Microservices with FastAPI

Prepared for Calgary / Edmonton Python Bootcamp 2020

Prerequisites

Knowledge of Python basics
- variables, naming convention, loops, functions, classes, object-oriented programming, testing, best practices
- Attendance at sessions 1 and 2 of the bootcamp is satisfactory
Understanding of RESTful web APIs
- What are RESTful APIs? How do we start thinking about them in Python?
- Provided by Zero To API

Virtual environment with Python 3.7+ (I will probably use conda)
Jupyter notebook or Google Colab
IDE for writing code (I will probably use sublime)
Terminal for executing code (likely this is possible from the IDE, but I will just use basic mac terminal)
RESTful client (I usually just use Jupyter notebooks and Python requests)

Note: The setup from Zero To API should be satisfactory for this presentation as well, as long as Python is 3.7+.

We will start by covering a few additional prerequisite topics for understanding FastAPI
- Access notebook in Google Colab
- Declarative programming with dataclasses and pydantic
- Decorators
- Async with asyncio
Next, we will then talk about microservices
- Pros, cons, comparison to monolith and realistic architectures
- No coding for this part!
Finally, FastAPI!
- What is it? Why is it great?
- Building an example application together
- We will consume the NHL API
- Notebook to access API here
  - Note: This will not actually work in Google Colab, you can only access localhost locally.