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Is there a safe way to convert float64 to int64 in Go?

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2024-02-08 21:50:34504browse

在 Go 中是否有安全的方法将 float64 转换为 int64?

php editor Zimo has a question about safely converting float64 to int64 in Go. We need to consider precision loss and range overflow. In Go, you can use the math package's Round function to round and convert floating point numbers to integers. However, it should be noted that if the floating point number exceeds the range of int64, an overflow error may occur during the conversion process. In order to avoid this situation, we can use the IsNaN function of the math package to check whether the floating point number is NaN, and then convert it to ensure the safety of the conversion. This ensures that precision loss and range overflow problems are avoided during the conversion process.

Question content

I know the int() or int64() type conversion function provided by Go. Considering that the maximum representable 64-bit floating point number math.MaxFloat64 is much larger than math.MaxInt64, is there a safe way to convert int64 to int64 (with truncation,)? A way to trigger an overflow error?

Workaround

If you are converting (not converting or typecasting) from float64 to int64, then you can convert the floating point value with Compares the nearest double-precision integer value of math.maxint64 to math.minint64. These numbers cannot be stored exactly in float64 values, but they will be stored as the next integer value above or below these numbers:

float64(math.MaxInt64) // 9223372036854775808
float64(math.MinInt64) // -9223372036854775808

So as long as your float64 value is between these two values, you know it can be converted to int64 without overflowing.

But please note that if you convert in the other direction, there is no guarantee that float64 can accurately represent all int64# up to int64 ## value, because double-precision floating-point values ​​contain only 52 bits of precision. In this case you have to check if the int64 value is between -1<<53 and 1<<53.

In either case, you can use the

math/big package to handle larger values.

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