5 Uncommon concepts that make you a unique Python programmer

 If you want to enhance your python knowledge, concepts are more important. Due to its adaptability, dynamic nature, resilience, and ease of learning, Python is a high-level, object-oriented language of programming that has recently gained popularity among professionals and students. It is currently the second most popular and preferred language after JavaScript. It can be utilized in practically all technological domains, including machine learning, data science, web development, analytics, automation, testing, artificial intelligence, and many more. Here will see about the uncommon concepts that make you a unique Python programmer:

1. Map Function

With the help of the built-in Python function map(), you may process every element in an iterable without explicitly utilizing a looping construct. It produces a map object after use, which is an iterator. The outcome of applying the supplied function to each item in the iterable produced this map object. Two arguments are required by the map() function.

• A function that will be applied to every element in the iterable is the first argument.

• The iterable on which the function is to be mapped is the second argument.

2. Collections

The data is stored in containers known as collections in the Python programming language. Sets, tuples, dictionaries, and lists are a few examples of general-purpose inherent containers found in Python. One module that implements customized container datatypes is Python collections. For example, list, tuple, set, and dictionary. To offer additional data structures, various libraries were created in Python. To enhance the capabilities of the built-in container, the Python language has a library called the collection. In the collection module, these are the top five data structures:

• Counter

• Namedtuple

• OrderedDict

• Defaultdict

• deque

 3. Generators

An object that can be iterated over is the result of a generator, a type of function. It includes, at the very least, a yield statement. When returning a value from a function in Python, the yield keyword prevents the function from losing any references to local variables or their current states. When someone requests an item from a generator, it is only generated once. They are less memory-intensive and occupy less memory space. In contrast to return, which ends the execution of the function, yield pauses it while returning the value checked against it each time. By joining the python programming online course it is possible to learn in-depth about the concepts of generators.

4. Decorators

A Python decorator feature allows you to add new functionality to existing code without changing it. With the help of decorators, a component of Python's metaprogramming, you can extend the functionality of already written code without changing its original structure at compile time. It behaves more like a callable Python function that can be called. It accepts a function, modifies it by adding features, and then returns the limited function. Function decorators and class decorators are the two categories of decorators. You can get detailed information about the two categories by joining free online courses Python on a reputable platform. @ appears before the function name in decorators. To comprehend decorators, one must first understand that functions in Python are class objects. They can be defined within a function, supplied as an argument in other functions, and even returned as a function, unlike other things.

5. itertools

Itertools, a great feature of Python's standard library, offers a number of methods that, due to delayed evaluation, make it easier to write streamlined, quick, and memory-efficient code. It is a Python module that carries out many iterator-building pieces that collectively make up iterator algebra, which enables rapid tool development in the Python programming language. Iterators themselves are the focus of the itertools methods, which produce more complicated iterators as a result. The following are a few examples of itertools' functions: count(), cycle(), repeat(), accumulate(), product(), permutations(), combinations(), etc. Each of these functions operates on its own set of inputs. Compared to the results obtained using conventional code, the result is generated much faster.

Final Thoughts

If you want to be an expert in Python programming, it is always important to know about the concepts and basics of Python. These are the five uncommon concepts you need to consider that make you a unique Python programmer.