Explaining the retry strategy in the Python Requests library in detail

Network requests may fail for various reasons, such as network fluctuations, temporary unavailability of services, etc. To enhance client-side robustness, it is a common practice to implement automatic retries for requests. In Python, therequestslibrary is one of the standard tools for handling HTTP requests. However, therequestsitself does not provide a retry mechanism directly, which requires the help of theurllib3libraryRetryclass to implement it.

In this article, we will describe how torequestsThe automatic retry of requests is implemented in the

1. The need for retries

In distributed systems, communication between services may fail for various reasons. The automatic retry mechanism can improve the reliability and fault tolerance of the system. A reasonable retry strategy can reduce the failure of requests due to temporary failures.

2. Implementation of the basic principles of retrying

existrequestsThe following steps are usually required to implement retries in

• Import the necessary modules.
• Create aHTTPAdapterExample.
• existHTTPAdapterupstream configurationRetryStrategy.
• Place the configuredHTTPAdapterMount toSessionObject on.
• Send the request using a Session object with retries configured.

3. Use urllib3 to implement retries

Here's a specific example showing how to add a new function to therequestsRequest to add retry logic.

3.1 Introducing modules

First, you need to import therequestslibraries andurllib3(used form a nominal expression)RetryClass.

import requests
from  import HTTPAdapter
from  import Retry

3.2. Configuring the retry policy

utilizationRetryclass to define the retry policy. Here you can specify the number of retries, the set of status codes, the type of exception, etc.

retries = Retry(
    total=5,  # of total retries
    backoff_factor=1,  # Exponential fallback factor
    status_forcelist=[500, 502, 503, 504],  # Specify which status codes trigger retries
    allowed_methods=frozenset(['GET', 'POST']),  # HTTP methods that allow retries
)

3.3. Creating an HTTPAdapter and Configuring Retries

Create aHTTPAdapterinstance and set the retry policy.

adapter = HTTPAdapter(max_retries=retries)

3.4. Mounting an Adapter to a Session

establishSessionobject for HTTP and HTTPS requests and mounts the above createdadapter。

pythonCopy code
session = ()
('http://', adapter)
('https://', adapter)

3.5 Sending requests

Use the retry policy configured with thesessionobject to send the request.

url = "/status/500"
response = (url)

4. Example: requesting a service that may return an error

Below is a complete example, including error handling.

import requests
from  import HTTPAdapter
from  import Retry

def request_with_retry(url, max_retries=5, backoff_factor=1, status_forcelist=None):
    if status_forcelist is None:
        status_forcelist = [500, 502, 503, 504]
        
    session = ()
    retries = Retry(total=max_retries,
                    backoff_factor=backoff_factor,
                    status_forcelist=status_forcelist,
                    method_whitelist=["GET", "POST"])
    adapter = HTTPAdapter(max_retries=retries)
    ('http://', adapter)
    ('https://', adapter)
    
    try:
        response = (url)
        response.raise_for_status()  # If the request returns a 4XX, 5XX response code, an HTTPError exception will be raised
        return response
    except  as e:
        print(f"HTTP Error: {e}")
    except  as e:
        print(f"Connection Error: {e}")
    except  as e:
        print(f"Timeout Error: {e}")
    except  as e:
        print(f"Request Exception: {e}")

url = "/status/500"
response = request_with_retry(url)

if response:
    print()

In this example, if the service responds with a 500 series error, or a connection exception, therequest_with_retryfunction will attempt the request up to five times.

reach a verdict

In Python, use therequestslibrary cooperationurllib3(used form a nominal expression)Retryclass that allows flexible implementation of an automatic retry mechanism for HTTP requests. This can significantly improve an application's ability to handle network fluctuations. This pattern is especially important in scenarios such as microservices and API calls. It should be noted that the number of retries and the strategy should be carefully chosen to prevent excessive retries from overloading the service.

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