|Morgan Bazalgette fec7b21875 Update readme||11 months ago|
|.travis.yml||3 years ago|
|LICENSE||3 years ago|
|README.md||11 months ago|
|binary.go||11 months ago|
|read_float.go||3 years ago|
|read_int.go||3 years ago|
|read_test.go||3 years ago|
|read_uint.go||11 months ago|
|write_float.go||3 years ago|
|write_int.go||3 years ago|
|write_test.go||11 months ago|
|write_uint.go||11 months ago|
A faster binary encoder.
go get howl.moe/binary
All slice-related methods have been removed - this is because they allocated their own slices (for reads). The way slices are implemented in binary protocols is often arbitrary, some specify the length, some only in certain cases, some use varints, others use different widths for the length. For this reason, we removed the methods.
ByteSlice and String have been kept, since those are even used internally.
There is no way to read a string directly like there was in the previous
version - this is because of the aforementioned variability in implementation
about encoding the length. You can still use the newly-added
io.Reader) passing a byte slice with the length desired.
Previously, every single tiny read and write allocated a byte slice. This is
actually quite expensive - it is a heap allocation, which needs to be tracked
by the garbage collector, and so on. Now the byte slice is pre-allocated in the
Reader/WriteChain itself (as an array,
buf byte, which is then used as a
c.buf[:]). This gives significant performance boosts:
$ git checkout v1 $ go test -bench=. goos: linux goarch: amd64 pkg: github.com/thehowl/binary BenchmarkWriteSmall-4 30000000 36.4 ns/op BenchmarkWriteMedium-4 5000000 263 ns/op BenchmarkWriteLong-4 1000000 1649 ns/op PASS ok github.com/thehowl/binary 4.421s $ git checkout master $ go test -bench=. goos: linux goarch: amd64 pkg: github.com/thehowl/binary BenchmarkWriteSmall-4 100000000 20.0 ns/op BenchmarkWriteMedium-4 20000000 91.7 ns/op BenchmarkWriteLong-4 3000000 412 ns/op PASS ok github.com/thehowl/binary 5.630s
As you can see, for writes of large chunks of data, this can be up to a 4x improvement.