# JSONL.help

> JSONL.help is the definitive developer reference for the JSON Lines format (JSONL, also known as NDJSON): guides, examples, specifications, and validation tools for streaming data, AI training datasets, and log processing.

## Docs

- [Definition](https://jsonl.help/definition/): Formal definition of the JSON Lines (JSONL/NDJSON) format.
- [Examples](https://jsonl.help/examples/): Real-world JSONL code samples and use cases.
- [Tutorial](https://jsonl.help/tutorial/): Step-by-step guide to working with JSONL.
- [Quick Start](https://jsonl.help/learn/): Get started with JSON Lines fast.
- [Validator](https://jsonl.help/validator/): Validate and lint JSONL/NDJSON data in your browser.
- [Best Practices](https://jsonl.help/best-practices/): Recommended practices for producing and consuming JSONL.
- [Advanced](https://jsonl.help/advanced/): Compression, parallel processing, schema evolution, and indexing.
- [FAQ](https://jsonl.help/faq/): Frequently asked questions about JSONL.

## Guides

- [Converting To and From JSONL](https://jsonl.help/convert/): Working commands for JSON, CSV, Parquet, Excel, SQL and YAML in both directions.
- [Schema Validation](https://jsonl.help/schema-validation/): Applying JSON Schema per line, handling mixed record types, and enforcing it in CI.
- [LLM Fine-Tuning](https://jsonl.help/llm-fine-tuning/): The chat messages shape, preference data, and how OpenAI, Vertex AI, Mistral and TRL differ.
- [JSONL vs Parquet](https://jsonl.help/jsonl-vs-parquet/): Row versus columnar, when each wins, and the land-as-JSONL then compact-to-Parquet pattern.

## Use Cases

- [Machine Learning](https://jsonl.help/use-cases/machine-learning/): JSONL for AI/ML training datasets.
- [Log Processing](https://jsonl.help/use-cases/log-processing/): JSONL for logs and observability.
- [Data Streaming](https://jsonl.help/use-cases/data-streaming/): JSONL for streaming pipelines.
- [Analytics Pipelines](https://jsonl.help/use-cases/analytics-pipelines/): JSONL in analytics workflows.
- [API Development](https://jsonl.help/use-cases/api-development/): JSONL for streaming API responses.

## Troubleshooting

- [Troubleshooting](https://jsonl.help/troubleshooting/): Diagnose JSONL parsing, encoding, memory, and performance problems.
- [Error Dictionary](https://jsonl.help/error-dictionary/): Every common JSONL parser error with cause and fix.
- [Common Mistakes](https://jsonl.help/common-mistakes/): The most frequent JSONL authoring mistakes and how to avoid them.

## Reference

- [Languages](https://jsonl.help/languages/): Reading and writing JSONL across programming languages.
- [Comparisons](https://jsonl.help/comparisons/): JSONL versus JSON, CSV, and other formats.
- [Advantages](https://jsonl.help/advantages/): Why JSONL is chosen for streaming, big data, and AI workloads.
- [Performance](https://jsonl.help/performance/): Parse speed, memory, and compression characteristics.
- [Tools](https://jsonl.help/tools/): jq recipes, CLI utilities, converters, and IDE setup.
- [Glossary](https://jsonl.help/glossary/): Key JSONL terms and definitions.
- [History](https://jsonl.help/history/): How the JSON Lines format emerged and where it is used today.
- [Case Studies](https://jsonl.help/case-studies/): How real platforms use JSONL in production.
- [Links](https://jsonl.help/links/): Curated JSONL tools, libraries, and resources.

## Site

- [Search](https://jsonl.help/search/): Search all JSONL.help documentation.
- [Privacy Policy](https://jsonl.help/privacy/): Analytics, local storage, and your privacy rights.