History of Python
Python is a general-purpose programming language that can be used for anything like developing Web pages, Machine learning, Data analysis or any sort of application. Python was developed by Guido Van Rossum at national research institutes for mathematics and computer science, Netherland. In contrast to popular belief that python was named after the snake python was named after the show “Monty python’s flying circus”. Guido Van Rossum starts working on python in late 1980 as a successor to the ABC language. Python version 1.0 was released in 1994 introduced features like Exception handling, Lambda function, Map, Reduce, and Filter. In 2000, python 2.0 was released with features like List
Comprehensions and Cycle-detecting garbage collection. Python 3.0 was released on the 3rd December 2008.Python 2.x and 3.x versions are used most of the time. As of today, python 3.7.4 is the latest stable version released in 2019. Python is mostly used for development, Web scraping, and software testing. Top IT companies like Google, Facebook, Instagram, Netflix, and others use python also some major applications of python can be used in the field like ML, AI, Data science, etc. Python also offers many libraries like NumPy, Pandas, Matplotlib.pyplot, and Scikit-learn and so on. Python is used in making some websites like Reddit, Quora also there are some popular games that devolved by using python like Battlefiels2, SIM4, and World of Tanks.
Features of Python
Python is gaining popularity in the programming community for a variety of reasons. The following are some of the features of Python:
Simplicity: Python is a simple programming language when we write a python
program we feel like writing English sentences. It means it makes you think more for a solution rather than syntax.
Open Sources: Python can be freely downloaded from the www python.org website. The Python software does not need to be paid. Its source code can be read, modified, and can be used in the program as desired by the programmers.
Portability: Python supports portability which means we can write our code and
share it with anybody if we want to and it could work with same way when we run
our code this makes the project and system much easier.
Interpreted: Python is an interpreted language because python code is executed line by line at a time which means the management of memory and CPU debugging become much simpler. The source code of python is converted into a form is called byte code.
Extensible Feature: Python is an extensible language, we can write some python
code into C or C++ language and also we can compile that code in C/C++ language> It makes python all more powerful.
Libraries Support: Python has huge libraries support which would help you to obtain a solution to your problems easier like NumPy, Pandas, Matplotlib, Scipy,
TensorFlow, sci-kit learn, seaborn, Keras, etc.
OOPS: Every programming language is either structure-oriented or object-oriented programming if it is object-oriented so everything will be implemented In terms of Classes and Objects. Python is a programming language that supports Oops. There are some concepts we learn in Oops which are,
Execution of a Python Program
Suppose we write a Python program called p.py. Here, p is the name of the program and .py is the name of the extension. Every Python program is typed with an extension name .py. After you have entered the program, the next step is to compile it using Python Complier. The compiler converts the Python program into something else which is called byte code. Byte code represents a fixed set of statements that represent all operations such as arithmetic operations, comparison operations, and memory-
related operations. The size of every byte code statement is 1 byte and therefore they are called with the name byte code. These byte code instructions are contained within the file p.pyc. Here, the file p.pyc represents a Python-compliant file. The next step is executing the python program. If we give the byte code directly to the computer, the computer will not be able to execute it. Any computer can run just the binary code that includes 1s and 0s. It is also called machine code. It is necessary to convert byte code into machine
code in order for our computer to understand and execute it.
Python for Machine Learning
Machine learning is a data analytics methodology that automates the construction of analytical models. Machine learning is based on the idea that a system can learn from data, identify the pattern and make a decision with minimal human intervention. Machine learning has other applications in autonomous automobiles, robotics, language processing,
and vision processing. Python is the most popular programming language used in machine learning and artificial intelligence during machine learning projects programmers used a number of python frameworks and libraries. A library is a pre-written code that developers use to solve common programming tasks. Python has a huge set of libraries for AI and machine learning. Here are some of them:
NumPy for multidimensional array
A Pandas which is a data analysis library that provides a concept called a data frame
Matplotlib for creating graphs and plots
Scipy for advanced computing
Scikit-learn which are the most popular machine learning that provides all these
common algorithms like decision tree, KNN, Random Forest, etc.
Python is a platform-independent language means it allows developers to implement things on one machine and use them on another machine without any change. python is supported by many platforms including Linux, Windows, and macOS.