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Python 3.3 switched internal storage to use one of ISO-8859-1, UCS-2, or UTF-32 depending on the largest code point in the string. [31] Python 3.12 drops some functionality (for CPython extensions) to make it easier to migrate to UTF-8 for all strings. [32] Java originally used UCS-2, and added UTF-16 supplementary character support in J2SE 5.0.
Only a small subset of possible byte strings are error-free UTF-8: several bytes cannot appear; a byte with the high bit set cannot be alone; and in a truly random string a byte with a high bit set has only a 1 ⁄ 15 chance of starting a valid UTF-8 character. This has the (possibly unintended) consequence of making it easy to detect if a ...
Numeric literals in Python are of the normal sort, e.g. 0, -1, 3.4, 3.5e-8. Python has arbitrary-length integers and automatically increases their storage size as necessary. Prior to Python 3, there were two kinds of integral numbers: traditional fixed size integers and "long" integers of arbitrary size.
In computer science, type conversion, [1] [2] type casting, [1] [3] type coercion, [3] and type juggling [4] [5] are different ways of changing an expression from one data type to another. An example would be the conversion of an integer value into a floating point value or its textual representation as a string, and vice versa.
The two-symbol system used is often "0" and "1" from the binary number system. The binary code assigns a pattern of binary digits, also known as bits, to each character, instruction, etc. For example, a binary string of eight bits (which is also called a byte) can represent any of 256 possible values and can, therefore, represent a wide variety ...
Python 2 also distinguishes two types of strings: 8-bit ASCII ("bytes") strings (the default), explicitly indicated with a b or B prefix, and Unicode strings, indicated with a u or U prefix. [25] while in Python 3 strings are Unicode by default and bytes are a separate bytes type that when initialized with quotes must be prefixed with a b.
Byte pair encoding [1] [2] (also known as BPE, or digram coding) [3] is an algorithm, first described in 1994 by Philip Gage, for encoding strings of text into smaller strings by creating and using a translation table. [4]
Then zero extend the number up to a multiple of 7 bits (such that if the number is non-zero, the most significant 7 bits are not all 0). Break the number up into groups of 7 bits. Output one encoded byte for each 7 bit group, from least significant to most significant group. Each byte will have the group in its 7 least significant bits.