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Python Microservices Development

You're reading from   Python Microservices Development Build, test, deploy, and scale microservices in Python

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785881114
Length 340 pages
Edition 1st Edition
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Author (1):
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Tarek Ziadé Tarek Ziadé
Author Profile Icon Tarek Ziadé
Tarek Ziadé
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Table of Contents (13) Chapters Close

Preface 1. Understanding Microservices 2. Discovering Flask FREE CHAPTER 3. Coding, Testing, and Documenting - the Virtuous Cycle 4. Designing Runnerly 5. Interacting with Other Services 6. Monitoring Your Services 7. Securing Your Services 8. Bringing It All Together 9. Packaging and Running Runnerly 10. Containerized Services 11. Deploying on AWS 12. What Next?

Asynchronous versus synchronous


Switching to an asynchronous model means you will need to use asynchronous code all the way down.

For example, if your microservice uses a Requests library that is not asynchronous, every call made to query an HTTP endpoint will block the event loop, and you will not benefit from asynchronicity.

And making an existing project asynchronous is not an easy task because it changes the design completely. Most projects that want to support asynchronous calls are redesigning everything from scratch.

Note

The good news is that there are more and more asynchronous libraries available, which can be used to build a microservice. On PyPI, you can search for aio or asyncio. This wiki page (https://github.com/python/asyncio/wiki/ThirdParty) is also a good place to look at.

Here's a short list of those that are relevant to building microservices:

  • aiohttp.Client: ;Can replace the requests package
  • aiopg: ;PostgreSQL driver on top of Psycopg
  • aiobotocore: ;AWS client--might be merged...
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