Python vs. PHP – When Does Polcode Choose Python Over PHP?
Behind every great web or mobile app is a well-implemented backend development service.
But which is the right backend framework for your next project? Why should you even consider your server-side programming language? Should it be based on PHP or Python?
Choosing one over another will have a lasting impact on the development process and maintenance of your application. Let’s get into considerations for when and where Python is an appropriate alternative to PHP.
Python vs. PHP – Apples to Oranges?
Even though developers will eternally compare PHP and Python, keep in mind that both languages are convincing options, highly effective and widely used. We build with both PHP and Python projects at Polcode, and when it comes down to it, any backend we’ve built could be written in either language. Sometimes, a project will start in PHP and fragments later on are built in Python as well.
PHP is still the most common server-side coding language for websites, which we use here at Polcode quite frequently. Its primary advantage is that PHP projects have faster time to market—websites can get up and running in no time, and modern PHP offers versatile, powerful tools for nearly every business case.
So when do we need Python?
Python has advantages when it comes to larger, more complex projects with specific business requirements involving huge amounts of data processing. PHP still reigns supreme when it comes to what most internet users are familiar with when browsing, shopping, reading or posting content—think Wikipedia, early Facebook, WordPress, ecommerce stores, etc.
For web apps that offer analytics tools, their technology needs to handle background activities, dynamic information processing, statistical analysis, and incoming live data from other websites. This is where Python comes in. For example, Python was chosen to handle the backend of sites like Netflix, Reddit and Instagram, which face huge scaling challenges and performance requirements. Web apps which need live data visualizations and predictive analytics also tend to prefer Python as the backend setup.
Crunching Large Numbers
Python is chosen over PHP when we need scripts to listen to events in a system and “stay” longer in memory. Python can handle large numbers of simultaneous processes and have memory management. PHP was created for typical quick web request-response format.
Serverless computing has very little support for PHP, so Python is the default language option. If we’re building an application based heavily in the cloud (e.g. data processing from AWS S3 via AWS Lambda scripts), then Python can help us handle processes like multimedia or data processing or applications with a varying amount of server load at different times.
Serverless can also be chosen on the business side, because (depending on situation) it can be more affordable when you don’t need to pay for a server running 24/7, nor provide maintenance and server infrastructure.
PHP itself is faster than Python, but scalable applications with lots of diverse traffic on the cloud are much easier to create using AWS and Python.
Python offers two-fold benefits for data scraping processes. Python is fast and efficient for automatically downloading and processing data from external sites, while also being supported with a ton of libraries and tools so that most projects don’t require coding from scratch. When it comes to any project needing data extraction, visualization or manipulation, Python fits the bill.
Internet of Things
While not strictly web development, Python is the most popular language choice when it comes to building IoT field devices—as well as the web apps that support them. Python can sit on the device level, reducing the complexity and data processes that happen over the cloud. Python is also supported by extensive libraries that make it essential in IoT development environments.
Data Solutions: AI, Machine Learning & Deep Learning
Last but certainly not least, Python’s is most well-known for its applications in neural networks, machine learning, deep learning, AI and data science. These processes rely on huge amounts of data and outputs from sophisticated algorithms. Python can handle these large processes with simplicity.
Extensive AI libraries do away with building your own algorithms and proprietary platforms. If you want to build anything in the AI space, developers can simply call on TensorFlow, OpenAI or PyTorch—Python-based deep learning libraries that are behind thousands of commercial apps to provide everything they need without starting from scratch.
The Right Tool for the Right Job
Part of Polcode’s job as a developer service team is to always pick the right tool for the job. Python and PHP are both excellent backend system languages.
Any projects that use machine learning, artificial intelligence, and data science are immediate candidates for Python use over PHP.
In some circumstances, PHP and Python can work “together”, depending on the setup. PHP scripts could handle requests from user interface. Python can be a subprocess module used just for the “data science” in the background.
Both PHP and Python provide their own advantages (and disadvantages)—all of which should be common knowledge for any digital partner serving backend development.