Unordered Map In Python

collision in hashing

Introduction to Unordered Maps 

The unordered map in python is a dynamic, efficient container for fast key-based operations, leveraging a hash table for optimal performance. Its strategic key hashing ensures consistent randomization, providing speed and reliability—ideal for managing large datasets and complex algorithms.

Let’s jump into the article to know more about Unordered Maps in Python.

Understanding Unoredred Map

Collision in hashing occurs when two different pieces of data produce the same hash value. This can happen due to the finite size of the hash table and the infinite number of possible data inputs. Collisions are a common challenge in hash tables, and they need to be managed effectively to maintain the integrity of the data structure.

Unordered Maps Python with Example


Unordered Map Techniques


In Python, the equivalent to C++’s unordered map is the dict (dictionary) data type. Here are some techniques and tips for working with dictionaries in Python:

1. Creating a Dictionary:
Use curly braces {} or the dict() constructor to create a dictionary.

my_dict = {"apple": 5, "banana": 3}

2. Inserting and Updating Elements:
Use square brackets to insert or update elements in a dictionary.


my_dict["apple"] = 7 # Update value for key "apple"
my_dict["orange"] = 4 # Insert new key-value pair

3. Accessing Elements:
Access elements using the key.


count = my_dict["apple"]

You can also use the get method to access a key with a default value if the key does not exist.


count = my_dict.get("apple", 0) # Default value is 0 if "apple" is not in the dictionary

4. Checking Existence:
Use the in keyword to check if a key exists in the dictionary.


if "banana" in my_dict:
# Key exists

5. Iterating Through Elements:
Use a for loop to iterate through keys, values, or key-value pairs.

for key in my_dict:
print("Key:", key, "Value:", my_dict[key])
for key, value in my_dict.items():
print("Key:", key, "Value:", value)

6. Deleting Elements:
Use the del keyword or the pop method to remove elements by key.


del my_dict["apple"]
value = my_dict.pop("banana")

7. Dictionary Comprehensions:
Use dictionary comprehensions for concise creation and transformation of dictionaries.


squares = {x: x**2 for x in range(5)}

8. Handling Missing Keys:
If you are unsure whether a key exists, you can use the setdefault method or the defaultdict from the collections module to handle missing keys more gracefully.


my_dict.setdefault("apple", 0) # Set default value if key is not present
from collections import defaultdict
my_dict = defaultdict(int)


9. Copying Dictionaries:
Be careful when copying dictionaries. Use the copy method or the dict constructor to create a shallow 

my_copy = my_dict.copy()

10. OrderedDict:
If you need to maintain the order of insertion, consider using collections.OrderedDict.

from collections import OrderedDict
ordered_dict = OrderedDict({"apple": 5, "banana"

Unordered Map

In Python, the closest equivalent to C++’s unordered map is the dict (dictionary) data type. The dict in Python is a hash table implementation that allows you to store key-value pairs. Here’s a simple example of using a dictionary as an unordered map in .

Implementation of Unordered Set In Python

# Creating an empty dictionary
my_dict = {}

# Inserting key-value pairs
my_dict["apple"] = 5
my_dict["banana"] = 3
my_dict["orange"] = 7

# Accessing elements
print("Number of apples:", my_dict["apple"])

# Checking existence
if "banana" in my_dict:
print("Banana is in the dictionary")

# Iterating through elements
for key, value in my_dict.items():
print("Key:", key, "Value:", value)

# Deleting elements
del my_dict["orange"]
print("Dictionary after deleting orange:", my_dict)

# Handling missing keys
default_value = my_dict.get("grape", 0)
print("Number of grapes (default 0):", default_value)

Explanation : 

  • Creating a Dictionary: my_dict = {} creates an empty dictionary.
  • Inserting and Updating Elements: my_dict[“apple”] = 5 adds a key-value pair. Use square brackets to insert or update elements.
  • Accessing Elements:
  • Access elements using the key: my_dict[“apple”].
  • get method allows accessing with a default value.
  • Checking Existence:
  • Check if a key exists using the in keyword.
  • Iterating Through Elements:for key, value in my_dict.items(): iterates through key-value pairs.
  • Use for key in my_dict: to iterate through keys.
  • Deleting Elements: Use del keyword or pop method to remove elements by key.
  • Handling Missing Keys: setdefault method or defaultdict from collections can handle missing keys.
  • Copying Dictionaries: Create a shallow copy using copy method or dict constructor.
  • OrderedDict: If order of insertion matters, use OrderedDict from collections.
  • Flexible and Powerful: Python dictionaries are versatile and powerful for a wide range of use cases.

Advantages of Unordered Sets


In conclusion, unordered maps, or dictionaries in Python, offer a powerful and flexible data structure for storing and retrieving key-value pairs. Their advantages include fast lookup times, flexibility with key types, dynamic sizing, efficient memory usage, and ease of use. The underlying hashing mechanism enables constant-time average complexity for essential operations, making unordered maps suitable for a variety of applications.

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