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Ethereum: Parsing JSON using jq and vm.ffi/FFI
When working with data returned from a conversion call, parsing JSON can be a crucial step in retrieving relevant information. However, using the Ethereum command-line tool jq or the vm.ffi Foreign Function Interface (FFI) module, you may encounter problems parsing JSON without any obvious errors.
In this article, we will explore why these methods fail and provide an alternative approach to achieve the desired result.
Why does it fail?
The main problem is how jq and vm.ffi/FFI interpret JSON data. By default, both tools expect a well-formed JSON string or object as input. If your conversion call returns invalid JSON, these tools will throw an error.
To overcome this limitation, we can use the “jsonschema” library to validate the received JSON data before attempting to parse it with “jq”. This approach ensures that our data conforms to the expected formats before extracting specific fields.
Solution: Using jsonschema and vm.parseJson
We will use the jsonschema library, which provides a powerful way to validate JSON data against a predefined schema. Additionally, we will use vm.parseJson, which allows us to parse JSON strings directly into C++ objects.
Here is an example implementation:
#include
#include
#include // Assuming jsonschema is installed and linked
// Define our JSON object
struct Data {
std::string id;
std::vector status;
};
int main() {
// Sample data from the conversion call
Json::Value jsonData = Json::arrayValue;
jsonData["id"].asString("example-id");
for (size_t i = 0; i < jsonData.arraySize(); ++i) {
Json::Value field(jsonData[i]);
if (field.isObject()) {
Json::Value status(field);
if (status.isArray()) {
status[0].asString("example-status");
}
}
}
// Validate JSON data against schema
JsonSchema schema;
schema.loadFromJsonValue(jsonData);
std::string expectedStatus = "example-status";
if (!schema.validate(expectedStatus)) {
std::cerr << "Invalid JSON: 'status' is expected for a single-element array." << std::endl;
return 1; // Returns a non-zero exit code to indicate an error
}
// Now we can safely parse JSON data using vm.parseJson
try {
Data parsedData;
vm.parseJson(jsonData.toStyledString(), parsedData);
std::cout << "Parsed data: id = " << parsedData.id << ", status = [" << parsedData.status[0] << "]" << std::endl;
} catch (const std::exception& e) {
std::cerr << "Error parsing JSON: " << e.what() << std::endl;
return 1; // Returns a non-zero exit code to indicate an error
}
return 0;
}
In this example, we define our data structure with fields id and status. We then create a sample JSON object from the conversion call, validate it against the schema using jsonschema'', and safely parse the JSON data usingvm.parseJson''.
Note that in a real-world situation, you need to ensure that your JSON data conforms to the expected format by checking for validation errors or using additional checks such as JSON syntax rules.
Conclusion
While jq and vm.ffi/FFI can handle certain JSON input, they may not be suitable for all cases. Usingjsonschema'' and`vm.parseJson”, you can create a robust solution for parsing JSON data from broadcast calls to Ethereum.
Remember to always validate your JSON data before attempting to parse it, ensuring that the expected structure is preserved throughout the parsing process.
Feel free to ask if you have any questions or need further clarification!