🚀✨ LRU Cache Implementation in Python

🔖 Description:
An efficient Least Recently Used (LRU) Cache implemented in Python using 🗂️ doubly linked list and 🔑 hashmap for O(1) operations.

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🛠️ Features

✅ Supports get(key) and put(key, value) in O(1) time
🔁 Automatically evicts the least recently used item when capacity is exceeded
🧩 Uses:

• 🗃️ Doubly Linked List to maintain usage order
• ⚡ Hash Map (dict) for quick key-node lookup

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📂 Files

• lru_cache.py – main implementation and example usage

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💻 Example Usage

lru = LRUCache(3)
lru.put(1, 1)
lru.put(2, 2)
lru.put(3, 3)
print(lru.get(1))  # Output: 1
lru.put(4, 4)      # Evicts key 2
print(lru.get(2))  # Output: -1
print(lru.get(3))  # Output: 3
print(lru.get(4))  # Output: 4
🎯 Why This Project?
💡 For CS (Computer Science) :

Demonstrates proficiency in classic data structures 🏗️ and algorithm design ⚙️

Shows understanding of system performance optimization 🚀 via caching strategies

📊 For DS (Data Science) :

Highlights coding 💻 and logical thinking 🧠 beyond library usage

LRU cache logic is commonly used in feature stores, database query optimization, and large-scale data pipelines

🔮 Future Work
🌟 Implement LFU Cache for frequency-based eviction
🌐 Build a RESTful API integrating this cache with a database
⚖️ Compare with Python’s built-in OrderedDict LRU implementations

🙋‍♂️ Author
Shuai Qian （Alex Quinn）