Hash Table Implementation in Python
Key Takeaways
- โPython's readability makes it ideal for learning Hash Table.
- โThe implementation achieves O(1) average time complexity.
- โPython's built-in data structures complement Hash Table implementations.
- โType hints improve code clarity and catch bugs early.
Hash Table in Python: Overview
Python Implementation
class HashTable:
def __init__(self, capacity: int = 16):
self.capacity = capacity
self.size = 0
self.buckets: list[list[tuple[str, any]]] = [[] for _ in range(capacity)]
def _hash(self, key: str) -> int:
return hash(key) % self.capacity
def put(self, key: str, value: any) -> None:
idx = self._hash(key)
for i, (k, _) in enumerate(self.buckets[idx]):
if k == key:
self.buckets[idx][i] = (key, value)
return
self.buckets[idx].append((key, value))
self.size += 1
if self.size > self.capacity * 0.75:
self._resize()
def get(self, key: str, default=None):
idx = self._hash(key)
for k, v in self.buckets[idx]:
if k == key: return v
return default
def delete(self, key: str) -> bool:
idx = self._hash(key)
for i, (k, _) in enumerate(self.buckets[idx]):
if k == key:
self.buckets[idx].pop(i)
self.size -= 1
return True
return False
def _resize(self) -> None:
old = self.buckets
self.capacity *= 2
self.buckets = [[] for _ in range(self.capacity)]
self.size = 0
for bucket in old:
for k, v in bucket:
self.put(k, v)
ht = HashTable()
ht.put("name", "Alice"); ht.put("age", 30)
print(ht.get("name")) # AliceStep-by-Step Explanation
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See PlansFrequently Asked Questions
Is Python good for implementing Hash Table?
Yes, Python is excellent for learning and implementing Hash Table. Its readable syntax makes the algorithm logic clear, and its standard library provides useful supporting data structures. While Python is slower than compiled languages, the asymptotic complexity is identical, making it perfect for understanding and interviews.
How does Python's built-in sort compare to Hash Table?
Python's built-in sort uses TimSort, a hybrid merge-sort and insertion-sort algorithm with O(n log n) worst case. Depending on Hash Table's complexity class, it may be faster or slower for specific inputs. Built-in sort is highly optimized in C, so it will outperform pure Python implementations.
Should I use type hints in my Hash Table Python code?
Yes, type hints improve code readability, enable better IDE support, and help catch type-related bugs early. They are especially valuable in algorithm implementations where the types of inputs and outputs should be clear to readers.
Can I use Hash Table in Python for large datasets?
For large datasets, consider the algorithm's complexity. If Hash Table has O(n) worst case, it may be slow for very large inputs. Python's NumPy and Pandas libraries offer optimized C-based alternatives for data-heavy operations.
What Python version should I use for Hash Table?
Use Python 3.10 or later for the best experience. Recent versions offer structural pattern matching, improved type hints, and performance improvements that benefit algorithm implementations.
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