DCT Infer - Generate SQL Schema

Create DuckDB-compatible CREATE TABLE statements by analyzing data file contents.

When to Use

Use this skill when you need to:

• Create database tables from existing data files
• Document the schema of a dataset
• Generate DDL for ETL pipelines
• Understand column types in a file
• Prepare data for SQL-based analysis

Installation

which dct || go build -o dct && chmod +x ./dct

Usage

dct infer <file> [flags]

Flags

• -t, --table <name>: Table name (default: "default")
• -n, --lines <number>: Number of lines to analyze for type inference (useful for large files)
• -o, --output <file>: Output to file instead of stdout

Examples

Basic schema inference:

dct infer data.csv

With custom table name:

dct infer data.parquet -t events

Save schema to file:

dct infer large.ndjson -n 1000 -t users -o schema.sql

Infer from specific number of rows:

dct infer bigfile.csv -n 500 -t transactions

Output Format

DuckDB-compatible CREATE TABLE statement:

create table users (
    "id" bigint,
    "name" varchar,
    "email" varchar,
    "created_at" timestamp,
    "is_active" boolean
)

Supported Data Types

The inferred schema uses DuckDB types:

• bigint - 64-bit integers
• integer - 32-bit integers
• double - Floating point numbers
• varchar - String/text data
• timestamp - Date and time
• date - Date only
• time - Time only
• boolean - True/false values
• array(...) - Array columns
• row(...) - Struct/nested columns

Best Practices

• Use -n flag for large files to speed up inference
• Column names are quoted to handle special characters
• Output is compatible with DuckDB and similar SQL databases
• For Parquet files, types are read directly from metadata
• For CSV/JSON, types are inferred from sample data

Integration Examples

With DuckDB

# Create table directly
dct infer data.csv -t my_table | duckdb mydb.duckdb

# Or save and execute
dct infer data.csv -t my_table -o schema.sql
duckdb mydb.duckdb < schema.sql

In Scripts

#!/bin/bash
for file in *.csv; do
    dct infer "$file" -t "$(basename "$file" .csv)" > "${file%.csv}.sql"
done

Related Skills

• dct-peek: Preview data before inferring schema
• dct-profile: Check data quality before creating tables