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Extension descriptor (YAML)

Read YAML files into DuckDB with native YAML type support, comprehensive extraction functions, and seamless JSON interoperability

Installing and Loading

INSTALL yaml FROM community;
LOAD yaml;

Example

-- Load the extension
LOAD yaml;

-- Query YAML files directly
SELECT * FROM 'config.yaml';
SELECT * FROM 'data/*.yml' WHERE active = true;

-- Create tables with YAML columns
CREATE TABLE configs(id INTEGER, config YAML);
INSERT INTO configs VALUES (1, E'server: production\nport: 8080\nfeatures: [logging, metrics]');

-- Extract data using YAML functions
SELECT 
    yaml_extract_string(config, '$.server') AS environment,
    yaml_extract(config, '$.port') AS port,
    yaml_extract(config, '$.features[0]') AS first_feature
FROM configs;

-- Convert between YAML and JSON
SELECT yaml_to_json(config) AS json_config FROM configs;
SELECT value_to_yaml({name: 'John', age: 30}) AS yaml_person;

-- Write query results to YAML
COPY (SELECT * FROM users) TO 'output.yaml' (FORMAT yaml, STYLE block);

About yaml

The YAML extension brings comprehensive YAML support to DuckDB, enabling seamless integration of YAML data within SQL queries.

Key Features:

• Native YAML Type: Full YAML type support with automatic casting between YAML, JSON, and VARCHAR
• File Reading: Read YAML files with read_yaml() and read_yaml_objects() functions supporting multi-document files, top-level sequences, and robust error handling
• Direct File Querying: Query YAML files directly using FROM 'file.yaml' syntax
• Extraction Functions: Query YAML data with yaml_extract(), yaml_type(), yaml_exists(), and path-based extraction
• Type Detection: Comprehensive automatic type detection for temporal types (DATE, TIME, TIMESTAMP), optimal numeric types, and boolean values
• Column Type Specification: Explicitly define column types when reading YAML files for schema consistency
• YAML Output: Write query results to YAML files using COPY TO with configurable formatting styles
• Multi-Document Support: Handle files with multiple YAML documents separated by ---
• Error Recovery: Continue processing valid documents even when some contain errors
• JSON Interoperability: Seamless conversion between YAML and JSON formats

Example Use Cases:

• Configuration file management and querying
• Log file analysis and processing
• Data migration between YAML and relational formats
• Integration with YAML-based CI/CD pipelines
• Processing Kubernetes manifests and Helm charts

The extension is built using yaml-cpp and follows DuckDB's extension development best practices, ensuring reliable performance and cross-platform compatibility.

Note: This extension was written primarily using Claude and Claude Code as an exercise in AI-driven development.

Added Functions

Added Types