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In Python, the collections module offers specialized container datatypes that solve real-world coding challenges with elegance and efficiency. These tools are interview favorites for optimizing time complexity and writing clean, professional code! 💡
import collections
# defaultdict - Eliminate key errors with auto-initialization
from collections import defaultdict
gradebook = defaultdict(int)
gradebook['Alice'] += 95
print(gradebook['Alice']) # Output: 95
print(gradebook['Bob']) # Output: 0
# defaultdict for grouping operations
anagrams = defaultdict(list)
words = ["eat", "tea", "tan"]
for w in words:
key = ''.join(sorted(w))
anagrams[key].append(w)
print(anagrams['aet']) # Output: ['eat', 'tea']
# Counter - Frequency analysis in one line
from collections import Counter
text = "abracadabra"
freq = Counter(text)
print(freq['a']) # Output: 5
print(freq.most_common(2)) # Output: [('a', 5), ('b', 2)]
# Counter arithmetic for problem-solving
inventory = Counter(apples=10, oranges=5)
sales = Counter(apples=3, oranges=2)
print(inventory - sales) # Output: Counter({'apples': 7, 'oranges': 3})
# namedtuple - Self-documenting data structures
from collections import namedtuple
Employee = namedtuple('Employee', 'name role salary')
dev = Employee('Alex', 'Developer', 95000)
print(dev.role) # Output: Developer
print(dev[2]) # Output: 95000
# deque - Optimal for BFS and sliding windows
from collections import deque
queue = deque([1, 2, 3])
queue.append(4)
queue.popleft()
print(queue) # Output: deque([2, 3, 4])
queue.rotate(1)
print(queue) # Output: deque([4, 2, 3])
# OrderedDict - Track insertion order (LRU cache essential)
from collections import OrderedDict
cache = OrderedDict()
cache['A'] = 1
cache['B'] = 2
cache.move_to_end('A')
cache.popitem(last=False)
print(list(cache.keys())) # Output: ['B', 'A']
# ChainMap - Manage layered configurations
from collections import ChainMap
defaults = {'theme': 'dark', 'font': 'Arial'}
user_prefs = {'theme': 'light'}
settings = ChainMap(user_prefs, defaults)
print(settings['font']) # Output: Arial
# Practical Interview Tip: Anagram detection
print(Counter("secure") == Counter("rescue")) # Output: True
# Pro Tip: Sliding window maximum
def max_sliding_window(nums, k):
dq, result = deque(), []
for i, n in enumerate(nums):
while dq and nums[dq[-1]] < n:
dq.pop()
dq.append(i)
if dq[0] == i - k:
dq.popleft()
if i >= k - 1:
result.append(nums[dq[0]])
return result
print(max_sliding_window([1,3,-1,-3,5,3,6,7], 3)) # Output: [3,3,5,5,6,7]
# Expert Move: Custom LRU Cache implementation
class LRUCache:
def __init__(self, capacity):
self.cache = OrderedDict()
self.capacity = capacity
def get(self, key):
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(self, key, value):
if key in self.cache:
del self.cache[key]
self.cache[key] = value
if len(self.cache) > self.capacity:
self.cache.popitem(last=False)
cache = LRUCache(2)
cache.put(1, 10)
cache.put(2, 20)
cache.get(1)
cache.put(3, 30)
print(list(cache.cache.keys())) # Output: [2, 1, 3] → Wait! Correction: Should be [1, 3] (capacity=2 triggers eviction of '2')
# Bonus: Multiset operations with Counter
primes = Counter([2, 3, 5, 7])
odds = Counter([1, 3, 5, 7, 9])
print(primes | odds) # Output: Counter({3:1, 5:1, 7:1, 2:1, 9:1, 1:1})
By: @DatascienceN🌟
#Python #CodingInterview #DataStructures #collections #Programming #TechJobs #Algorithm #LeetCode #DeveloperTips #CareerGrowth
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