🌍 JQ::Lite — Design

Purpose

JQ::Lite is a lightweight JSON query engine designed to make structured data easy to filter, transform, and reuse across diverse environments.

Its goal is simple:

Make JSON processing reliable, portable, and human-readable — everywhere.

1. Why Lightweight Matters

JSON has become the universal format for:

• APIs and service integration
• Observability and telemetry
• Configuration and automation
• Machine-to-machine communication

However, many environments still face practical constraints:

• Limited or restricted runtime environments
• Legacy or long-lived systems
• Minimal base images and offline deployments

JQ::Lite is built to operate reliably under these constraints, providing a small, dependency-minimal JSON processor that can be used where heavier tools are unavailable or impractical.

2. A Common Interface for Structured Data

JQ::Lite treats JSON as a first-class interface between systems.

Key design principles:

• JSON-in / JSON-out processing
• Compatibility with UNIX pipelines
• Identical behavior as a CLI tool and as a library

This makes it suitable for workflows where structured data flows between scripts, services, automation tools, and humans.

3. Design Philosophy

JQ::Lite follows a conservative and long-term design approach:

• Prefer clarity over cleverness
• Favor portability over performance tricks
• Avoid unnecessary dependencies
• Maintain predictable behavior across versions

The goal is not to chase trends, but to provide a stable, dependable utility that continues to work across time and platforms.

4. Type Semantics and Numeric Coercion

jq-lite currently distinguishes JSON types using Perl scalar flags, so type() reports "number" only for true numeric values (including scientific notation) and reports "string" for numeric-looking strings.

Arithmetic operators, however, follow Perl-style numeric coercion and will implicitly coerce numeric-looking strings into numbers (for example, "1e3" + 1 evaluates to 1001). This means type classification and arithmetic behavior are not strictly aligned today.

This behavior is an explicit design discussion item: we may keep the permissive coercion for compatibility, or move toward stricter jq-style runtime errors for string arithmetic in a future breaking change.

5. Open and Reproducible Workflows

Modern data pipelines often depend on proprietary platforms or tightly coupled ecosystems.

JQ::Lite intentionally avoids this:

• Fully open source
• No vendor lock-in
• No cloud dependency
• Usable in restricted or offline environments

This allows users to build reproducible, inspectable data transformations that can be versioned, audited, and shared.

6. Structured Data as Text

As infrastructure, observability, and automation increasingly rely on structured data, text-based workflows remain essential.

JQ::Lite supports this by enabling:

• Text-based JSON transformations
• Git-friendly configuration and processing logic
• Simple integration with automation systems and scripts

This keeps data processing transparent, reviewable, and automatable.

7. Ecosystem Compatibility

JQ::Lite is designed to integrate naturally with other tools and workflows.

JSON producer
    ↓
jq-lite (filter / transform)
    ↓
script / CLI / automation

The tool does not prescribe how data should be used — it simply ensures that extracting and shaping JSON remains easy and reliable.

Summary

| Aspect | Focus | |---------------|---------------------------------------------------| | Scope | Lightweight JSON querying and transformation | | Philosophy | Portability, clarity, long-term stability | | Usage | CLI and library | | Environment | Offline, restricted, legacy, and modern systems | | Longevity | Designed to remain usable across platforms/years |

Conclusion

JQ::Lite aims to be a small, dependable building block in the broader ecosystem of structured data processing.

By keeping JSON handling simple, portable, and transparent, it helps ensure that data remains usable — regardless of environment or scale.

© 2025 Shingo Kawamura