Python 3. x refers to the family of major versions (3.0, 3.1, 3.2, and so on) of the Python programming language that was released after Python 2.7. Python 3.0 was a significant and intentional departure from Python 2. x, aimed at improving the language’s design, addressing inconsistencies, and modernizing its features. The “x” in “3. x” represents the specific version number within the Python 3 family.

Here are some of the benefits of using Python-3.x:

• Unicode support: Python-3.x is a Unicode-only language, which means that all strings are represented as Unicode. This makes it easier to work with text data in Python-3.x.
• New features: Python-3.x has a number of new features, such as the print statement, division, and exceptions. These features make Python-3.x more powerful and expressive.
• Performance: Python-3.x is generally faster than Python-2. This is because Python-3.x uses a more efficient garbage collector.
• Backward compatibility: Python-3.x is backward compatible with most Python-2 code. This means that you can typically run Python-2 code in Python-3.x without any changes.

What are the top use cases of Python-3.x?

Python 3. x is a general-purpose programming language that can be used for a wide variety of tasks. However, some of the top use cases of Python 3. x include:

• Web development: Python is a popular language for web development. It is used to create web applications, websites, and web services.
• Data science: Python is a powerful language for data science. It is used to analyze data, build machine learning models, and create data visualizations.
• Machine learning: Python is a popular language for machine learning. It is used to build machine learning models, train and deploy models, and evaluate model performance.
• Natural language processing: Python is a powerful language for natural language processing. It is used to extract meaning from text, build chatbots, and create text analytics applications.
• Systems programming: Python can be used for systems programming. It is used to write operating systems, device drivers, and embedded systems software.

What are features of Python-3.x?

Python 3.x is a major revision of the Python programming language, with many new features and changes. Some of the key features of Python 3.x include:

• Unicode support: Python 3.x is a Unicode-only language, which means that all strings are represented as Unicode. This makes it easier to work with text data in Python 3.x.
• New print statement: The print statement in Python 3.x has been changed. In Python 2, the print statement could be used to print any type of object. In Python 3, the print statement can only be used to print strings.
• Division: Division in Python 3.x is now always a floating-point division. In Python 2, division could be either floating-point or integer division, depending on the types of the operands.
• Exceptions: The exception handling system in Python 3.x has been changed. In Python 2, exceptions were handled using the try/except/finally statements. In Python 3, exceptions are handled using the try/except/else/finally statements.
• New data types: Python 3. x introduces a number of new data types, such as bytes, byte array, and collections.Counter types.
• New operators: Python 3.x introduces a number of new operators, such as the walrus operator (:=) and the augmented assignment operators.
• New modules: Python 3. x includes a number of new modules, such as the collections, DateTime, and pathlib modules.

What is the workflow of Python-3.x?

The workflow of Python-3.x is the process of writing, running, and debugging Python code. The basic steps involved in the workflow are:

• Write the code: The first step is to write the Python code. This can be done in a text editor or in an integrated development environment (IDE).
• Run the code: Once the code is written, it can be run. This can be done by using the Python command from the command line or by running the code from within an IDE.
• Debug the code: If the code does not run correctly, it will need to be debugged. This involves finding and fixing the errors in the code.
• Repeat: The steps above can be repeated as needed until the code is working correctly.

How Python-3.x Works & Architecture?

Python-3.x is an object-oriented programming language. This means that everything in Python is an object, including numbers, strings, and functions. Objects have properties and methods. Properties are data associated with an object, and methods are actions that can be performed on an object.

Python-3.x is an interpreted language. This means that the code is not compiled into machine code before it is executed. Instead, the Python interpreter reads the code and executes it line by line. This makes Python-3.x a very flexible language, as it can be used on a wide variety of platforms.

The architecture of Python-3.x is based on the following components:

• The interpreter: The interpreter is the program that executes Python code. It reads the code line by line and executes it.
• The standard library: The standard library is a collection of modules that are included with Python. These modules provide a wide variety of functionality, such as file I/O, data structures, and networking.
• Third-party modules: There are a large number of third-party modules available for Python. These modules provide additional functionality, such as machine learning, web development, and scientific computing.

How to Install and Configure Python-3.x?

Installing and configuring Python 3.x is a straightforward process. Here’s a step-by-step guide to help you install and configure Python 3.x on your system:

1. Download Python:

Visit the official Python website at https://www.python.org/downloads/ and download the latest version of Python 3.x for your operating system (Windows, macOS, or Linux).

2. Installation:

Follow the installation steps based on your operating system:

For Windows:

• Run the downloaded executable file.
• Check the box that says “Add Python X.Y to PATH” (where X.Y represents the version number).
• Click “Install Now.”

For macOS:

• Run the downloaded installer package.
• Follow the installation prompts.
• Python may already be installed on macOS. To check, open the Terminal and type python3 –version.

For Linux:

• Open a terminal.
• Navigate to the directory where the downloaded file is located.
• Run the following commands:

tar -xvf Python-X.Y.Z.tgz
cd Python-X.Y.Z
./configure
make
sudo make install

3. Verify Installation:

After installation, verify that Python 3.x is installed correctly:

• Open a terminal or command prompt.
• Type python3 –version or python3 -V and press Enter.
• You should see the installed Python version, such as “Python 3.9.2”.

4. Environment Setup (Optional):

You might need to configure your environment variables to make it easier to run Python from the command line:

For Windows:

Add the Python installation directory (usually C:\PythonXY) to the system PATH variable.

For macOS and Linux:

The installation usually adds Python to the PATH automatically. To use python3 or pip3 commands, you can simply run them in the terminal.

5. Installing Additional Packages (Optional):

Python has a rich ecosystem of packages and libraries available on the Python Package Index (PyPI). You can use the package manager pip to install additional packages.

• Open a terminal or command prompt.
• To install a package, use the following command:

pip3 install package-name

Web development has changed a lot since DevOps first hit the scene. The languages used have shifted, where languages are used has shifted, the likely back-end hosting environment has changed – but DevOps has folded these issues in and just kept plugging along.

We’re going to approach this from two angles – what languages you’re likely to use, and what DevOps offers. This is not a “Best Billion Web Development Languages for 2021!” article; there are plenty of those out there, and you are more than welcome to read them. This is more about using these languages in a DevOps environment, which has become standard for web apps more than any other type of development.

We’ll start by observing that your web app is, more than likely, going to have at least three parts – HTML, CSS and JavaScript. This is not news to those of you doing it daily, but we’re just setting the bar, here. Other languages may be used to generate or populate any/all of the above, but, in the end, these three languages get sent to the browser, so will be part of the equation.

Backends add an incredible amount of complexity to this equation. I’ve done Ruby backends that did most of their work in C++ and Java; I’ve done pure Java backends that spit out the required three components; I’ve done Node backends that had very little actual HTML/JavaScript source code, but generated a ton of both – it’s all there. And the hosting environments for backends have changed. When DevOps started, most hosts were virtual machines (VMs) or hardware, whereas now we’re mostly running cloud instances or containers. Those backends have to be configured and managed, too, along with all of the dependencies that your application requires. When you think about it, we really have created quite a messy environment.

But DevOps has risen to this challenge.

I’ve long been an Atlassian fan, and find them to be a great tool for managing the agile side of DevOps. Add in Ansible, for the operations side, and you have a good thing going. I recently looked into GitLab, and GitOps – through GitLab – offers a compelling alternative to Atlassian’s offerings; more so since Atlassian made some rather unpopular changes right about the time I was wrapping up my look at GitLab.

The key is that Git holds all the code. By adding in the scripts to spin up those increasingly complex backends and secure the entire infrastructure, you get an “App in a (virtual) box.” No matter what DevOps toolchain you use, tying this in is simple, because it already works well with Git and associated tools.

Developers tend to care more about the development side of the equation (imagine that!), so let’s talk a bit about what’s going on out there.

PHP is hanging on solidly, with a bulk of applications and (perhaps more importantly) libraries to keep it in the running. PHP is one of the original “generate an HTML page” languages, and is slowly being displaced. It isn’t a bad choice for your web projects, but it isn’t the only – or at this point, the most popular – choice.

Java is still somewhat popular, and while it offers good support for web development, it is … heavy? Is that the word? It’s something for this type of development, and has ceded ground to other languages when it comes to pure-play web development. The skills are transferrable to other targets, so it is a good broad-use language. Like the other serious players in this space, there are web-centric libraries and frameworks that make Java hum. I’m a fan of Spring, but the options are pretty broad.

JavaScript wins this race today. It is used on both client and server, there are a ton of developers and DevOps people available who can be productive in JavaScript from day one, and it is increasingly used in other contexts – meaning skills could transfer to other projects. Like any language, there are trade-offs, but the portability aspect makes the trade-offs things that many are willing to work to overcome. Libraries and frameworks abound to make JS development faster and more dynamic. Personally, I like Node for server-side development, and Angular for clients that need more than straight HTML/CSS offers (probably because it’s the one I’ve used the most).

Python is definitely a contender in this space, as it is in most others today. With Django (or whatever your framework of choice), it functions well for web development, and its popularity has given it a host of support libraries to get things done. Developers are easy to find, and skills are broadly applicable, as Python is used in most areas of Dev and Ops at this point.

Windows aficionados are still using C#, and it does have good hooks into Microsoft DevOps tools, so any Microsoft shop should include it in evaluations. I’ve done C# on Azure for web apps, and for me it was … different, but not broken. In a Microsoft shop, C# will be familiar, and at this point, most developers are familiar with web clients, so merging the two is only a tiny bit of a learning curve, but not a major one.

Ruby does seem to have ceded its spot to Python. It is unlikely you’ll find a steady flow of ruby developers to fill those positions, but it is a highly intuitive language that you can train Java, and even Python developers in, if necessary. Ruby is well-supported for web development; indeed, it feels more natural using Ruby for web work than command line tools (at least to me, YMMV). There are web frameworks to make Ruby more intuitive in web development, and jRuby offers deep integration with Java to make use of already existing Java classes.

All in all, JavaScript should be the strong contender for a new project today, but any of these tools will serve the need. They are all well-supported, and DevOps tools start with integration to most of these languages. Do what’s best for your environment, and keep rocking it.

Java has long been one of the most widely used programming languages ​​among developers in a special form of a love-hate relationship. However, those times are long gone. This is also shown by the latest statistics from GitHub.

Microsoft’s developer platform houses by far the largest number of code projects and thus paints a very clear picture of the relationships between programming languages. The data of this year confirmed the trend of the previous year, according to which Python has now stably overtaken Java and has settled more firmly in second place.

At the top, however, nothing has changed for many years: JavaScript is firmly in the lead here. After all, the script language is the basis of almost all web applications and, with the ever-increasing relocation of software to the cloud, tends to attract even more development capacities.

TypeScript on the rise
This ultimately rubs off on the shooting star of the scene: The TypeScript developed by Microsoft only entered the Top 10 in 2017 and has been able to make up three places since last year and fight its way up to 4th place. The developers benefit here from the fact that they have a complete programming language in their hands, which is based on JavaScript. Every code that was written in the popular scripting language is also fully-fledged TypeScript code so that a huge pool of libraries and frameworks was available right from the start.

GitHub itself is still doing very well. When Microsoft took over the platform, there was a huge outcry and numerous announcements that projects and developers wanted to look for alternatives – but that rarely happened in practice. Rather, Microsoft was able to successfully expand GitHub and today there are 56 million registered developers who made around 1.9 billion contributions to over 60 million software projects last year. 72 percent of the 50 largest companies in the world also use the platform for their internal work.