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Python Microservices, Part 1: Choices, Key Concepts, and Project setup

Satish Chandra Gupta
Machine Learning Practitioner. I learn & write about doing ML in production. Cofounder: SlangLabs.in. Ex: Amazon, Microsoft Research. Newsletter: ML4Devs.com
Originally published at slanglabs.in ・1 min read

Evaluate languages and frameworks, learn asyncio and layered design, and setup lint, test, code coverage tooling from the very beginning.


At SlangLabs, we are building a platform for programmers to easily and quickly add multilingual, multimodal Voice Augmented eXperiences (VAX) to their mobile and web apps. Think of an assistant like Alexa or Siri, but running inside your app and tailored for your app.

The platform consists of:

  • Console to configure a buddy for an app, SDKs for Android and Web (JavaScript) providing voice-to-action capabilities,
  • Microservices that SDKs invoke to infer the intent inherent in the voice utterance of an end-user, and extract associated entities, and
  • Analytics to analyze end-user behavior and improve the experience.

This blog post is to share the best practices and lessons we have learned while building the microservices.

(Based on a PyCon India 2019 tutorial)

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