Friday, September 22, 2023

Advanced Python Concepts: Generators, Decorators, and Context Managers

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To understand the advanced Python concepts efficiently one needs to focus on what exactly Python is? So, Python is an interpreted, object-oriented, high-level programming language with dynamic semantics.

Definition

It is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn’t specialized for any specific problems.

Python’s clean object-oriented design provides enhanced process control, and the language is equipped with excellent text processing and integration capabilities, as well as its own unit testing framework, which makes it more efficient. Internet of Things(IoT) Opportunities. Interpreted Language.

ADVANCED PYTHON CONCEPTS

Advanced Python concepts are usually defined as fundamentals which are difficult to grasp by the beginners and intermediate, so a person who does not fall into the category of either a beginner or intermediate, can easily understand the advanced Python concepts, that we are going to discuss.
There are numerous advanced Python concepts but we are going to focus on only the below mentioned concepts, as of now-

  1. Comprehension– It allows us to write a concise line to create new sequences (such as lists, set, dictionary etc.) using sequences which have already been defined. Python also has below mentioned types of comprehensions-
    List Comprehensions
    Dictionary Comprehensions
    Set Comprehensions
    Generator Comprehensions
  2. LambdaIt– It is also known as an anonymous function. It has no body and doesn’t require the def keyword for definition.
  3. Context managers– They are used to manage resources. The usage of resources like file operations or database connections is widespread.
  4. Exception handling– An exception is a condition that occurs during the execution of the program and interrupts the execution.
  5. Collections– Collections in Python are general purpose inbuilt containers like sets, tuples, dictionaries, and lists.
  6. Map– It permits us to process all the elements present in an iterable without explicitly using a looping construct
  7. RegEx– These are expressions that contain specific characters as patterns to be matched.
  8. Itertools– It provides a number of functions that help in executing clean, fast, and memory-efficient codes to enable lazy evaluations.
  9. Magic methods– Also called Dunder and are touted to be special types of functions that are invoked internally.
  10. Closures– It maintains references to object from earlier scopes.
  11. Inheritance– It allows us to define a class that inherits all the methods and properties of another class.
  12. Argument– In Python, *args passes variable number of non-keyworded arguments list and on which operation of the list can be performed.

As the title suggests we are now going to closely look onto the most important Concepts of Advanced Python that one should definitely be familiar with.

DECORATORS

It’s a very essential part of Advanced Concepts of Python that we’re going to study now-

A decorator in Python is any callable Python object that is used to modify a function or a class. A reference to a function “func” or a class “C” is passed to a decorator and the decorator returns a modified function or class.

A decorator is a function that takes another function and extends the behavior of this function without explicitly modifying it. It is a very powerful tool that allows to add new functionality to an existing function.
Decorators can be classified into further more categories including function decorators and class decorators.

Function Decorator- A function decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure. Decorators are usually called before the definition of a function you want to decorate.

Class Decorator- A Python class decorator adds a class to a function, and it can be achieved without modifying the source code. For example, a function can be decorated with a class that can accept arguments or with a class that can accept no arguments.

GENERATOR

Another crucial aspect of the Advanced Concept of Python-

A generator in Python is an easy way of creating an iterable object without having to implement the whole iteration protocol. It is just a simple function that contains a yield statement instead of the return one.

In Python, a generator is a function that returns an iterator that produces a sequence of values when iterated over. Generators are useful when we want to produce a large sequence of values, but we don’t want to store all of them in memory at once.

Python provides a generator to create your own iterator function. A generator is a special type of function which does not return a single value, instead, it returns an iterator object with a sequence of values. In a generator function, a yield statement is used rather than a return statement.

Memory is saved as the items are produced when required, unlike normal Python functions. This fact becomes very important when you need to create a huge number of iterators. This is also considered as the biggest advantage of generators. Can be used to produce an infinite number of items.

CONTEXT MANAGER

Last but definitely not the least is the Context Manager, which is another Concept of Advanced Python learning-

A context manager usually takes care of setting up some resource, e.g. opening a connection, and automatically handles the clean up when we are done with it. Probably, the most common use case is opening a file.

Context managers are a powerful tool in Python that allows you to manage resources efficiently and with ease. They provide a clean and concise way to allocate and deallocate resources, making your code more readable and less prone to errors.

They allow you to provide and reuse common setup and teardown code. In other words, with context managers, you can perform any pair of operations that needs to be done before and after another operation or procedure, such as: Open and close. Lock and release.

Conclusion

This is not the end of the Python world as discussed above, there are various other advanced concepts of Python that are yet to be discussed. It doesn’t really matter if you are a beginner intermediate or a professional, seeking to polish your professionalism you are forever welcome to get the Python training certification course from Uncodemy, Udemy, Cetpa and other reputed training institutes which is the best Python Training Course Provider in Patna, Kanpur, Gorakhpur, Noida and other cities in India. Undoubtedly, there are several institutes where you can get the Python training course but if you have come to this blog and you have read it till here, you know where you have to go! So, don’t hold yourself anymore and become a part of this comprehensive Python training course specially crafted by the experts to provide you the best and updated knowledge of the Python world.

Read Also: The Benefits of Learning Full Stack Development Course: From Versatility to High Paying Jobs

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