search
HomeBackend DevelopmentPython TutorialDay Our First Python Program | Days Python

Day Our First Python Program |  Days Python

Day 3: Modules and Pip | 100 Days Python

Python is a fantastic language for beginners and experienced developers alike. Today, we’re diving into the foundational concepts to set you up for success with your very first Python program. From understanding functions to writing and running your own code, we'll guide you step-by-step so you can follow along and get hands-on with Python programming. This guide will focus on understanding each line of code and seeing how Python executes it.


Why “Hello World” in Python?

In programming, the "Hello World" program is traditionally the first step for beginners. It helps you verify that your development environment is set up correctly and allows you to see how code flows in action. When you execute this program in Python, you'll gain a clearer understanding of how functions work, how to print output to the console, and how to structure Python code.

Setting Up Your Python Environment

To get started, open your preferred code editor or environment, like Replit, VSCode, or a Python terminal. We'll be using a Python script to demonstrate how code runs line-by-line, but any setup that can interpret Python will work just as well. You may also want to follow along using the REPL (Read, Evaluate, Print, Loop) for interactive learning.


Writing Your First Python Code: The Print Function

In Python, the print() function is commonly used to output text to the console. This function is foundational and allows us to display any message or result we want.

Let’s take a look at our very first line of code in Python:

print("Hello World")

Understanding the Code

  1. print - This is a built-in Python function designed to display the text or data inside the parentheses on the screen.
  2. Parentheses () - Parentheses are used in Python to invoke or call functions. When you type print(), you’re calling the print function.
  3. Quotation Marks "" - Anything within double quotes (or single quotes) is interpreted as a string—a series of characters. Here, "Hello World" is our string.

When you run this code, the output will be:

Hello World

Common Errors in Python

It’s easy to make minor mistakes, especially as a beginner. Let’s discuss a common error you might encounter.

If you mistakenly type:

print(Hello World)

You’ll receive a syntax error because Python doesn’t recognize Hello World as a string without the quotation marks. To fix this, simply place double or single quotes around Hello World.

Running Code Line-by-Line with Scripts

Scripts allow us to write multiple lines of code that execute sequentially. For example, you can add multiple print statements in a script, and Python will run each line in order. Here’s a short script to illustrate this:

print("Hello World")

Expected Output

Hello World

This method ensures each line runs one after the other, from top to bottom. It’s a practical way to execute code, especially when working with longer programs.

Python for Basic Arithmetic

Python is not only great for printing text; it can also handle arithmetic operations. You can use basic operators within the print function to calculate and display results:

print(Hello World)

This code multiplies 17 by 13 and outputs the result, 221. You can use other operators like (addition), - (subtraction), / (division), and * (multiplication) in the same way.

Here’s another example:

print("Hello World")
print(5)
print("Goodbye!")

The output here would be:

Hello World
5
Goodbye!

Using the REPL for Instant Feedback

If you’re using a Python REPL (Read, Evaluate, Print, Loop) environment, you can execute single commands and immediately see their results. For instance, typing 8 9 in the REPL will instantly show 17.

Example

print(17 * 13)

In a script, however, Python will execute a set of instructions in order. This is useful when you want to automate a sequence of steps rather than input each command individually.


Committing to 100 Days of Code

The 100 Days of Code challenge is an excellent way to commit to learning Python. However, consistency is key, and taking on this challenge means dedicating yourself to daily practice. If you’re looking for shortcuts, this course may not be for you; programming requires steady, hands-on practice.

Leave your progress in the comments with "I’m present," and keep practicing to make the most of your coding journey. Remember, there’s no elevator to success—you have to take the stairs!

What’s Next?

This introduction is just the beginning. We’ll cover more advanced topics in the upcoming blogs and write more complex programs. Each lesson will build on the previous one, helping you deepen your understanding of Python step-by-step.

Stay consistent, keep practicing, and you’ll soon find yourself more comfortable with Python. Enjoy your journey through the 100 Days of Code, and remember, Python is a powerful tool that can open doors to countless opportunities in technology.

Buy me a Coffee

The above is the detailed content of Day Our First Python Program | Days Python. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Explain the performance differences in element-wise operations between lists and arrays.Explain the performance differences in element-wise operations between lists and arrays.May 06, 2025 am 12:15 AM

Arraysarebetterforelement-wiseoperationsduetofasteraccessandoptimizedimplementations.1)Arrayshavecontiguousmemoryfordirectaccess,enhancingperformance.2)Listsareflexiblebutslowerduetopotentialdynamicresizing.3)Forlargedatasets,arrays,especiallywithlib

How can you perform mathematical operations on entire NumPy arrays efficiently?How can you perform mathematical operations on entire NumPy arrays efficiently?May 06, 2025 am 12:15 AM

Mathematical operations of the entire array in NumPy can be efficiently implemented through vectorized operations. 1) Use simple operators such as addition (arr 2) to perform operations on arrays. 2) NumPy uses the underlying C language library, which improves the computing speed. 3) You can perform complex operations such as multiplication, division, and exponents. 4) Pay attention to broadcast operations to ensure that the array shape is compatible. 5) Using NumPy functions such as np.sum() can significantly improve performance.

How do you insert elements into a Python array?How do you insert elements into a Python array?May 06, 2025 am 12:14 AM

In Python, there are two main methods for inserting elements into a list: 1) Using the insert(index, value) method, you can insert elements at the specified index, but inserting at the beginning of a large list is inefficient; 2) Using the append(value) method, add elements at the end of the list, which is highly efficient. For large lists, it is recommended to use append() or consider using deque or NumPy arrays to optimize performance.

How can you make a Python script executable on both Unix and Windows?How can you make a Python script executable on both Unix and Windows?May 06, 2025 am 12:13 AM

TomakeaPythonscriptexecutableonbothUnixandWindows:1)Addashebangline(#!/usr/bin/envpython3)andusechmod xtomakeitexecutableonUnix.2)OnWindows,ensurePythonisinstalledandassociatedwith.pyfiles,oruseabatchfile(run.bat)torunthescript.

What should you check if you get a 'command not found' error when trying to run a script?What should you check if you get a 'command not found' error when trying to run a script?May 06, 2025 am 12:03 AM

When encountering a "commandnotfound" error, the following points should be checked: 1. Confirm that the script exists and the path is correct; 2. Check file permissions and use chmod to add execution permissions if necessary; 3. Make sure the script interpreter is installed and in PATH; 4. Verify that the shebang line at the beginning of the script is correct. Doing so can effectively solve the script operation problem and ensure the coding process is smooth.

Why are arrays generally more memory-efficient than lists for storing numerical data?Why are arrays generally more memory-efficient than lists for storing numerical data?May 05, 2025 am 12:15 AM

Arraysaregenerallymorememory-efficientthanlistsforstoringnumericaldataduetotheirfixed-sizenatureanddirectmemoryaccess.1)Arraysstoreelementsinacontiguousblock,reducingoverheadfrompointersormetadata.2)Lists,oftenimplementedasdynamicarraysorlinkedstruct

How can you convert a Python list to a Python array?How can you convert a Python list to a Python array?May 05, 2025 am 12:10 AM

ToconvertaPythonlisttoanarray,usethearraymodule:1)Importthearraymodule,2)Createalist,3)Usearray(typecode,list)toconvertit,specifyingthetypecodelike'i'forintegers.Thisconversionoptimizesmemoryusageforhomogeneousdata,enhancingperformanceinnumericalcomp

Can you store different data types in the same Python list? Give an example.Can you store different data types in the same Python list? Give an example.May 05, 2025 am 12:10 AM

Python lists can store different types of data. The example list contains integers, strings, floating point numbers, booleans, nested lists, and dictionaries. List flexibility is valuable in data processing and prototyping, but it needs to be used with caution to ensure the readability and maintainability of the code.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

SublimeText3 English version

SublimeText3 English version

Recommended: Win version, supports code prompts!

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.