Overview to Python programming language
Python is a high-level and object-oriented scripting language. It is a highly readable language. It regularly uses English keywords, whereas other languages use more punctuation. It has less syntactical structures than several different languages.
- Python is Object-Oriented − Python supports Object-Oriented style or method of programming that encapsulates code inside objects.
- Python is a Beginner-friendly Language − Python is a popular language for the beginner-level programmers and encourages the growth of a wide variety of applications from secure text processing to www browsers to games.
History of Python
Guido van Rossum originally developed Python in the late 1980s as a member of the NRIMC in the Netherlands. It is derived from many languages, including C, C++, and other scripting languages. As it is copyrighted, and its code is now available under the GNU.
What is a python programming language?
Python is a rendered, object-oriented, high-level programming language with authoritative interpretation. It’s high-level built-in data structures, mixed with compelling typing and sturdy binding, make it very engaging for rapid application development. It can be used as a scripting or glue language to join present components together.
Python is easy, simple to learn; its syntax maintains readability, and it decreases the value of program maintenance. Python supports modules and packages, which helps program modularity and code reuse. The Python editor and the vast conventional library are accessible in the source for free of cost for all major platforms.
Why learn Python?
Python is a high-level programming language. It is pretty simple to learn and gives robust typing. Python code has its truly ‘natural’ way to do it. Its codes are easy to read and understand (thanks to the need for semicolons and braces). Python programming language works on any platform, ranging from windows to Linux to Macintosh, Solaris, etc. The integrity of Python is something that makes it so accessible. The following gives a highlight of its features:
- Highly interesting language
- Complete visual layout
- Less syntactic exceptions
- Excellent string manipulation
- Rich and dynamic typing
- Interpreted nature
- Perfect for scripting and rapid application
- Suitable for many platforms
Top 10 reasons to learn Python
Programming languages have always stayed at the top throughout the ages, and each decade marks the launch of a unique language sweeping developers off their feet. Python is one of the most common and in-demand programming languages. A recent Stack Overflow survey noted that Python has taken over other languages such as Java, C, C++, and has earned its space to the top. It makes Python certification one of the standard sought-after programming certifications. The top 10 reasons to learn Python includes:-
1. Easy to learn
Python is very easy and comfortable to learn. It is a highly influential language, and it almost matches the English language. So, what adds to its integrity? Python is
- Free & open source
- Interpreted
- High-level
- Blessed with the large community
Moreover, in Python, you need not deal with complex syntax.
2. Portable and extensible
The portable and extensible features of Python lets programmers perform cross-language programs seamlessly. Python is supportable by all platforms, including from Windows to Linux to Macintosh, Play station, amongst others.
3. Web Development
Python has a pattern of frameworks including Django, Flask, etc. for creating websites. These frameworks make Python capable of delivering the code much faster and stable. Many websites, such as Instagram and Pinterest, are built on these frameworks.
You can also conduct web scraping by using Python, where you can retrieve details from any other websites.
4. Artificial Intelligence
AI is the subsequent massive development in the tech world. You can make a machine copy of the human brain, which can think, examine, and make choices.
Moreover, libraries such as Keras and TensorFlow make machine learning functionality into the mix. It provides the capability to learn without being explicitly programmed. Furthermore, libraries such as OpenCV support computer vision or image recognition.
5. Computer Graphics
All small, large, online, or offline projects use Python. It is used to develop desktop and GUI applications. It uses ‘Tkinter’ library to implement a fast & simple way to build applications. It is also applied in game development where you can print the logic of using a module ‘pygame,’ which also works on android devices.
6. Testing Frameworks
Python is excellent for verifying plans or products for authorized companies. It has several built-in testing frameworks that cover debugging & most active workflows. It has several tools and modules, such as Selenium and Splinter, to make tasks more comfortable.
It helps to test cross-platform & cross-browser with frameworks such as PyTest and Robot Framework. Testing is a tiresome task, and Python is the supporter for it, so every tester should surely go for it.
7. Big Data
Python manages several hassles of data. It helps parallel computing, where you can apply Python for Hadoop as well. In Python, you have a library called “Pydoop,“ and you can print a MapReduce program in python and process data existing in the HDFS cluster. Hence, Python is broadly used for Big Data, where you can quickly process data.
Also, See The Importance of Big Data in the Corporate Sector and its Benefits
8. Automation and Scripting
Many people only recognize that Python is a programming language, but Python can also be utilized as a Scripting language. In scripting:
- The code is written in the kind of scripts and get printed
- The machine scans and evaluates the code
- Error checking is done while Runtime
You can use code several times once it is verified. So by automation, you can automate several tasks in a program.
9. Data Science
Python is the primary language for the diverse data scientist. For ages, educational scholars and private researchers were utilizing the MATLAB language for scientific analysis.
Use Python in data science began to evolve with the release of Python statistical engines such as ‘Numpy‘ and ‘Pandas.’ Python also allows with the tabular, matrix as entirely as statistical data, and it even conceives it with modern libraries such as ‘Matplotlib’ and ‘Seaborn.’
10. Popularity and high salary
Python engineers have the highest wages in the programming sector. The average salary of a Python Developer in the United States is around $116,028 per year. Also, Python has a definite hike in demand over the last few years.
Fundamentals of Python
The following are the fundamentals of Python:
- Datatypes
- Flow Control
- Functions
- File Handling
- Object & Class.
Let us discuss it in detail below.
1. Datatypes:
Objects express all data values in Python and a particular purpose or value of a datatype.
There are eight basic data types in Python.
- Boolean
- Numbers
- Strings
- Bytes & Byte Arrays
- Lists
- Tuples
- Sets
- Dictionaries
2. Flow Control
Flow Control allows us to determine flow in executing our programs. To imitate the real world, you require to modify real-world situations into a program. For this, you need to manage the execution of your program statements applying Flow Controls. There are six essential flow controls used in Python programming:
- if
- for
- while
- break
- continue
- Pass
3. Functions
Functions in Python are a collection of similar statements that does a specific task. Functions make the program more prepared and assist in code re-usability.
4. File Handling:
File Handling relates to those actions that are used to read or write a file. To implement file handling, we need to perform these steps:
- Open File
- Read / Write File
- Close File
5. Object and Class:
A python is an object-oriented programming language. The object is simply a set of data (variables) and methods (functions) that operate on those data. Class is nothing but a blueprint for the object.
Python Features
These are some of the Characteristics of Python. These include:-
- Easy-to-read − Python code is more simply defined and evident to the eyes.
- Easy-to-learn − Python has keywords, a smooth structure, and a precisely defined syntax. It lets the novice to pick up the language swiftly.
- Interactive Mode − the Python, has provision for an interactive mode that allows interactive testing and debugging of pieces of code.
- A broad standard library − Python’s bulk of the library is highly compact and cross-platform. It is compatible with UNIX, Windows, and Macintosh.
- Easy-to-maintain − Python’s source codes are moderately easy-to-maintain.
- Extendable − Programmers can continue low-level modules to the Python interpreter. These modules allow programmers to add or customize their tools to be extra efficient.
- Databases − Python presents interfaces to all-important marketing databases.
- Portable − The Python, can work on a wide variety of hardware platforms and has an identical interface on all platforms.
- GUI Programming − The Python, helps GUI applications that can be built and ported to various system calls, libraries, and windows systems, such as Windows MFC, and the X Window system of Unix.
- Scalable − Python presents a more solid structure and support for large programs than shell scripting.
Apart from the features mentioned above, Python has a massive list of great features; some of them are discussed below:
- It carries functional and structured programming techniques as well as OOP.
- It can be utilized as a scripting language and can be edited to byte-code for developing large applications.
- It presents very high-level dynamic data types and promotes active type checking.
- It holds an automatic garbage collection.
- It can integrate with C, C++, CORBA, and Java.
What is Python used for?
Python is a secure programming language. It is utilized for:
- Web development (server-side)
- Software development
- Mathematics
- System scripting
Let us note various operations that Python language can perform:
- Python can be applied on a server to build web applications.
- Python can be managed alongside software to design workflows.
- Python can join to database systems. It can also view and adjust files.
- Python can be applied to manage big data and deliver complex mathematics.
- Python can be employed for rapid prototyping or production-ready software development.
Is it easy to learn Python?
Yes! Python is so simple to learn. Python gives the best readability and uncluttered simple-to-learn syntax, which serves beginners to use this programming language. The code method guidelines, PEP 8, present a collection of rules to help the formatting of code.
Python has a high data structure; it has good potency and speed. It is user friendly; hence everyone can code and complete their tasks on time.
How can I learn Python by myself?
Python is presently the most successful primary teaching language at top US universities. No course in the world can guide you on how to learn Python programming in a few weeks. The most reliable way to study Python is by doing it yourself. And the most robust way to prepare yourself programming is by writing code. You will embrace more ground faster if you simply find the most suitable programming resources and do it by yourself.
These are the steps which will help you to learn Python on your own:
- Buy a good computer instead of a laptop, and install Windows or Linux. Mac is also ok.
- Buy genuine Python Programming books, particularly the ones suggested on the official Python website
- Download and install Python.
- Download and install a good text editor (e.g., Notepad++, Atom, etc.). Don’t use MS Word.
- Sit back on your computer and take out your manuals.
- Type each coding exercise manually using your preferred text editor (Don’t copy-paste)
- Always study and practice.
- Take advantage of YouTube videos and several other motivational videos online.
- Visit Python programming conversations if feasible, ask several questions. Learn from the best Python programmers.
There are many resources for learning Python programming:
Python.org – Nothing can substitute the official Python website.
GitHub – People use GitHub to build software. More than 28 million people use GitHub to create, fork, and add to over 80 million projects. It is one of the most useful resources for Python programmers.
LearnPython.org – It is a free interactive Python tutorial for people who need to learn Python fast.
TutorialsPoint.com – This tutorial is best for software programmers who need to learn Python programming language from scratch.
Recommended Python Programming Books:
Python 3.6 Tutorial by Guido van Rossum
Learning Python by Mark Lutz (O’Reilly Media)
Introducing Python by Bill Lubanovic (O’Reilly Media)
Python Programming by John M. Zelle
Python Crash Course by Eric Matthes
Learn Python the Hard Way by Zed Shaw
Python Cookbook by David Beazley and Brian K. Jones (O’Reilly Media)
Programming Python by Mark Lutz (O’Reilly Media)
Why is Python so popular?
It is a well-established reality that Python is one of the most popular programming languages. But have you ever admired why Python is so popular? What is the mystery behind Python’s global success and popularity? We will provide you the answer to all the questions in a single line – Python is one of the best programming languages of all.
Whatever be your growth and Data Science requirement, you just identify it – Python will take charge of it. Python is an open-source, high-level, general-purpose programming language that includes the features of object-oriented, essential, and functional programming.
It is founded way back in 1989 by Guido Van Rossum. It emphasizes the DRY (Don’t Repeat Yourself) principle, which improves the readability of Python code. Python’s robust string manipulation, a large number of user-friendly libraries, and natural shell access present it a valuable tool for fast automating monotonous tasks.
While Python’s easy syntax provides for writing readable codes, it can be additionally referred to as complex software development processes to help test-driven software application development, machine learning, and data analytics. Python can work on all the critical operating systems, including Windows, Linux, and iOS.
Since it works on cross-platform operating systems, it can be utilized to promote a host of applications, including web apps, gaming apps, ML apps, text processing, and so many more. But past its inherent simplicity and versatility, what makes Python stand out is its vast collections of libraries and packages that can provide a broad range of development as quite as Data Science requirements.
Applications of Python
We have listed some of the applications of Python below:
1. Web development:
Python allows many options for web development. For example, you have use Django, Flask, and Bottle for designing web frameworks and even excellent content management methods like Plone and Django CMS. These web frameworks are packed with standard libraries and modules which analyze tasks like content management, database interaction, and interfacing with internet protocols like HTTP, SMTP, XML, and POP.
Python web frameworks are famous for their security, scalability, and versatility. To add to that, Python’s Package Index begins with helpful libraries like Requests, Feedparser, and Twisted Python.
2. Numeric and Scientific applications:
Thanks to its extensive library base, Python has enhanced a vital tool in scientific and numeric computing. Python tells the design for applications that deal with computation and logical data processing. Apps like FreeCAD and Abaqus are coded in Python. Some of the most beneficial Python packages for scientific and numeric computation incorporate:
- Numeric Python (fundamental numeric package)
- SciPy (scientific numeric library)
- Pandas (data analytics library)
- Natural Language Toolkit (Mathematical And text analysis)
- IPython (command shell)
3. Game Development:
As we have discussed earlier, Python comes packed with many helpful extensions (libraries) that occur in handy for the development of interactive games. For example, libraries like PySoy (a 3D game engine that helps Python 3) and PyGame are two Python-based libraries generally used for game development. Python is the basis for modern games like Battlefield 2, World of Tanks, Disney’s Toontown Online, and Civilization-IV. Also, It is managed as a scripting language by various game engines.
4. AI and Machine Learning:
AI and ML designs and projects are intrinsically distinct from conventional software. When we speak about AI/ML projects, the tools and technologies utilized, and the skill set needed is different from those adopted in the development of traditional software projects.
AI/ML applications need a language that is durable, secure, resilient and has tools that can examine the several requirements of such projects. Python has all these features, and hence, it has matched one of the most preferred languages by Data Science professionals. Python’s integrity, flexibility, platform independence, the vast collection of dynamic libraries, and an active community make it the ideal tool for developing AI and ML applications.
5. Desktop GUI:
Python not only possesses an English-like syntax, but it too features a modular design and the capacity to run on various operating systems. These features, connected with its costly text processing tools, make Python an attractive choice for creating desktop-based GUI applications.
Python offers many GUI toolkits and frameworks that make desktop application development a breeze. PyQt, Tkinter, PyGUI, and PySide are some of the most beneficial Python-based GUI frameworks that enable developers to build deeply functional Graphical User Interfaces (GUIs).
6. Development of software:
Python packages and applications strive to clarify the process of software development. From developing complicated applications that include scientific and numeric computing to extending desktop and web applications, Python can do it all. It is the reason why Software Developers use Python as a base language to create, control, test, and manage software.
For example, SCons is created explicitly for build control. Buildbot and Apache Gump support are designed for automated continuous compilation and testing, and Roundup and Trac are best for bug tracking and project management. Python also carries data analyzation and visualization, thereby further analyzing the method of building custom solutions reduces the more effort and time investment.
7. Business Applications:
Enterprise-level software or business applications are strikingly distinct from conventional ones. Business applications require features like readability, scalability, and extensibility. Primarily, business applications are developed to suit the demands of an organization, preferably than the needs of individual customers.
Thus, these applications must be able to integrate with legacy systems like existing databases and non-web apps. After business applications are developed, holding in mind the system wants to present to the particular needs of an organization’s operating model, the whole development process becomes tough.
It is where Python can make a notable difference. Python’s high performance, scalability, and readability are just the characteristics required for developing fully-functional and compelling business applications.
Conclusion
After learning about all the features and real-world applications of Python, it is reliable to conclude that Python is proficient in handling virtually any development requirement. In the past few years, Python applications have achieved newfound traction in the field of Data Science as well, especially in Machine Learning. We hope you all have learned a lot from our comprehensive Python tutorial.
