Understanding Principles of Python
Fundamentals of Python step by step
Table of Contents
∘ Python’s place in Data Science and machine learning
∘ Applications of Python
∘ Why We Use Python?
∘ Advantages
∘ Disadvantages
∘ Is Python Too Slow?
∘ Phyton and Matlab
∘ Who Use Python?
∘ Python has many development tools.The Python programming language is a basic structure used for data science, machine learning, system automation, web and API development, and more. It is an objective-based programming language.
Since 1991, the Python programming language has been treated only as a complementary language for unnecessary programs. He even published a book called” Automate the Boring Stuff”.
However, in the last few years, Python has come to the fore as a first-class programming language in modern software development, infrastructure management and data analysis. No longer a backdoor builder for hackers, it has earned a reputation as a shining language in web application creation and key roles in system management, data analytics and machine learning.
Python’s place in Data Science and machine learning
Sophisticated data analyses have become the most important issues for it today. Python, on the other hand, has been the most convenient programming language for these situations. Many of the libraries in the Python interface are useful on machine learning and data science. In these areas, high-quality commands in libraries have helped the continuous development of machine learning libraries and other numerical algorithm libraries. And they continue to help.
Applications of Python
- Web and Internet development
- Scientific calculations and statistics
- Artificial intelligence
- Desktop interface development
- Software development
- Network interface
Why We Use Python?
Advantages
- Free of charge: Python is completely free and can be used and distributed without copyright restrictions. Despite being free, for over 25 years Python has had a very active community and is constantly getting up-to-date and time-keeping improvements.
- Portable: Python is a portable language developed in ANSI C. It is also available on different platforms such as Unix, Linux, Windows, DOS, Macintosh, real-time systems, OS / 2, Android and iOS mobile phones. This is possible because it is an interpreted language , so the same code can run on any platform as long as the Python interpreter is installed.
- Easy to use: Python is a high-level language that is both simple and powerful. The syntax and different modules and functions already contained in the language are consistent, intuitive and easy to learn, and the design of the language is based on the principle of least confusion. So you can know in advance the reaction of the code that you have written. So you won’t be surprised. The behavior of the program coincides with what is expected.
- Advanced library: Each Python installation includes a standard library, a collection of more than 200 modules to perform the most diverse tasks, such as interacting with the operating system and file system, or managing different protocols. Python standard library, systems management, networking, text processing, database interfaces, graphics systems, and XML processing. The Python standard library has a clear naming interface, is well documented, and is easy to learn and use. In addition, the Python package directory allows you to download and install thousands of additional modules created and maintained by the community. It can also be worked with code written earlier with the import property. If you are starter level, you can find some useful information from this link in Python’s official site.
- It can be integrated with other languages: In addition to the classical interpreter written in C (and called CPython), there are other interpreters that allow integration with several other languages. IronPython allows you to use Python within the .NET Framework, use its functions, and interact with other .Net languages . You can use Jython to integrate Python and Java. There are other interpreters, such as PyPy: a high-performance application written in Python.
- Automatically manages memory: Python is a high-level language that adopts a garbage collection mechanism that automatically deals with memory allocation and release . This allows the programmer to freely use variables without having to worry about declaring them and manually allocating and releasing memory areas.
Disadvantages
Although Python is generally suitable for writing quality applications, it has some shortcomings and areas that it cannot afford.
- Because it is a high-level programming language, it is not suitable for system-level programming. However, this category does not include device drivers or the operating system kernel.
- It is also not ideal in cases that call for cross-platform independent binary files.
- You can develop an application for Windows, MacOS and Linux operating systems. But the app that will be created will not be too great an app
- In general, Python does not provide much functionality in heavy programs, since the programming language is also at the forefront of speed. Because of this, you can use languages such as C / C++, one of the oldest programming languages.
Is Python Too Slow?
Among the negative rumors said about Python is that it is slow. In general terms, Yes, Python is slow. Programs created through Python usually run slower than corresponding programs in C / C ++ or Java.
What’s the reason for this slowness? This requires slow synchronization, as assembly programs analyze line-by-line code. The fact that objects contained in Python are determined through the code used makes it difficult to optimize its speed for the language, even when compiled. The speed of the Python, however, may not be as important an issue as it seems, and there are ways to mitigate it.
Phyton and Matlab
It can be done in scientific calculations with Phtyon. One of the most important programs used for scientific computation is Matlab. However, in addition to highly specialized toolboxes, Matlab cannot be replaced. Compared to Matlab, there are many advantages to using Python for scientific calculation:
Primarily MATLAB is commercial software and is expensive. And Python is completely free. You can find many open source scientific computing libraries for Python. Users can install Python and most of its extension libraries on any computer for free.
Secondly, Python is an easier to learn and more rigorous programming language compared to Matlab. It allows users to write code that is easier to read and maintain.
Finally, MATLAB focuses mainly on engineering and scientific computing. However, even in computing, various requirements such as file management, interface design, and networking are often encountered. And Python has a rich library of extensions that can easily complete a variety of advanced tasks, and developers can use Python to implement the various functions that a complete application requires.
Who Use Python?
Today Python is used in many large companies in the IT market, including:
NASA uses Python to improve control systems; Yahoo! Developed some internet services in Python; It uses Google, Youtube and RedHat Python.
Python has many development tools.
Tkinter: Python’s default graphical interface interface. Tkinter is a Python module that interfaces with Tk. The Tkinter library provides an interface to the Tk API and belongs to the TCL / Tk GUI toolkit.
PYGTK: GTK + library for Python GUI program development. GTK is the library used to implement GIMP and Gnome.
PyQt: Qt development library for Python. QT is the library that implements the KDE environment. Qt consists of a series of modules containing 300 classes and more than 5750 functions and methods, including qtcanvas, qtgl, qtnetwork, qtsql, qttable, qtui, and qtxml. PyQt also supports a module called qtext that contains the qscintilla library. This library is the Qt interface of the scintillar editor class.
wxPython: GUI programming framework, people familiar with MFC will love it. It is almost the same architecture. Note: for beginners or users with low design requirements, using Boa Constructor can facilitate the rapid development of WxPython.
PIL: Python provides powerful graphics processing capabilities and support for a wide range of graphics file formats. The library can convert, print, and display graphic formats. It can also handle some graphic effects, such as zooming in, zooming out, and rotating graphics. It is a powerful tool for Python users to perform image processing.
Psyco: is a Python code accelerator. It can increase the execution speed of Python code to the same level as the compiled language.
xmppy: Jabber server uses the developed XMPP protocol, and Google Talk is also an IM system that uses the XMPP protocol. Python has an xmpppy module that supports this protocol. In other words, we can communicate with the Jabber server through this module.
Pymedia: Python module for multimedia operations. Multimedia processing (wav, mp3, ogg, avi, divx, dvd, cdda, etc.) Provides a rich and simple interface for. Available under Windows and Linux platforms.
Pmw: Python megawidgets, Python super GUI component set, a high-level GUI component built using the Tkinter module in Python, each Pmw contains one or more Tkinter components to achieve more useful and complex functions.
PyXML: a toolkit for parsing and processing XML documents with Python 4dom in the package is fully compliant with the W3C DOM specification. Includes the following: xmlproc: a compatible XML parser . Expat: a fast, unverified XML parser. PyHtml has others on the same level as PySGML.
Pygame: multimedia development and game software development modules. You can download Pip install directly using Pygame.
PyOpenGL: the module includes the “OpenGL application programming interface”, where the python programmer can integrate 2D and 3D graphics into the program.
NumPy, NumArray, SAGE: NumArray is an extended Python library, basically a matrix library, used to deal with fixed type arrays of random dimensions. Its basic code is written in C, so the speed advantage is obvious. SAGE is a mathematical software package based on NumPy and many other tools. The goal is to replace tools such as Magma, Maple, Mathematica, and Matlab.
MySQLdb: used to connect to the MySQL database . There is also the zmysqlda module, where you can connect to the mysql database for zope.
Sqlite3: used to connect to the Sqlite database.
Python-ldap: OpenLDAP 2.it provides a set of object-oriented APIs for easy access to the ldap directory service in Python based on X.
smtplib: send email.
ftplib: the FTP class and some methods are defined for client ftp programming. If you want to know the details of Ftp protocol, please refer to Rfc959.
PyOpenCL: OpenCL’s Python interface, where the GPU can be used to implement parallel computing.
Xes-lib: Xueersi library can be used for sending mail, checking weather and other functions.
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