Awesome
Fixed-Point Decimals
To use in money, look at github.com/nikolaydubina/fpmoney
Be Precise. Using floats to represent currency is almost criminal. — Robert.C.Martin, "Clean Code" p.301
int64inside- does not use
floatneither in parsing nor printing - as fast as
int64in parsing, printing, arithmetics — 3x faserfloat, 20x faster shopspring/decimal, 30x fasterfmt - zero-overhead
- preventing error-prone fixed-point arithmetics
- Fuzz tests, Benchmarks
- JSON
- 200LOC
import fp "github.com/nikolaydubina/fpdecimal"
var BuySP500Price = fp.FromInt(9000)
input := []byte(`{"sp500": 9000.023}`)
type Stocks struct {
SP500 fp.Decimal `json:"sp500"`
}
var v Stocks
if err := json.Unmarshal(input, &v); err != nil {
log.Fatal(err)
}
var amountToBuy fp.Decimal
if v.SP500.GreaterThan(BuySP500Price) {
amountToBuy = amountToBuy.Add(v.SP500.Mul(fp.FromInt(2)))
}
fmt.Println(amountToBuy)
// Output: 18000.046
Implementation
Parsing and Printing is expensive operation and requires a lot of code.
However, if you know that your numbers are always small and simple and you do not care or do not permit lots of fractions like -1234.567, then parsing and printing can be greatly simplified.
Code is heavily influenced by hot-path from Go core strconv package.
It is wrapped into struct to prevent bugs:
- block multiplication by
fpdecimaltype, which leads to increase in decimal fractions and loose of precision - block additions of untyped constants, which leads to errors if you forget to scale by factor
Benchmarks
Parse
$ go test -bench=BenchmarkParse -benchtime=5s -benchmem .
goos: darwin
goarch: arm64
pkg: github.com/nikolaydubina/fpdecimal
BenchmarkParse/fromString/small-10 534307098 11.36 ns/op 0 B/op 0 allocs/op
BenchmarkParse/fromString/large-10 254741558 23.42 ns/op 0 B/op 0 allocs/op
BenchmarkParse/UnmarshalJSON/small-10 816873427 7.32 ns/op 0 B/op 0 allocs/op
BenchmarkParse/UnmarshalJSON/large-10 272173255 22.16 ns/op 0 B/op 0 allocs/op
BenchmarkParse_int_strconv_Atoi/small-10 1000000000 4.87 ns/op 0 B/op 0 allocs/op
BenchmarkParse_int_strconv_Atoi/large-10 420536834 14.31 ns/op 0 B/op 0 allocs/op
BenchmarkParse_int_strconv_ParseInt/small/int32-10 561137575 10.67 ns/op 0 B/op 0 allocs/op
BenchmarkParse_int_strconv_ParseInt/small/int64-10 564200026 10.64 ns/op 0 B/op 0 allocs/op
BenchmarkParse_int_strconv_ParseInt/large/int64-10 219626983 27.17 ns/op 0 B/op 0 allocs/op
BenchmarkParse_float_strconv_ParseFloat/small/float32-10 345666214 17.36 ns/op 0 B/op 0 allocs/op
BenchmarkParse_float_strconv_ParseFloat/small/float64-10 339620222 17.68 ns/op 0 B/op 0 allocs/op
BenchmarkParse_float_strconv_ParseFloat/large/float32-10 128824344 46.68 ns/op 0 B/op 0 allocs/op
BenchmarkParse_float_strconv_ParseFloat/large/float64-10 128140617 46.89 ns/op 0 B/op 0 allocs/op
BenchmarkParse_float_fmt_Sscanf/small-10 21202892 281.6 ns/op 69 B/op 2 allocs/op
BenchmarkParse_float_fmt_Sscanf/large-10 10074237 599.2 ns/op 88 B/op 3 allocs/op
PASS
ok github.com/nikolaydubina/fpdecimal 116.249s
$ go test -bench=BenchmarkPrint -benchtime=5s -benchmem .
goos: darwin
goarch: arm64
pkg: github.com/nikolaydubina/fpdecimal
BenchmarkPrint/small-10 191982066 31.24 ns/op 8 B/op 1 allocs/op
BenchmarkPrint/large-10 150874335 39.89 ns/op 24 B/op 1 allocs/op
BenchmarkPrint_int_strconv_Itoa/small-10 446302868 13.39 ns/op 3 B/op 0 allocs/op
BenchmarkPrint_int_strconv_Itoa/large-10 237484774 25.20 ns/op 18 B/op 1 allocs/op
BenchmarkPrint_int_strconv_FormatInt/small-10 444861666 13.70 ns/op 3 B/op 0 allocs/op
BenchmarkPrint_float_strconv_FormatFloat/small/float32-10 55003357 104.2 ns/op 31 B/op 2 allocs/op
BenchmarkPrint_float_strconv_FormatFloat/small/float64-10 43565430 137.4 ns/op 31 B/op 2 allocs/op
BenchmarkPrint_float_strconv_FormatFloat/large/float32-10 64069650 92.07 ns/op 48 B/op 2 allocs/op
BenchmarkPrint_float_strconv_FormatFloat/large/float64-10 68441746 87.36 ns/op 48 B/op 2 allocs/op
BenchmarkPrint_float_fmt_Sprintf/small-10 46503666 127.7 ns/op 16 B/op 2 allocs/op
BenchmarkPrint_float_fmt_Sprintf/large-10 51764224 115.8 ns/op 28 B/op 2 allocs/op
PASS
ok github.com/nikolaydubina/fpdecimal 79.192s
Arithmetics
$ go test -bench=BenchmarkArithmetic -benchtime=5s -benchmem .
goos: darwin
goarch: arm64
pkg: github.com/nikolaydubina/fpdecimal
BenchmarkArithmetic/add-10 1000000000 0.316 ns/op 0 B/op 0 allocs/op
BenchmarkArithmetic/div-10 1000000000 0.950 ns/op 0 B/op 0 allocs/op
BenchmarkArithmetic/divmod-10 1000000000 1.890 ns/op 0 B/op 0 allocs/op
BenchmarkArithmetic_int64/add-10 1000000000 0.314 ns/op 0 B/op 0 allocs/op
BenchmarkArithmetic_int64/div-10 1000000000 0.316 ns/op 0 B/op 0 allocs/op
BenchmarkArithmetic_int64/divmod-10 1000000000 1.261 ns/op 0 B/op 0 allocs/op
BenchmarkArithmetic_int64/mod-10 1000000000 0.628 ns/op 0 B/op 0 allocs/op
PASS
ok github.com/nikolaydubina/fpdecimal 6.721s
References
Appendix A: Comparison to other libraries
- https://github.com/shopspring/decimal solves arbitrary precision, fpdecimal solves only simple small decimals
- https://github.com/Rhymond/go-money solves typed number (currency), decodes through
interface{}and float64, no precision in decoding, expects encoding to be in cents
Appendix B: Benchmarking shopspring/decimal
2022-05-28
$ go test -bench=. -benchtime=5s -benchmem ./...
goos: darwin
goarch: arm64
pkg: github.com/shopspring/decimal
BenchmarkNewFromFloatWithExponent-10 59701516 97.7 ns/op 106 B/op 4 allocs/op
BenchmarkNewFromFloat-10 14771503 410.3 ns/op 67 B/op 2 allocs/op
BenchmarkNewFromStringFloat-10 16246342 375.2 ns/op 175 B/op 5 allocs/op
Benchmark_FloorFast-10 1000000000 2.1 ns/op 0 B/op 0 allocs/op
Benchmark_FloorRegular-10 53857244 106.3 ns/op 112 B/op 6 allocs/op
Benchmark_DivideOriginal-10 7 715322768 ns/op 737406446 B/op 30652495 allocs/op
Benchmark_DivideNew-10 22 262893689 ns/op 308046721 B/op 12054905 allocs/op
BenchmarkDecimal_RoundCash_Five-10 9311530 636.5 ns/op 616 B/op 28 allocs/op
Benchmark_Cmp-10 44 133191579 ns/op 24 B/op 1 allocs/op
Benchmark_decimal_Decimal_Add_different_precision-10 31561636 176.6 ns/op 280 B/op 9 allocs/op
Benchmark_decimal_Decimal_Sub_different_precision-10 36892767 164.4 ns/op 240 B/op 9 allocs/op
Benchmark_decimal_Decimal_Add_same_precision-10 134831919 44.9 ns/op 80 B/op 2 allocs/op
Benchmark_decimal_Decimal_Sub_same_precision-10 134902627 43.1 ns/op 80 B/op 2 allocs/op
BenchmarkDecimal_IsInteger-10 92543083 66.1 ns/op 8 B/op 1 allocs/op
BenchmarkDecimal_NewFromString-10 827455 7382 ns/op 3525 B/op 216 allocs/op
BenchmarkDecimal_NewFromString_large_number-10 212538 28836 ns/op 16820 B/op 360 allocs/op
BenchmarkDecimal_ExpHullAbraham-10 10000 572091 ns/op 486628 B/op 568 allocs/op
BenchmarkDecimal_ExpTaylor-10 26343 222915 ns/op 431226 B/op 3172 allocs/op
PASS
ok github.com/shopspring/decimal 123.541sa
Appendix C: Why this is good fit for money?
There are only ~200 currencies in the world.
All currencies have at most 3 decimal digits, thus it is sufficient to handle 3 decimal fractions.
Next, currencies without decimal digits are typically 1000x larger than dollar, but even then maximum number that fits into int64 (without 3 decimal fractions) is 9 223 372 036 854 775.807 which is ~9 quadrillion. This should be enough for most operations with money.
Appendix D: Is it safe to use arithmetic operators in Go?
Sort of...
In one of iterations, I did Type Alias, but it required some effort to use it carefully.
Operations with defined types (variables) will fail.
var a int64
var b fpdecimal.FromInt(1000)
// does not compile
a + b
However, untyped constants will be resolved to underlying type int64 and will be allowed.
const a 10000
var b fpdecimal.FromInt(1000)
// compiles
a + b
// also compiles
b - 42
// this one too
b *= 23
Is this a problem?
- For multiplication and division - yes, it can be. You have to be careful not to multiply two
fpdecimalnumbers, since scaling factor will quadruple. Multiplying by constants is ok tho. - For addition substraction - yes, it can be. You have to be careful and remind yourself that constants would be reduced 1000x.
Both of this can be addressed at compile time by providing linter.
This can be also addressed by wrapping into a struct and defining methods.
Formed is hard to achieve in Go, due to lack of operator overload and lots of work required to write AST parser.
Later has been implemented in this pacakge, and, as benchmarks show, without any extra memory or calls overhead as compared to int64.
Appendix E: Print into destination
To avoid mallocs, it is advantageous to print formatted value to pre-allocated destination.
Similarly, to strconv.AppendInt, we provide AppendFixedPointDecimal.
This is utilized in github.com/nikolaydubina/fpmoney package.
BenchmarkFixedPointDecimalToString/small-10 28522474 35.43 ns/op 24 B/op 1 allocs/op
BenchmarkFixedPointDecimalToString/large-10 36883687 32.32 ns/op 24 B/op 1 allocs/op
BenchmarkAppendFixedPointDecimal/small-10 38105520 30.51 ns/op 117 B/op 0 allocs/op
BenchmarkAppendFixedPointDecimal/large-10 55147478 29.52 ns/op 119 B/op 0 allocs/op
Appendix F: DivMod notation
In early versions, Div and Mul operated on int and Div returned remainder.
As recommended by @vanodevium and more in line with other common libraries, notation is changed.
Bellow is survey as of 2023-05-18.
Go, https://pkg.go.dev/math/big
func (z *Int) Div(x, y *Int) *Int
func (z *Int) DivMod(x, y, m *Int) (*Int, *Int)
func (z *Int) Mod(x, y *Int) *Int
Go, github.com/shopspring/decimal
func (d Decimal) Div(d2 Decimal) Decimal
// X no DivMod
func (d Decimal) Mod(d2 Decimal) Decimal
func (d Decimal) DivRound(d2 Decimal, precision int32) Decimal
Python, https://docs.python.org/3/library/decimal.html
divide(x, y) number
divide_int(x, y) number // truncates
divmod(x, y) number
remainder(x, y) number
Pytorch, https://pytorch.org/docs/stable/generated/torch.div.html
torch.div(input, other, *, rounding_mode=None, out=None) → [Tensor] // discards remainder
torch.remainder(input, other, *, out=None) → [Tensor] // remainder
numpy, https://numpy.org/doc/stable/reference/generated/numpy.divmod.html
np.divmod(x, y) (number, number) // is equivalent to (x // y, x % y
np.mod(x, y) number
np.remainder(x, y) number
np.divide(x, y) number
np.true_divide(x, y) number // same as divide
np.floor_divide(x, y) number // rounding down
Appendix G: generics switch for decimal counting
Go does not support numerics in templates. However, defining multiple types each associated with specific number of decimals and passing them to functions and defining constraint as union of these types — is an attractive option. This does not work well since Go does not support switch case (casting generic) back to integer well.
Appendix H: string vs []byte in interface
The typical usage of parsing number is through some JSON or other mechanism. Those APIs are dealing with []byte.
Now, conversion from []byte to string requires to copy data, since string is immutable.
To improve performance, we are using []byte in signatures.
Using string
BenchmarkParse/fromString/small-10 831217767 7.07 ns/op 0 B/op 0 allocs/op
BenchmarkParse/fromString/large-10 275009497 21.79 ns/op 0 B/op 0 allocs/op
BenchmarkParse/UnmarshalJSON/small-10 553035127 10.98 ns/op 0 B/op 0 allocs/op
BenchmarkParse/UnmarshalJSON/large-10 248815030 24.14 ns/op 0 B/op 0 allocs/op
Using []byte
BenchmarkParse/fromString/small-10 523937236 11.32 ns/op 0 B/op 0 allocs/op
BenchmarkParse/fromString/large-10 257542226 23.23 ns/op 0 B/op 0 allocs/op
BenchmarkParse/UnmarshalJSON/small-10 809793006 7.31 ns/op 0 B/op 0 allocs/op
BenchmarkParse/UnmarshalJSON/large-10 272087984 22.04 ns/op 0 B/op 0 allocs/op