Python is one of the most versatile programming languages at a coder’s disposal. It is an object-oriented language with an extensive library of functions that can perform practically anything.
There are a number of Python Programming Questions for Practice that will help you understand this programming language better. These questions will cover various topics like list collections, tuples, dictionaries and sets.
What is a tuple?
A tuple is a data structure that is used in a variety of ways across multiple disciplines, including computer science and mathematics. Tuples are finite sequences of values that can be repeated, and they are an important part of the relational data model on which many database systems are based.
The tuple is also a convenient way to store values that may need to be accessed over and over again throughout a program. For example, a college might need to store the names of all its students in tuples. This would be much easier than storing all the students’ addresses in a list because the names would need to be accessed only once.
Another reason for using tuples is that they are immutable, which makes them safer to use than lists. This is especially important when working with data that is meant to remain constant throughout the life of a program. Tuples are sometimes used instead of lists when working with data structures like dictionaries or sets that require that one of the elements be an immutable value.
When working with tuples, it is important to note that whereas lists have square brackets to indicate the start and end of their contents, tuples have round parentheses. Tuples can be indexed like lists and can also be recursively expanded to include more values.
It is also possible to perform range indexing with tuples, which allows you to get a range of items from a tuple by starting at the first index and then adding or subtracting values to get each value in the tuple that you want. Tuples also respond to the + and * operators just like strings, meaning that they can be concatenated or repeated, but unlike lists, you cannot remove an individual tuple element once it has been created.
What is a list?
A list is one of four built-in Python data types that can be used to store collections of items. The others are Tuple, Set, and Dictionary. Lists are mutable, meaning that they can be changed after they are created. This allows for flexibility in the design of applications, as you can add and remove elements at will. This also means that lists can grow or shrink as needed.
Like other languages, Python has a set of functions to work with lists. These include functions such as res, sum, and max. They can be used to calculate or check the size of a list, find the maximum value, or even check whether a list is strictly increasing.
Another important function is range, which can be used to determine the length of a list. This can be useful when you need to know how many items are in a list before adding or removing them. It is also possible to use the function lrght(list) to find the largest item in a list.
In addition to these built-in functions, Python has a number of other ways to work with lists. One way is to use a list comprehension, which is a concise way of creating a list. This is done by using a for loop within square brackets. A list comprehension can be used to create a list of integers, a list of words, or even a list of colors.
Another way to work with lists is to use the ilist() and lislist() functions. These functions can be used to create a list of items or a list of items in a particular order. This can be helpful when you are working with a large list of items that need to be sorted by an order other than the default.
What is a dictionary?
Dictionaries are a data type in Python that holds a set of key-value pairs. They are a bit like lists in that they are dynamic and can grow and shrink throughout the course of a program, but differ in a few ways. Dictionaries are mutable, meaning that they can be updated with new items and old items can be removed.
In order to add a key-value pair to a dictionary, you have to use square bracket notation to create the key and then provide the value as the second argument. Once you have added an item to a dictionary, you can get the value by using the key as the index. You can also remove an item from a dictionary by using the del keyword. This will remove the key and associated value from the dictionary. However, the value is still stored in the variable so you can retrieve it later if needed.
Aside from the mutability, the other main difference between dictionaries and lists is that lookups for keys in a dictionary happen in constant time regardless of the size of the dictionary. This makes dictionaries much more performant than lists which require a lot of iteration to find the item you are looking for.
You can also do a few other things with dictionaries, like search for a particular key and if it is not present in the dictionary, return the default value that you specify. This is helpful if you are trying to do something that will change the default behavior of the dictionary. Alternatively, you can use the pop() method to remove a key-value pair from a dictionary but save the value for later retrieval.
What is a function?
A function is a set of code that performs a particular task. Programmers use functions to modularize a program, which allows it to run more efficiently. A function can return a value, or it may pass the control to the next statement in the program.
Functions can be used to perform iterative tasks, such as recursive operations. A recursive function calls itself over and over again until a condition is met. For example, the recursive function below calculates the sum of numbers from 0 to 10.
When writing a Python program, you must understand how functions work. For example, you must know that a function can only be called using the def keyword. You must also know that any variables created in a function are local variables; they can only be accessed by the function in which they are defined.
In Python, you can pass arguments to a function by using the __next__() method or by passing them by reference. When an argument is passed by reference, a copy of the actual object is passed. Changing the values of the actual object will change the value of the copy.
A function can be declared with the def keyword followed by a header, which ends with a colon. The header is followed by the function body, which consists of one or more Python statements that are indented a fixed amount (4 spaces is the default) from the def keyword. The last statement in the body of a function must be either break or continue. A function can also contain a docstring, which is a multiline string that describes what the function does. The docstring is displayed when the function is invoked.
What is a class?
In object-oriented programming, a class is a type that bundles data and functionality together. It defines a set of attributes that define the class’s state and also provides functions for maintaining and modifying that state. A class instance contains data that can be accessed by calling the class’s methods.
A class can be created in one of two ways: a class expression or a class declaration. A class expression can be anonymous or it can have a name that is different from the variable that it is assigned to. Class declarations are used to declare a new class or a tightly related class hierarchy. They can be either let or const and they are executed in strict mode regardless of whether or not the “use strict” directive is enabled.
The classes in a Python program are organized into modules, which provide a way to structure the code and logically organize it. A module is a group of Python commands, definitions, or executable code. A Python program is a collection of modules that are run in sequence to produce the desired output.
Modules allow for better code reuse, reducing the need to write repetitive code. They also help to keep the code organized and easier to read.
Python has a number of built-in libraries to perform common tasks such as string manipulation, datetime handling, and numeric computation. These libraries can be used to add new features to Python, or they can be used as a basis for writing your own applications. Some examples of the most popular libraries in Python are NumPy and SciPy. These libraries are useful for implementing scientific computing algorithms such as numerical integration, optimization, and machine learning.