Comparing C++ to Python

Computer coding languages are no different from other languages used around the world to communicate. There are subtle differences and some similarities. At a basic level there are even some universal laws or rules of language that apply. For Python and C++, this is just as true. This paper will compare C++ to Python and show where strengths and weaknesses appear.
The key difference between C++ and Python is that the former simply acts as a general purpose language for programmers. If French is a highly-advanced Western language, Python may be viewed as its equivalent in the coding world. C++ on the other hand would be viewed as a language like Latin—the root of many of the Western languages and therefore applicable to most. C++ comes from the original C language. C++ is static, free-form, multi-paradigm and compiled. Python is also general purpose but it is much more high-level: it is cleaner, direct, easily read and allows for quick programming.
C++ is generally viewed as a programming language for intermediate level users. It contains low-level and high-level features, and utilizes classes that allow for more complex calls to be made. C++ was designed to enhance C but then began to be seen as a preferred language in its own right. Today, however, when programmers want fast results, Python acts as a shortcut because its code is much brief in expression than that of other languages. Concepts can be written in fewer lines.
One of Python’s main strengths is that it allows programmers to program quickly. Compared to C++, Python is like a Tesla Roadster that is able to go from 0 to 60 mph in 2 seconds flat. C++ on the other hand is like an old golf cart that will never even hit 60 mph. Then why do programmers prefer C++? The fact that is that even though Python allows programmers to go faster when developing a program, Python programs still run more slowly than C++. Other programmers prefer Python because they love it for its quick programming times: Python has a high-level of data types that are already built in to the application, which enables a programmer to spend as little time as possible making a declaration about a type of argument or variable. Python is also designed so that it has a very powerful list of dictionary types, so that there is strong syntactical support written directly into the application. It is like a writer using Microsoft Word and not having to worry about checking spelling or editing because the application does that for him as he goes. It reduces the amount of time that must be spent in the writing process, and for a programmer that means faster results.
However, Python must work hard when it comes to running. An example of how this is so can be found in a simple evaluation process: if one is evaluating an a + b expression, Python will examine the objects to determine their type because this is not clear during compilation. Once the object type is found, then the program begins the next operation, and so on, all of which may lead to overloading. C++ allows the programmer to declare the variables up front so that there is no risk of overloading, as the program can perform the simple evaluation without trouble.
How this basic comparison impacts one’s view of Python and C++ is that Python is commonly seen as a “glue language” while C++ is seen as a “low-level implementation language” (Rossum, 2015). In other words, the two programs can actually be combined together so that when it comes to writing the code, Python can be a great and useful application while running the code can find that C++ is superior. Switching between the two and taking the code from one to the other and back again as it is worked on by programmers can be a useful means of developing.
Some of the things that programmers love about Python are its list/dict comprehension, its built-in syntax generator, also known as stateful coroutine. C++ also offers this today but by way of its library, whereas with Python stateful coroutine is available directly through the core language of the program. Python also allows the programmer to change variable types at run-time (C++ is static so the programmer must declare the variable type at time of writing—which has its positives and its negatives: for instance, in C++ it is evident what the variable type is from the beginning and it also makes run-time quicker). This leads to one of the problems of Python: everything is an object. In C++, variables are defined and int, float and class can all go on the stack without being jumbled up and unclear. C++ determines class members when they are compiled. Python does not determine them until the program is ready to run (which allows the programmer to re-assign functions and methods if desired, but which can also cause run-time to be substantially slower than C++).
C++ also has virtually no reflection via RTTI. Python is designed to be full-on reflective, so that iterations can proceed over any class method. This power of reflection allows Python to easily serialize all objects.
One of the biggest issues, too, is that Python wastes memory. It is simply not an efficient use of memory because a simple list of integers will require 200 bytes on a 64-bit computer whereas C++ can carry an integer array and only use 16 bytes. This means that in hardware terms, C++ is the more efficient of the two, even though Python has some very effective tricks that make it seem like the more efficient instrument when writing code. It is a spoiler of memory and can cause machines to become sluggish and slow as a result (Veksler, 2016).
The end result of Python’s mismanagement of memory is that it is ultimately a slow-going application. So when it comes to using Python to type the language, the application is stellar, when it comes to using Python to run the language, the application falls to pieces. This does not mean that Python is worthless on the run-end of things but that it makes the process slow and when compared to C++, the overall performance may be seen as about even when these programs are used exclusively. Python does have programming advantages but so too does C++ and in the end it depends upon the programmer’s preference.
In conclusion, there are good aspects and bad aspect to both Python and C++. Each has its strengths and weaknesses. Python is certainly easy to use when it comes to writing the code. When it comes to running the code, Python is slow, as it uses an interpreter while C++ compiles declarations ahead of time. C++ is much easier on memory whereas Python uses a lot of memory. Python is supportive of quick development but is not efficient for running the development. C++ is still a standard language development system that a lot of applications use when being built. Python acts more as a developer’s crutch, assisting the developer in writing the language. But as has been already shown, the two do not need to be exclusive. Both can be used and the programmer can switch between the two by translating files. As Goldwasser and Letscher (2007) point out, C++ is a universally used programming language, while Python offers many great advancements and additions to C++ while C++ offers a stable platform for declaring variables up front and adding them to the stack without eating too much into a system’s memory.

References
Goldwasser, M., Letscher, D. (2007). A transition guide: Python to C++. Retrieved
from https://pdfs.semanticscholar.org/9ad1/030685050e949d1a3d6d92bababcbe075e07.pdf
Rossum, G. (2015). Comparing Python to other languages. Retrieved from
https://www.python.org/doc/essays/comparisons/
Veksler, M. (2016). What is the difference between Python an C++? Retrieved from
https://www.quora.com/What-is-the-difference-between-Python-and-C++