Introduction

In Python, a tuple is a collection of ordered and immutable elements. This means its elements cannot be modified once a tuple is created. Tuples are similar to lists in Python, but have some key differences, which make them useful in certain situations.

Following are properties of Python sets:

• Ordered: Tuples maintain the order of data insertion
• Immutable: We can not modify tuples items
• Heterogeneous: Tuples can contain different types of data
• Duplicates: Tuples allow duplicate items

Types of Data That Can Be Stored in Python Lists

In Python, a tuple can store a collection of items of any data type. This means that a tuple can store elements of different types or a mix of types. For example, a tuple can store integers, strings, floats, and other tuples or lists. Here are a few examples of tuples that store different types of data:

# A tuple that stores integers and strings
my_tuple = (1, 2, 3, "hello", "world")

# A tuple that stores a mix of types
another_tuple = (1, 2.5, "hello", [1, 2, 3])

# A tuple that stores other tuples
nested_tuple = ((1, 2), (3, 4), (5, 6))

You can also store complex data structures, like classes and objects in a tuple. But it’s important to note that while the data inside a tuple is immutable, the objects or classes stored within them can still be mutable.

In summary, a Python tuple can store a collection of items of any data type, including integers, strings, floats, other tuples, lists, classes, and objects. 

Tuples built-in functions:

Implement tuple in python 

Here’s a basic example of how to create a tuple in Python:

# A tuple with three elements
my_tuple = (1, 2, 3)

# A tuple with a single element
another_tuple = (4,)  # The comma is necessary when creating a tuple with only one element

You can also create a tuple by using the tuple() function:
# Create a tuple from a list
my_list = [1, 2, 3]
my_tuple = tuple(my_list)

# Create a tuple from a string
my_string = "hello"
my_tuple = tuple(my_string)

Once a tuple is created, you can access its elements using indices, just like with lists. For example:

# Accessing the first element of a tuple
first_element = my_tuple[0]

# Accessing the last element of a tuple
last_element = my_tuple[-1]

You can also use negative indices to access elements from the end of the tuple.

One important difference between tuples and lists is that you can use tuples as keys in a dictionary, but you can’t use lists as keys. This is because keys in a dictionary must be immutable, and a tuple is immutable, whereas a list is not. For example:

# Using a tuple as a key in a dictionary
my_dict = {(1, 2): "hello"}

# Using a list as a key in a dictionary
# This will raise a TypeError
my_list = [1, 2]
my_dict = {my_list: "hello"}

You can also use the built-in len() function to get the length of the tuple and in keyword to check if an element is present in the tuple.

# Get the length of the tuple
tuple_len = len(my_tuple)

# Check if an element is present in the tuple
is_present = 2 in my_tuple

You can also perform some other common operations on tuples, such as concatenation and slicing:

# Concatenating two tuples
new_tuple = my_tuple + another_tuple

# Slicing a tuple
sliced_tuple = my_tuple[1:3] # Will create a new tuple containing elements at index 1 and 2

Another thing to note is that while Lists are mutable, Tuples are immutable, so you cannot modify its elements or add new elements to it.

# Changing the value of a tuple element will raise a TypeError
# my_tuple[0] = 100

# Adding new element to tuple will raise TypeError
# my_tuple.append(4)

Use Cases of Python tuples

Tuples in Python are commonly used in various situations because of their simple and efficient nature. Here are a few examples of when and how you might use tuples in your code:

1. As an ordered collection of elements: Tuples are ordered collections of elements, so they can be used to store a group of related items, such as a collection of coordinates, a list of colors, or a set of related configuration settings.
2. As a return value for a function: Tuples can be used as the return value for a function, which allows you to return multiple values from a single function call.
3. As a key in a dictionary: Tuples can be used as keys, allowing you to store values associated with a specific combination of items.
4. As an element of another data structure: Tuples can be elements of another data structure such as a list, set, etc.
5. As an immutable sequence: Tuples are immutable, which means that once they are created, their elements cannot be modified. This can be useful when you want to ensure that certain data remains constant throughout the lifetime of your program.
6. For efficient Data Storing: Tuples use less memory as compared to lists. Also, as they are immutable they need less processing power while working with them
7. For unpacking values: Python allows an assignment of multiple variables simultaneously from a tuple or list.
8. For comparison: You can use comparison operators on tuples and it will compare based on the element-by-element comparison in the tuple

These are just a few examples of the many ways you might use tuples in Python. Depending on your specific use case, there may be other benefits and features of tuples that make them a better choice than other data types.

Limitations of Python tuples

There are several limitations of Python tuples when compared to other data structures such as lists and dictionaries:

1. Immutability: Once a tuple is created, its elements cannot be modified. This means you cannot add, remove, or change the values of elements within a tuple.
2. Limited functionality: Because tuples are immutable, they do not have many of the built-in methods that lists have. For example, you cannot use the .append() or .remove() methods on a tuple.
3. Limited sorting capabilities: Sorting of tuples is only possible by creating a new tuple, or list, or using the sorted() method with a key as a custom sorting function
4. Performance: Because tuples are immutable, they use slightly less memory than lists. However, they may be slightly slower to work with than lists in some cases.
5. Concatenation and repetition: Concatenation and repetition can be achieved by using the + and * operators on a tuple but unlike a list, with a larger tuple, it can be memory and performance intensive

Overall, while tuples are useful in certain situations where immutability is important, they are generally less flexible and have fewer built-in capabilities than lists and dictionaries.