What is with the name of this programming language? And not to mention all the hype that it has created these days. Machine Learning and Artificial Intelligence have become synonymous to Python and honestly, it is the ‘thing’. So, is it easy to master such a weapon? Shoot your worries, and read on to get answers to all the questions that might have been bugging you.
Ever wondered how did Python get such an appalling name?
“Monty Python’s Flying Circus”, a BBC comedy series from the 1970s inspired Van Rossum to name this language as python. However uncanny it may sound, this programming language is very ‘friendly’. From beginners, all the way up to the professionals, python is a great language. It is basically a high-level programming language which is customized to support different programming approaches according to the real world problems.
Meaning, Python is multi-paradigm programming followed by dynamic semantics, designed by Guido Van Rossum. It was initially released in the year 1991.
The filename extensions are .py, .pyc, .pyd, .pyo. Python is a general-purpose programming language with its high-level built-in data types which is extended for the real and complex application development.
Python is used to build both desktop and web applications. In Python, we are provided with modules and packages which tends to increase programs modularity and code reusability.
How Python Makes Programming Simple?
Having a spectrum of applications, Python is simple and easy to code language.
It happens a lot of times that we as programmers find it difficult to handle a large bunch of variables and methods especially when we are dealing with a magnanimous application.
Therefore to overcome these complex situations and for the ease of a programmer in Python, we are given a key. In this key, we need not declare variables, parameters, functions, and methods.
This, in turn, makes the code short and flexible and hence the part of compile-time checking code is being saved. Although, it tracks the types of all values at runtime and flags code that does not make sense as it runs.
Not only is this, but most beginners without any keen interest in programming are easily repelled by even looking at the code, let alone trying to understand it.
Here, Python is kind of famous for its simplicity for a piece of code although the key feature which creates a difference is the indentation that is the “whitespace” which affects its meaning.
This feature gives a logical meaning to the code while, as compared to other languages indentation might not have been seen as a problem.
Along with it, the debugging in python is incredibly fast which will never cause a segmentation fault.
Python uses English keywords instead of punctuations which makes it highly extensible for the users. So now after becoming familiar with Java and C++ those of you deplore coding, Python is here to break the convention for you.
It is constantly evolving, maintaining peace with its ease and application in latest technologies.
What are some of its real-life applications?
After these interesting insights about the programming language, let’s have a look at some of its application in real life which might amaze you!
- Facebook is using Machine Learning to tag in posts and images.
- Of 75% of what we watch is recommended by Netflix. Recommendations are made by Machine Learning. And machine learning is implemented by python.
- Alexa is Amazon’s Virtual Personal Assistance used for speech recognition, weather detection etc.
- Python also contributed in a large part to functionality in YouTube.
Steps that Python has climbed within the past few years!
Being aware of different versions of python gives a better understanding of how it works.
It is continuously reinforced with varied features from time to time, thus enhancing its utility.
In meantime, version 3.7.2 is serving us with its latest and upgraded features. Python 3.0 is a major and an incompatible release.
Here, let us subsequently discuss in brief about all the different versions of python:
- Version 1:
Version 1.0 was the very extended and modified version which was released in January 1994. This version consists of notable and major features like “ lambda”, “map”, “filter” and “reduce”. Version 1.0 is followed by the versions 1.2, 1.3, 1.4, 1.5. 1.6. As the development of these versions, the major difference was seen in 1.4 python version which contains the Modula -3 inspired keyword arguments and built-in support for complex numbers, not only this but the basic form of data hiding by name mangling were also included.
- Version 2:
Under this, it introduced the list comprehensions which is a syntactic construct used for creating a list based on existing one along with it a garbage collection system was also introduced which was capable of collecting reference cycles. Version 2 was enlisted with 2.1, 2.2, 2.3, 2.4, 2.5, 2.6 and 2.7.
Many of us are aware of the fact that Python 2.1 was analogous to python 1.6.1 as well as python 2.0 as its license was renamed under Python Software Foundation License.
The major innovation and changes were seen in python 2.2 which was the unification of python types which were written in type C and classes into one hierarchy. This modification brings us to the model which was purely based on object-oriented concepts.
With the strings of continuous versions many versions for ex. 2.6 and 2.7, were coincided with similar features which were resolved later.
- Version 3:
There is no need to state that our current version of python is named under this version i.e. 3.7.2.
Python 3.0 was designed to rectify the fundamental flaw which was related to the language part. This could not be implemented while retaining the full backward compatibility of 2.X series which necessitated the need of this version.
The central idea behind the introduction of this version was the “reduce feature duplication by removing old ways of doing things”. This version gives a new definition which gives emphasis on removing duplicative constructs and modules.
Nonetheless, Python 3.0 remained a multi-paradigm language which was further continued with its subversions 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, and 3.7.
We as coders still have options among object-orientation, structured programming, functional programming, and other paradigms, but within such broad choices, the details were intended to be more obvious in Python 3.0 than they were in Python 2.x.
What makes Python this popular?
So far we have discussed how the prior versions contributed to give rise for the introduction of more developed versions with advanced features.
The versatile behavior of python language has built a series of diversified applications which we use today. The basic principles behind python to be more popular are as follows:
1. Easy interaction
The package of python contains numerous third-party modules which are capable of interacting with other languages and platforms.
2. Comprehensive Libraries
It includes a large standard library which consists of areas like internet protocols, string operations, web services tools, and operating system interfaces. Many tasks which have already been scripted into this library helps to reduce the length of the code in a significant manner.
3. Open Source
Python is developed under an OSI-approved open source license which makes it free to use by other users and it can be easily distributed and can also be used for commercial purposes.
4. Productivity and Speed
As we already know that python follows an object-oriented approach which in turn enhances process control system and possesses strong integration and text processing capabilities and its own unit testing framework, all of which contribute to the increase in its speed and productivity.
5. Learning ease
One of the significant attributes which keep people to hold on to python is its excellent readability and easy to learn syntax which is a plus point for the beginners to wrap the language in a conventional manner.
These points are the basic approximations of how python is different.
Where does Python fall short?
Like any other programming language python also comes with its shortcomings.
The sorts of tasks Python is not well-suited for are worth noting!
Python is a high-level language, so it’s not suitable for system-level programming—device drivers or OS kernels are out of the picture.
It’s also not ideal for situations that call for cross-platform standalone binaries. You could build a standalone Python app for Windows, MacOS, and Linux, but not elegantly or simply.
In mobile development, domain python is not a very good option. People who work with python may face several issues with the design of the language as it requires more testing and only pops error at the runtime. Python has limitations with database access which as compared to technologies like JDBC and ODBC is underdeveloped and primitive in nature.
Finally, Python is not the best choice when speed is an absolute priority in every aspect of the application. As many of us might have used C and C++, as compared to them we see python is slow in nature. Not only this but sometimes python does not gives us a satisfactory result in memory management tasks and also the flexibility towards data types makes it use more memory.
Having said this, it does not imply that python programs would forever be slow! The section of the program which defines its speed can be optimized. Using projects like Numba and Cython, this part of the code can be converted to C/C++. Thus, overcoming the drawback.
Over the past 1 year…
In recent years, Python has come up as a language which is now used in almost every sector. It has spiked up the charts conquering the most common area which is web and internet development. Python has a gamut of frameworks available for example Django, Pyramid, Flask and Bottle.
We can also write CGI scripts. With the help standard GUI library, we can easily draft a user interface for many applications. It also serves in the scientific community like SciPy, Pandas, IPython and many more.
Python proves to be a great support language for the software developers as it gives the remarkable results in control and management, testing.
Last but not the least python has proved that its simplicity makes it an extraordinary language not only for professionals but also for the students.
How to embark your journey of coding in Python?
If this was intriguing enough then I would strongly suggest that you start development using Python. We are excited to share with you these basic tips and tricks to bolster your learning!
Tip 1: Code every day
Be consistent. Practice every day, initial days can be daunting. But don’t give up!
Tip 2: Write It out
Take notes. Plan out your program’s logic paper before moving it to the screen.
Tip 3: Go Interactive!
Use Python’s interactive shell to run commands that you’ve learned recently. It’ll give you a better understanding.
Tip 4: Take Breaks
Giving undivided attention to the program while coding is necessary, but many a time you get a brain block. Go get fresh air! A fresh mind and a fresh perspective can help you solve a problem quicker.
Tip 5: Surround Yourself with Others Who Are Learning
Work together with people, share tips and tricks. Find more python enthusiasts like you!
Tip 6: Teach
As a common adage goes, the more you teach the more you learn. Well, that’s true and works for programming too.
Tip 7: Pair Program
This is an agile software development technique. Wherein two programmers work together, one person drives, the other navigates. They switch their roles frequently. This would expand your thinking bandwidth.
Tip 8: Build Something, Anything
As a beginner, building something would provide you with a valuable learning experience. So, go for it, build any game or app you wish.
Tip 9: Contribute to Open Source
This would give your work an expert’s eye. Also, you’ll learn the best practices in the long run.
Now you are all set to commence with Python Development.
Go, nail it.
Happy Coding! 🙂
ps: And for those we can’t get enough of Python, I would really recommend that you check out this amazing Python Guide.