A comprehensive implementation of linked list data structures demonstrating three key algorithmic techniques: Multiple Pass, Slow-Fast Pointer, and Temporary Head.
# Run all examples
python examples/demo_all.py
# Run specific technique demos
python examples/demo_multiple_pass.py
python examples/demo_slow_fast.py
python examples/demo_temporary_head.py
# Run all tests
python tests/run_all_tests.py.
├── src/                          # Source code
│   ├── __init__.py              # Package initialization
│   ├── linked_list_base.py      # Base Node and LinkedList classes
│   ├── multiple_pass.py         # Multiple pass technique implementation
│   ├── slow_fast.py             # Slow-fast pointer technique implementation
│   └── temporary_head.py        # Temporary head technique implementation
├── tests/                        # Unit tests
│   ├── __init__.py              # Test package initialization
│   ├── test_linked_list_base.py # Base class tests (9 tests)
│   ├── test_multiple_pass.py    # Multiple pass tests (10 tests)
│   ├── test_slow_fast.py        # Slow-fast pointer tests (14 tests)
│   ├── test_temporary_head.py   # Temporary head tests (20 tests)
│   └── run_all_tests.py         # Test runner (53 total tests)
├── examples/                     # Demo scripts
│   ├── demo_multiple_pass.py    # Multiple pass technique demo
│   ├── demo_slow_fast.py        # Slow-fast pointer technique demo
│   ├── demo_temporary_head.py   # Temporary head technique demo
│   └── demo_all.py              # Comprehensive demo
├── docs/                         # Documentation
│   └── README_TESTS.md          # Test documentation
└── README.md                    # This file
Purpose: Find the middle element of a linked list Algorithm: Two-pass approach - count nodes, then traverse to middle Time Complexity: O(n) | Space Complexity: O(1)
from src import MultiplePassLinkedList
llist = MultiplePassLinkedList()
for i in range(1, 6):
    llist.append(i)
middle = llist.find_middle()  # Returns 3Purpose: Detect cycles in linked lists Algorithm: Two pointers moving at different speeds Time Complexity: O(n) | Space Complexity: O(1)
from src import SlowFastLinkedList
llist = SlowFastLinkedList()
for i in range(1, 6):
    llist.append(i)
llist.create_cycle(1)  # Create cycle: 5 -> 2
cycle_start = llist.find_cycle_start()  # Returns 2Purpose: Simplify deletion and reversal operations Algorithm: Use dummy node to handle edge cases Time Complexity: O(n) | Space Complexity: O(1)
from src import TemporaryHeadLinkedList
llist = TemporaryHeadLinkedList()
for i in range(1, 6):
    llist.append(i)
llist.delete_node(1)  # Delete head - simplified with dummy node
llist.reverse()       # Reverse list using temporary headThe project includes comprehensive unit tests with 53 total tests covering:
- ✅ Core functionality and edge cases
- ✅ Algorithm correctness verification
- ✅ Different data types (integers, strings, mixed)
- ✅ Error handling and invalid inputs
- ✅ Performance characteristics
# Run all tests with detailed output
python tests/run_all_tests.py
# Run specific test modules
python -m unittest tests.test_multiple_pass -v
python -m unittest tests.test_slow_fast -v
python -m unittest tests.test_temporary_head -v| Technique | Operation | Time | Space | Use Case | 
|---|---|---|---|---|
| Multiple Pass | Find Middle | O(n) | O(1) | When you need exact middle | 
| Slow-Fast | Cycle Detection | O(n) | O(1) | Detect loops/cycles | 
| Slow-Fast | Find Middle | O(n) | O(1) | One-pass middle finding | 
| Temporary Head | Deletion | O(n) | O(1) | Simplified edge cases | 
| Temporary Head | Reversal | O(n) | O(1) | Clean reversal logic | 
# Import all classes
from src import (
    LinkedList,
    MultiplePassLinkedList,
    SlowFastLinkedList,
    TemporaryHeadLinkedList
)
# Create and populate lists
llist = MultiplePassLinkedList()
for i in range(1, 6):
    llist.append(i)
# Use specific techniques
middle = llist.find_middle()# Cycle detection example
cycle_list = SlowFastLinkedList()
for i in range(1, 8):
    cycle_list.append(i)
cycle_list.create_cycle(2)  # Create cycle at position 2
if cycle_list.find_cycle_start():
    print("Cycle detected!")This implementation demonstrates:
- Algorithm Design Patterns: Common techniques used in competitive programming
- Edge Case Handling: Proper handling of empty lists, single elements, etc.
- Code Organization: Clean separation of concerns and modular design
- Testing Practices: Comprehensive unit testing with edge cases
- Documentation: Clear explanations and usage examples
- All code follows Python best practices
- Comprehensive tests are required for new features
- Documentation should be updated for any changes
- Examples should demonstrate real-world usage