For the sake of simplicity, I am dividing this into 3 parts:
- Variable Declaration
- Taking input and Declaring Output
- Operators and Expressions
1.Variable Declaration
Unlike other programming languages like c, cpp and java ,you don’t need to declare the type of a variable explicitly. This feature is called Dynamic Typing.
in C,
int a = 6;
here, the variable is declared as integer.
but in Python,
a = 6
and the variable a can be redeclared as
a = "hello world"
?️NOTE:
Variable names are case-sensitive., so a and A are considered different variables.
✨ Features and Rules In Declaration
- Variable names must begin with an alphabet or an underscore (_)
a = 6 #valid _a = 6 #valid -a = 6 #invalid
- The "_" variable stores the result of the last expression in interactive Python mode. This can be visible in Jupiter Notebook
a = 5 b = 6 a + b #11 print(_) #11
- In python, multiple variables can be declared in one line
a, b, c = 5, 6, 7
- Use the global keyword to modify a global variable inside a function
global x def print(): return x #there will be no error
- Unlike c and cpp ,Python does not have a built-in way to declare constants. By convention, variable names in all caps are treated as constants.
PI=3.14
2.Taking input and Declaring Output
print()
The print() function is a built-in Python function used to display output to the console.
a=10000 print("hello world") #hello world print("hello", "world")#hello world print("hello world",a) #hello world 10000
In print function, there are two main parameters.
- sep : It determines how multiple objects are separated when printed. It is usually preset to " ".
- end : It defines what is printed at the end of the output.It is usually preset to "n".
example:
print("hello world") print("hi") # hello world # hi
print("hello", "world", sep="-", end = " ") print("hi") # hello-world hi
for the complete documentation of print, click here
✨ Features of Print()
- You can use escape sequences (e.g., n for a newline, t for a tab, and __ for a backslash) to include special characters in the printed output.
print("hello\nworld") #hello #world print("hello\tworld") #hello world print("happy\trecking")#happy\trecking
- print() is often used for debugging and tracing code execution because it provides a quick way to output variable values and program state.
x = 5 y = 10 print(f"x: {x}, y: {y}") # x: 5, y: 10
input()
The input() function in Python is used to take user input from the console.
int a = 6;
?️NOTE:
By default, input() returns a string, so if you need to use the input as a different type (e.g., int, float), you need to convert it.
a = 6
In the upcoming blog, we'll delve into Python operators and conditional statements. Happy Learning???
The above is the detailed content of Day Mastering the Basics of Python. For more information, please follow other related articles on the PHP Chinese website!

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

Dealing with noisy images is a common problem, especially with mobile phone or low-resolution camera photos. This tutorial explores image filtering techniques in Python using OpenCV to tackle this issue. Image Filtering: A Powerful Tool Image filter

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Python, a favorite for data science and processing, offers a rich ecosystem for high-performance computing. However, parallel programming in Python presents unique challenges. This tutorial explores these challenges, focusing on the Global Interprete

This tutorial demonstrates creating a custom pipeline data structure in Python 3, leveraging classes and operator overloading for enhanced functionality. The pipeline's flexibility lies in its ability to apply a series of functions to a data set, ge

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

Dreamweaver Mac version
Visual web development tools

Notepad++7.3.1
Easy-to-use and free code editor

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft
