Implementing microservices with Python

Python is an amazingly versatile language.

As you probably already know, it's used to build many different kinds of applications--from simple system scripts that perform tasks on a server to large object-oriented applications that run services for millions of users.

According to a study conducted by Philip Guo in 2014, published on the Association for Computing Machinery (ACM) website, Python has surpassed Java in top U.S. universities, and is the most popular language to learn computer science.

This trend is also true in the software industry. Python sits now in the top five languages in the TIOBE index (http://www.tiobe.com/tiobe-index/), and it's probably even bigger in the web development land, since languages like C are rarely used as main languages to build web applications.

However, some developers criticize Python for being slow and unfit for building efficient web services. Python is slow, and this is undeniable. But it still is a language of choice for building microservices, and many major companies are happily using it.

This section will give you some background on the different ways you can write microservices using Python, some insights on asynchronous versus synchronous programming, and conclude with some details on Python performances.

This section is composed of five parts:

• The WSGI standard
• Greenlet and Gevent
• Twisted and Tornado
• asyncio
• Language performances