Numbers in Dart

Dart apps often target multiple platforms. For example, a Flutter app might target iOS, Android, and the web. The code can be the same, as long as the app doesn’t rely on platform-specific libraries or use numbers in a way that’s platform dependent.

This page has details about the differences between native and web number implementations, and how to write code so that those differences don’t matter.

Dart number representation

In Dart, all numbers are part of the common Object type hierarchy, and there are two concrete, user-visible numeric types: int, representing integer values, and double, representing fractional values.

Depending on the platform, those numeric types have different, hidden implementations. In particular, Dart has two very different types of targets it compiles to:

• Native: Most often, a 64-bit mobile or desktop processor.
• Web: JavaScript as the primary execution engine.

The following table shows how Dart numbers are usually implemented:

For native targets, you can assume that int maps to a signed 64-bit integer representation and double maps to a 64-bit IEEE floating-point representation that matches the underlying processor.

But on the web, where Dart compiles to and interoperates with JavaScript, there is a single numeric representation: a 64-bit double-precision floating-point value. For efficiency, Dart maps both int and double to this single representation. The visible type hierarchy remains the same, but the underlying hidden implementation types are different and intertwined.

The following figure illustrates the platform-specific types (in blue) for native and web targets. As the figure shows, the concrete type for int on native implements only the int interface. However, the concrete type for int on the web implements both int and double.

An int on the web is represented as a double-precision floating-point value with no fractional part. In practice, this works pretty well: double-precision floating point provides 53 bits of integer precision. However, int values are always also double values, which can lead to some surprises.

Differences in behavior

Most integer and double arithmetic has essentially the same behavior. There are, however, important differences—particularly when your code has strict expectations about precision, string formatting, or underlying runtime types.

When arithmetic results differ, as described in this section, the behavior is platform specific and subject to change.

Precision

The following table demonstrates how some numerical expressions differ due to precision. Here, math represents the dart:math library, and math.pow(2, 53) is 2⁵³.

On the web, integers lose precision past 53 bits. In particular, 2⁵³ and 2⁵³+1 map to the same value due to truncation. On native, these values can still be differentiated because native numbers have 64 bits—63 bits for the value and 1 for the sign.

The effect of overflow is visible when comparing 2⁶³-1 to 2⁶³. On native, the latter overflows to -2⁶³, as expected for two’s-complement arithmetic. On the web, these values do not overflow because they are represented differently; they’re approximations due to the loss of precision.

Identity

On native platforms, double and int are distinct types: no value can be both a double and an int at the same time. On the web, that isn’t true. Because of this difference, identity can differ between platforms, although equality (==) doesn’t.

The following table shows some expressions that use equality and identity. The equality expressions are the same on native and web; the identity expressions are usually different.

Types and type checking

On the web, the underlying int type is like a subtype of double: it’s a double-precision value without a fractional part. In fact, a type check on the web of the form x is int returns true if x is a number (double) with a zero-valued fractional part.

As a result, the following are true on the web:

• All Dart numbers (values of type num) are double.
• A Dart number can be both a double and an int at the same time.

These facts affect is checks and runtimeType properties. A side effect is that double.infinity is interpreted as an int. Because this is a platform-specific behavior, it might change in the future.

Bitwise operations

For performance reasons on the web, bitwise (&, |, ^, ~) and shift (<<,>>, >>>) operators on int use the native JavaScript equivalents. In JavaScript, the operands are truncated to 32-bit integers that are treated as unsigned. This treatment can lead to surprising results on larger numbers. In particular, if operands are negative or don’t fit into 32 bits, they’re likely to produce different results between native and web.

The following table shows how native and web platforms treat bitwise and shift operators when the operands are either negative or close to 32 bits:

String representation

On the web, Dart generally defers to JavaScript to convert a number to a string (for example, for a print). The following table demonstrates how converting the expressions in the first column can lead to different results.

What should you do?

Usually, you don’t need to change your numeric code. Dart code has been running on both native and web platforms for years, and number implementation differences are rarely a problem. Common, typical code—such as iterating through a range of small integers and indexing a list—behaves the same.

If you have tests or assertions that compare string results, write them in a platform-resilient manner. For example, suppose you’re testing the value of string expressions that have embedded numbers:

void main() {
  var count = 10.0 * 2;
  var message = "$count cows";
  if (message != "20.0 cows") throw Exception("Unexpected: $message");
}

The preceding code succeeds on native platforms but throws on the web because message is "20 cows" (no decimal) on the web. As an alternative, you might write the condition as follows, so it passes on both native and web platforms:

if (message != "${20.0} cows") throw ... 

For bit manipulation, consider explicitly operating on 32-bit chunks, which are consistent on all platforms. To force a signed interpretation of a 32-bit chunk, use int.toSigned(32).

For other cases where precision matters, consider other numeric types. The BigInt type provides arbitrary-precision integers on both native and web. The fixnum package provides strict 64-bit signed numbers, even on the web. Use these types with care, though: they often result in significantly bigger and slower code.