Benchmarks

whenever is compared against Python’s standard library (+ dateutil), Arrow, and Pendulum across nine common datetime operations.

Benchmarks are run with pyperf on an Apple M1 Pro (32 GB, macOS 26.3) using Python 3.14.3 (PGO+LTO), whenever 0.9.5, Arrow 1.4.0, and Pendulum 3.2.0.

Timing

Lower is better. Bars exceeding the axis cutoff are annotated with >.

Timing comparison — whenever vs stdlib, Arrow, Pendulum

Why is whenever faster?

  • No layering. Arrow and Pendulum wrap Python’s datetime.datetime rather than replacing it. Every operation pays the overhead of crossing extra Python abstraction layers that whenever avoids entirely.

  • Optimised parsing and formatting. The Rust extension uses hand-written, single-pass byte-level parsers and formatters: no regex, no intermediate string objects, no strptime/strftime round-trips.

  • Front-loaded computation. Every ZonedDateTime stores its UTC offset at construction time. Operations like “normalize to UTC” or “subtract two instants” become simple integer arithmetic with no timezone database lookup at operation time. This also makes timezone conversion and arithmetic consistently fast.

  • Compiled core. The default wheel is a Rust CPython extension, giving C-level performance with safe, auditable code. The pure-Python fallback still benefits from the front-loaded computation model and outperforms Arrow on most simple operations.

What about the pure-Python version of whenever?

For simple operations — now(), ISO parsing, UTC normalization — it is noticeably faster than Arrow and Pendulum. For timezone-heavy operations such as ZonedDateTime construction or timezone conversion it is slower, as those use pure-Python timezone code instead of the C-optimized zoneinfo module. Overall it is in the same ballpark as Arrow and Pendulum.

Running the benchmarks yourself

See benchmarks/comparison/README.md for setup instructions.

cd benchmarks/comparison
./run.sh --fast --update-docs   # quick run, update these charts
uv run python run_whenever.py --only now --fast   # single benchmark