West Midlands | 26 March SDC | Iswat Bello | Sprint 2 | Implement an LRU cache in python#193
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Iswanna wants to merge 10 commits into
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West Midlands | 26 March SDC | Iswat Bello | Sprint 2 | Implement an LRU cache in python#193Iswanna wants to merge 10 commits into
Iswanna wants to merge 10 commits into
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- Add 'key' attribute to Node to facilitate dictionary cleanup during eviction - Maintain pointers for doubly linked list functionality
- Initialize head and tail pointers for the Doubly Linked List - Add documentation explaining MRU (head) and LRU (tail) logic
- Add logic to insert nodes at the front of the list (Most Recently Used) - Ensure tail pointer is set correctly when adding to an empty list - Update previous/next pointers of existing head to maintain bi-directional links
- Add logic to remove and return the least recently used (tail) node - Handle single-node list resets by clearing both head and tail pointers - Ensure the new tail's 'next' pointer is cleared to prevent memory leaks
- Add logic to disconnect a node from any position in the list - Update head and tail pointers when removing boundary nodes - Nullify removed node pointers to ensure a clean disconnection
- Add constructor with validation to ensure limit is at least 1 - Initialize dictionary for O(1) key-to-node lookups - Initialize LinkedList to track item access order
- Add O(1) lookup functionality using the dictionary - Implement move-to-front logic to mark accessed items as Most Recently Used - Return None for keys not present in the cache
- Add logic to update existing keys and move them to the front (MRU) - Implement eviction of the Least Recently Used (tail) node when the limit is reached - Ensure the lookup dictionary and linked list stay synchronized during eviction - Add new nodes to both the dictionary and the front of the list
- Verify that updating existing keys correctly refreshes their MRU status - Test edge case for a cache with a limit of one - Add test for retrieving non-existent keys (returning None) - Confirm support for complex data types like lists and dictionaries
- Explain hybrid architecture (Dictionary + Doubly Linked List) - Document the "why" behind O(1) time complexity requirements - Detail the space-vs-time trade-off used in the design - Summarize testing strategy for edge cases and eviction logic
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| def __init__(self, key, value): | ||
| self.key = key | ||
| self.value = value | ||
| self.next = None | ||
| self.previous = None |
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To practice code reuse, you could import the linked list you implemented in the other exercise and store the key-value pairs as a tuple in each node.
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Thank you for the suggestion.
By storing the key and value together as a tuple inside the node, I could use the Linked List I already built without having to write a new one for this file. Thanks for the suggestion.
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Learners, PR Template
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Changelist
In this PR, I have implemented a standalone LRU (Least Recently Used) Cache. This task required building a purpose-built Doubly Linked List and Dictionary hybrid to ensure O(1) worst-case time complexity for both
getandsetoperations.A detailed explanation of the architecture and the logic behind the pointer management is available in the
CHANGES_MADE.mdfile.Key Features
NodeandLinkedListclass specifically for the requirements of an LRU Cache, separate from previous tasks.Nodeclass to store both keys and values. This enables the "reverse lookup" required to synchronize the dictionary when a node is evicted from the tail of the list.limitis reached.Testing Done
Verified the implementation with
unittestinlru_cache_test.py, including:getoperations move items to the front of the list.Learning Reflection
This implementation demonstrates the Space-vs-Time trade-off. By using extra memory for a dictionary and a bidirectional linked list, I ensured that the speed of the system is not sacrificed as the data set grows.