Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
in our benchmarks there's no real gain or loss, however in terms of functionality we get better serialization of objects when using interpolation - formally any object with a circular reference would result in the whole object being serialized as [Circular]. Now we label circular references properly, but 2x faster than json-stringify-safe (instead using fast-safe-stringify). This is how we end up with roughly the same benchmarks (because we replace json-stringify-safe for pino and use it instead of tryStringify for quick-format).
also log format version (v prop) is bumped since circular reference output is different
benchmarks:
benchPinoMulti_10000: 311.975ms
benchPinoMulti2_10000: 293.021ms
benchPinoInterpolate_10000: 306.162ms
benchPinoInterpolate2_10000: 304.980ms
benchPinoInterpolateAll_10000: 448.825ms
benchPinoInterpolateAll2_10000: 434.358ms
benchPinoInterpolateExtra_10000: 537.417ms
benchPinoInterpolateExtra2_10000: 530.803ms
benchPinoInterpolateDeep_10000: 5872.619ms
benchPinoInterpolateDeep2_10000: 5894.609ms
benchPinoMulti_10000: 287.413ms
benchPinoMulti2_10000: 289.061ms
benchPinoInterpolate_10000: 304.053ms
benchPinoInterpolate2_10000: 300.175ms
benchPinoInterpolateAll_10000: 467.555ms
benchPinoInterpolateAll2_10000: 451.627ms
benchPinoInterpolateExtra_10000: 582.479ms
benchPinoInterpolateExtra2_10000: 572.805ms
benchPinoInterpolateDeep_10000: 5850.142ms
benchPinoInterpolateDeep2_10000: 5877.385ms