Software development is a practice that is here to stay for several years. And so will every component that is used to create software apps. For a fair amount of time now, Python has proven itself to be one of the best programming languages to be used for development.
It is said to be easy to learn, understand, and write code in. It helps development teams accelerate the process and deliver the product quickly. While several developers are now preferring Python as the programming language, some industries need it.
Industries That are Reliant on Python
Here are the industries that use apps developed only by Python:
Going by syntax, Python is probably the simplest programming language currently available. Contrary to other programming languages, Python gives more prominence to code readability and enables developers to use English keywords in place of punctuations.
The easy-going nature of Python helps developers a great deal in the maintenance and updating of software without the need for them to put in any extra effort. Several experts of programming languages have also proclaimed that Python is ‘everywhere’.
As it is a small-sized language, it can show up on embedded devices on any type of server. It is also pointed out that that Disqus, PBS, Reddit, and NASA use Python for website and app development.
As a matter of fact, Python is said to be one of the languages that can be used to program a Raspberry Pi along with a single-board computer system at the same time.
What makes the prospects better is the fact that there are several real-world projects that actively promote the use of these types of systems to learn Python code and specialize in it.
There are several built-in Python libraries and web app development frameworks such as Pyramid, Flask, and Django all of which open in a new tab. Python is considered the ideal language for back-end web development projects. It also includes APIs that shorten the amount of time that is spent on repurposing lines of code.
Scientific Computing and Data Science
Python is frequently used for the purpose of scientific research and computing. It has plenty of science-friendly and science-specific libraries such as SciPy, sci-kit-learn, and more. Here are a few of them along with the purpose they are used for:
· Astropy: Used for astronomy purposes.
· BioPython: Used in biology and informatics.
· Graph-Tool: To check statistics with graphs.
· Psychopy: Used for neuroscience purposes and experiments with psychology.
Python can play a pivotal role in data parsing, data scripting, and data functionality based on the algorithms that are written. It is considered a great advantage of both learning Python and adopting it.
There are several other tools that are integrated with Python like pandas and NumPy to orchestrate data analysis through efficient visualization and navigation.
With the unparallel rise of data science drastically coming upon us, several tech roles are expected to be on the vacant docket of many companies. The biggest benefit here is that you will always have access to one of the best programming languages there is.
By using Python for Machine Learning, you are following the millennial developer rule. Most developers these days prefer a combination of experience along quality to create any type of software.
Using Python for Machine Learning, you set yourself on the path of achieving this quicker than you expect. Just in case you are unaware, Machine Learning involves aspects like speech recognition, financial services, AI, and more.
For instance, when you log in to Netflix, you get a recommendation that helps you to continue watching from the point you left out. Even though a team is employed to manually handle this, it becomes easier with ML.
To learn Python for machine learning, users will need to clear a test by learning about various machine learning libraries and frameworks like sci-kit-learn and TensorFlow.
Robotics and Reinforcement Learning
Reinforcement Learning is another field that where the use of Python is heavily relied upon. Robotics approaches learning a particular action in a specific state of environment. It requires an agent to constantly evaluate the environment and make attempts at choosing an optimal action for a given time step.
While this appears to be a simple concept, it can become complex as comprises of a mesh of algorithms and can be experimental during application. This concept is also somewhere along the lines of Machine Learning as it provides a base platform for Reinforcement research and application development.
Python comes way above other programming languages when the domain in question is FinTech. According to several surveys, Python is the most used programming language in the Fintech industry.
It is a fast-growing language that has the backing of organizations like Bank of America which makes it easy for developers to choose. The seamless code readability allows developers to navigate the tech stack in an existing fintech app and convert the code to Python.
Develop Python-Based Apps with 91Social
For the best software development using a language like Python, you need to partner up with 91Social. We are providing top-quality development services to clients in the above-mentioned industries which makes our case stronger as Python-Based developers.