Python 3: Project-based Python, Algorithms, Data Structures - Project: Job Scheduler execution flow

The video tutorial explains hash maps, focusing on their structure, hash functions, and search performance. It highlights the constant time complexity of hash maps and discusses handling collisions. The tutorial concludes with a brief overview of implementing hash maps in Python using dictionaries.

What is the primary advantage of using a hash map over a binary search?

• It is easier to implement.

• It provides constant time complexity for search operations.

• It works better with unsorted data.

• It requires less memory.

What is a key requirement for a key used in a hash map?

• It must be an immutable data type.

• It must be a floating-point number.

• It must be a list.

• It must be a mutable data type.

What does a hash function do with a key in a hash map?

• It converts the key into a unique string.

• It sorts the keys in ascending order.

• It maps the key to a specific index.

• It encrypts the key.

How does searching in a hash map achieve constant time complexity?

• By using a binary search algorithm.

• By accessing the index directly using the hash function.

• By sorting the data before searching.

• By storing data in a linked list.

What is a collision in the context of hash maps?

• When two keys map to the same index.

• When a key cannot be hashed.

• When a key is not found in the hash map.

• When a hash function fails to produce an output.

How can collisions be handled in a hash map?

• By deleting the existing record.

• By creating a list at the index and appending the new record.

• By ignoring the new record.

• By rehashing the entire map.

In Python, what data structure is typically used to implement a hash map?

• List

• Dictionary

• Set

• Tuple