如何设置Odoo API数据获取响应超时？批量取产品超时求助

Hi there, I’ve run into similar timeout headaches with Odoo’s XML-RPC API when dealing with big datasets, so let’s walk through how to fix this:

1. Adjust Client-Side Timeout Settings #

That "operation timed out" error usually happens because your XML-RPC client hits its default time limit before the server finishes sending back 2000 product records. Since you’re using XmlRpcMethod (likely in a .NET environment), you can explicitly set a longer timeout on your RPC client instance.

Here’s how to tweak your code:

// Assuming loRpcRecord is your XmlRpcClient instance
loRpcRecord.Timeout = 300000; // Set to 5 minutes (in milliseconds) - adjust as needed

object[] laProducts = loRpcRecord.read(lsOdooDBName, liUserid, lsOdooDBPassword, OdooHelper.Models.Product, OdooHelper.Methods.Read, laCombineProductIds);

Most XML-RPC clients have a default timeout around 100 seconds—bumping this to a larger value gives the server enough time to process and return the larger dataset.

2. Tune Odoo Server Configuration #

If adjusting the client timeout doesn’t do the trick, you’ll need to increase timeout limits on the Odoo server itself. Open your Odoo config file (odoo.conf) and add/update these parameters:

# Extend HTTP timeout (in seconds) - default is 60
http_timeout = 120

# Optional: Boost server capacity for larger requests
workers = 4
limit_memory_soft = 2048000000
limit_memory_hard = 2560000000

• http_timeout: Controls how long the Odoo server waits for a request to complete before timing out.
• Increasing worker count and memory limits helps the server handle heavy data processing more smoothly.

If you’re using a reverse proxy (like Nginx) in front of Odoo, don’t forget to update its timeout settings too—look for proxy_connect_timeout and proxy_read_timeout in your Nginx config.

3. Fetch Data in Batches (Recommended Best Practice) #

Even with extended timeouts, pulling 2000 records in one go is risky—network blips or server load can still cause failures. A more reliable approach is to split your laCombineProductIds array into smaller chunks and fetch them one at a time.

Example batch processing code:

int batchSize = 500; // Adjust based on your server's performance
List<object> allProducts = new List<object>();

for (int i = 0; i < laCombineProductIds.Length; i += batchSize)
{
    int[] batchIds = laCombineProductIds.Skip(i).Take(batchSize).ToArray();
    object[] batchProducts = loRpcRecord.read(lsOdooDBName, liUserid, lsOdooDBPassword, OdooHelper.Models.Product, OdooHelper.Methods.Read, batchIds);
    allProducts.AddRange(batchProducts);
}

object[] laProducts = allProducts.ToArray();

This reduces the load on both client and server for each request, making the whole process way more resilient to timeouts.

Why This Happens #

Fetching 2000 products means the server has to query more data, serialize it into XML, and send it over the network—all of which takes longer than the default timeout thresholds (either on the client or server side). Adjusting timeouts or splitting into batches fixes this by giving the system more breathing room, or reducing the amount of data processed in one go.

内容的提问来源于stack exchange，提问作者Ghanshyam Lakhani