mywheel 0.3

Network Optimization Python Code

🛞 mywheel

High-performance data structures and algorithms in Python

mywheel provides efficient implementations of fundamental data structures optimized for specific use cases in graph algorithms, EDA (Electronic Design Automation), and network optimization. All implementations prioritize memory efficiency and time complexity over Python's standard library alternatives.

🚀 Quick Start

Installation

pip install mywheel

Usage Examples

Doubly Linked List with O(1) Operations

from mywheel import Dllist, Dllink

# Create list
dlist = Dllist(0)  # sentinel node
dlist.append(Dllink("A"))
dlist.append(Dllink("B"))

# O(1) operations
node = dlist.popleft()  # Remove first
dlist.appendleft(Dllink("C"))  # Add to front

Bounded Priority Queue for Small Integer Keys

from mywheel import BPQueue, Dllink

# Efficient for keys in range [-5, 5]
bpq = BPQueue(-5, 5)

# Add items with integer keys
bpq.append(Dllink("task1"), 3)
bpq.append(Dllink("task2"), 5)

# Extract highest priority item
item = bpq.popleft()

Round-Robin Iteration

from mywheel import Robin

# Create 5-part cycle
robin = Robin(5)

# Iterate excluding starting position
for part in robin.exclude(2):
    print(part)  # Prints: 3, 4, 0, 1

Array-Like Utilities

from mywheel import MapAdapter

# Adapt list to dict-like interface
lst = [10, 20, 30, 40]
mapping = MapAdapter(lst)

mapping[0] = 99
assert mapping[0] == 99

📊 Performance Characteristics

Data Structure	Insert	Delete	Lookup	Memory	Best For
Dllist	O(1)	O(1)	N/A	Minimal	Frequent front/back operations
BPQueue	O(1)*	O(k)	O(1)	O(b-a)	Small bounded integer keys
Robin	O(n)	N/A	O(1)	O(n)	Round-robin scheduling
MapAdapter	O(1)	N/A	O(1)	O(n)	Dict-like list access

* O(1) amortized for bounded keys

🎯 Used In

• digraphx - Graph algorithms and data structures
• netlistx - VLSI netlist partitioning
• ckpttnpy - Multi-level circuit partitioning

✨ Features

• Memory Efficient: Uses __slots__ and sentinel nodes to minimize overhead
• Type Safe: Full type hints with mypy support
• Well Tested: 100% coverage with pytest and hypothesis
• Zero Dependencies: Pure Python, no external runtime dependencies
• Python 3.8+: Supports all modern Python versions

🔧 Development

# Clone and install
git clone https://github.com/luk036/mywheel.git
cd mywheel
pip install -e ".[testing]"

# Run tests
pytest

# Run type checking
mypy src/mywheel

# Run linting
pre-commit run --all-files

See CONTRIBUTING.md for detailed guidelines.

👉 Note

This project has been set up using PyScaffold 4.5. For details and usage information on PyScaffold see https://pyscaffold.org/.