How viable is it to create microservices in Python?
Developers have discovered many reasons to build microservices in Python, from its foundation in object-oriented programming, to its ability to handle REST APIs, to its out-of-the-box support for application prototyping. In particular, its proponents praise Python’s range of built-in features that help isolate key application processes and integrate dynamic collections of distributed services.
As is the case with any programming language, however, Python also introduces its share of challenges to navigate. For some, especially those unfamiliar with interpreted languages or who have pressing needs for fast compile times, Python may not be the ideal language for their microservices development efforts.
Let’s explore the reasons why developers might want to build microservices in Python, look at outstanding features that streamline application building processes, and highlight potential roadblocks developers may encounter. We will also evaluate some of the competing languages that offer a slightly different approach to distributed service development projects.
Why Language Choice Matters in Microservices Development
Although designed to operate as independently as possible, microservices still need to communicate and share data using a variety of messaging components, network protocols, event triggers, calls APIs and other integration techniques. The separation of responsibilities between services, including the logic that drives these operations, is fundamental to fostering independence within microservices architectures.
Rather than going through a centralized messaging system, services need to communicate with each other to perform discrete tasks and scale as needed. This means that developers of languages chosen for their microservices project should ideally support a number of important communication formats and protocols.
Any language used to build microservices must support REST, which primarily relies on HTTP requests that post, read, and delete data. However, protocols such as Remote Procedure Call (RPC), gRPC, and GraphQL are also considered by some to be essential for microservices communication.
Developers building microservices will also rely on containers to create unique, repeatable application environments and enforce scoped contexts between services. As such, the language used should also provide strong support for building, deploying, and orchestrating containers.
Benefits of Python for Microservices Development
Python is an object-oriented language that allows developers to treat elements as objects and organize them into reusable entities within a clear modular structure. This allows them to quickly write application code, plug in boilerplate functions, and test programs before converting them to script. Python is also a strongly typed language, which means it provides uniform consistency and minimizes errors when enforcing data types. Developers can also reuse the same code in a single application or in multiple modules, using built-in functions.
Python’s advanced scripting capabilities also allow developers to automate system provisioning and configurations for microservices. Individual code changes are replicated throughout the codebase. Developers can create and customize web interfaces through server-side scripting, enhanced by Python’s backward compatibility with legacy languages such as PHP and the ASP.NET framework. Python’s standard library is supplemented by thousands of third-party libraries for writing REST services, and plenty of support is available from the Python user community.
Finally, Python provides strong support for containers. This support includes built-in container data types such as lists, tuples, and sets and those available through the standard library. Developers can package dependencies and run microservices in isolated environments to test them with these Python features.
The limitations of Python
Of course, there are a few things to consider before rushing into developing microservices with Python. For example, the speed of execution and the nature of the interpreter environment are often cited as the main potential drawbacks when using Python to build microservices.
For one, Python is an interpreted language, which means it generates non-machine code at runtime. Then an interpreter such as CPython, Jython, PyPy or PyCharm transforms it at runtime into bytecode instructions executed in the virtual environment of the CPU. This can lead to significantly slower execution times than those found in Rust and other languages that compile directly to native code.
Python can also be tricky when it comes to errors and crashes. Since Python is dynamically typed, it is possible for errors skipped during the compilation step to suddenly appear during runtime, causing applications to delay operations or, at worst, experience total failures.
This is an obvious problem for microservices, since microservice instances can be dynamically deployed, deleted, or changed. While there are some type-safety mechanisms that developers can rely on, developers will still need to pay close attention to variable assignments and application testing processes if they choose to build microservices. in Python.
Python isn’t the only choice when it comes to microservices development, and there are a few options to consider if this doesn’t seem like the right fit. Other general-purpose languages, including Go, Java, and .NET languages, offer tangible benefits when building microservices.
Go, also known as Golang, does not have a catalog of predefined functions to rival that of Python, but it offers developers a safe and simple way to manage complex networks of service instances and distributed collections of functional libraries. . Go is a statically typed and compiled language, offering high memory safety and garbage collection as some of its main features. Go also uses lightweight threads called goroutines to promote concurrency – a big advantage when it comes to microservices.
Java provides stability and consistency for distributed applications. In tandem with the Java Spring Boot framework, developers can use the auto-configuration tool to quickly create REST APIs and bind applications. Java developers also have Spring Cloud framework resources for integration and batch and stream processing.
.NET languages such as C#, F#, and Visual Basic are designed to produce software as part of Microsoft’s proprietary development language. Early versions of the .NET Core framework focused on developing microservices and extending API access. Developers can include dependencies and run multiple instances of .NET Core using the platform’s modular architecture. .NET is particularly useful for microservices because it offers connectors for prebuilt external applications as well as APIs that facilitate communications between components.