A JSON Parser For Solidity

in json •  7 years ago  (edited)

A JSON Parser For Solidity

Because smart contract development is still in its infant stages, there aren't many libraries around. In particular – when dealing with oracle responses – the lack of a proper JSON parser is painful. Thus, I created one that is hopefully useful and makes dealing with JSON in Solidity a bit easier.

Developing smart contracts in Ethereum has become easier with the advent of frameworks such as Truffle and services such as oraclize.it. In particular, using oracles to access information that is external to the blockchain has become simple enough for contract development. However, most of the data that is fed into the blockchain via transactions from oracles comes in as JSON formatted data. This requires a smart contract to parse a JSON object to process the data supplied by an oracle.

String processing is particularly expensive on the Ethereum blockchain. Thus, the JSON parser should be ‟lightweight” and not use much computation for parsing and processing a JSON string.

As there was not JSON parser for Solidity that I'm aware of, I set out to create my own. As a basis I ported the code from jsmn to Solidity. The main design consideration of jsmn is parsing a JSON string in a single pass and avoid copying substrings along the way. Thus, the parser only generates meta data on the provided string that can be used for locating and accessing objects later on.

Single Pass, Fixed Memory, No Copying

The parser works by parsing the supplied string character by character once. Along the way it creates tokens, which each identify an object in the string and indicate its starting and ending position in the string. A token has this structure:

struct Token {
    JsmnType jsmnType;
    uint start;
    bool startSet;
    uint end;
    bool endSet;
    uint8 size;
}

The JsmnType encodes the type of the token. Valid values are:

enum JsmnType { UNDEFINED, OBJECT, ARRAY, STRING, PRIMITIVE }

Note that number, boolean and null are all treated as JsmnType.PRIMITIVE. They can be distinguished by evaluating the first character of the token.

Next are the two values start and end. They encode the starting and the ending position of the substring identifying the object. The size indicates the number of sub-objects for that object (that is the number of children in the JSON hierarchy). For technical reasons there are two more variables (startSet and endSet) that are false on initialization and flip to true once the values for start or end have been set by the parse. They are needed because Solidity has the habit of initializing every variable to its default value. A newly created Token would return 0 for both token.start and token.end. The parser uses startSet to distinguish a newly initialized token from a token whose object actually starts at position 0 in the string.

Installation

The library is available on Github or on the Ethereum Package Manager ethpm as package jsmnsol-lib. If you are using truffle you can easily include the library by running truffle install jsmnsol-lib.

Usage

Note: The following description is valid for version 0.1.x of the parser, which is the beta release. If the version is >0.1.x at the time of reading, please refer to the Github repo for a more recent documentation.

The library basically requires only one call: function parse(string json, uint numberElements) internal returns (uint, Token[], uint). This call takes two input parameters:

  • string json: The string containing the JSON
  • uint numberOfT3okens: The maximum number of tokens to allocate for parsing. This parameter ensures reasonable gas consumption. Whenever the string has more objects than numberOfTokens allows, the parser returns with an error.

After parsing, it returns the three values (uint returnCode, Token[] tokens, uint actualNumber). These are:

  • uint returnCode: The returnCode indicates whether or not the call was successful. A value of 0 shows a successful parsing, any non-zero value marks an error. The valid values are:
uint constant RETURN_SUCCESS = 0;
uint constant RETURN_ERROR_INVALID_JSON = 1;
uint constant RETURN_ERROR_PART = 2;
uint constant RETURN_ERROR_NO_MEM = 3;
  • Token[] tokens: The array with the actual result of the parsing, the tokens. It has tokens.length == numberElements (i.e. the value of the input parameter), but not all tokens have useful values.
  • uint actualNumber: The number of parsed tokens in tokens. Only tokens from 0(actualNumber-1) contain useful tokens. The remaining values in the array (actualNumbertokens.length) only contain the default values and can be disregarded for further processing.

A Simple Example

The JSON that we want to parse is this:

{
    "key1": {
        "key1.1": "value",
        "key1.2": 3,
        "key1.3": true
    }
}

The actual JSON that we pass to the parser is a minified version of the JSON above so that we have the following string: { "key1": { "key1.1": "value", "key1.2": 3, "key1.3": true } }.

After a call to parse(json, 10), the parser would return three values:

  • uint: The return value. It is zero for success and non-zero for errors
  • Token[]: An array of tokens. The array has 10 elements.
  • uint: The number of tokens returned. This number is generally less than the length of the token array. It should be used to access the tokens. Indices greater than the number of elements return a default token.

The token array would look like this:

#JsmnTypestartendstartSetendSetsize
0OBJECT062truetrue1
1STRING37truetrue1
2OBJECT1060truetrue3
3STRING1319truetrue1
4STRING2328truetrue0
5STRING3238truetrue1
6PRIMITIVE4142truetrue0
7STRING4551truetrue1
8PRIMITIVE5458truetrue0
9UNDEFINED00falsefalse0

Use Case: Response Data From an Oracle

One of the possible use cases for the parser is processing an oracle response. For instance, if you are using oraclize.it as oracle, the data that is returned in the callback is most likely a JSON string that is the result of a call to a REST API. Usually these responses include all kinds of data that is probably not relevant for the smart contract. It might, however, be the case that the contract is not only interested in one specific datum from the JSON, but more than one. An example would be a bet for a football match: A call to an API (this one specifically is the response of GET https://api.football-data.org/v1/fixtures/152250?head2head=0) returns the result of the match as JSON:

{
    "fixture": {
        "_links": {
            "self": {
                "href": "http://api.football-data.org/v1/fixtures/152250"
            },
            "competition": {
                "href": "http://api.football-data.org/v1/competitions/430"
            },
            "homeTeam": {
                "href": "http://api.football-data.org/v1/teams/16"
            },
            "awayTeam": {
                "href": "http://api.football-data.org/v1/teams/11"
            }
        },
        "date": "2016-08-27T13:30:00Z",
        "status": "FINISHED",
        "matchday": 1,
        "homeTeamName": "FC Augsburg",
        "awayTeamName": "VfL Wolfsburg",
        "result": {
            "goalsHomeTeam": 0,
            "goalsAwayTeam": 2
        },
        "odds": {
            "homeWin": 3.0,
            "draw": 3.3,
            "awayWin": 2.37
        }
    }
}

For winner determination the only interesting part of that response is the result part of the response. From that result part, we need two elements, namely the number for goalsHomeTeam and the number of goalsAwayTeam. We need to compare the numbers to decide on the winner of the match. There are two steps to facilitate processing of the response:

Reduce The Result to Fewer Elements...

The first step to make that reponse useful is to reduce it to the actually needed parts. oraclize.it provides a means to filter a response from a server with JSONPath). By filtering the response with $.fixture.result oraclize would only return the following part of the JSON to our smart contract (again as a minified string actually):

{
    "goalsHomeTeam": 0,
    "goalsAwayTeam": 2
}

...And Parse Them

This bit is much less expensive to process on-chain. We can use the parser to parse this string. It would return the following tokens:

#JsmnTypestartendstartSetendSetsize
0OBJECT042truetrue2
1STRING316truetrue1
2PRIMITIVE1920truetrue0
3STRING2336truetrue1
4PRIMITIVE3940truetrue0

Now we can use the two tokens token[2] and token[4] to access the two interesting numbers. To extract the substring for token[2] we would call: string goalsHT_string = getBytes(json, token[2].start, token[2].end). This call returns a string. To do useful comparisons on the actual numbers, we still need to convert that string to a uint. A call to uint goalsHT = parseInt(goalsHT_string) accomplishes that.

This procedure of combining a filter on the result via JSONPath and then parsing the result with the parser allows processing of oracle responses with a smart contract.

Final Words

This parser is still in beta; this is its first release. Because of the gas cost it should not be used to parse large JSON files as that will most likely fail. String processing is computation intensive and thus expensive. However, for small JSONs (possibly already reduced by a suitable JSONPath) it can be economical to parse them on-chain and save another call to an oracle to get another part of the JSON.

If you find the library useful, I would appreciate a comment or a donation. Issues and or feature request can be filed on Github.

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