stock-data-skill
OpenClaw Skill for stock data analysis
Parse and validate JSON data from construction APIs, IoT sensors, and BIM exports. Transform nested JSON to flat DataFrames.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install datadrivenconstruction/json-parserInspect the source and compatibility requirements, then follow its installation steps.
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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.
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: bool
data: Any
errors: List[str]
record_count: int
class ConstructionJSONParser:
"""Parse JSON data from construction sources."""
def __init__(self):
self.errors: List[str] = []
def parse_file(self, file_path: str) -> JSONParseResult:
"""Parse JSON from file."""
try:
with open(file_path, 'r', encoding='utf-8') as f:
data = json.load(f)
return JSONParseResult(True, data, [], self._count_records(data))
except json.JSONDecodeError as e:
return JSONParseResult(False, None, [f"JSON Error: {e}"], 0)
except Exception as e:
return JSONParseResult(False, None, [str(e)], 0)
def parse_string(self, json_string: str) -> JSONParseResult:
"""Parse JSON from string."""
try:
data = json.loads(json_string)
return JSONParseResult(True, data, [], self._count_records(data))
except json.JSONDecodeError as e:
return JSONParseResult(False, None, [f"JSON Error: {e}"], 0)
def _count_records(self, data: Any) -> int:
"""Count records in data."""
if isinstance(data, list):
return len(data)
elif isinstance(data, dict):
return 1
return 0
def flatten_json(self, data: Dict, prefix: str = '') -> Dict[str, Any]:
"""Flatten nested JSON to single-level dict."""
flat = {}...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# 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
```python
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: bool
data: Any
errors: List[str]
record_count: int
class ConstructionJSONParser:
"""Parse JSON data from construction sources."""
def __init__(self):
self.errors: List[str] = []
def parse_file(self, file_path: str) -> JSONParseResult:
"""Parse JSON from file."""
try:
with open(file_path, 'r', encoding='utf-8') as f:
data = json.load(f)
return JSONParseResult(True, data, [], self._count_records(data))
except json.JSONDecodeError as e:
return JSONParseResult(False, None, [f"JSON Error: {e}"], 0)
except Exception as e:
return JSONParseResult(False, None, [str(e)], 0)
def parse_string(self, json_string: str) -> JSONParseResult:
"""Parse JSON from string."""
try:
data = json.loads(json_string)
return JSONParseResult(True, data, [], self._count_records(data))
except json.JSONDecodeError as e:
return JSONParseResult(False, None, [f"JSON Error: {e}"], 0)
def _count_records(self, data: Any) -> int:
"""Count records in data."""
if isinstance(data, list):
return len(data)
elif isinstance(data, dict):
return 1
return 0
def flatten_json(self, data: Dict, prefix: str = '') -> Dict[str, Any]:
"""Flatten nested JSON to single-level dict."""
flat = {}...OpenClaw Skill for stock data analysis
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