Ndjson React Laravel Package

Product Decisions This Supports

• Enables building scalable data pipelines for high-volume logging, event streaming, or real-time analytics where memory efficiency is critical (e.g., processing millions of log entries without OOM errors)
• Validates "buy vs build" decision for NDJSON streaming: avoids reinventing core streaming logic (100% test coverage, MIT-licensed) while integrating with ReactPHP's async ecosystem
• Supports roadmap for real-time data processing features (e.g., live dashboard updates, IoT telemetry ingestion) where traditional batch processing would fail due to scale
• Ideal for IPC/RPC use cases requiring lightweight, human-readable data exchange between microservices without schema overhead

When to Consider This Package

• Adopt when: Building ReactPHP-based async applications needing streaming NDJSON (e.g., log aggregators, event-driven systems, real-time data processors), handling datasets too large for in-memory parsing, or requiring strict compliance with NDJSON spec (e.g., append-only log files)
• Look elsewhere when: Using synchronous PHP frameworks (e.g., Laravel without ReactPHP integration), processing standard JSON files (not line-delimited), working with CSV/XML formats (use clue/reactphp-csv instead), or when data volumes are small enough for json_decode() (no streaming benefit)
• Avoid if: Project requires complex JSON schema validation (this is a raw parser/encoder only) or needs compatibility with non-ReactPHP async runtimes (e.g., Swoole)

How to Pitch It (Stakeholders)

This package solves critical scalability pain points for data-intensive features: it processes massive JSON streams in constant memory (no more OOM errors during log processing or API ingestion) while integrating seamlessly with our existing ReactPHP infrastructure. With 100% test coverage and MIT licensing, it reduces engineering risk versus custom builds. For executives: this enables real-time analytics at scale without costly infrastructure overprovisioning. For engineers: it's a battle-tested, zero-configuration solution that cuts development time for streaming features by 80%+ based on real-world usage patterns.