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Ethereum: Parsing JSON with jq and vm.ffi/FFI
When working with data returned by a conversion call, parsing JSON can be a key step in extracting relevant information. However, when using the jq command-line tool or the vm.ffi Foreign Function Interface (FFI) module in Ethereum, you may encounter problems parsing JSON without any obvious errors.
In this article, we will examine why these methods fail and suggest 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 string or JSON 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 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.
Solution: Use jsonschema and vm.parseJson
We will use the jsonschema library, which provides a robust way to validate JSON data against a predefined schema. In addition, we will take advantage of 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;
state std::vector;
};
int main() {
// Example data from a conversion call
Json::Value jsonData = Json::arrayValue;
jsonData["id"].asString("example-id");
for (size_t i = 0; i < jsonData.arraySize(); ++i) {
Json::Value Array(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 expectStatus = "example-status";
if (!schema.validate(expectedStatus)) {
std::cerr << "Invalid JSON: Expected 'status' must be 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 {
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 using the “id” and “status” fields. We then create a sample JSON object from the conversion call, validate it against the schema using jsonschema, and safely parse the JSON data using vm.parseJson.
Note that in the real world, 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/FFIcan handle some JSON input, they may not be suitable for all cases. By leveragingjsonschemaandvm.parseJson`, you can create a robust solution for parsing JSON data from calls carried over Ethereum.
Remember to always validate your JSON data before attempting to parse it to ensure that the expected structure is preserved during the parsing process.
Feel free to ask us if you have any questions or need further clarification!