◈

export_analysis_json

Data PipelineDataExport

INSTALLATION

$python -c "exec(open('export_analysis_json.py').read())"

#or paste directly into your Claude Code terminal

[ ABOUT ]

Writes the analysis results list to a JSON file at the specified path, including a `generated_at` ISO timestamp and a total `count` field. The timestamp and count make the export file self-documenting — downstream consumers can verify data freshness without querying Supabase directly.

JSON export is useful for debugging, sharing snapshots of market state, or feeding data to visualization tools that cannot connect to Supabase directly. For automated pipelines, consider naming the file with a timestamp suffix (e.g. `analysis_2026-05-19.json`) rather than overwriting a static filename, so historical snapshots are preserved.

[ USAGE EXAMPLE ]

example.py

path = export_json(results, "analysis_2026-05-19.json")
# → {"generated_at": "2026-05-19T00:12:43", "count": 100, "data": [...]}

[ FULL CODE ]

export_analysis_json.py

import json, datetime def export_json(results, path="analysis.json"): with open(path, "w") as f: json.dump({"generated_at": datetime.now().isoformat(), "count": len(results), "data": results}, f, indent=2) return path

[ METADATA ]

CategoryData Pipeline

ComplexityIntermediate

LanguagePython 3.10+

TagsData, Export

[ ASK CLAUDE ]

Ask AI about this skill before installing it.

[ RELATED SKILLS ]

fetch_ohlcv_coingecko

Fetch OHLCV data for any coin from CoinGecko API

data

fetch_top100_coingecko

Fetch top 100 cryptocurrencies by market cap from CoinGecko

data

cache_to_supabase

Store Claude analysis results to Supabase PostgreSQL database

data