Getting Started with Fast API and Docker
FastAPI
FastAPI is a modern, web frame work for building API’s with Python 3.6 and above based on Python hints to validate, serialize and automatically work with data and generate OpenAPI documents.
Why fastAPI
FastAPI has is one of the latest python api's for web development. It has some of this features:

1. It is indeed fast It is fast when we compare it to other major Python frameworks like Flask and Django.
2. Support for asynchronous code This is one of exciting feature of FastAPI that it supports asynchronous code out of the box using the async/await Python keywords.
3. Very short development time It takes like 8 lines of code to comeup with a hello, word program
4. Easy testing It has a feature of test driven development with the help using the TestClient provided by fastAPI.
5. Excellent documentation It has one of the easiest documentation that one can understand.
6. Easy deployment You can easily deploy your FastAPI app via Docker using FastAPI provided docker image Requirements Python 3.6+ Installation of fastapi on windows. pip install fastapi Installation on Mac and Linux pip3 install fastapi uvicorn Example First create a folder at your own location of choice mkdir foldername && cd foldername create a virtual environment inside the folder you created python3 -m venv env activate the virtual environment created called env source env/bin/activate Create a python file with the following code and save as myapp.py from fastapi import FastAPI, Depends

app = FastAPI()

@app.get('/')
async def root():
return {'message': 'Hello World!'}
Then to run the server, we use the following command:
uvicorn myapp:app --reload
To know it it works with no error, you will see this in your commandline
INFO: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO: Started reloader process [84109] using statreload
INFO: Started server process [84111]
INFO: Waiting for application startup.
INFO: Application startup complete.
Now to open in browser, use the following link
http://127.0.0.1:8000/docs
you will see the following output

before going to docker, we can create a requirement.txt file that has all the tools that you have installed in one place by running;
pip3 freeze > requirement.txt
DOCKER
Docker is an open source platform for building ,deploying and managing containerized applications.
Docker container is a virtualized runtime environment that provides isolation capabilities for separating the execution of applications from the underpinning system
Why docker

1. speed - docker has both execution speed,startuo speed and operational speed.
2. consistency - Build an image once and use it any where. The same image that is used to run the tests is used in production. This avoids the works in my machine problems.
3. Flexibility - Containers are portable. Well to an extent (as long as the host is running some form of linux or linux vm). Building a docker image Create a docker file and save with this commands FROM python:3.9

WORKDIR /code

COPY ./requirements.txt ./requirements.txt

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

COPY ./app

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]

Then build your image
docker build -t myimage ./