Written by Prashanthi Devi
Either you are a beginning your career or an expert shifting from a different programming platform or a company which wants to go ahead with the new implementation of Python, we want to throw light on few myths related to the Python programming language in the current market.
- Python involves huge cost
Python is an open source and can download from the official site for free of cost. Python coding language was developed first in the year 1991. Built, operated and managed by Python Software Foundation(PSF) which provides its users with Open Source License(OSL) even to the organizations ranging from small to large scale.
Most of its licenses are open source but not all. Some of its contributions come from General Public License(GPL) also. Here the organization needs to bear the charges for not adding the customizations done by the developer to the open source, which will remain exclusive to the company developing it.
- Difficult to learn and is a time-consuming process
Initially, assembly language was used for performing the operations. Later coding languages came into existence to improve the processing functionality which was syntax (involves curly braces and semicolon) oriented.
Learning Python does not require any specific knowledge of programming. But there exists an added advantage to the coding experts as they can relate well with its concepts due to the familiarity in code.
Being a high-level language Python is easy to code and implement. Most of it has simple mathematical calculations and instructions. The developer empowered with documentation which is quite well and complete. You can also find answers in forums of Python’s official site. It has a large supporting community and plenty of resources to take care of your issues relating to programming.
Most of the statements written in a Python program will look familiar with instructions resembling English language and contains very less syntax.
On an average Python, learning takes about three months and six months to excel in it. Python does not alter its naming conventions so frequently between the modules which ease the developers in formulating the code.
Have a look at the code below regarding matrix addition; you will understand its simplicity
# Adding two matrices by implementing the nested loop
A = [[10,8,5],
B = [[13,9,7],
add = [[0,0,0],
# changing rows
for i in range(len(A)):
# iterate through columns
for j in range(len(A)):
add[i][j] = X[i][j] + B[i][j]
for p in add:
- Not compiled and used only for scripting
Python is termed interpreted language as it falls under the category, but it also supports the term compiled as well similar to other programming languages like Java. The process is automated in a way that it does not get detected. A separate compiler not required with Python and it mostly compiles on a Virtual Machine.
Python is not a scripting language on the whole. It is more of a general purpose language and can also use for scripting. Most of the scripting languages do not showcase features like networking, exception and, regular expression.
It is the most trusted and reliable programming language and can automate some specific set of tasks in the program, and can extract information from the given data and less code intensive compared to other coding types. Python is a dynamically typed language and uses automated memory management.
- Does not scale
Python can scale widely both vertically and horizontally much better in comparison with others, but there exists a confusing point in this. This process in here is not automated hence will need some engineering effort to achieve it.
Scaling is not a mere single and straightforward entity it relates to various forms as making most of the underlying memory, persistent database servers like SQL, and enhancement from a single system to a distributed one. With Very few companies face scalability issues with python and among most of those who suffer it is due to the lack of proper architecture and not because of wrong coding.
- Python is slow and weakly typed
In the olden days, CPU’s were costly, and the same can be applied to the memory as well. But nowadays you can buy better hardware which is cheaper compared to your time to support Python programming. Speed is not our only concern the performance and length of code matters as well. With pythons increased functionality within a limited code dominates its trait of the little slowdown in speed.
Python, very strongly typed, and dynamic language unlike its peers as in PHP and can consider in broad areas of development. It can also use a scripting language. It supports multiple programming paradigms also as oops, imperative and functional.
- Does not support concurrency
Concurrency is when two tasks starting at the same time executed in overlapping time intervals. Frameworks of Python include Twisted and Gevent and Python runtimes such as PyPy and Stackless help to involve in customizing concurrency. There are two categories of parallel system implementation in Python namely processes and threads.
The processes are the programming instance that runs on a computer and help in speeding up the Cpu operations. It has a separate memory space which is independent. They can have multiple threads.
The thread is a continuous set of instructions within a process. The threads share the same memory space and are best for input-output tasks. Threading is well known to achieve concurrency and parallel processing with Python than process.
- Gaming cannot develop
It has several sets of libraries good to go with developing games. Pysoy and Pygame are the most used among these. These also include artificial intelligence and machine learning systems and is great to visualize far before developing. The gaming libraries in Python are very helpful to gain a complete grip and pace over coding.
- Python is not for big projects
Primarily when working with larger companies a lot of coding comes into picture due to the vast and varied implementation of the code. Reuse of code gives an added advantage. Python provides the user with a predefined set of libraries, and you can also clone them to create a new one with those of your own according to the functionality and reuse them multiple times to reduce the amount of time and work invested in composing the code. Most of the newly customized libraries are added to python and can reuse by other organizations.
With Python, large companies such as Facebook, Instagram, Youtube and Google employ Python for the varied set of successful projects. Its extensive set of libraries and diverse set of packages adds to its performance. With its robust code review capabilities and tools, you can quickly perform analysis of python code before it is checked in.
Other coding languages are complicated and take quite a long time to design a program and implement. Python, on the contrary, takes less time mostly a few months to ultimately achieve its functionality. Optimizing the code is of prime concern in any coding language, and the same is for Python also.
- Python is not for secure, critical systems and lacks support
Many have a wrong perception regarding python as less secure due to the little coding and simple syntax it has. Most of the coders consider that the code is prone to cyber attacks which is just an assumption. Python can also be used similarly to other languages to develop networking security structures. It is so secure in a familiar way and can apply for building automation testing and security testing tools which perform much faster than the others and can use for developing critical functioning systems even on a small level.
An official support team is always there to cater to the security issues if faced by any organizations using Python. You can anytime reach them, and the details will remain confidential and stay within the support team. Python’s adaptation from eBay, Paypal, and many other secure third-party global payment sites also proves its legitimacy.
- Less in demand
Python strictly contradicts the above statement is more in demand than its peers. Ranked the top 4th preceded by Java, C, C++ python can guarantee you a long-lasting career.
Python also meets the trending payment criteria ranging from $80,000 to $120,000 per year.
Not only the architects, but also the analysts, admin, developers, and software engineers come into this frame breaking the restrictions of future growth and appraisal. That means there is every possibility to earn more than the bracket shown.
Most of these myths came into the picture about a specific instance or a situation and not considered as general. There are quite many misconceptions about Python which are just myths, and a more clear picture of it can obtain by moving further with its implementation.
Prasanthi Korada loves pursuing excellence through writing and has a passion for technology. She has successfully managed several websites. She currently writes for mindmajix.com, a global training company that provides e-learning and professional certification training. She is based out of Kakinada and has an experience of 4 years in the field of content writing and blogging. She can be contacted at [email protected]. Connect with her also on LinkedIn and Twitter