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__init__.py
Set project version statically due to Hatchling limitation
Marco Ricci
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__init__.py
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# SPDX-FileCopyrightText: 2024 Marco Ricci <m@the13thletter.info> # # SPDX-License-Identifier: MIT """A Python reimplementation of James Coglan's "sequin" Node.js module. James Coglan's "sequin" Node.js module provides a pseudorandom number generator (using rejection sampling on a stream of input numbers) that attempts to minimize the amount of information it throws away: (non-degenerate) rejected samples are fed into a stream of higher-order numbers from which the next random number generation request will be served. The sequin module is used in Coglan's "vault" module (a deterministic, stateless password manager that recomputes passwords instead of storing them), and this reimplementation is used for a similar purpose. The main API is the [`Sequin`] [sequin.Sequin] class, which is thoroughly documented. """ from __future__ import annotations import collections from collections.abc import Iterator, Sequence from typing_extensions import assert_type __all__ = ('Sequin', 'SequinExhaustedError') __author__ = 'Marco Ricci <m@the13thletter.info>' # Use importlib.metadata.version(...) to query the version. class Sequin: """Generate pseudorandom non-negative numbers in different ranges. Given a (presumed high-quality) uniformly random sequence of input bits, generate pseudorandom non-negative integers in a certain range on each call of the `generate` method. (It is permissible to specify a different range per call to `generate`; this is the main use case.) We use a modified version of rejection sampling, where rejected values are stored in "rejection queues" if possible, and these rejection queues re-seed the next round of rejection sampling. This is a Python reimplementation of James Coglan's [Node.js sequin module][JS_SEQUIN], as introduced in [his blog post][BLOG_POST]. It uses a [technique by Christian Lawson-Perfect][SEQUIN_TECHNIQUE]. I do not know why the original module is called "sequin"; I presume it to be a pun on "sequence". [JS_SEQUIN]: https://www.npmjs.com/package/sequin [BLOG_POST]: https://blog.jcoglan.com/2012/07/16/designing-vaults-generator-algorithm/ [SEQUIN_TECHNIQUE]: https://checkmyworking.com/2012/06/converting-a-stream-of-binary-digits-to-a-stream-of-base-n-digits/ """ def __init__( self, sequence: str | bytes | bytearray | Sequence[int], /, *, is_bitstring: bool = False ): """Initialize the Sequin. Args: sequence: A sequence of bits, or things convertible to bits, to seed the pseudorandom number generator. Byte and text strings are converted to 8-bit integer sequences. (Conversion will fail if the text string contains non-ISO-8859-1 characters.) The numbers are then converted to bits. is_bitstring: If true, treat the input as a bitstring. By default, the input is treated as a string of 8-bit integers, from which the individual bits must still be extracted. Raises: ValueError: The sequence contains values outside the permissible range. """ def uint8_to_bits(value): """Yield individual bits of an 8-bit number, MSB first.""" for i in (0x80, 0x40, 0x20, 0x10, 0x08, 0x04, 0x02, 0x01): yield 1 if value | i == value else 0 if isinstance(sequence, str): try: sequence = tuple(sequence.encode('iso-8859-1')) except UnicodeError as e: raise ValueError('sequence item out of range') from e else: sequence = tuple(sequence) assert_type(sequence, tuple[int, ...]) self.bases: dict[int, collections.deque[int]] = {} def gen() -> Iterator[int]: for num in sequence: if num not in range(2 if is_bitstring else 256): raise ValueError('sequence item out of range') if is_bitstring: yield num else: yield from uint8_to_bits(num) self.bases[2] = collections.deque(gen()) def _all_or_nothing_shift( self, count: int, /, *, base: int = 2 ) -> Sequence[int]: """Shift and return items if and only if there are enough. Args: count: Number of items to shift/consume. base: Use the base `base` sequence. Returns: If there are sufficient items in the sequence left, then consume them from the sequence and return them. Otherwise, consume nothing, and return nothing. Notes: We currently remove now-empty sequences from the registry of sequences. Examples: >>> seq = Sequin([1, 0, 1, 0, 0, 1, 0, 0, 0, 1], ... is_bitstring=True) >>> seq.bases {2: deque([1, 0, 1, 0, 0, 1, 0, 0, 0, 1])} >>> seq._all_or_nothing_shift(3) (1, 0, 1) >>> seq._all_or_nothing_shift(3) (0, 0, 1) >>> seq.bases[2] deque([0, 0, 0, 1]) >>> seq._all_or_nothing_shift(5) () >>> seq.bases[2] deque([0, 0, 0, 1]) >>> seq._all_or_nothing_shift(4) (0, 0, 0, 1) >>> 2 in seq.bases # now-empty sequences are removed False """ try: seq = self.bases[base] except KeyError: return () stash: collections.deque[int] = collections.deque() try: for i in range(count): stash.append(seq.popleft()) except IndexError: seq.extendleft(reversed(stash)) return () # Clean up queues. if not seq: del self.bases[base] return tuple(stash) @staticmethod def _big_endian_number( digits: Sequence[int], /, *, base: int = 2 ) -> int: """Evaluate the given integer sequence as a big endian number. Args: digits: A sequence of integers to evaluate. base: The number base to evaluate those integers in. Raises: ValueError: `base` is an invalid base. ValueError: Not all integers are valid base `base` digits. Examples: >>> Sequin._big_endian_number([1, 2, 3, 4, 5, 6, 7, 8], base=10) 12345678 >>> Sequin._big_endian_number([1, 2, 3, 4, 5, 6, 7, 8], base=100) 102030405060708 >>> Sequin._big_endian_number([0, 0, 0, 0, 1, 4, 9, 7], base=10) 1497 >>> Sequin._big_endian_number([1, 0, 0, 1, 0, 0, 0, 0], base=2) 144 >>> Sequin._big_endian_number([1, 7, 5, 5], base=8) == 0o1755 True """ if base < 2: raise ValueError(f'invalid base: {base!r}') ret = 0 allowed_range = range(base) n = len(digits) for i in range(n): i2 = (n - 1) - i x = digits[i] if not isinstance(x, int): raise TypeError(f'not an integer: {x!r}') if x not in allowed_range: raise ValueError(f'invalid base {base!r} digit: {x!r}') ret += (base ** i2) * x return ret def generate(self, n: int, /) -> int: """Generate a base `n` non-negative integer. We attempt to generate a value using rejection sampling. If the generated sample is outside the desired range (i.e., is rejected), then attempt to reuse the sample by seeding a "higher-order" input sequence of uniformly random numbers (for a different base). Args: n: Generate numbers in the range 0, ..., `n` - 1. (Inclusive.) Must be larger than 0. Returns: A pseudorandom number in the range 0, ..., `n` - 1. Raises: ValueError: The range is empty. SequinExhaustedError: The sequin is exhausted. Examples: >>> seq = Sequin([1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1], ... is_bitstring=True) >>> seq2 = Sequin([1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1], ... is_bitstring=True) >>> seq.generate(5) 3 >>> seq.generate(5) 3 >>> seq.generate(5) 1 >>> seq.generate(5) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... SequinExhaustedError: Sequin is exhausted Using `n = 1` does not actually consume input bits: >>> seq2.generate(1) 0 But it still won't work on exhausted sequins: >>> seq.generate(1) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... SequinExhaustedError: Sequin is exhausted """ if 2 not in self.bases: raise SequinExhaustedError('Sequin is exhausted') value = self._generate_inner(n, base=2) if value == n: raise SequinExhaustedError('Sequin is exhausted') return value def _generate_inner( self, n: int, /, *, base: int = 2 ) -> int: """Recursive call to generate a base `n` non-negative integer. We first determine the correct exponent `k` to generate base `n` numbers from a stream of base `base` numbers, then attempt to take `k` numbers from the base `base` sequence (or bail if not possible). If the resulting number `v` is out of range for base `n`, then push `v - n` onto the rejection queue for base `r` = `base` ** `k` - `n`, and attempt to generate the requested base `n` integer from the sequence of base `r` numbers next. (This recursion is not attempted if `r` = 1.) Otherwise, return the number. Args: n: Generate numbers in the range 0, ..., `n` - 1. (Inclusive.) Must be larger than 0. base: Use the base `base` sequence as a source for pseudorandom numbers. Returns: A pseudorandom number in the range 0, ..., `n` - 1 if possible, or `n` if the stream is exhausted. Raises: ValueError: The range is empty. Examples: >>> seq = Sequin([1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1], ... is_bitstring=True) >>> seq2 = Sequin([1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1], ... is_bitstring=True) >>> seq._generate_inner(5) 3 >>> seq._generate_inner(5) 3 >>> seq._generate_inner(5) 1 >>> seq._generate_inner(5) # error condition: sequin exhausted 5 Using `n = 1` does not actually consume input bits, and always works, regardless of sequin exhaustion: >>> seq2._generate_inner(1) 0 >>> seq._generate_inner(1) 0 Using an unsuitable range will raise: >>> seq2._generate_inner(0) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ValueError: invalid target range """ if n < 1: raise ValueError('invalid target range') if base < 2: raise ValueError(f'invalid base: {base!r}') # p = base ** k, where k is the smallest integer such that # p >= n. We determine p and k inductively. p = 1 k = 0 while p < n: p *= base k += 1 # The remainder r of p and n is used as the base for rejection # queue. r = p - n # The generated number v is initialized to n because of the # while loop below. v = n while v > n - 1: list_slice = self._all_or_nothing_shift(k, base=base) if not list_slice: if n != 1: return n else: v = 0 v = self._big_endian_number(list_slice, base=base) if v > n - 1: # If r is 0, then p == n, so v < n, or rather # v <= n - 1. assert r > 0 if r == 1: continue self._stash(v - n, base=r) v = self._generate_inner(n, base=r) return v def _stash(self, value: int, /, *, base: int = 2) -> None: """Stash `value` on the base `base` sequence.""" if base not in self.bases: self.bases[base] = collections.deque() self.bases[base].append(value) class SequinExhaustedError(Exception): """The sequin is exhausted. No more values can be generated from this sequin. """