I am sure that python is not a new word for most people especially those from a programming background and even to those who are not must have heard a word or two about it. Essentially, python is a programming language that is easy to learn and a solution to several modern-day programing hurdles. So yes, python has nothing to do with snakes but is basically a very useful programming language Having been developed by Guido van Rossum in the late 1980s, python has gained a lot of popularity in the present world. Python is a diverse language that is easy to learn as it does not differ from other programming languages such as Java, Fortran, C and C++. However, it is worth noting that python stands out from other languages in that it is reliable, its syntax is easy to understand and is faster to execute as compared to other languages.
Python is considered an object-oriented, procedural and functional programming language. An object-oriented language simply means that it uses objects to represent real world entities. Moreover, it being procedural that the program executes from the first command keyed in to the last. On the hand, what is meant by a functional language is that the language is built over logical functions rather than the execution of commands. Basically, functions in python are defined using the ‘def’ keywords. Keywords are words that have a special meaning in a programming language therefore have to avoid being used to avoid confusion. An example of a function in python is
def my_function():
print("function exist!")
It is also important to note that Python is a case sensitive language. This means that if an uppercase letter was used anywhere in an object, if a lowercase letter is used in place of the uppercase, an error will result as the compiler reads as two different things hence execution will not take place.
Arguably, python is used in various domains has many libraries. Some of the top libraries that python has include Pandas, Scipy, Django, Kivy, NumPy, IPython and PyTorch.
Django for instance, is used for developing the back end of websites. Scipy on the other hand has features like those in MATLAB, useful for processing multidimensional arrays especially in engineering and mathematics. IPython is used in parallel computing whereas Kivy is used in Graphic User Interface (GUI), to develop multi-touch applications. Meanwhile, NumPy and Pandas do not have much difference as they all deal with mathematical computations. However, despite the small similarities, the three operate in completely different contexts. NumPy for instance, is mostly used in providing objects for multi-dimensional arrays hence facilitating operations on large data therefore ensuring efficient execution of such operations. This is mostly because they use less memory space as compared to Pandas. Pandas on the other hand, are helpful when it comes to data manipulation and analysis. This is done as it offers data structures enabling manipulation of time series and numerical tables. Pandas are capable of offering in-memory 2-dimensional table data frame hence making them at times slower than NumPy. Lastly, PyTorch being a tensor library is used mainly in deep learning applications which require heavy matrix computations such as in machine learning. This goes on to illustrate further that although Python is a simple language, it is really powerful.
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