sq + jq: The Dynamic Duo for Data Mangling

When it comes to transforming data on the command line, sq and jq make a powerful combination. While jq is the gold standard for JSON manipulation, sq brings SQL-like querying to structured data formats.

Visit sq.io to learn more about sq.

Why This Combo Rocks

sq is a free/libre open-source data wrangling swiss-army knife to inspect, query, join, import, and export data. You could think of sq as jq for databases and documents, facilitating one-liners like:

sq '@postgres_db | .actor | .first_name, .last_name | .[0:5]'

sq excels at querying databases and converting between formats, while jq shines at transforming JSON structures. Together, they form a pipeline that can handle complex data transformations with elegance.

The Sweet Spot

The magic happens when you need to:

• Extract data from databases/Excel/CSV in specific formats
• Transform complex nested structures
• Chain operations that leverage each tool’s strengths
• Work with mixed data sources (SQL → JSON → processed output)

Real-World Example

Check out this gist for practical examples with a CSV file of sq and jq working together to tackle common data processing tasks.

The combination transforms what would be complex multi-step processes into concise, readable pipelines.