Modules

Introduction To Python
  1. Advantages Of Learning Python As The First Programming Language
  2. Easy Python Setup Guide For Beginners
Basic Syntax And Variables
  1. Python Syntax Fundamentals
  2. Python Variables And Data Types
  3. Python Basic Operations
Control Flow
  1. Python Conditional Statements
  2. Python Loops
Functions And Modules
  1. Defining And Calling Python Functions
  2. Introduction To Python Modules And Importing
  3. Understanding Python Built In Functions Part 1
  4. Understanding Python Built In Functions Part 2
  5. Understanding Python Built In Functions Part 3
  6. Understanding Python Built In Functions Part 4
  7. Understanding Python Lambda Functions
Python Lists And Touples
  1. Manipulate Python Lists And Touples
  2. 5 Ways To Remove Items From A Python List By Index
  3. 5 Different Approaches To Check For Duplicate Values In Python Lists
  4. 5 Different Approaches To Check For A Specific Value In Python Lists
  5. 5 Various Approaches To Modify Elements In Python Lists
  6. Understanding Shallow Copy And Deep Copy In Python Lists
  7. 6 Various Approaches To Duplicating Lists In Python
  8. Exploring 8 Various Iteration Techniques In Python Lists
  9. Exploring Python List Concatenation Methods
  10. All You Must Know About Python Slicing
  11. Exploring Various Methods For Comparing Python Lists
  12. Converting Various Data Types To Python Lists
  13. Removing Duplicate Values From Python Lists
  14. Extend A Python List To A Desired Length
  15. Shorten A Python List To A Specific Length
  16. Efficient Ways To Creating Sequences In Python
Python Dictionaries
  1. Manipulate Python Dictionaries
  2. Understanding Python Enumerate Dictionary
  3. Efficient Ways Removing Items From Python Dictionaries
  4. 5 Different Ways To Check For Duplicate Values In Python Dictionaries
  5. Check For A Specific Value In Python Dictionaries
  6. Get Values By Key In Python Nested Dictionary
  7. Modify Values By Key In Python Nested Dictionary
  8. 7 Different Ways To Duplicating A Dictionary In Python
  9. 5 Various Iteration Techniques In Python Dict
  10. 4 Different Methods For Dictionary Concatenation In Python
  11. 4 Different Ways Of Comparing Python Dicts
  12. Converting Various Data Types To Python Dictionaries
  13. Efficient Ways To Remove Duplicate Values From Python Dictionaries
  14. Extend A Python Dictionary To A Desired Length
  15. Shorten Python Dictionaries To A Specific Length
  16. Efficient Approaches To Remove An Item By Value In Python Dictionaries
Python Sets
  1. Manipulate Python Sets
File Handling
  1. Reading From And Writing To Files In Python
  2. Python File Modes And Handling Exceptions
Object Oriented Programming
  1. Python Classes And Objects
  2. Python Inheritance Encapsulation And Polymorphism
Python Advanced Data Structures
  1. Python Collection Module
  2. Advanced Python Data Manipulation Techniques
Error Handling And Debugging
  1. Python Exception Handling
  2. Python Debugging Techniques And Tools
Regular Expressions
  1. Python Regular Expressions In Text Processing
  2. Python Regular Expressions Pattern Matching
Concurrency And Parallelism
  1. Threading Vs Multiprocessing In Python
  2. How To Achieve Concurrency And Parallelism In Python
  3. Concurrent Programming With Asyncio
Working With Apis
  1. Making Http Requests In Python
  2. Parsing Json Xml Responses In Python
Build Apis With Python Requests
  1. Python Requests Crud Operations
  2. Retry In Python Requests
  3. Python Requests Timeout
Build Apis With Python Urllib3
  1. Disabling Hostname Verification In Python Example
Build Apis With Python Aiohttp
  1. Asynchronous Crud Operations In Python
Database Interaction
  1. Connecting To Databases In Python
  2. Python Crud Operations And Orm Libraries
Python For Web Development
  1. Introduction To Python Web Frameworks
  2. Building Web Applications Using Flask
  3. Building Web Applications Using Django
  4. Building Web Applications Using Fastapi
Data Analysis And Visualization
  1. Introduction To Numpy Pandas And Matplotlib
  2. Analyzing Datasets And Visualizations In Python
Machine Learning With Python
  1. Machine Learning Concepts And Python
  2. Introduction To Scikit Learn And Tensorflow Keras
Python Typing Module
  1. Type Error Not Subscriptable While Using Typing
All Course > Python > Build Apis With Python Aiohttp Dec 08, 2023

Retry in Python aiohttp async requests

Retry in Python aiohttp is the action of automatically resubmitting unsuccessful async HTTP requests. Async HTTP requests can be failed because of many reasons. Server failure, network issues, and rate limitations are a few reasons that make request failures.

Python aiohttppackage is a famous third-party library to make asynchronous HTTP requests. But, it doesn’t have in-built functionality to make retries whenever async requests are getting failed. Therefore we are using aiohttp-retry client to make retries on async requests in Python. Because aiohttp-retry library has been built on top of aiohttp library, the client session is the same as aiohttp client session. The only difference is, aiohttp-retry client session takes a few more additional parameters to handle the retry operation.

What is the backoff factor in Python aiohttp-retry?

So let’s take an example to figure out what is backoff factory in aiohttp-retry. Assume you want to retry on failed async HTTP request a maximum of 5 times with a backoff factor of 2s. Then once the request is failed, python aiohttp-retry will trigger retry the after each following second. The first retry will start just after the initial request is get failed.

  • First retry → After 2*0 → 0s, 
  • Second retry → After 2*2 → 4s 
  • Third retry → After 2*4 → 8s
  • Fourth retry → After 2*8 → 16s
  • Fifth retry → After 2*16 → 32S

If the async request is still failed, it will throw an error after 0s+4s+8s+16s+32s → 60s

Retry in Python aiohttp example

To demonstrate GET, POST, PUT, and DELETE operations,  we are using a publicly available API endpoint. This API will return user details as JSON. Also, we are using the Python aiohttp client library to trigger retries automatically. In Each example, we are feeding the number of total retries and the backoff factor.

GET in Python aiohttp

# retry on get
import json
import asyncio
import requests
from aiohttp_retry import RetryClient, ExponentialRetry

REQUEST_RETRY = 3
BACKOFF_FACTOR = 1

async def get():
    url = "https://gorest.co.in/public/v2/users"
    headers = {
        "Content-Type": "application/json",
        "Accept": "application/json",
    }

    try:
        retry_options = ExponentialRetry(attempts=REQUEST_RETRY)

        async with RetryClient(retry_options=retry_options) as session:

            async with session.get(
                    url, headers=headers, ssl=False
            ) as response:
                respstr = str(await response.text())
                if response.status != 200:
                    raise Exception(
                        "Request failed: Response http code {}, response {}".format(
                            response.status, respstr
                        )
                    )
            json_res = json.loads(respstr)
            print(json.dumps(json_res, indent=4))

    except Exception as e:
        raise Exception("Error while request: {}".format(e))

if __name__ == "__main__":
    futures = [get()]
    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(futures))

POST in Python aiohttp

# retry on post
import json
import asyncio
import requests
from aiohttp_retry import RetryClient, ExponentialRetry

REQUEST_RETRY = 3
BACKOFF_FACTOR = 1


async def post():
    url = "https://gorest.co.in/public/v2/users"
    headers = {
        "Content-Type": "application/json",
        "Authorization": "Bearer <ACCESS-TOKEN>",
        "Accept": "application/json"
    }

    payload = {
        "name": "Tenali Ramakrishna",
        "gender": "male",
        "email": "[email protected]",
        "status": "active"
    }

    payload = json.dumps(payload)

    try:
        retry_options = ExponentialRetry(attempts=REQUEST_RETRY)

        async with RetryClient(retry_options=retry_options) as session:

            async with session.post(
                    url, data=payload, ssl=False, headers=headers
            ) as response:
                respstr = str(await response.text())

                if response.status != 200:
                    raise Exception(
                        "Request failed: Response http code {}, response {}".format(
                            response.status, respstr
                        )
                    )

            json_res = json.loads(respstr)

            print(json.dumps(json_res, indent=4))

    except Exception as e:
        raise Exception("Error while request: {}".format(e))

if __name__ == "__main__":
    futures = [post()]
    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(futures))

PUT in Python aiohttp

# retry on put
import json
import asyncio
import requests
from aiohttp_retry import RetryClient, ExponentialRetry

REQUEST_RETRY = 3
BACKOFF_FACTOR = 1


async def put():
    url = "https://gorest.co.in/public/v2/users/547"
    headers = {
        "Content-Type": "application/json",
        "Authorization": "Bearer <ACCESS-TOKEN>",
        "Accept": "application/json"
    }

    payload = {
        "name": "Tenali Ramakrishna",
        "gender": "male",
        "email": "[email protected]",
        "status": "active"
    }

    payload = json.dumps(payload)

    try:
        retry_options = ExponentialRetry(attempts=REQUEST_RETRY)

        async with RetryClient(retry_options=retry_options) as session:

            async with session.put(
                    url, data=payload, ssl=False, headers=headers
            ) as response:
                respstr = str(await response.text())

                if response.status != 200:
                    raise Exception(
                        "Request failed: Response http code {}, response {}".format(
                            response.status, respstr
                        )
                    )

            json_res = json.loads(respstr)

            print(json.dumps(json_res, indent=4))

    except Exception as e:
        raise Exception("Error while request: {}".format(e))

if __name__ == "__main__":
    futures = [put()]
    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(futures))

DELETE in Python aiohttp

# retry on delete
import json
import asyncio
import requests
from aiohttp_retry import RetryClient, ExponentialRetry

REQUEST_RETRY = 3
BACKOFF_FACTOR = 1


async def delete():
    url = "https://gorest.co.in/public/v2/users/547"
    headers = {
        "Content-Type": "application/json",
        "Authorization": "Bearer <ACCESS-TOKEN>",
        "Accept": "application/json"
    }

    try:
        retry_options = ExponentialRetry(attempts=REQUEST_RETRY)

        async with RetryClient(retry_options=retry_options) as session:

            async with session.delete(
                    url, ssl=False, headers=headers
            ) as response:
                respstr = str(await response.text())

                if response.status != 200:
                    raise Exception(
                        "Request failed: Response http code {}, response {}".format(
                            response.status, respstr
                        )
                    )

            json_res = json.loads(respstr)

            print(json.dumps(json_res, indent=4))

    except Exception as e:
        raise Exception("Error while request: {}".format(e))

if __name__ == "__main__":
    futures = [delete()]
    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.wait(futures))

Conclusion

Python aiohttp library doesn’t have a way to trigger retries on failure async HTTP requests. Therefore we can use aiohttp client library.

Comments

There are no comments yet.

Write a comment

You can use the Markdown syntax to format your comment.

Tags: python aiohttp retry