Choosing JSON Tools

R has several JSON packages. They overlap on basic parsing and writing, but they do not all make the same trade-offs. This article describes where RJSONIO fits so that package authors and users can make a practical choice.

RJSONIO’s Role

RJSONIO is maintained as a stable, extensible JSON package. Its strongest fit is code that depends on established RJSONIO behavior or needs features such as:

fromJSON(), toJSON(), and isValidJSON() with the existing interface;
parser handlers and callbacks;
custom serialization through S4 methods;
parsing from files and connections;
explicit control over JSON generation options.

This is a compatibility and extensibility role. It does not require claiming that one JSON package is always better than another.

Package Selection

For new code, choose based on the work being done:

Need	Practical choice
Keep existing `RJSONIO` behavior stable	Use `RJSONIO`
Use parser callbacks or custom handlers	Use `RJSONIO`
Serialize S4 or custom objects through methods	Use `RJSONIO`
Work mainly with tidy data frames and web APIs	Also evaluate `jsonlite`
Optimize for maximum parsing speed	Also evaluate `yyjsonr` or `RcppSimdJson`
Validate JSON schemas or transform JSON with jq-style queries	Use a specialized package

The point is not to make every package do every job. RJSONIO should remain predictable for the jobs it already supports while performance and documentation improve over time.

Compatibility Contract

Maintenance changes should follow these rules:

public functions keep their existing arguments and return shapes;
examples in the manual, vignettes, and tests continue to run;
old regression tests remain part of the test suite;
performance changes must preserve JSON output for the covered cases;
behavior changes are documented in NEWS.md.

These rules help users decide when upgrading is low risk.

Performance Comparisons

The repository includes optional benchmark scripts under benchmarks/, and the pkgdown site includes a benchmark article. Benchmark results are machine-specific. They are useful for local checks and regression tracking, but they should not be treated as universal rankings.