Python module with Numpy BitGenerator to integrate with np.random, and other Python use.
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from pathlib import Path
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from typing import Any
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import cffi
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src = Path(__file__).parent.parent / "src"
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if not src.is_dir():
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raise RuntimeError("Unable to find RandQuik C sources in {src}")
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ffi = cffi.FFI()
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ffi.cdef(
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"""
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typedef struct cha_ctx { uint32_t input[16]; } cha_ctx;
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int cha_generate(uint8_t* out, uint64_t outlen, const uint8_t key[32], const uint8_t iv[16]);
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void cha_init(cha_ctx* ctx, const uint8_t* key, const uint8_t* iv);
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void cha_wipe(cha_ctx* ctx);
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int cha_update(cha_ctx* ctx, uint8_t* out, uint64_t outlen);
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"""
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)
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lib = ffi.dlopen("../build/librandquik-chacha20.so")
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def _processKeys(key, iv):
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if len(key) != 32:
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raise ValueError("key must be 32 bytes")
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if len(iv) != 16:
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raise ValueError(
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"iv must be full 16 bytes, starting with the counter - usually zeroes - followed by nonce"
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)
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return ffi.from_buffer(key), ffi.from_buffer(iv)
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def _processBuffer(out):
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if not out:
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raise ValueError("Output buffer of non-zero size is required")
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try:
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outlen = out.nbytes
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except AttributeError:
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out = memoryview(out)
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outlen = out.nbytes
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if getattr(out, "readonly", None):
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raise ValueError("The output buffer must be writable, not e.g. `bytes`")
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return ffi.from_buffer(out), outlen
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class Cha:
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def __init__(self, key: bytes | Any, iv: bytes | Any):
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"""Construct a generator that holds its internal state, moving forward on each call."""
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key, iv = _processKeys(key, iv)
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self.ctx = ffi.new("cha_ctx*")
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lib.cha_init(self.ctx, key, iv)
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def __del__(self):
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lib.cha_wipe(self.ctx)
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def __call__(self, out: bytearray | Any):
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"""Fill the parameter with random bytes"""
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out, outlen = _processBuffer(out)
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lib.cha_update(self.ctx, out, outlen)
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return out
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def generate(out: bytearray | Any, key: bytes | Any, iv: bytes | Any):
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"""Setup a generator, fill the out buffer and dispose the generator"""
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key, iv =_processKeys(key, iv)
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out, outlen = _processBuffer(out)
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lib.cha_generate(out, outlen, key, iv)
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return out
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