def mnemonic_from_entropy(entropy: Entropy,
version_str: str = "standard",
lang: str = "en") -> Mnemonic:
"""Convert input entropy to Electrum versioned mnemonic sentence.
Input entropy can be expressed as
binary 0/1 string, bytes-like, or integer.
In the case of binary 0/1 string and bytes-like,
leading zeros are considered redundant padding.
"""
if version_str not in _MNEMONIC_VERSIONS:
err_msg = f"unknown electrum mnemonic version: '{version_str}'; "
err_msg += f"not in {list(_MNEMONIC_VERSIONS.keys())}"
raise BTClibValueError(err_msg)
version = _MNEMONIC_VERSIONS[version_str]
bin_str_entropy = bin_str_entropy_from_entropy(entropy)
int_entropy = int(bin_str_entropy, 2)
base = WORDLISTS.language_length(lang)
while True:
# electrum considers entropy as integer, losing any leading zero
# so the value of bin_str_entropy before the while must be updated
nbits = int_entropy.bit_length()
bin_str_entropy = bin_str_entropy_from_entropy(int_entropy, nbits)
indexes = wordlist_indexes_from_bin_str_entropy(bin_str_entropy, base)
mnemonic = mnemonic_from_indexes(indexes, lang)
# version validity check
s = hmac.new(b"Seed version", mnemonic.encode(), sha512).hexdigest()
if s.startswith(version):
return mnemonic
# next trial
int_entropy += 1
def mnemonic_from_entropy(entropy: Optional[Entropy] = None,
lang: str = "en") -> Mnemonic:
"""Convert input entropy to BIP39 checksummed mnemonic sentence.
Input entropy can be expressed as
binary 0/1 string, bytes-like, or integer;
it must be 128, 160, 192, 224, or 256 bits.
In the case of binary 0/1 string and bytes-like,
leading zeros are not considered redundant padding.
In the case of integer, where leading zeros cannot be represented,
if the bit length is not an allowed value, then the binary 0/1
string is padded with leading zeros up to the next allowed bit
length; if the integer bit length is longer than the maximum
length, then only the leftmost bits are retained.
"""
if entropy is None or entropy == "":
entropy = secrets.randbits(128)
bin_str_entropy, checksum = _entropy_checksum(entropy)
base = WORDLISTS.language_length(lang)
indexes = wordlist_indexes_from_bin_str_entropy(bin_str_entropy + checksum,
base)
return mnemonic_from_indexes(indexes, lang)
def test_indexes() -> None:
for entropy in ("0", "00000000000"):
indexes = wordlist_indexes_from_bin_str_entropy(entropy, 2048)
assert indexes == [0]
entropy = "000000000000"
indexes = wordlist_indexes_from_bin_str_entropy(entropy, 2048)
assert indexes == [0, 0]
test_vector = [
[1268, 535, 810, 685, 433, 811, 1385, 1790, 421, 570, 567, 1313],
[0, 0, 2047, 2047, 2047, 2047, 2047, 2047, 2047, 2047, 2047, 0],
[0, 0, 2047, 2047, 2047, 2047, 2047, 2047, 2047, 2047, 2047, 0],
]
for indx in test_vector:
entropy = bin_str_entropy_from_wordlist_indexes(indx, 2048)
indexes = wordlist_indexes_from_bin_str_entropy(entropy, 2048)
assert indexes == indx