Dictionaries in Python programming language

Dictionaries in Python programming language

• 1.
  Dictionaries in Python
• 2.
  What are Dictionaries? •Key-value pair data structures • Unordered, mutable, and dynamic • Also known as associative arrays or hash maps in other languages
• 3.
  Dictionary Basics • Createdusing curly braces {} • Each item has a key and value, separated by colon : • Keys must be unique and immutable student = { "name": "John Smith", "age": 20, "major": "Computer Science" }
• 4.
  Multiple ways tocreate dictionaries # Empty dictionary dict1 = {} dict2 = dict() # Using dict() constructor dict3 = dict(name="John", age=20) # From list of tuples pairs = [("apple", 1), ("banana", 2)] dict4 = dict(pairs)
• 5.
  Accessing Values • Usingsquare bracket notation [ ] • Using get() method (safer) student = {"name": "John", "age": 20} # Using brackets print(student["name"]) # Output: John # Using get() print(student.get("age")) # Output: 20 print(student.get("grade", "N/A")) # Default value if key doesn't exist
• 6.
  Modifying Dictionaries student ={"name": "John", "age": 20} # Adding new key-value pair student["grade"] = "A" # Updating existing value student["age"] = 21 # Updating multiple values student.update({"age": 22, "major": "Physics"})
• 7.
  Several methods toremove items student = {"name": "John", "age": 20, "grade": "A"} # Remove specific key del student["grade"] # Pop item with specified key student[“score”] = student.pop("grade") # Remove and return last item last_item = student.popitem() # Clear all items student.clear()
• 8.
  Common dictionary methods •keys() - Returns list of all keys • values() - Returns list of all values • items() - Returns list of key-value pairs student = {"name": "John", "age": 20} print(student.keys()) print(student.values()) print(student.items())
• 9.
  Creating dictionaries using comprehension #Square numbers squares = {x: x**2 for x in range(5)} # Result: {0: 0, 1: 1, 2: 4, 3: 9, 4: 16} # Filtering with conditions even_squares = {x: x**2 for x in range(5) if x % 2 == 0} # Result: {0: 0, 2: 4, 4: 16}
• 10.
  Dictionaries can containother dictionaries students = { "John": { "age": 20, "grades": {"math": "A", "physics": "B"} }, "Mary": { "age": 19, "grades": {"math": "B", "physics": "A"} } }
• 11.
  Common Use Cases •Search • Counting occurrences • Configuration settings • Caching results • Graph representations • JSON-like data structures
• 12.
  Dictionary Performance • O(1)average case for insertions, deletions, and lookups • Hash table implementation • Comparison with lists: • Lists: O(n) for search • Dictionaries: O(1) for search
• 13.
  Slide 12: MemoryUsage • Higher memory usage than lists • Each key-value pair stores: • Hash of the key • Key itself • Value • Additional metadata
• 14.
  Slide 13: BestPractices • Use meaningful keys • Check for key existence before access • Use get() with default values • Consider using collections.defaultdict • Keep keys immutable
• 15.
  Slide 14: CommonPitfalls # Mutable keys (will raise TypeError) bad_dict = {[1, 2]: "value"} # Error! # Key doesn't exist student["grade"] # KeyError if 'grade' doesn't exist # Modifying while iterating for key in d: d[key+1] = 0 # Bad practice!
• 16.
  Special Dictionary TypesFrom collections from collections import defaultdict, OrderedDict, Counter # defaultdict - provides default values d = defaultdict(list) d["new_key"].append(1) # No KeyError! # OrderedDict - maintains insertion order (pre-Python 3.7) od = OrderedDict() # Counter - counts occurrences c = Counter(['a', 'b', 'a', 'c', 'a'])
• 17.
  Dictionary Views • Dynamicviews of dictionary entries d = {"a": 1, "b": 2} keys = d.keys() values = d.values() items = d.items() # Views update automatically d["c"] = 3 print(keys) # dict_keys(['a', 'b', 'c'])
• 18.
  Type Hints withDictionaries from typing import Dict, List, Union # Simple dictionary grades: Dict[str, float] = {"math": 95.5, "physics": 89.0} # Complex dictionary student: Dict[str, Union[str, int, List[str]]] = { "name": "John", "age": 20, "courses": ["math", "physics"] }
• 19.
  Set-like operations withdictionary views d1 = {"a": 1, "b": 2} d2 = {"b": 3, "c": 4} # Keys operations keys1 = d1.keys() keys2 = d2.keys() # Union, intersection, difference print(keys1 | keys2) # Union print(keys1 & keys2) # Intersection print(keys1 - keys2) # Difference
• 20.
  Real-world Example def word_frequency(text:str) -> Dict[str, int]: """Count word frequencies in text.""" words = text.lower().split() frequency = {} for word in words: frequency[word] = frequency.get(word, 0) + 1 return frequency text = "the quick brown fox jumps over the lazy dog" print(word_frequency(text))
• 21.
  Practice Exercises • Createa phone book dictionary • Implement a cache using dictionary • Count character frequencies in a string • Create a nested dictionary for a school database • Implement a simple graph using dictionary • Python Documentation • Real Python Tutorials • Python Cookbook