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Ethereum: analyze json using jq is vm.ffi/ffi
When working with the data returned by a cast call, Json analysis can be a crucial step in the extraction of relevant information. However, when using thejqjq or the FFI module (interface of the foreign function), the FFI module are used.
In this article, we will explore why these methods fail and will provide an alternative approach to achieve the desired result.
Why does it fail?
The main problem lies in the way `jq is VM ‘. Baffi/FFI interpret the Json data. By default, both tools expect a JSON string or object well formed as input. If the cast call returns Json not valid, these tools will increase a mistake.
To overcome this limitation, we can use the Jsonschema 'library to validate the Json data coming before trying to analyze them with jq. This approach guarantees that our data comply with the formats planned before trying to extract specific fields.
The solution: using Jsonchema is VM.Parsjson
We will use theJsonschema ‘library, which provides a robust way to validate Json data compared to a predefined scheme. In addition, we will use VM.Parsejson, which allows us to analyze the Json strings directly in the C ++ objects.
Here is an example:
`Cpp
#include
#include
#include
// define our Json object
Stuct data {
STD :: string id;
STD :: Vector Status;
};
Int Main () {
// example of data from a call to cast
Json :: Value Jsondata = Json :: Arrayvalue;
jSondata [“Id”]. Attring (“Example-ID”);
for (size_t i = 0; i
Json :: Value Field (Jsondata [i]);
If (Field.isobject ()) {
Json :: state value (field);
If (status.isarray ()) {
State [0] .Assrring (“Example-Status”);
}
}
}
// validates Json data against a scheme
Jsconschema scheme;
Scheme.loadfromjsonvalue (jSondata);
STD :: String foreseen = “Example-Status”;
If (! Scheme.Validate (expected)) {
STD :: Cerr << "Json not valid: the expected state" is an array with an element. "<< Std :: Endl;
Return 1; // returns a different exit code from scratch to indicate the error
}
// Now, we can safely analyze Json data using VM.Parsjson
Attempt {
Parseddata data;
VM.Parsjson (jSondata.tostyledstring (), parseddata);
STD :: Cout << "data analyzed: id =" << Parseddata.id << ", status = [" << Parseddata.status [0] << "]" << std :: endl;
} Catch (Const Std :: Exception & e) {
STD :: Cerr << "Error analyzes Json:" << E.What () << STD :: Endl;
Return 1; // returns a different exit code from scratch to indicate the error
}
Return 0;
}
`
In this example, we define our structure is given with fields Id and Status. So let's create a Json object from an example from a cast call, we validate it against a scheme usingJsonschema ‘and analyze the Json data safely using VM.Parsejson’.
Note that in a scenario of the real world, it is necessary to make sure that the Json data comply with the format expected by checking validation errors or using further checks such as the rules of Json syntax.
Conclusion
While jq is VM ‘. Baffi/FFIcan manage some Json inputs, may not be suitable for all cases. By exploitingJsonchema` is VM.Parsejson, you can create a robust solution to analyze Json data from the cast calls on Ethereum.
Remember to always validate Json data before trying to analyze them, ensuring that the planned structure is maintained during the analysis process.
Feel free to ask if you have questions or you need further clarifications!