query_sql
Execute SQL queries on downloaded blockchain data files. Pass file paths from query_dataset results to analyze transaction or block data. Supports DuckDB for direct table references or read_parquet().
Instructions
Run a SQL query against downloaded blockchain data files
IMPORTANT WORKFLOW: This function should be used after calling query_dataset
to download data. Use the file paths returned by query_dataset as input to this function.
Workflow steps:
1. Download data: result = query_dataset('transactions', blocks='1000:1010', output_format='parquet')
2. Get file paths: files = result.get('files', [])
3. Execute SQL using either:
- Direct table references: query_sql("SELECT * FROM transactions", files=files)
- Or read_parquet(): query_sql("SELECT * FROM read_parquet('/path/to/file.parquet')", files=files)
To see the schema of a file, use get_sql_table_schema(file_path) before writing your query.
DuckDB supports both approaches:
1. Direct table references (simpler): "SELECT * FROM blocks"
2. read_parquet function (explicit): "SELECT * FROM read_parquet('/path/to/file.parquet')"
Args:
query: SQL query to execute - can use simple table names or read_parquet()
files: List of parquet file paths to query (typically from query_dataset results)
include_schema: Whether to include schema information in the result
Returns:
Query results and metadata
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| files | No | ||
| include_schema | No | ||
| query | Yes |
Input Schema (JSON Schema)
{
"properties": {
"files": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Files"
},
"include_schema": {
"default": true,
"title": "Include Schema",
"type": "boolean"
},
"query": {
"title": "Query",
"type": "string"
}
},
"required": [
"query"
],
"title": "query_sqlArguments",
"type": "object"
}