• By Han Xinzi @Showmeai
  • Tutorial address: www.showmeai.tech/tutorials/5…
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The introduction

This series of tutorials begins with the Python programming language, which has always been tepid, even by most people, due to its low power, lack of support for multiple cores and concurrency.

With the technological innovation, the function of physical hardware is improving continuously, and the complexity of software is also increasing, and the development efficiency is more and more valued by enterprises. At the same time, in the field of big data and scientific computing, rapid analysis and verification are needed, and convenience and speed of development are very important. As a result, many people realize that development efficiency is more important than machine efficiency, and Python is gaining favor with more and more developers.

From 2012 to 2014, cloud computing heated up, and a large number of startups and Internet giants crowded into the cloud computing field. OpenStack, the most famous open source cloud accounting channel, was developed based on Python. In recent years, big data and artificial intelligence, machine learning/deep learning, and the most active and supported programming language in the whole ecosystem are Python.

Today Python has become one of the most popular programming languages on the Internet. As you can see in the “Top 10 Programming Languages Chart,” Python quickly moved into the Top three, and for a time became the most popular language.

Content abstract

This article provides a brief introduction to Python. Reading this article, you will learn:

  • A brief introduction to Python;
  • Python history;
  • Python features features;
  • Python application scenarios;

Introduction of Python

Python is a high-level scripting language that combines interpretation, compilation, interactivity, and object-oriented programming.

Python is designed to be very readable, and it has a more distinctive syntax structure than other languages that use English keywords more often, and some punctuation marks in other languages (see the following tutorial on Basic Python Syntax).

  • Python is an interpreted language: this means there is no compilation part of the development process. Similar to PHP and Perl.
  • Python is an interactive language: this means that you can execute code directly after a Python prompt >>>.
  • Python is an object-oriented language: this means that Python supports an object-oriented style or programming technique in which code is wrapped in objects.
  • Python is a Beginner’s language: Python is a great language for beginning programmers, supporting a wide range of application development, from simple word processing to WWW browsers to games.

Python history

Python was designed by Guido van Rossum (father of Python, Master of Mathematics and Computer Science, University of Amsterdam) at the Dutch National Institute for Mathematical and Computer Science in the late eighties and early nineties.

Python itself has evolved from many other languages, including ABC, Modula-3, C, C++, Algol-68, SmallTalk, Unix shell, and other scripting languages.

  • Python version 1.0 was released in January 1994, and the major new features in this version are Lambda, Map, Filter, and Reduce.
  • Python2.0 was released in October 2000. The main new features in this release are memory management and cyclic detection garbage collector and Unicode support. A particularly important change, however, is in the development process, where Python now has a more transparent community.
  • Python3.0 was released in December 2008. Python3.x is not backward compatible with python2. x.

Python2.7 is the last python2. x release that supports some Python 3.1 syntax in addition to Python2.x syntax.

Python features

  • 1. Easy to learn: Python is easier to learn with relatively few keywords, a simple structure, and a well-defined syntax.
  • 2. Easy to read: Python code is more clearly defined.
  • 3. Easy to maintain: Python succeeds because its source code is fairly easy to maintain.
  • 4. An extensive standard library: One of Python’s greatest strengths is its rich library, which is cross-platform and works well with UNIX, Windows, and Macintosh.
  • 5. Interactive mode: Interactive mode support, you can input from the terminal to execute the code and get the results of the language, interactive testing and debugging code snippets.
  • 6. Portability: Due to its open source nature, Python has been ported (that is, made to work) to many platforms.
  • 7. Extensible: If you need a key piece of code that runs fast, or you want to write algorithms that you don’t want to expose, you can do that in C or C++ and call it from your Python program.
  • 8. Databases: Python provides interfaces to all major commercial databases.
  • 9.GUI programming: Python supports GUI creation and portability to many system calls.
  • 10. Embeddable: You can embed Python into C/C++ programs to give users of your programs the ability to “script”.

Python Application Scenarios

  • General software development

Python supports functional programming and OOP object-oriented programming, and can undertake any kind of software development work, so routine software development, scripting, network programming, and so on are standard capabilities.

  • Scientific computing

With the development of NumPy, SciPy, Matplotlib, Enthoughtlibrarys and many other libraries, Python is becoming more and more suitable for scientific calculations and drawing high-quality 2D and 3D images.

Compared with Matlab, the most popular commercial software in the field of scientific computing, Python is a general-purpose programming language, with a wider range of applications and more library support than the scripting language used by Matlab. Although many advanced functions and Toolbox in Matlab cannot be replaced at present, there are still a lot of work in daily scientific research and development that can be replaced by Python.

  • Automated operation and maintenance

This is almost the preserve of Python applications, the language of choice for operations engineers, which is already well known for automation platforms such as Saltstack and Ansible.

  • Cloud computing

OpenStack, the open source cloud computing solution, is developed based on Python.

  • WEB development

Don’t have too many Python-based Web development frameworks, such as The familiar Django, Tornado, Flask, etc. The Python+Django architecture, which has a wide range of applications, is fast to develop and has a low threshold of learning, can help you quickly build usable WEB services.

  • Web crawler

Also known as the Web spider, it is the core tool for the big data industry to obtain data. Without web crawlers automatically, day and night, and intelligently crawling the Internet for free data, big data-related companies would be three-quarters less likely. There are many programming languages that can write web crawlers, but Python is definitely one of the mainstream among them, and its Scripy crawler framework is widely used.

  • The data analysis

On the basis of a large amount of data, combined with scientific computing, machine learning and other technologies, data cleansing, de-weighting, normalization and targeted analysis is the cornerstone of the big data industry. Python is one of the dominant languages for data analysis.

  • Artificial intelligence (ai)

Python is a mainstream programming language in the field of machine learning, neural network, deep learning and other aspects of artificial intelligence, and has been widely supported and applied.

Information and code download

This series of tutorials can be downloaded from Github on ShowMeAI, which can be run locally in Python. If you can use Google Colab, you can also use Google Colab.

The Python sketchbooks covered in this tutorial series can be downloaded at:

  • Python quick table

Expanded Reference materials

  • Python tutorial – Python3 documentation
  • Python Tutorial – Official website of Liao Xuefeng

ShowMeAI related articles recommended

  • Python is introduced
  • Python installation and environment configuration
  • Basic Python syntax
  • Basic Python data types
  • Python operator.
  • Python conditional control with if statements
  • Python loop statements
  • Python while loop
  • The python for loop
  • Python break statement
  • Python continue statement
  • Python pass statement
  • Python strings and operations
  • Python list
  • The python tuple
  • Python dictionary
  • Python set
  • Python functions
  • Python iterators and generators
  • Python data structures
  • Python module
  • Python file reading and writing
  • Python file and directory operations
  • Python error and exception handling
  • Object-oriented programming in Python
  • Python namespaces and scopes
  • Python time and date

ShowMeAI series tutorials recommended

  • Illustrated Python programming: From beginner to Master series of tutorials
  • Illustrated Data Analysis: From beginner to master series of tutorials
  • The mathematical Basics of AI: From beginner to Master series of tutorials
  • Illustrated Big Data Technology: From beginner to master