In hashing, you deploy an algorithm for the purpose of mapping data of any size but to a fixed length.
Hash functions are used to compute hash values.
What is a hash ?
A hash is a fixed-size integer that identifies a specific value. Each value should have its particular hash such that you will obtain the same hash even if it is not the same object for the same value.
>>> f = “Life is wonderful!”
Hash Tables and Hashmaps in Python
In the scope of computing science terminology, let’s see what is a hash table and hashmap.
A map is considered to be an associative container mapping from a key to a value. A map can be implemented in several ways including a binary tree or a hash table.
A hash table is a design for storing arbitrary data, and that data need not comprise a separate key and value.
Hence, a hash table stores elements, each of which need not have a unique key and value elements; in case it has, it is also a hashmap.
You can use the principle of hash tables in applications including database indexing, caching, password authentication etc.
Python hash( ) function
There are several things that depend on the concept of hash, and hash table is an important one.
Python consists of a built-in function to generate the hash of an object i.e. the hash ( ) function.
This function considers an object as input and returns the hash as an integer.
By default, only immutable types are hashable in Python. These include integers, strings, or tuples.
What is a good hash function?
A hash function is regarded a good hash function in the following cases:
- It mitigates the amount of collision as much as it can
- It should not produce the bucket locations that are bigger than the hash table.
- The hash function should be a good address of the hash table.
- The hash function should be simple to comprehend and easy to compute.
- The hash function should generate the keys that will get distributed uniformly in the case of an array.
- When all the input data is used, the hash function becomes the ideal one.
- An efficient hash function should map the keys in an evenly manner.
- The cost of implementing a hash function must be small such that applying the hashing technique turns out a good option.
Dictionaries in Python : the way of implementing hash tables
A dictionary is a set of key value pairs. Dictionaries are the most vital Python implementation.
They have a good relationship between the key and value pairs. When you need to capture unique objects in any alogrithm, dictionaries are the ideal choice.
Python dictionaries are also created with the help of hash tables. The Python dictionary is defined as follows:
… “Tendulkar”: 887,
… “Dhoni”: 836,
… “Kohli”: 844,
… “Sharma”: 813,
… “Rahane”: 535,
Here we have formed a dictionary named cricket_players that comprises some Indian cricket players and their world rating.
In order to retrieve a key value, you just need to specify the key with the help of square brackets.
Advantages of hash tables
- Speed is the primary advantage of hash table in comparison to other data structures. This becomes more evident when the number of entries is huge.
- Hashtables are specifically efficient when the maximum number of entries can be forecasted. Hence the bucket array can be assigned once with the optimum size with no need of resizing.
- A hash table has a great advantage over address tables in the sense that it maintains the size constraint.
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