- Explains how Chainstack’s global node feature can boost your DApp’s reliability by balancing traffic automatically based on user location.
- Demonstrates a JavaScript load balancer script using multiple Chainstack endpoints, distributing requests across different regions to avoid single-point failures.
- Shows examples with both web3.js and ethers.js, detailing how to fail over to the next endpoint if one fails.
- Concludes that both global nodes and custom load-balancing approaches help ensure your blockchain app can handle high traffic and unexpected downtimes.
Main article
In the world of API requests, error handling is not just a best practice—it’s a necessity. Effectively handling HTTP status codes is crucial for ensuring smooth and reliable communication between clients and servers. Whether you’re a seasoned developer or just starting out, understanding how to automate the retrieval of response codes from any request can help you build more robust applications, implement effective retry logic, and create comprehensive error backlogs. This guide will walk you through the best practices for error handling in API requests, with a focus on handling HTTP status codes and implementing retry logic.Importance of handling HTTP status codes
HTTP status codes are the server’s way of telling the client about the status of the operation it requested. They play a vital role in API requests as they can indicate success, failure, or need for further action. By properly handling these status codes, you can ensure your application responds appropriately to each possible outcome of an API request. This can significantly enhance the user experience and the overall performance of your application.Overview of HTTP status codes
HTTP status codes are grouped into five major categories, each representing a specific class of responses. These include:- 1xx (informational) — the request has been received and understood, and the client should continue the process.
- 2xx (success) — the action was successfully received, understood, and accepted.
- 3xx (redirection) — the client must take additional action to complete the request.
- 4xx (client errors) — the request contains bad syntax or cannot be fulfilled.
- 5xx (server errors) — the server failed to fulfill an apparently valid request.
Practical example
Before we can handle HTTP status codes, we first need to know how to retrieve them. In Python, this can be done using thestatus_code
attribute of the response object. This attribute holds the status code that the server returned for the HTTP request.
Let’s consider a scenario where we’re interested in getting the logs of the latest block. We can do this using the following Python code:
response_code
variable. Now that we know how to retrieve the status code of a response, we can move on to handling these codes and analyzing error responses.
Analyzing error responses
In addition to dealing with response codes, it’s also important to analyze other information in the response to understand and deal with errors. This can be particularly useful when the server returns a 4xx or 5xx status code, indicating a client or server error. For instance, let’s consider a possible response for aeth_getLogs
request that contains an error content in the output:
error
field, which contains further information about the error that occurred. We can extract this information in our Python code like this:
error
field. If it does, we store the content of this field in the error_content
variable. This information can be used to implement a retry logic and keep a record of whenever those errors happen in time.
Importance of implementing retry logic
Incorporating retry logic into your code can significantly enhance the reliability of your application. By leveraging the tools and techniques we have discussed, you can implement a retry mechanism that automatically handles temporary failures and retries the request when necessary. This can reduce the impact of temporary failures on you, increase system availability, and ensure data integrity. In the worst-case scenario, this enables you to keep track of the errors you face with precise timestamps for such incidents. Implementing retry logic is particularly important when dealing with 5xx server errors. These errors indicate a problem with the server and are often temporary. By implementing a retry logic, your application can automatically retry the request after a short delay, giving the server a chance to recover. This can significantly improve the user experience by reducing the number of failed requests the user has to deal with.Implementing retry logic in code
Now that we understand the importance of implementing retry logic let’s dive into how to implement it in our Python code. Our retry logic aims to automatically retry the request when a temporary failure occurs. This can be a 5xx server error, a connection error, or any other type of error that we deem temporary. Here’s an example of how to implement retry logic in Python using both the response code and error messages to determine when to retry a request:retries
variable). For each iteration of the loop, which represents an attempt to fetch the logs, the code performs the following steps:
- A
POST
request is sent to the Ethereum node with the defined headers and payload. - If the HTTP status code of the response is not 200 (indicating a successful request), the code prints a message indicating that the request failed and the current attempt number. Then, it waits for the specified delay period (the
delay
variable) before proceeding to the next iteration of the loop. This delay provides a pause before retrying, which can be helpful in cases where the server might be temporarily overloaded or experiencing other transient issues. - If the status code is 200 (indicating a successful request), the response is parsed into JSON format and checked for an
error
key. Iferror
is present, the code prints a message with the error details and the current attempt number, waits for the specified delay period, and proceeds to the next iteration of the loop. This handles cases where the request was technically successful, but the response indicates an error condition that might be resolved with a retry. - If there’s no
error
key in the response but theresult
is empty, the code prints a message indicating this fact and the current attempt number, waits for the specified delay period, and proceeds to the next iteration of the loop. This handles situations where the request was successful and didn’t result in an error but didn’t provide any logs to process.