Python Development - What Can You Do With Python In 2020?

What can you do with Python? Probably, quite a bit. In fact, if you want to use Python for your projects, you 're not alone; Netflix, Facebook, and Google are just a few of the high-powered companies that are making use of Python regularly.

Python is a great programming language due to its easy readability and a wide variety of applications and there are plenty of Python projects available to programmers of all levels. Such ventures are not limited, but include:

#Automation

#Computing

#Machine Learning

#Web Development

#Machines

#Games

#Education and more...

Python for Automation

If you are looking to test your skills for a smaller project, scripting is a good place to start. Because of its simplicity to write and how easy it is to transfer code to similar projects Python is often used for automation tasks.

Scripting basically means designing small scripts to execute routine activities, such as sorting keyword-based texts, creeping through a list of documents to rename similar names, or link and watermark PDFs.

Not only does scripting help remove repetitive work but the project's simplicity helps developers to frequently test their scripts.

A wide variety of resources are available to help you start your automation projects. For example, Fabric is a library which can help you automate your command line. On the other hand, Beautiful Soup helps you pull the data from different locations.

In reality, the final tool, GitHub, serves as a repository for each of the Python projects mentioned in this article. The website is a network of developers and projects and offers you an invaluable asset range during your Python adventures.

Python for Computing

One other pretty simple Python application is the ability to create data collection and breakdown programs. For example, you can mine a website for information with Python, and run a results analysis.

Python can be used for a range of computing tasks, from creating simple lists of numbers or specific terms to generating extensive graphs of the findings. However, in general, the difficult the request for information, the harder the coding is.

Pandas is a great resource, helping you move to the actual data analysis beyond simple data collection with Python.

You should check out SciPy, which provides tools for scientists and engineers if you're looking for more programs, specifically those that can assist with scientific computing.

Unlike other Python resources, these are open-source, ensuring you 're able to change the code and share your own version.

Specific applications are vast for this kind of coding. On a Twitter feed, you can run data analytics to try to analyze trends, monitor stock prices, and set notifications when they reach a certain dollar value or track online sales data when you run your own business. Of course, these are just scratching the surface for the ways in which scientific and numerical computing could be used.

Organizations like Spotify, which uses Python-based technology to evaluate the music catalogue and deliver reliable reviews and playlists, employ this form of the project on a much broader scale.

Python for Machine Learning

Combine automation and scientific/numeric computing, and you have the machine learning building blocks that are responsible for everything from the movies Netflix recommends you to your photo library identifying your visual subjects.

Machine learning works essentially because a system is programmed to try and identify a specific trend – such as your distinctive facial features or your interest in Television shows – and then make decisions based on what it has already learned for new information.

While it may sound overwhelming, machine learning really has quite a few to do, including for beginners. Remember the project we mentioned earlier, which would allow you to build a program for monitoring stock prices? Machine learning could take it a step further, allowing you to develop a stock market prediction system.

Know anybody else has sloppy handwriting? In fact, Python can be used to teach a machine to read. Or, if you run a website, you could be able to build a chatbot to support consumers at all hours of the day. Machine learning like robotics has great potential for making your life simpler!

Python for Web Development

All that being said, Python is more than just useful for automation tasks and has become extremely prevalent as a web development system. Instagram is currently one of the world 's best Python apps!

As Hui Ding, who worked as Instagram's Director of Technology until 2018, explains: "Python is user-friendly to developers – it's easy to get up to speed and get the product out."

Python is most useful for backend coding when working with web development, creating programs that have similar functions to the numeric computing tasks. Typically the rest of the work depends on web frameworks which work with Python coding.

If you haven't done much web development before, starting with a micro web-framework such as Flask or Bottle could be worthwhile. These frameworks are a perfect choice for smaller projects and seem to provide more versatility, meaning it's easier to make improvements further down the road of the project.

Of course, the smaller size of micro web-frameworks means it won't be able to support project growth, depending on what you do.

That is where web-frameworks full-stack joins. These include popular frameworks such as Django, used in Instagram, and Pyramid. Full-stack web frameworks are useful for larger projects; they come with a wide range of libraries and frameworks to help you.

Python for Machines

Do you want to see your code coming to life in the real world? When you combine your Python expertise with something like Raspberry Pi, there are all sorts of opportunities to build exciting machinery. You can do just about anything with only a few spare parts and some imagination.

For example, by creating motion-sensitive lighting or programming a way for the heating to adjust based on how many people are inside, you can bring your automation skills into your home.

Basically, the sky's the limit for what you can create with a combination of Python and Raspberry Pi, with some extra tech.

Of course, these ideas for a Python project are just the prelude. The sky's the limit for what you are able to produce. If you're beginning your first simple automation project or moving deep into a machine learning program, with Python there's always more to do and explore.