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Extension repository on GitHub

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