Hey @Vito,
When working with the Visa Developer Platform, it’s essential to handle different error response formats gracefully, as you might encounter various error messages that do not conform strictly to the OpenAPI specification. Here’s how you can approach this:
General Approach to Error Handling
1. Primary Deserialization Attempt:
- First, attempt to deserialize the error response based on the OpenAPI specification provided for each service.
2. Fallback Deserialization:
- If the primary deserialization fails, implement a fallback mechanism to handle more generic error formats. This usually involves logging the raw error message and extracting key information such as HTTP status codes, error messages, and relevant metadata.
3. Logging:
- Always log the raw error response for debugging and future reference.
Example Strategy in Pseudocode
```python
# START
try:
# Attempt to deserialize based on OpenAPI spec
error_response = deserialize_to_openapi_format(response)
except DeserializationError:
log("Failed to deserialize using OpenAPI format")
# Fallback deserialization
try:
error_response = deserialize_to_generic_format(response)
except DeserializationError:
log("Failed to deserialize using generic format. Logging raw response")
log(response.raw)
# Optionally, create a generic error response object
error_response = create_generic_error_response(response.raw)
# END
```
Identifying Non-MLE Services
To determine if a service is not an MLE (Mutual Link Establishment) service and thus might use a different error format:
1. Service Documentation:
- Review the service documentation on the Visa Developer Portal to understand the expected error response formats.
2. API Specifications:
- Look for any notes in the OpenAPI specifications that might indicate variations in error response formats.
3. Environment-Specific Errors:
- Some errors, like the absence of a sandbox environment, might not be documented in the API specs. These can be identified by specific HTTP status codes or error messages.
Example Logic for Handling Non-MLE Services
```python
# START
def handle_api_error(response):
try:
# Attempt primary deserialization
error_response = deserialize_to_openapi_format(response)
except DeserializationError:
log("Primary deserialization failed")
if is_non_mle_service(response):
try:
# Attempt to deserialize using non-MLE format
error_response = deserialize_to_non_mle_format(response)
except DeserializationError:
log("Non-MLE deserialization failed. Logging raw response")
log(response.raw)
error_response = create_generic_error_response(response.raw)
else:
log("Unknown service type. Logging raw response")
log(response.raw)
error_response = create_generic_error_response(response.raw)
return error_response
def is_non_mle_service(response):
# Placeholder logic to determine if the service is non-MLE
return "specific-indicator" in response.headers or "specific-indicator" in response.body
# END
```
- Primary Deserialization: Try deserializing based on OpenAPI specifications.
- Fallback Mechanism: Implement a fallback for generic error formats.
- Logging: Always log the raw error response.
- Non-MLE Identification: Use service documentation and specific indicators to handle non-MLE services differently.
By following this structured approach, you can handle various error response formats more robustly and ensure your application can adapt to different scenarios without failing on deserialization.
Thanks,
Diana
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