How does jc compare to jq for parsing command output?

jc is designed to convert unstructured command output into JSON, while jq is for querying and transforming existing JSON. They are complementary: jc structures the data, and jq can filter it, as shown in the dig example with piping to jq.

How to parse a custom command that isn't in jc's parser list?

You can write a parser plugin in Python using the provided templates and place it in the jcparsers directory. This requires Python programming skills and is documented in the parser plugins section.

Does jc work on Windows?

Yes, jc has parsers for Windows commands like `ipconfig` and `systeminfo`, and it can be installed via pip or binaries. However, many parsers are Unix-specific, so compatibility varies, and warnings may need suppression with `-q`.

How to handle errors in jc streaming parsers?

Use the `-qq` option to ignore parsing errors, which adds a `_jc_meta` object with success status and error details. This prevents pipeline breaks, as described in the streaming parsers section.

Can jc parse real-time data from commands like top?

Yes, jc has streaming parsers like `--top-s` that output JSON Lines as data is received, enabling real-time processing. However, unbuffered output (`-u`) may be needed to reduce latency, with trade-offs in speed.

What's the performance impact of using jc?

jc adds parsing overhead, which can affect latency in pipelines. Streaming parsers optimize memory but may slow down with unbuffered output, and batch processing benefits from slicing options to skip lines.

jc — CLI Tool for JSON Conversion

What is jc?

jc is a command-line tool and Python library that converts the output of command-line utilities, common file formats, and strings into JSON, YAML, or Python dictionaries. It solves the problem of parsing unstructured command output by providing a standardized, machine-readable format that integrates seamlessly with tools like jq and automation scripts.

Target Audience

System administrators, DevOps engineers, and developers who work with command-line tools and need to parse or automate output in scripts, Ansible playbooks, or monitoring pipelines.

Value Proposition

jc offers a comprehensive set of parsers for over 150 commands and formats, supports both streaming and batch processing, and works as both a CLI tool and a Python library, making it uniquely versatile for automation and data transformation tasks.

CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts.

Use Cases

Best For

Parsing command output in Bash scripts for further processing with jq
Converting system monitoring commands (like `ps`, `netstat`, `df`) into JSON for logging or dashboards
Integrating command output into Ansible, SaltStack, or Nornir automation workflows
Transforming log files (e.g., CSV, syslog) into structured data for analysis
Streaming real-time command output (e.g., `ping`, `top`) as JSON Lines
Simplifying ad-hoc data extraction from CLI tools without writing custom parsers

Not Ideal For

Systems where CLI tools already provide native JSON or structured output options (e.g., `docker inspect --format json`)
High-performance, low-latency pipelines where parsing overhead is critical and raw text processing is preferred
Environments that cannot install Python or where binary dependencies are restricted, such as minimal container images
Parsing output from unsupported or custom commands without the ability to write a Python plugin

Pros & Cons

Pros

Extensive Parser Library

Supports over 150 command outputs, file types, and strings, providing a wide range of pre-built parsers for common use cases, as detailed in the parsers table.

CLI and Library Flexibility

Works as both a command-line tool for piping and a Python library for programmatic parsing, enabling seamless integration into scripts and applications like Ansible.

Structured Type Conversion

Converts output to JSON with proper types (int, float, boolean, null) and a strict schema per parser, improving data reliability for automation tasks.

Streaming Capabilities

Offers streaming parsers that output JSON Lines for memory-efficient processing of large data streams, such as from `ping` or `top` commands, with options for unbuffered output.

Cons

Platform-Specific Limitations

Many parsers are only compatible with specific operating systems (e.g., Linux, macOS), and running on unsupported platforms requires suppressing warnings or may not work correctly, as noted in the compatibility section.

Performance Overhead

Adds parsing latency, especially for streaming parsers where unbuffered output can be slower; the README admits that unbuffered output is not ideal for large data streams.

Custom Parser Complexity

For unsupported commands, users must write Python plugin modules, which requires programming knowledge and adds maintenance burden, as outlined in the parser plugins section.

What is jc?

Target Audience

System administrators, DevOps engineers, and developers who work with command-line tools and need to parse or automate output in scripts, Ansible playbooks, or monitoring pipelines.

Value Proposition

Use Cases

Best For

Parsing command output in Bash scripts for further processing with jq
Converting system monitoring commands (like `ps`, `netstat`, `df`) into JSON for logging or dashboards
Integrating command output into Ansible, SaltStack, or Nornir automation workflows
Transforming log files (e.g., CSV, syslog) into structured data for analysis
Streaming real-time command output (e.g., `ping`, `top`) as JSON Lines
Simplifying ad-hoc data extraction from CLI tools without writing custom parsers

Not Ideal For

Systems where CLI tools already provide native JSON or structured output options (e.g., `docker inspect --format json`)
High-performance, low-latency pipelines where parsing overhead is critical and raw text processing is preferred
Environments that cannot install Python or where binary dependencies are restricted, such as minimal container images
Parsing output from unsupported or custom commands without the ability to write a Python plugin

Pros & Cons

Pros

Extensive Parser Library

Supports over 150 command outputs, file types, and strings, providing a wide range of pre-built parsers for common use cases, as detailed in the parsers table.

CLI and Library Flexibility

Works as both a command-line tool for piping and a Python library for programmatic parsing, enabling seamless integration into scripts and applications like Ansible.

Structured Type Conversion

Converts output to JSON with proper types (int, float, boolean, null) and a strict schema per parser, improving data reliability for automation tasks.

Streaming Capabilities

Offers streaming parsers that output JSON Lines for memory-efficient processing of large data streams, such as from `ping` or `top` commands, with options for unbuffered output.

Cons

Platform-Specific Limitations

Performance Overhead

Adds parsing latency, especially for streaming parsers where unbuffered output can be slower; the README admits that unbuffered output is not ideal for large data streams.

Custom Parser Complexity

For unsupported commands, users must write Python plugin modules, which requires programming knowledge and adds maintenance burden, as outlined in the parser plugins section.

jc

What is jc?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

jc

What is jc?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?