A 400 error typically means there is something wrong with the request you're sending, and it's often related to the format or content of the CSV file. Here's how you can diagnose and resolve this issue:
1. Check for Errors in the CSV File
Header Mismatch: Ensure the headers in your CSV file match the expected format for the system you're importing to.
Invalid Characters: Look for invalid characters (e.g., non-UTF-8 encoded text, special characters).
Empty or Invalid Rows: Ensure there are no completely empty rows or rows with missing required fields.
File Size: Check if the file size exceeds the system's allowed limit.
2. Review System Logs
If the system youโre using has logging enabled, check its logs for details on the failed requests. Look for error messages or stack traces.
If you're using an API, enable request and response logging to capture the full details.
3. Inspect the HTTP Request
If youโre sending the CSV via an API, capture the HTTP request using tools like Postman, cURL, or a browser's developer tools.
Verify the Content-Type header (e.g., text/csv or application/csv).
Double-check the endpoint URL and parameters.
4. Enable Debugging
Enable verbose or debug mode if your software or library supports it. This can reveal additional information about the issue.
5. Test with a Minimal File
Create a small sample CSV file with just a few rows of valid data and try importing that. If it works, gradually add more data to identify problematic entries.
6. Provide Logs
If you want to provide logs, here's what could be useful:
Details of the error message, if any.
A sample of the CSV file (with sensitive data removed or anonymized).
The response body and headers of the failed request (if available).
Any relevant server-side logs, if accessible.
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