Python Basics 6

Set in Python, Set Methods in Python, Hash Value

Index

1. Set in Python

2. Set Methods in Python

3. Hash Value

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1. Set in Python

Definition:
A set in Python is an unordered collection of unique elements. Sets are defined by curly braces {} or by using the set()function. Since sets do not allow duplicate elements, they are useful for eliminating duplicates and performing mathematical set operations like union, intersection, and difference.

Syntax:

# Creating a set with curly braces 

my_set = {1, 2, 3, 4} # Creating a set using the set() function 

my_set = set([1, 2, 3, 4])

Explanation:
Sets are optimized for fast membership testing, which means checking if an item is part of a set is very efficient. However, since sets are unordered, they do not support indexing, slicing, or other sequence-like behavior. This makes them different from lists and tuples.

Basic Example:

# Creating a set and adding an element 

fruits = {"apple", "banana", "cherry"} 

fruits.add("orange") print(fruits)

Output:{'banana', 'orange', 'cherry', 'apple'}

Advanced Example:

# Performing set operations 

set1 = {1, 2, 3} 

set2 = {3, 4, 5} 

# Union 

union_set = set1.union(set2) 

print(union_set) 

# Output: {1, 2, 3, 4, 5} 

# Intersection 

intersection_set = set1.intersection(set2) 

print(intersection_set) 

# Output: {3}

Rules/Exceptions:

• Sets cannot have mutable elements like lists or dictionaries as their members because these do not have a consistent hash value.

• While sets themselves are mutable, the elements inside a set must be immutable.

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2. Set Methods in Python

Definition:
Set methods are built-in functions that allow you to perform common set operations, such as adding or removing elements, and performing union, intersection, and difference operations.

Explanation:
Some of the commonly used set methods include:

• add(): Adds an element to the set.

• remove(): Removes a specific element from the set. If the element is not found, it raises a KeyError.

• discard(): Removes a specific element without raising an error if the element is not found.

• union(): Returns a new set with elements from both sets.

• intersection(): Returns a set that contains only elements found in both sets.

• difference(): Returns a set that contains elements in one set but not in another.

• clear(): Removes all elements from the set.

Basic Example:

# Using the add() and remove() methods 

numbers = {1, 2, 3} 

numbers.add(4) 

numbers.remove(2) 

print(numbers)

Output:{1, 3, 4}

Advanced Example:

# Using union() and difference() methods 

set1 = {"a", "b", "c"} 

set2 = {"b", "c", "d"} 

# Union 

union_set = set1.union(set2) 

print(union_set) 

# Output: {'a', 'b', 'c', 'd'} 

# Difference 

difference_set = set1.difference(set2) 

print(difference_set) 

# Output: {'a'}

Rules/Exceptions:

• The remove() method will raise an error if the element is not found, while discard() will not, which makes discard() safer in situations where the element might not be present.

• Operations like union and intersection do not modify the original sets unless explicitly assigned back.

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3. Hash Value

Definition:
A hash value is a unique identifier generated by a hash function for a data element (like an integer, string, or object). In Python, the hash() function is used to compute the hash value of an object. Hash values are important in sets and dictionaries because they determine how elements are stored and retrieved efficiently.

Explanation:
Hash values enable quick data retrieval in sets and dictionaries by converting keys or elements into a fixed-size integer. The hash() function is only applicable to immutable objects like strings, numbers, and tuples. Mutable objects like lists and dictionaries cannot be hashed because their content can change, leading to an inconsistent hash value.

Basic Example:

# Hashing an integer and a string 

hash_int = hash(42) 

hash_str = hash("Python") 

print(hash_int) 

print(hash_str)

Advanced Example:

# Using hash values in a custom object
class Student:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def __hash__(self):
        return hash((self.name, self.age))

# Creating a set of students
student1 = Student("Vishal", 25)
student2 = Student("Raj", 24)
student_set = {student1, student2}
print(student_set)

Rules/Exceptions:

• Immutable objects like strings, numbers, and tuples are hashable, while mutable objects like lists, dictionaries, and sets are not.

• Hash values are used internally by Python to optimize performance in data structures like sets and dictionaries, enabling constant time complexity for lookups.

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Conclusion

In this edition of FM University, we explored sets in Python, their methods, and the concept of hash values. Understanding these topics is crucial for working efficiently with collections of unique items and performing set operations. The concept of hash values is foundational for data structures that require fast access, such as sets and dictionaries.

- Vishal Rajput