Firstly, What is FastAPI ?

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based.

Some of the features FastAPI offers are :

Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic).
Fast to code: Increase the speed to develop features by about 200% to 300%. *
Fewer bugs
Robust.

Let’s Look at some of Tech Companies using FastAPI:

Microsoft
Uber
Netflix

Installation of FastAPI :

pip install fastapi

pip install “uvicorn[standard]”

NOTE : Python Version 3.6+ .

Running A FastAPI File:

uvicorn main:app — reload

NOTE : Name the API file main.py always or else the file wont run.

Simple Example of FastAPI [OCR_FASTAPI]

Python code for OCR

import cv2

import pytesseract

img = cv2.imread(‘7.png’)

cv2.imshow(‘sample image’ , img)

cv2.waitKey(0)

cv2.destroyAllWindows()

text = pytesseract.image_to_string(img)

print(text)

Now Let’s look at the FastAPI Code for this python code :

from typing import Optional
from fastapi import FastAPI
import pytesseract
import numpy as np
import cv2
import urllib.request
from pydantic import BaseModel

app = FastAPI()

class DataModel(BaseModel):
url:str

def url_to_image(url):

download the image, convert it to a NumPy array, and then read

it into OpenCV format

resp = urllib.request.urlopen(url)
image = np.asarray(bytearray(resp.read()), dtype=”uint8")
image = cv2.imdecode(image, cv2.IMREAD_COLOR)

return the image

return image

[@app](twitter.com/app "Twitter profile for @app").get(‘/’)
def serverstatus():
return {“status”: “Running”}

[@app](twitter.com/app "Twitter profile for @app").post(“/text/”)
def read_root(dm:DataModel):
baseurl = dm.url
image = url_to_image(baseurl)
text = pytesseract.image_to_string(image)
return { “result”: text}

One of the best and important features of FastAPI is you can test your API with FastAPI’S Software:

Usually Once you run the API : You will be run on your localhost. http://127.0.0.1:8000