Last element (worst case)
- Maximum time: 1 second
- Should efficiently iterate through large lists
Implementation Guidelines
- Use enumeration to track both index and value
- Use the comparator to check for matches (don't assume
==)
- Return the first match - if duplicates exist, return the first occurrence
- Raise NotFoundError with a descriptive message when not found
- Handle edge cases:
- Empty lists (should raise NotFoundError)
- Single-element lists
- Element not in list
- Duplicate elements (return first occurrence)
- Custom comparators (not just equality)
Testing
Run the test suite to verify your implementation:
python3 -m colorful_test test_search.py
All tests related to linear() must pass, including:
- Finding elements at various positions (first, middle, last)
- Handling different data types (integers, floats, strings, objects)
- Raising NotFoundError when appropriate
- Working with custom comparators
- Performance test with a large dataset
Example Usage
from search import Search, NotFoundError
# Basic search
data = [5, 3, 8, 1, 9, 2]
index = Search.linear(data, 8, lambda a, b: a == b)
print(index) # 2
# String search
words = ['apple', 'banana', 'cherry']
index = Search.linear(words, 'banana', lambda a, b: a == b)
print(index) # 1
# Not found
try:
Search.linear(data, 10, lambda a, b: a == b)
except NotFoundError as e:
print(e) # 10 was not foundError Handling
The NotFoundError exception is already defined in search.py. Your implementation should:
raise NotFoundError(f"{target} was not found")Acceptance Criteria
Resources
Note: Do not modify the test files. Ensure your implementation passes all existing tests.
Implement Linear Search Algorithm
Description
Implement the
linear()method in theSearchclass (search.py). This method should use the linear search algorithm to find an element in a list based on a custom comparator function.Requirements
Method Signature:
Parameters:
data: A list of elements to search throughtarget: The element to findcomparator: A function that takes two elements and returnsTrueif they matchReturns:
Raises:
NotFoundErrorif the target is not found in the listAlgorithm Details
Linear search works by:
NotFoundErrorif the entire list is searched without finding the targetTime Complexity:
Space Complexity: O(1)
Performance Requirements
Your implementation must pass the performance test with the following criteria:
Implementation Guidelines
==)Testing
Run the test suite to verify your implementation:
All tests related to
linear()must pass, including:Example Usage
Error Handling
The
NotFoundErrorexception is already defined insearch.py. Your implementation should:Acceptance Criteria
Resources
Note: Do not modify the test files. Ensure your implementation passes all existing tests.