2.2.1.1. Numeric Types

When working with binary data, numbers are integral to structuring and interpreting the data. Beyond the default integer types (such as uint8, uint16, etc.), caterpillar introduces specialized integer formats to accommodate various binary data representations.

The library supports several types of numbers, categorized into integers, floating point numbers, and special primitives. Below are the available types:

Integer Types

Unsigned and signed integers are the most commonly used types for storing numeric values. The following integer types are available:

• Signed Integers:

  • int8, int16, int24, int32, int64, see Common Structs

• Unsigned Integers:

  • uint8, uint16, uint24, uint32, uint64, see Common Structs

• Platform-Specific Sizes:

  • ssize_t, size_t (signed and unsigned sizes), see Common Structs

Floating Point Types

For floating-point numbers, caterpillar offers the following types:

• float16, float32, float64, see Common Structs

Special Primitives

In addition to numbers, there are some special primitive types that are often used in binary data manipulation:

• boolean: A boolean value (True/False)

• char: A single character

• void_ptr: A void pointer, typically used in scenarios involving memory addresses or raw data pointers

Custom-sized Integers

In Caterpillar, you can define integers with custom sizes in bits, allowing you to work with non-standard bit lengths. When defining these integers, you specify the bit count, and Caterpillar internally ensures that only the necessary number of bytes are used.

For example, you can define a 24-bit signed integer or a 40-bit unsigned integer:

>>> uint24 = Int(24)      # three-byte signed integer
>>> uint40 = UInt(40)     # five-byte unsigned integer

Variable-sized Integer

The py.VarInt/c.VarInt type in both Python and Caterpillar C allows you to handle integers with variable lengths, which is useful when the size of the integer can change depending on the data being packed or unpacked. This type automatically adjusts the number of bytes required based on the value.

>>> field = F(vint) # or F(VarInt())

Changed in version 2.6.0: vint is now usable without a Field wrapper.