Python is a modern programming language, built by Guido Van Rossouim in The 1980s, but it was publicly released in 1991. Rest is history. It is an interpreted, dynamically typed programming language. It is a high-level, object-oriented language which can run equally on different platforms such as Windows, Linux, UNIX, and Macintosh. Its high-level built-in data structures, combined with dynamic typing and dynamic binding. It is widely used in data science, machine learning and artificial intelligence domain. It is easy to learn and require less code to develop the applications.

An Interpreted language executes its statements line by line. Programs written in an interpreted language runs directly from the source code, with no intermediary compilation step. Other interpreted languages: Visual Basic, PHP, JavaScript

PEP 8 stands for Python Enhancement Proposal is a style guide that facilitates the reading of the code and the consistency between programs of different users. This guide is not mandatory to follow, but it is highly recommended. PEP 8 is a python tool used by millions of Python developers to check the readability of their program.

There are several built-in data types in Python. Python doesn't require data type to be defined explicitly during variable declaration. Python variables are labels and they just binding a label to the object. Built-in types are: int, float, complex, str, list, tup, set, frozenset, bool, dict. Read More...

Python has a private heap space that stores all the objects. The Python memory manager regulates various aspects of this heap, such as sharing, caching, segmentation, and allocation. The user has no control over the heap; only the Python interpreter has access. The allocation of heap space for Python objects is done by Python's memory manager. The core API gives access to some tools for the programmer to code. Python also has an inbuilt garbage collector, which recycles all the un-used memory and so that it can be made available to the heap space. Read More...

In Java, we get a .class file that contains the byte-code of the program we want to execute. Similarly, In Python .pyc file contains the byte-code of the python program that we want to execute.

When a program has multiple classes of almost identical behavior, Inheritance can be complex to implement. Instead of Inheritance, in such situations, Metaclasses can be used. It allows us to specify a particular behavior for many classes in a program. One very popular Metaclass is ABCMeta, it is used to specify abstract classes in program.

Generator functions are almost similar to a basic python function, but instead of return keyword in their return statement, it has yield keyword in their return statement. syntax of generator function: def myfunc(): yield 1 Read More...

A list is a mutable data structure while a tuple is an immutable one. A mutable object in python has the ability to change its values. Lists are dynamic: you can add items to them or override and remove existing ones. Tuples are fixed size: they don't have an append or an extend method. You cannot remove items from them either. Both tuples and lists are supporting indexing and allow using the in operator to check for existing elements in the collection. There are some situations where I think tuples might be useful: If you declare a collection of items that you know will never change. If you look for performance, tuples are faster than lists since they're read-only structures. Tuples are safer they cannot modify accidentally. Read More...

A module is simply a python file that's intended to be imported into scripts or other modules. It contains functions, classes, and global variables. A package is a collection of modules that are grouped together inside a folder to provide consistent functionality. Packages can be imported just like modules. They usually have an __init__.py file in them that tells the python interpreter to process them as such. A library is a collection of packages.

The Global Interpreter Lock (GIL) prevents the python interpreter from executing more than one thread at the same time. Put simply, the GIL forces that only one thread is executed at any point in time in python. This represents a big performance bottleneck in CPU-bound applications that rely on multi-threaded code.

A decorator is a function that receives a function as input and returns a function as output. The goal of a decorator is to extend the behavior of the input function without changing its core mechanism. Using a decorator also prevents you from repeating yourself. It forces you to write a generic code once and then tap it to every function that needs it. A typical use-case where decorators are using is logging mechanism. for example, that you want to log to the terminal all the values of the parameters that are passed to every function that is called in your program. Instead of modifying every function definition, you can write one single decorator that does this logging task and apply it to all the functions that need it. Read More...

Python is neither call by value nor call by reference. It is call by sharing (also known as "call by object" or "call by object sharing") Read More...

== is an operator that tests the equality of data, while is an operator that tests for identity. Two objects can have equal values without necessarily being identical (i.e., having the same memory address). Remember that a is b is syntactic sugar for id(a) == id(b)

Python supports functional programming paradigm. Central in functional programming are higher-order functions. A higher-order function is a function that takes in another function as an argument. map is used to apply a transformation to every element in an iterable. filter is used on an iterable to keep only certain elements that meet a certain condition. reduce is used on an iterable to combine all its elements in some way. Read More...

A namespace is a naming system used to make sure that names are unique to avoid naming conflicts. Python uses LEGB Rule to avoid naming conflicts. Read More...

range () function returns a python list object, and xrange () returns an xrange object. xrange doesn't generate a static list at runtime, as range does. It creates the values as you need them with special technique called yielding. This technique is used with a type of object known as generators.

It's an environment variable, which is used when a module is imported. Whenever a module imported, PYTHONPATH is also looked up to check for the presence of the imported modules in various directories. The interpreter uses it to determine which module to load.

Both of these are used to pass a variable number of arguments in a function. We use *args for nonkeyword arguments, whereas **kwargs is used for keyword-based arguments (e.g., a key-value pair). *args Example: def myfunc(*args): for arg in args: print(arg) myfunc("Welcome", "To", "Learner Landmark") ##output Welcome To Learner Landmark **kwargs Example: here kwargs is a dict type def myfunc(**kwargs): for key, value in kwargs.items(): print(key, value) myfunc(username='learnerlandmark', email='learnerlandmark@gmail.com', city='Hyderabad') ##output username learnerlandmark email learnerlandmark@gmail.com city Hyderabad

Arrays and lists, in Python, have the same way of storing data. But array can hold only a single data type elements whereas list can hold any data type elements. list has the disadvantage of consuming large memory. Example: import array as arr myarr = arr.array('i', [1,2,3,4]) mylist = [1,'hello', 3.141] print(myarr) print(mylist) ## output array('i', [1, 2, 3, 4]) [1, 'hello', 3.141]

An iterator holds the entire sequence in memory before returning the first result. An iterator uses "return". A generator computes each result at the time it is requested. The next result is unknown. Read More...

self is used to represent the instance of the class. Python has different types of methods class methods, instance methods, and static methods. Here instance methods first parameter is self, which represents the current object. self parameter is used to bind current object attributes with given arguments. But unlike in C++, self is not a keyword in Python.