New and Exciting Features of Python Programming 2.10-4: A Must have for Better and Faster Computer

Python for Everyone:

With its unprecedented power and usefulness, Python has become of the hottest and fastest growing programming language since it was launched by Guido Van Rossum and is become one of the buzzwords in Digital Transformation together with other domains in the Pantheon of Technology – Data Science and Big Data.

Data Science is a multi-disciplinary skill in Statistics, Computer Science and Business Management. Data Science was regarded as the solution to provide scalable insights with the availability of Big Data. The advancement in Technology makes these domains and areas visible to almost sectors and industries. Big enterprises invested huge amount of money to install Data Science team in their organization to take care the operations of the business.

Skills in Statistics, Data Mining or Data Wrangling was successfully used and applied to these companies and areas because of the Computer Programming Language such as Python. Business Models was carefully curated by experts in Business Management. Thus, Data Science was regarded as the sexiest job in the 20th Century because it encapsulated a wide spectrum of knowledge, skills, and expertise.

Based on Stack Overflow Developer’s Survey in 2019, Python was regarded as the second and the most preferred language with 73% of the developers are choosing it over other programming languages and is expected to dominate the Marketplace for Programming Languages.

Alright.

Let’s start with our discussion.

WHAT ARE THE NEW AND EXCITING FEATURES OF PYTHON 3.10-4?

Switch Statements is one of the Big Updates to be found in Python 3.10 – 4 from the old or previous Context Managers, although it was yet in the Production environment, but its going to be the best one. We can still use the current interpreter.

This upgrade to Python 3.10-4 is currently in Alpha, but its worth to explore and learn about these upcoming new features. These features will surely give you a lot of convenience and ease of using Python. In this Article, I will be discussing some of the new features and I will also be discussing some of the minor fixes and changes.

In this Video, I will be discussing the following.

1. Error Messages

2. Structural Pattern Matching (Switch Statement)

3. The Union Operator

4. Better Context Managers

Error Messages

One of the most common reason of Error in Python is when a certain statement is not in compliance with the prescribed usage. This what we called a “syntax” error. Usually, when Python encounter this kind of error, it immediately reports it with a reason. There are some who do not understand this reason that is why it can be frustrating.

With this new feature, there will be big improvements with regards to the syntax, indentation, attribute, and name errors. It is now straightforward error messages or direct to the point.

Cases in Error Message

1 Case 1: Dictionary Not Close

SyntaxError: unexpected EOF while parsing

To others, this seems very confusing, and they don’t understand what this syntax error is is or where to locate this error. The Error here is the “{”. The Syntax Error occur for not closing the Dictionary.

2. Invalid String Literal

SyntaxError: EOL while scanning string literal

The cause of this Error is the unterminated string literal. You noticed that there is no closing apostrophe at the end of the email.

3. Missing “:” Before Blocks

SyntaxError: invalid syntax

In this Error, it is not clear what part in the syntax that makes the script error. So we cannot decipher what is the Error in this syntax only to find that we forgot to write or end the line 1 with “:”.

4. Inappropriate Indentation

PROPER INDENTATION

Before dig into why indentation error happens in Python, let us figure out the basic idea of Python.

Python Programming Language was first introduced in 1991 and from then, programmers around the world have adapted to it and created numerous applications for web and mobile. In Python, proper organization is vital of codes is very important for them to easily locate the problem is there is an error between each line of code. Code should be arranged with correct whitespaces and therefore if there is any instance that a certain line of code is not in line with the other, the overall code will not run, and the interpreter will simply return an error function.

In Python, all the lines of code are arranged according to blocks, so it becomes easier for you to spot an error. For example, if you have used the if statement in any line, the next line must have an indentation.

Structural Pattern Matching (Switch Statement)

Its very time and about time to improve the Structural Pattern Matching.

The pattern matching will be going to take the value following match and it allows us to write out other potential cases, each defined by case. Where we find a match between the match-case we will execute the respective code.

Switch statements are mostly seen in various programming languages which provide a neater avenue of implementing a conditional logic. They come in easy and very useful when there a lot of conditions to evaluate.

For illustration, we will be using structural pattern matching to write a simple function — get_mood(day: str) -> str that will return a string which value depends on the input parameter. The returned value gets more exciting as we are going through the weekend. A little and simple function, but will do for demonstration purposes:

In a nutshell, structural pattern matching will provide a neater way to organize your code and avoid a bunch of if-else statements. To recap:

· Use the case keyword to evaluate for a condition (case ‘Monday’ is identical to if day == ‘Monday’)

· Separate multiple conditions with the pipe operator — | — e.g., if two input values should result in the same return value

· Use the underline operator — _ — to specify the default case.

Union Operator

The union() method returns a set that contains all items from the original set, and all items from the specified set(s).

You can specify as many sets you want, separated by commas.

It does not have to be a set, it can be any iterable object.

If an item is present in more than one set, the result will contain only one appearance of this item.

Hints or clue are big thing in Python. As you probably know, Python will not require you to specify the data types for variable upon declaration, but it provides a different option how to do so.

It really frustrating, though when declaring a function which accepts a number that can be an integer of a float. In this case, how can you specify the data type? In Python 3.10, we can use the “Union” operator.

When declaring a function that returns a square root of a number with type hints look like this one below.

There must have a better solution — and there is — starting from Python 3.10. You can ditch the Union operator altogether and separate potential data types with the pipe operator — |.

BETTER CONTEXT MANAGERS

The concept behind Python 3.10 about the Context Manager is now new. What is new is that it allows the enclosing parenthesis for continuation across multiple text lines in the context managers.[1]

Let’s take this example. I have two TXT files:

· first_file.txt — contains “This is the first file.”

· second_file.txt — contains “And this is the second file.”

We’ll now use context manager to open and process the contents from both.

The output is shown below:

As you can see, you can now manage multiple files in a much more organized manner. Not a very significant feature, but definitely a very good improvement.