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Ethereum: Parsing JSON using jq and vm.ffi/FFI
When working with data returned from a cast call, parsing JSON can be a key step in extracting relevant information. However, if you are using thejqcommand-line tool or the FFI (Foreign Function Interface)vm.ffi module on Ethereum, you may encounter problems parsing JSON without any obvious errors.
In this article, we will examine why these methods do not work and provide an alternative approach to achieve the desired result.
Why does it fail?
The main problem lies in howjqandvm.ffi/FFIinterpret JSON data. By default, both tools expect a well-formed JSON string or object as input. If the cast returns invalid JSON, these tools will throw an error.
To overcome this limitation, we can use thejsonschema’ library to validate incoming JSON data before attempting to parse it with jq'. This approach ensures that our data conforms to the expected formats before attempting to extract specific fields.
The solution: usingjsonschema’ and vm.parseJson'
We will use thejsonschema’ library, which provides a robust way to validate JSON data against a predefined schema. We will also take advantage of the vm.parseJson' function, 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 state;
};
int main() {
// Example data from a cast 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 state(field);
if (status.isArray()) {
status[0].asString("example-status");
}
}
}
// Validate JSON data against a schema
JsonSchema schema;
schema.loadFromJsonValue(jsonData);
std::string expectStatus = "example-status";
if (!schema.validate(expectedStatus)) {
std::cerr << "Invalid JSON: 'status' is expected as a single-element array." << std::endl;
return 1; // Returns a non-zero exit code to indicate an error
}
// We can now 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 "id" and "status" fields. We then create a sample JSON object from a cast call, validate it against a schema using "jsonschema", and safely parse the JSON data using "vm.parseJson".
Note that in a real-world scenario, you will need to verify that the JSON data conforms to the expected format by checking for validation errors or additional checks such as JSON syntax rules.
Conclusion
While "jq" and "vm.ffi/FFI” can handle some JSON input, they may not be suitable for all cases. By leveraging “jsonschema” and “vm.parseJson”, you can create a robust solution for parsing JSON data from calls made over Ethereum.
Remember to always validate JSON data before attempting to parse it, ensuring that the expected structure is preserved during the parsing process.
Feel free to ask if you have any questions or need further clarification!
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