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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 crucial step to extract relevant information. However, when using the jq command-line tool or the vm.ffi FFI (Foreign Function Interface) module on Ethereum, you may encounter issues when parsing JSON without 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 lies in how jq and vm.ffi/FFI interpret JSON data. By default, both tools expect a string or a well-formed 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.
The Solution: Using jsonschema and vm.parseJson
We will be using the jsonschema library, which provides a robust way to validate JSON data against a predefined schema. Additionally, we will be leveraging 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
// Defining our JSON object
struct Data {
std::string id;
std::vector status;
};
int main() {
// Sample 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 field(jsonData[i]);
if (field.isObject()) {
Json::Value status(field);
if (status.isArray()) {
status[0].asString("example-status");
}
}
}
// Validate JSON data with a schema
JsonSchema schema;
schema.loadFromJsonValue(jsonData);
std::string expectedStatus = "example-status";
if (!schema.validate(expectedStatus)) {
std::cerr << "Invalid JSON: 'status' was expected to be an array with one element." << std::endl;
return 1; // Return a non-zero exit code to indicate an error
}
// Now, we can safely parse the JSON data using vm.parseJson
try {
Data parsedData;
vm.parseJson(jsonData.toStyledString(), parsedData);
std::cout << "Data parsed: 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; // Return 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 conversion 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 should 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 build a robust solution for parsing JSON data from conversion calls on Ethereum.
Always remember to validate your JSON data before attempting to parse it, ensuring that the expected structure is maintained throughout the parsing process.
Feel free to ask if you have any questions or need further clarification!
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