Comparison of Scripting Languages - Research Paper Example

? Comparison of Scripting Languages Task Scripting languages are methods of programming languages that are typically interpretedbut not compiled. They are mostly written to enable features of web sites, tolerate fast advance, and can link simply with other programs written in other languages (Milano, 2010). In scripting languages, it is easier to write a code and programs arededuced one command separately. Scripting languages are overall purpose and not obviously concerned with scientific applications, therefore, they make any type of work easy and probable. They are categorized into scientific concerned and general purpose scripting languages. Examples of scientific based one are Matlab and Octave while those of general purpose are python and Perl. However, we are going to compare and contrast Matlab, Python, and Octave scripting languages by analyzing. According to Chapman, Matlab is a computer program enhanced to perform scientific and engineering calculations (2008). It started as a program to calculate matrix mathematics but with time, it improved to a malleable calculating program capable of resolvingbasically any technical difficult. Python is a dynamically, securely, and powerfully typed language. Python offers the clean and easy word order of the prevalent scientific calculating environments, grounded on your preferredhigh-performance FORTRAN, C, and C++ codes (Langtangen, 2008). While Octave is software, same as Matlab that has a well-matched scripting interface. However, Octave image processing purposes are not as broad as those provided by Matlab. Python, Matlab, and Octave scripting languages have many things in common. They have no affirmation of variables, and simple and suitable word order that make them easy to use ad to learn. In addition, they easily go together with GUIs, simulation, and visualization. However, Matlab and Octave are more independent languages, while Python requires coupling with several other packages in order to make an environment of reasonable functionality. Federico argues that, dynamic typing is easily found in scripting languages such as Python, while in Matlab and Octave both dynamic and static typing is found (2010). In addition, Python is much stronger programming language compared to Matlab and Octave making it the most convenient to use in computing scientific calculations. However, this python feature makes it to be preferred to by scientists can perform weighty operations compared to Matlab and Octave. The time needed to load and change input files folder of the Matlab, Octave, and Python differ considerably. Python is the fastest followed by Matlab and Octave respectively. These show that Python can load fastest compared to the other two, however, it is the best in loading. In terms of the power structure examination, Python has the best performance compared to Matlab and Octave. This makes it efficient in the calculation and extremely fast compared to Matlab, though, Octave is the slowest of all. These clearly illustrate that Python programming language is stronger compared to Matlab and Octave. The Python, Matlab, and Octave environments differ considerably. The Python environment is incredibly open and is made in such a way that external tool can be integrated with it. For example, calling a program like FORTRAN from the Python is extremely easier, and the Python borders can take benefit of object- concerned scheme and easy gluing to GUIs, and visualization. However, calculating with FORTRAN from these boarders can be done in either short scripts or interacting full over a Python shell. Therefore, Python interfaces can be used to existing libraries like a way of making your own custom-made environment for resolving predicaments. Conversely, Matlab and Octave environments are not open, therefore, they cannot be easily be integrated with external tools. The characteristic of the toolbox of the Python, Matlab, and Octave also differ according to how can be contained. In Matlab and Octave, the toolbox is mostly characterized by a bunch of M-files. In addition, the functions and classes in the toolbox of Matlab and Octave cannot be contained in one file (Chapman, 2008). These make their module congested and not easy to use because one has to take a lot of time looking for a functions and classes. Conversely, for Python environment a whole toolbox with many functions and classes can be confined in one file. This make working with Python easier because it is well organized compared to Matlab and Octave. In addition an individual who unfamiliar to it and is willing to learn, can learn it easily because it is well organized. Python, Matlab, and Octave being scripting languages commonly competing in computing scientific calculations, the most convenient is used. In calculations, functions are the major factors that are used. However, a language that can proffer the best way of using and transferring these functions is preferred to that which cannot provide. Matlab and Octave being in the category of scientific system of scripting languages have failed to enable transfer functions as arguments to functions simply. Conversely, Python being the strongest of Matlab and Octave can simply relocate functions as augments to functions. These characteristic of Python bas made it to be commonly used compared to Matlab and Octave. In the present societal context, combined varied data structures in scientific calculation should be easy to construct and use. However, a scripting language that can easily construct and use these combined data structures is highly recommended compared other scripting languages that cannot easily construct. Matlab and Octave that are meant for scientific calculations are expected to have this characteristic, conversely, they do not have. Therefore, people have preferred using Python because combined diverted data structures are easily constructed and used. Since, time is a factor to all of us, a scripting language that can help someone to take the shortest time possible in a task is preferred. This has made Python to be commonly used compared to Matlab and Octave. Scripting languages are not able to do weighty mathematics operations directly, but require proficient C, C++, and FORTRAN (Milano, 2010). Inventions of libraries like C, C++, and FORTRAN, which are difficult to use, have made people to a way to make them simpler. A scripting language that can support their interface well is encouraged in order to make the procedure easier. C, C++, and FORTRAN are exceptionally important in computing scientific calculations; therefore, their code should be interfaced in order to use them easily. However, they can be interfaced with Matlab and Octave, the interfacing is not well supported making it hard.Conversely, python is one of the scripting languages where interfacing with C, C++, and FORTRAN code is well reinforced making, therefore, making the interfacing simpler. This aspect has made Python to be advantageous over the Matlab and Octave. Matrix factorization performance is exceptionally common in mathematics, a scripting languages that can easily perform them is preferred to those that can perform them slowly. Grouping indexing is a common factor in computing matrix operations, therefore, for a scripting language that is used in computing them should be very fast. In this case, Octave and Matlab are comparable because Octave is slower than Matlab. Matlab being better than Octave it is preferred because it is easier to perform matrix calculations using it. However, Python is the most convenient because it is characterized by a capability to work scalar functions with grouping indexing. This makes it the best scripting language that can be used to execute matrix problems. Matlab and Octave are scientific computing languages that are more number crunching than performing the real calculations. A typical scientific scripting language should be able to shuffle statistics in and out of different tools, and control numerical operations involving numerous numbers of data records (Langtangen, 2008). However, Matlab and Octave being in the scientific category lack this characteristic making the insufficient on computing operations. Conversely, such works are easily accomplished in Python compared to Matlab and Octave. In addition, the Tk-based GUI tools accessible through Python simplify wrapping of the existing programs with GUI. This has made it the best scripting language for graphical user interface over the Matlab and Octave. Scripting languages are exceptionally important in daily life. However, they differ with their effectiveness, all of them are important in one way or another. Comparing the three scripting methods has clearly shown that Python is the most convenient to Matlab and Octave. However, the three scripting languages have a similarity, but the speed in these similarities differs. A scientist who uses Python as his scripting language does his faster compared to the scientists who use Matlab and Octave. The features of Python are the ones that have made it the most convenient programming language over the Matlab and Octave. However, there should be a room of improvement to make Python even more convenient and easy to use. The source of the python language being free and running on many platforms makes it a wonderful programming language to use in computing scientific calculations. References Chapman, S. (2008). Essentials of MATLAB Programming Volume 10. New York: Cengage Learning Publisher. Langtangen, H. (2008). Python scripting for computational science. New York: Springer Publisher. Milano, F. (2010). Power System Modeling and Scripting. New York: Springer publisher. Read More