Micro-benchmarks for parsing, serialization and the binary formats, written with Google Benchmark. They are not run by CI; see When to run them.
| benchmark | what it does |
|---|---|
ParseFile, ParseString | parse JSON from a file stream or a string |
Accept | validate JSON from a string (json::accept) |
ParseIndented | parse the large files re-indented by 4 spaces, for the lexer's whitespace handling |
Dump | serialize, compact (-) and indented (4) |
ToCbor, BinaryToCbor | write CBOR; BinaryToCbor writes binary values of growing size |
FromMsgpack | read MessagePack; unchanged over the years, so its numbers stay comparable across releases |
FromBinaryBuffer, FromBinaryFile | read CBOR, MessagePack, UBJSON, BJData and BSON from a buffer or a FILE* |
FromBinaryShape | read deeply nested, container-heavy and scalar-heavy documents in every binary format |
FromCborChunkedString | read CBOR strings split into indefinite-length chunks |
ViewParse, ViewRead | parse with json_document into a new document, or into one that is reused; compare with ParseString |
ViewParseIndented | as ParseIndented, with a reused json_document |
ViewAccept | validate with json_document::accept; compare with Accept |
ViewMaterialize | convert a parsed json_document into a json value |
ViewDump | serialize a parsed json_document; compare with Dump |
SaxParse | parse with a SAX handler that only counts events, so no values are built |
Copy, CopyAssign, CopyRing | copy a parsed document and destroy a copy, both timed: a temporary copy, an assignment over an earlier copy, and replacing the oldest of eight live copies |
CopyOnly, DestroyOnly | only the copy or only the destruction, the other half untimed; a fast destructor can leave work to the next allocations, so these tell the halves apart but do not compare versions |
Equal, Iterate | compare a parsed document with a copy, or visit every value with range-based for loops |
Flatten, FlattenOrdered, Unflatten | flatten() for json and ordered_json, and unflatten() |
Diff, Patch | diff() against the document with every eighth scalar changed, and applying that patch |
JsonPointerParse, JsonPointerToString, JsonPointerAt, JsonPointerContains | the JSON pointers of every scalar in a document: parse them from strings, turn them back into strings, look them up with at() and contains() |
GetVectorInt, GetVectorDouble, GetMap | get<std::vector<std::int64_t>>(), get<std::vector<double>>() and get<std::map<std::string, json>>() on large arrays and a large flat object |
ToJsonStrings | create a json array from a std::vector of 100,000 strings, copied or moved, and destroy it again |
The input files are those of nativejson-benchmark (canada, citm_catalog, twitter), a large jeopardy file, and number-heavy files (floats, signed_ints, ...). bytes_per_second counts the bytes read or written: the JSON text when parsing, the output when serializing.
make target.-DJSON_TestDataDirectory=<build directory>/test_files.JSON_GOOGLE_BENCHMARK_VERSION and the archive's URL_HASH in CMakeLists.txt together. Results are kept comparable by building both sides of a comparison with the same version, not by keeping that version forever (see Comparing two versions).single_include/nlohmann/json.hpp, so run make amalgamate after changing anything in include/.GCC and Clang builds use -O3 -flto -DNDEBUG.
From the repository root, this builds everything from scratch in cmake-build-benchmarks and runs all benchmarks:
make run_benchmarks
To build once and run selectively:
cmake -S tests/benchmarks -B build-benchmarks -G Ninja -DCMAKE_BUILD_TYPE=Release cmake --build build-benchmarks build-benchmarks/json_benchmarks --benchmark_filter='ParseString|Dump'
Useful options of json_benchmarks:
| option | effect |
|---|---|
--benchmark_list_tests | list the benchmarks instead of running them |
--benchmark_filter=<regex> | run only the benchmarks whose names match |
--benchmark_repetitions=<n> | run every benchmark n times and add mean, median, standard deviation and coefficient of variation |
--benchmark_enable_random_interleaving=true | run the repetitions in random order, which spreads out drifts such as thermal throttling |
--benchmark_min_time=<seconds>s | run each benchmark at least this long (e.g. 2s) |
--benchmark_out=<file> --benchmark_out_format=json | also write the results to a file, e.g. for compare.py |
Each line shows the wall-clock Time and the CPU time per iteration, the number of Iterations Google Benchmark chose, and the throughput in bytes_per_second. With repetitions, the lines ending in _median are the ones to compare. A _cv (coefficient of variation) above a few percent means the machine was too noisy for small differences to mean anything.
To see what a change or a release did, build the same benchmarks twice: once against the header of the version to compare with, and once against the current one. JSON_BENCHMARK_INCLUDE_DIR names the directory holding the nlohmann/json.hpp to benchmark. For example, to compare the current checkout with 3.12.0:
# the header of the version to compare with mkdir -p build-baseline-header/nlohmann git show v3.12.0:single_include/nlohmann/json.hpp > build-baseline-header/nlohmann/json.hpp # the same benchmarks, built against either header cmake -S tests/benchmarks -B build-baseline -G Ninja -DCMAKE_BUILD_TYPE=Release \ -DJSON_BENCHMARK_INCLUDE_DIR="$PWD/build-baseline-header" cmake -S tests/benchmarks -B build-current -G Ninja -DCMAKE_BUILD_TYPE=Release cmake --build build-baseline cmake --build build-current # run both, back to back build-baseline/json_benchmarks --benchmark_repetitions=10 --benchmark_enable_random_interleaving=true \ --benchmark_out=build-baseline/results.json --benchmark_out_format=json build-current/json_benchmarks --benchmark_repetitions=10 --benchmark_enable_random_interleaving=true \ --benchmark_out=build-current/results.json --benchmark_out_format=json
Google Benchmark ships a tool to compare the two result files. It needs NumPy and SciPy:
python3 -m venv build-venv build-venv/bin/pip install numpy scipy build-venv/bin/python build-current/_deps/benchmark-src/tools/compare.py -a benchmarks build-baseline/results.json build-current/results.json
The tool's own tools/requirements.txt pins NumPy and SciPy versions that need Python 3.11 or later; with an older Python, unpinned versions work as well. In its output:
Time and CPU columns are relative changes: -0.35 means 35% faster, +0.10 means 10% slower;_pvalue lines report a Mann-Whitney U test of whether the two versions differ. It needs at least 9 repetitions, and a p-value below 0.05 means the difference is unlikely to be noise;OVERALL_GEOMEAN summarizes all benchmarks;-a shows only the aggregates, not every repetition.Both builds use the same Google Benchmark, the one CMakeLists.txt names, so only the header differs. For the same reason, do not compare against result files from an earlier checkout: a different Google Benchmark, compiler or machine state can shift the numbers as much as the change under test. Rerun the baseline instead.
The header you compare with must support everything the benchmarks use. The current benchmarks build against 3.12.0; the View* benchmarks (in src/benchmarks_view.cpp) are only built if the directory also holds nlohmann/json_view.hpp. Only benchmarks present in both result files are compared, so for older releases, either filter the benchmarks or build that release's own tests/benchmarks against its own header.
performance, e.g. sudo cpupower frequency-set --governor performance. Google Benchmark prints a warning when frequency scaling is enabled. Pinning the process to a core (taskset -c 2 ...) helps as well._cv as noise.They are a manual step, not part of CI: shared CI runners vary more between runs than most of the effects measured. Run the comparison above before a release, comparing the previous release tag with develop, and for pull requests that claim to change performance.