json-parser

name	json-parser
description	Parse and validate JSON data from construction APIs, IoT sensors, and BIM exports. Transform nested JSON to flat DataFrames.
homepage	https://datadrivenconstruction.io
metadata	{"openclaw":{"emoji":"🏷️","os":["win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"]}}}

JSON Parser for Construction Data

Overview

Construction systems increasingly use JSON for data exchange - from IoT sensors to BIM metadata exports. This skill handles parsing, validation, and flattening of JSON structures.

Python Implementation

import json
import pandas as pd
from typing import Dict, Any, List, Optional, Union
from dataclasses import dataclass
from pathlib import Path


@dataclass
class JSONParseResult:
    """Result of JSON parsing operation."""
    success: 
    data: 
    errors: []
    record_count: 


 :
    

     ():
        .errors: [] = []

     () -> JSONParseResult:
        
        :
             (file_path, , encoding=)  f:
                data = json.load(f)
             JSONParseResult(, data, [], ._count_records(data))
         json.JSONDecodeError  e:
             JSONParseResult(, , [], )
         Exception  e:
             JSONParseResult(, , [(e)], )

     () -> JSONParseResult:
        
        :
            data = json.loads(json_string)
             JSONParseResult(, data, [], ._count_records(data))
         json.JSONDecodeError  e:
             JSONParseResult(, , [], )

     () -> :
        
         (data, ):
             (data)
         (data, ):
             
         

     () -> [, ]:
        
        flat = {}
         key, value  data.items():
            new_key =   prefix  key

             (value, ):
                flat.update(.flatten_json(value, new_key))
             (value, ):
                 ((i, (, , , , ()))  i  value):
                    flat[new_key] = value
                :
                     i, item  (value):
                         (item, ):
                            flat.update(.flatten_json(item, ))
                        :
                            flat[] = item
            :
                flat[new_key] = value
         flat

     () -> pd.DataFrame:
        
         (data, ):
            flat_records = [.flatten_json(r)  (r, )  {: r}  r  data]
             pd.DataFrame(flat_records)
         (data, ):
             ((v, )  v  data.values()):
                
                 pd.DataFrame(data)
            :
                flat = .flatten_json(data)
                 pd.DataFrame([flat])
         pd.DataFrame()

     () -> []:
        
        parts = path.split()
        current = data

         part  parts:
             (current, )  part  current:
                current = current[part]
             (current, )  part.isdigit():
                current = current[(part)]
            :
                 []

         current  (current, )  [current]

     () -> [, ]:
        
        flat = .flatten_json(data)
        missing = [f  f  required_fields  f   flat]
        present = [f  f  required_fields  f  flat]

         {
            : (missing) == ,
            : missing,
            : present,
            : (present) / (required_fields) * 
        }



 ():
    

     () -> pd.DataFrame:
        
        elements = []

        
           data:
            elements = data[]
           data:
            elements = data[]
           data:
            elements = data[]
         (data, ):
            elements = data

          elements:
             pd.DataFrame()

        
        flat_elements = []
         elem  elements:
             (elem, ):
                flat = .flatten_json(elem)
                flat_elements.append(flat)

         pd.DataFrame(flat_elements)

     () -> [, ]:
        
        props = {}

        
         key  [, , , ]:
             key  element  (element[key], ):
                props.update(element[key])

         props



 ():
    

     () -> [, ]:
        
         {
            : data.get()  data.get(),
            : data.get()  data.get(),
            : data.get()  data.get(),
            : data.get(, ),
            : data.get(, )
        }

     () -> pd.DataFrame:
        
        readings = [.parse_sensor_reading(r)  r  data]
         pd.DataFrame(readings)