Developed by Guido van Rossum in 1990’s, Python is an all purpose programming language that is object-oriented, and interactive. Similar to the programming language Perl, Python’s source code can be found under the GNU General Public License (GPL).
Why you should learn Python?
Python is an asset to working professionals or even students who are aspiring to become software engineers, especially when they are/they want to work in the web development domain. Few advantages of learning Python are:
- Python is a Beginner’s Language − Python is a great choice for beginner-level programmers. It is highly compatible with a lot of applications, be it games, WWW browsers or simple text processing
- Python is Interactive − With Python, the user can directly interact with the interpreter to write their programs
- Python is Interpreted − The interpreter processes this programming language at runtime. There is no need for the user to compile the program before executing it
- Python is Object-Oriented− Python supports Object-Oriented programming style that contains codes within objects
Reasons Why Python Is Used Widely Over The Web
As mentioned above, Python is a popular language for both students and working professionals. Herebelow, I have highlighted some reasons for its wide usage:
- Python is very easy to learn, read and maintain– As the language has a simple structure, clearly defined syntax and simple structure, you can learn the language in no-time. It’s code is defined clearly and its source code maintainability is also very easy
- Python is Portable– It can run on many different hardware platforms and on all its platforms possesses the same interface
- Scalable-There is a lot of support for large programs and also a better structure in Python
- GUI Programming– In Python, GUI applications are supported. They can be developed and then ported to many libraries, system calls and Windows systems including Macintosh,X Window system of Unix and Windows MFC
- Large Libraries– Python has a large number of libraries that has cross-platform compatibility and are also portable
- Extendable– Low-level modules can be added to Python that can make tools more efficient
Characteristics of Python
Some of the distinguishing features of Python are:
- It can be effortlessly combined with C++, C, ActiveX, Java, CORBRA and COM
- Automatic garbage collection is readily supported
- The language also supports OOP, structured and functional programming methods
- It can be easily compiled to bye-code for developing big applications and can also be employed as a scripting language
- It offers a high-level dynamic data types and is also compatible with dynamic type checking
Applications Of Python
- Web Development
- Data Analysis/Visualization
- Machine Learning
Python For Web Development
Of late, Python based frameworks such as Flask and Django have become popular for web development. With these frameworks, you can develop server-side code in Python..
Frameworks are necessary as it makes developing common backend logic easier. What this involves are mapping various URLs to parts of Python code, handling databases, and producing the HTML files that users see on their browsers.
Amongst the many frameworks in Python, Flask and Django are two of the most popular ones. I recommend you to use one of them if you are a beginner.
What’s the difference between Django and Flask?
- With Django, you will get an all inclusive experience. What this means is that you get a database interface, an ORM (object-relational mapping), a directory structure for your apps, an admin panel and out of the box projects
- With Flask, you get flexibility, control and flexibility. You are free to determine how to implement things as Flask is un- opinionated.
You should probably choose:
- Django, if your main concern is the final product. This is especially true when you are working on applications that are straight forward, where there is only one way of doing things.
- Flask, if your main focus is on learning and experiencing. You should also choose this framework when you want more control regarding the components to use
Python for Data Analysis / Visualization
Python has one of the most popular libraries for data visualization, ie Matplotlib. The advantages of this library are:
- Easy to start
- There are libraries based on it, like seaborn. Thus, learning Matplotlib will enable users to get familiar with other libraries
Python for Machine Learning
Python has two main libraries for machine learning. They are TensorFlow and Scikit-learn.
- A low-level library, TensorFlow enables you to develop custom machine learning algorithms
- Scikit-Learn has some of the popular machine learning algorithms in-built in it