What Does Facebook Hydra Mean For The Future of Python

Ever since its inception in the year 1089 by Guido Van Rossum, the programming language Python has along far away. Sheldon did its creator knew that Python would in today's world be utilized for a variety of purposes such as research, development, scripting, among many others. Built as a successor in the ABC language, Python does not just find its applications in software development but also in research.

Through the means of models based on Machine learning, Python is helping the world transform into a better place. Apart from these, the programming language is being used for web applications, graphic user interface applications, software development apps, numeric apps, etc. It is also being used for developing some business and 3D gaming applications.

There are many reasons that Python is a developer's favorite language. Be it the flexibility, abundance of robust libraries, strong mathematical foundation, ease of coding, platform independence, readability, etc. Today, Python stands as the world's most widely used language with over 8 million developers around the globe.

Even though its usability as an enterprise-level development tool is questionable, it's giving JAVA a fierce competition. Try to understand it from the fact that JAVA was once the world's popular development language.

One of the best virtues of Python comes from its openness. It is a general-purpose, open-source programming language that can be used for the broadest number of applications. Having said this, you can find all popular organizations creating their versions of the word. Be it Microsoft's Cognitive Toolkit popularly known as CNTK, Google's Tensorflow or Facebook's PyTorch.

Each is designed to serve a specific purpose and aid developers around the world achieve greater success with Python development. With new libraries and frameworks in the picture, it is becoming quite convenient for developers to build sophisticated applications and harness the best of Python.

One such framework that has been launched recently launched by the online networking giant Facebook is Hydra. Hydra is fundamentally designed to aid complex computations and application building in Python. With this, Facebook will provide the other open-source framework in Python after PyTorch.

Other popular open-source frameworks developed by organizations have specific purposes of serving too. Microsoft's CNTK is a deep learning framework that describes neural networks in Machine Learning as a structured series of computational steps that are directed by a graph.

TensorFlow is primarily a mathematics library used for neural networks along with a plethora of other tasks. While PyTorch aims at assisting applications in computer vision and natural language processing, among others.

Facebook's latest Hydra, on the other hand, is a framework for elegantly configuring complex applications. Even though Python might seem like a quintessential programming language, it becomes sluggish with increasing complexity. Some of the high-level programming concepts such as multi-threading work poorly with Python.

In a step to resolve such underlying issues with the programming language, the framework Hydra is brought into the picture. To get a more in-depth insight into what Hydra holds for the future of Python, let's take a look at some of its features-

Focus on the Problem

One of the best qualities of Hydra is that it enables users to focus on the problem. Python users are already familiar with wasting time on boilerplate code such as logging, command-line flags, loading configuration files etc. Hydra eliminates all of this and helps you concentrate on the critical issues. This approach aids developers in saving a lot of time and increasing their efficiency when it comes to writing the code. In other words, Hydra may be the key to work efficiency for developers.

Powerful Configuration

Hydra lets the user compose a configuration dynamically. It means that developers can get a correctly built configuration for all runs individually. Hydra also aims at making test runs faster. When creating an application, developers devote a significant chunk of their time in experimentally testing it.

However, Hydra facilitates overriding everything from the command line, making it easier to test and modify applications. Apart from this, one of the main tasks of Hydra is to remove the need to maintain multiple configuration files. Its robustness reflects in the way that it enables faster decision making and quick implementation.

With its rock-solid architecture in place, Hydra enables its integration with the user's infrastructure. Even though it is in its nascent stages right now, Facebook aims at taking the pluggable architecture a notch higher with time.

In more versions to come, some Hydra plugins will enable launching a user's code directly on the Amazon Web Services or other similar cloud technology platforms straight from the command line interface. Again.

Not only will this feature save a lot of execution and testing time for applications, but it also enables a more unified approach to programming.

Being an open-source framework, Hydra promises to eliminate the need to write significant portions of the code again and again. This means it is much easier for Python developers to add particular functionality to projects for new use cases. Not only does it aim at reducing errors but also prototype complex research projects. It is already being used at Facebook to accomplish this task with ease.

With Hydra, configurations are composed and overridden just before the application runs. This resolves one of the underlying issues in Python - maintaining multiple configurations or modifying them.

All these features of Hydra matter because it picks some of the most fundamental issues of Python that have been troubling developers for a long time. It targets those pain points by making development much faster, integrated and smoother.

While a piece of code needs to accept and progress with new requirements in the applications, Python was the opposite. It turned slow-paced on complex applications, giving users a reason to switch to other languages such as Google's Go.

But with Hydra in the picture, there reduced chances of bugs and a platform for the code to evolve more naturally with changing requirements.

For the future of Python, it means a more problem-focused and more straightforward implementation approach.

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