the_information_nexus/tech_docs/linux/structured_syntax.md

Certainly! For each file type—JSON, CSV, and YAML—let's identify the best tools for common use cases and provide a quick guide with syntax examples to get you started.

JSON: jq

Installation: Debian-based Linux:

sudo apt-get install jq

Common Use Case: Extracting Data

• Extract value(s) of a specific key:

  jq '.key' file.json
  

• Filter objects based on a condition:

  jq '.[] | select(.key == "value")' file.json
  

Modifying Data:

• Modify a value:

  jq '.key = "new_value"' file.json
  

Pretty-Printing:

• Format JSON file:

  jq '.' file.json
  

CSV: csvkit

Installation: Debian-based Linux:

sudo apt-get install csvkit

Common Use Case: Analyzing Data

• Print CSV file with headers:

  csvlook file.csv
  

• Convert JSON to CSV:

  in2csv file.json > file.csv
  

Filtering and Querying:

• Query CSV using SQL-like commands:

  csvsql --query "SELECT column FROM file WHERE column='value'" file.csv
  

Combining and Exporting:

• Combine multiple CSV files:

  csvstack file1.csv file2.csv > combined.csv
  

YAML: yq (Version 4.x)

Installation: Using pip:

pip install yq

Note: This also installs jq because yq is a wrapper around jq for YAML files.

Common Use Case: Extracting Data

• Extract value(s) of a specific key:

  yq e '.key' file.yaml
  

• Filter objects based on a condition:

  yq e '.[] | select(.key == "value")' file.yaml
  

Modifying Data:

• Modify a value:

  yq e '.key = "new_value"' -i file.yaml
  

Conversion to JSON:

• Convert YAML to JSON:

  yq e -o=json file.yaml
  

Combining Tools in Workflows

• While jq and yq cover JSON and YAML manipulation respectively, csvkit provides a robust set of utilities for CSV files. These tools can be combined in workflows; for example, converting CSV to JSON with csvkit and then manipulating the JSON with jq.
• For Python developers, these command-line operations can complement the use of Python libraries like json, csv, and PyYAML, allowing for quick data format conversions or manipulations directly from the terminal.

Summary

This guide presents a focused tool for each data format—jq for JSON, csvkit for CSV, and yq for YAML—along with basic syntax for common tasks like data extraction, modification, and format conversion. Integrating these tools into your development workflow can significantly enhance your productivity and data manipulation capabilities directly from the command line.