Introduction
Python wrapper for Kaldi's native I/O. The internal implementation uses C++ code from Kaldi. A Python wrapper with pybind11 is provided to read ark/scp files from Kaldi in Python.
Note: This project is self-contained and does not depend on Kaldi.
Installation
pip install --verbose kaldi_native_io
or
git clone https://github.com/csukuangfj/kaldi_native_io
cd kaldi_native_io
python3 setup.py install
Pre-built wheels
We publish pre-built wheels for CPython 3.8 – 3.15 on the following platforms:
| Platform | Architectures |
|---|---|
| Linux | x86_64, aarch64, armv7l |
| macOS | x86_64, arm64, universal2 |
| Windows | x86 (win32), x64, ARM64 |
Notes:
- Windows ARM64 wheels are provided for CPython 3.11 and later only (CPython has no native Windows ARM64 builds before 3.11).
- Linux armv7l wheels are provided for CPython 3.9 and later only.
Features
-
Native support for ALL types of
rspecifierandwspecifiersince the C++ code is borrowed from Kaldi. -
Support the following data types (More will be added later on request.)
- Note: We also support Python
bytesclass
- Note: We also support Python
| C++ Data Type | Writer | Sequential Reader | Random Access Reader |
|---|---|---|---|
Python's bytes |
BlobWriter |
SequentialBlobReader |
RandomAccessBlobReader |
int32 |
Int32Writer |
SequentialInt32Reader |
RandomAccessInt32Reader |
std::vector<int32> |
Int32VectorWriter |
SequentialInt32VectorReader |
RandomAccessInt32VectorReader |
std::vector<int8> |
Int8VectorWriter |
SequentialInt8VectorReader |
RandomAccessInt8VectorReader |
std::vector<std::vector<int32>> |
Int32VectorVectorWriter |
SequentialInt32VectorVectorReader |
RandomAccessInt32VectorVectorReader |
std::vector<std::pair<int32, int32>> |
Int32PairVectorWriter |
SequentialInt32PairVectorReader |
RandomAccessInt32PairVectorReader |
float |
FloatWriter |
SequentialFloatReader |
RandomAccessFloatReader |
std::vector<std::pair<float, float>> |
FloatPairVectorWriter |
SequentialFloatPairVectorReader |
RandomAccessFloatPairVectorReader |
double |
DoubleWriter |
SequentialDoubleReader |
RandomAccessDoubleReader |
bool |
BoolWriter |
SequentialBoolReader |
RandomAccessBoolReader |
std::string |
TokenWriter |
SequentialTokenReader |
RandomAccessTokenReader |
std::vector<std::string> |
TokenVectorWriter |
SequentialTokenVectorReader |
RandomAccessTokenVectorReader |
kaldi::Vector<float> |
FloatVectorWriter |
SequentialFloatVectorReader |
RandomAccessFloatVectorReader |
kaldi::Vector<double> |
DoubleVectorWriter |
SequentialDoubleVectorReader |
RandomAccessDoubleVectorReader |
kaldi::Matrix<float> |
FloatMatrixWriter |
SequentialFloatMatrixReader |
RandomAccessFloatMatrixReader |
kaldi::Matrix<double> |
DoubleMatrixWriter |
SequentialDoubleMatrixReader |
RandomAccessDoubleMatrixReader |
std::pair<kaldi::Matrix<float>, HtkHeader> |
HtkMatrixWriter |
SequentialHtkMatrixReader |
RandomAccessHtkMatrixReader |
kaldi::CompressedMatrix |
CompressedMatrixWriter |
SequentialCompressedMatrixReader |
RandomAccessCompressedMatrixReader |
kaldi::Posterior |
PosteriorWriter |
SequentialPosteriorReader |
RandomAccessPosteriorReader |
kaldi::GausPost |
GaussPostWriter |
SequentialGaussPostReader |
RandomAccessGaussPostReader |
kaldi::WaveInfo |
- | SequentialWaveInfoReader |
RandomAccessWaveInfoReader |
kaldi::WaveData |
- | SequentialWaveReader |
RandomAccessWaveReader |
MatrixShape |
- | SequentialMatrixShapeReader |
RandomAccessMatrixShapeReader |
Note:
MatrixShapedoes not exist in Kaldi. Its purpose is to get the shape information of a matrix without reading all the data.
Usage
Table readers and writers
Write
Create a writer instance with a wspecifier and use writer[key] = value.
For instance, the following code uses kaldi_native_io.FloatMatrixWriter to
write kaldi::Matrix<float> to a wspecifier.
import numpy as np
import kaldi_native_io
base = "float_matrix"
wspecifier = f"ark,scp,t:{base}.ark,{base}.scp"
def test_float_matrix_writer():
with kaldi_native_io.FloatMatrixWriter(wspecifier) as ko:
ko.write("a", np.array([[1, 2], [3, 4]], dtype=np.float32))
ko["b"] = np.array([[10, 20, 30], [40, 50, 60]], dtype=np.float32)
Read
Sequential Read
Create a sequential reader instance with an rspecifier and use for key, value in reader
to read the file.
For instance, the following code uses kaldi_native_io.SequentialFloatMatrixReader to
read kaldi::Matrix<float> from an rspecifier.
import numpy as np
import kaldi_native_io
base = "float_matrix"
rspecifier = f"scp:{base}.scp"
def test_sequential_float_matrix_reader():
with kaldi_native_io.SequentialFloatMatrixReader(rspecifier) as ki:
for key, value in ki:
if key == "a":
assert np.array_equal(
value, np.array([[1, 2], [3, 4]], dtype=np.float32)
)
elif key == "b":
assert np.array_equal(
value,
np.array([[10, 20, 30], [40, 50, 60]], dtype=np.float32),
)
else:
raise ValueError(f"Unknown key {key} with value {value}")
Random Access Read
Create a random access reader instance with an rspecifier and use reader[key]
to read the file.
For instance, the following code uses kaldi_native_io.RandomAccessFloatMatrixReader to
read kaldi::Matrix<float> from an rspecifier.
import numpy as np
import kaldi_native_io
base = "float_matrix"
rspecifier = f"scp:{base}.scp"
def test_random_access_float_matrix_reader():
with kaldi_native_io.RandomAccessFloatMatrixReader(rspecifier) as ki:
assert "b" in ki
assert "a" in ki
assert np.array_equal(
ki["a"], np.array([[1, 2], [3, 4]], dtype=np.float32)
)
assert np.array_equal(
ki["b"], np.array([[10, 20, 30], [40, 50, 60]], dtype=np.float32)
)
There are unit tests for all supported types. Please visit https://github.com/csukuangfj/kaldi_native_io/tree/master/kaldi_native_io/python/tests for more examples.
Read and write a single matrix
See
- https://github.com/csukuangfj/kaldi_native_io/blob/master/kaldi_native_io/python/tests/test_float_matrix_writer_reader.py
- https://github.com/csukuangfj/kaldi_native_io/blob/master/kaldi_native_io/python/tests/test_double_matrix_writer_reader.py
def test_read_write_single_mat():
arr = np.array(
[
[0, 1, 2, 22, 33],
[3, 4, 5, -1, -3],
[6, 7, 8, -9, 0],
[9, 10, 11, 5, 100],
],
dtype=np.float32,
)
mat = kaldi_native_io.FloatMatrix(arr)
mat.write(wxfilename="binary.ark", binary=True)
mat.write(wxfilename="matrix.txt", binary=False)
m1 = kaldi_native_io.FloatMatrix.read("binary.ark")
m2 = kaldi_native_io.FloatMatrix.read("matrix.txt")
assert np.array_equal(mat, m1)
assert np.array_equal(mat, m2)
# read range
# Note: the upper bound is inclusive!
m3 = kaldi_native_io.FloatMatrix.read("binary.ark[0:1]") # row 0 and row 1
assert np.array_equal(mat.numpy()[0:2], m3.numpy())
m4 = kaldi_native_io.FloatMatrix.read(
"matrix.txt[:,3:4]"
) # column 3 and column 4
assert np.array_equal(mat.numpy()[:, 3:5], m4.numpy())
os.remove("binary.ark")
os.remove("matrix.txt")
a = np.array([[1, 2], [3, 4]], dtype=np.float32)
b = np.array([[10, 20, 30], [40, 50, 60]], dtype=np.float32)
with kaldi_native_io.FloatMatrixWriter("ark,scp:m.ark,m.scp") as ko:
ko.write("a", a)
ko["b"] = b
"""
m.scp contains:
a m.ark:2
b m.ark:35
"""
m5 = kaldi_native_io.FloatMatrix.read("m.ark:2")
assert np.array_equal(m5.numpy(), a)
m6 = kaldi_native_io.FloatMatrix.read("m.ark:35")
assert np.array_equal(m6.numpy(), b)
os.remove("m.scp")
os.remove("m.ark")
Read and write a single vector
See
- https://github.com/csukuangfj/kaldi_native_io/blob/master/kaldi_native_io/python/tests/test_float_vector_writer_reader.py
- https://github.com/csukuangfj/kaldi_native_io/blob/master/kaldi_native_io/python/tests/test_double_vector_writer_reader.py
def test_read_write_single_vector():
a = np.array([1, 2], dtype=np.float32)
v = kaldi_native_io.FloatVector(a)
v.write(wxfilename="binary.ark", binary=True)
b = kaldi_native_io.FloatVector.read("binary.ark")
assert np.array_equal(a, b.numpy())
a = np.array([1, 2], dtype=np.float32)
b = np.array([10.5], dtype=np.float32)
with kaldi_native_io.FloatVectorWriter("ark,scp:v.ark,v.scp") as ko:
ko.write("a", a)
ko["b"] = b
"""
v.scp contains:
a v.ark:2
b v.ark:22
"""
va = kaldi_native_io.FloatVector.read("v.ark:2")
assert np.array_equal(va.numpy(), a)
vb = kaldi_native_io.FloatVector.read("v.ark:22")
assert np.array_equal(vb.numpy(), b)
os.remove("v.scp")
os.remove("v.ark")
def test_read_write_single_vector():
a = np.array([1, 2], dtype=np.float64)
v = kaldi_native_io.DoubleVector(a)
v.write(wxfilename="binary.ark", binary=True)
b = kaldi_native_io.DoubleVector.read("binary.ark")
assert np.array_equal(a, b.numpy())
os.remove("binary.ark")
a = np.array([1, 2], dtype=np.float64)
b = np.array([10.5], dtype=np.float64)
with kaldi_native_io.DoubleVectorWriter("ark,scp:v.ark,v.scp") as ko:
ko.write("a", a)
ko["b"] = b
"""
v.scp contains:
a v.ark:2
b v.ark:30
"""
va = kaldi_native_io.DoubleVector.read("v.ark:2")
assert np.array_equal(va.numpy(), a)
vb = kaldi_native_io.DoubleVector.read("v.ark:30")
assert np.array_equal(vb.numpy(), b)
os.remove("v.scp")
os.remove("v.ark")
Read a single int32 vector
def test_read_single_item():
a = [10, 20]
b = [100, 200, 300]
# You can also generate a text format by adding ",t" if you like
# with kaldi_native_io.Int32VectorWriter("ark,scp,t:v.ark,v.scp") as ko:
with kaldi_native_io.Int32VectorWriter("ark,scp:v.ark,v.scp") as ko:
ko.write("a", a)
ko["b"] = b
"""
v.scp contains:
a v.ark:2
b v.ark:21
"""
va = kaldi_native_io.read_int32_vector("v.ark:2")
assert va == a
vb = kaldi_native_io.read_int32_vector("v.ark:21")
assert va == b
Read/Write Waves
See
- https://github.com/csukuangfj/kaldi_native_io/blob/master/kaldi_native_io/python/tests/test_wave_reader.py
- https://github.com/csukuangfj/kaldi_native_io/blob/master/kaldi_native_io/python/tests/test_wave_data.py
def test_wave_writer():
file1 = "/ceph-fj/fangjun/open-source-2/kaldi_native_io/build/BAC009S0002W0123.wav"
if not Path(file1).is_file():
return
file2 = "/ceph-fj/fangjun/open-source-2/kaldi_native_io/build/BAC009S0002W0124.wav"
if not Path(file2).is_file():
return
print("-----test_wave_writer------")
file2 = f"cat {file2} |"
wave1 = kaldi_native_io.read_wave(file1)
wave2 = kaldi_native_io.read_wave(file2)
wspecifier = "ark,scp:wave.ark,wave.scp"
with kaldi_native_io.WaveWriter(wspecifier) as ko:
ko.write("a", wave1)
ko["b"] = wave2
"""
wave.scp has the following content:
a wave.ark:2
b wave.ark:123728
"""
wave3 = kaldi_native_io.read_wave("wave.ark:2")
wave4 = kaldi_native_io.read_wave("wave.ark:123728")
assert wave1.sample_freq == wave3.sample_freq
assert wave2.sample_freq == wave4.sample_freq
assert np.array_equal(wave1.data.numpy(), wave3.data.numpy())
assert np.array_equal(wave2.data.numpy(), wave4.data.numpy())
Read/Write Python's bytes
See
base = "blob"
wspecifier = f"ark,scp:{base}.ark,{base}.scp"
rspecifier = f"scp:{base}.scp"
def test_blob_writer():
with kaldi_native_io.BlobWriter(wspecifier) as ko:
ko.write("a", bytes([0x30, 0x31]))
ko["b"] = b"1234"
def test_sequential_blob_reader():
with kaldi_native_io.SequentialBlobReader(rspecifier) as ki:
for key, value in ki:
if key == "a":
assert value == bytes([0x30, 0x31])
elif key == "b":
assert value == b"1234"
else:
raise ValueError(f"Unknown key {key} with value {value}")
def test_read_single_item():
a = bytes([10, 20])
b = b"1234"
with kaldi_native_io.BlobWriter("ark,scp:b.ark,b.scp") as ko:
ko.write("a", a)
ko["b"] = b
"""
b.scp contains:
a b.ark:2
b b.ark:20
"""
va = kaldi_native_io.read_blob("b.ark:2")
assert va == a, (va, a)
vb = kaldi_native_io.read_blob("b.ark:20")
assert vb == b, (vb, b)
# test range read
# [start:end], both ends are inclusive
# Must satisfy 0 <= start <= end < length of the data
# start 0, end 2
vc = kaldi_native_io.read_blob("b.ark:20[0:2]")
assert vc == b"123", (vc, b"123")
# start 1, end 2
vd = kaldi_native_io.read_blob("b.ark:20[1:2]")
assert vd == b"23", (vd, b"23")
# start 2, end 2
ve = kaldi_native_io.read_blob("b.ark:20[2:2]")
assert ve == b"3", (ve, b"3")
# start 2, end -1
# -1 means the end of the data
vf = kaldi_native_io.read_blob("b.ark:20[2:-1]")
assert vf == b"34", (vf, b"34")
# [:] means all the data
vg = kaldi_native_io.read_blob("b.ark:20[:]")
assert vg == b"1234", (vg, b"1234")
os.remove("b.scp")
os.remove("b.ark")
Metadata
Release files for kaldi-native-io 1.23.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
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Built distributions (wheels)
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twine/5.0.0 CPython/3.14.8
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Release files / kaldi_native_io-1.23.0-cp314-cp314-win32.whl
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Release files / kaldi_native_io-1.23.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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Release files / kaldi_native_io-1.23.0-cp314-cp314-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
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Release files / kaldi_native_io-1.23.0-cp314-cp314-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp314-cp314-macosx_11_0_arm64.whl |
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Release files / kaldi_native_io-1.23.0-cp314-cp314-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp314-cp314-macosx_10_15_x86_64.whl |
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Release files / kaldi_native_io-1.23.0-cp314-cp314-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp314-cp314-macosx_10_15_universal2.whl |
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twine/5.0.0 CPython/3.14.8
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Release files / kaldi_native_io-1.23.0-cp313-cp313-win_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-win_arm64.whl |
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Release files / kaldi_native_io-1.23.0-cp313-cp313-win_amd64.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-win_amd64.whl |
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Release files / kaldi_native_io-1.23.0-cp313-cp313-win32.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-win32.whl |
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Release files / kaldi_native_io-1.23.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
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Release files / kaldi_native_io-1.23.0-cp313-cp313-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
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Release files / kaldi_native_io-1.23.0-cp313-cp313-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-macosx_11_0_arm64.whl |
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Release files / kaldi_native_io-1.23.0-cp313-cp313-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-macosx_10_15_x86_64.whl |
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Release files / kaldi_native_io-1.23.0-cp313-cp313-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp313-cp313-macosx_10_15_universal2.whl |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-win_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-win_arm64.whl |
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| Size | 852.7 kB |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-win_amd64.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-win_amd64.whl |
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| Size | 794.5 kB |
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twine/5.0.0 CPython/3.12.10
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Release files / kaldi_native_io-1.23.0-cp312-cp312-win32.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-win32.whl |
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| Size | 716.9 kB |
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twine/5.0.0 CPython/3.12.10
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Release files / kaldi_native_io-1.23.0-cp312-cp312-manylinux_2_31_armv7l.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-manylinux_2_31_armv7l.whl |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
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| Size | 1.3 MB |
| Tags | CPython 3.12 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 1.2 MB |
| Tags | CPython 3.12 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-macosx_11_0_arm64.whl |
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| Size | 971.2 kB |
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No |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-macosx_10_15_x86_64.whl |
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| Size | 1.1 MB |
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Release files / kaldi_native_io-1.23.0-cp312-cp312-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp312-cp312-macosx_10_15_universal2.whl |
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| Size | 2.1 MB |
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Release files / kaldi_native_io-1.23.0-cp311-cp311-win_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-win_arm64.whl |
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| Size | 852.1 kB |
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twine/5.0.0 CPython/3.11.9
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Release files / kaldi_native_io-1.23.0-cp311-cp311-win_amd64.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-win_amd64.whl |
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| Size | 794.3 kB |
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twine/5.0.0 CPython/3.11.9
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Release files / kaldi_native_io-1.23.0-cp311-cp311-win32.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-win32.whl |
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| Size | 717.0 kB |
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Release files / kaldi_native_io-1.23.0-cp311-cp311-manylinux_2_31_armv7l.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-manylinux_2_31_armv7l.whl |
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| Size | 1.1 MB |
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No |
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twine/5.0.0 CPython/3.12.3
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Release files / kaldi_native_io-1.23.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
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| Size | 1.3 MB |
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No |
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twine/5.0.0 CPython/3.11.17
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Release files / kaldi_native_io-1.23.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 1.2 MB |
| Tags | CPython 3.11 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 |
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No |
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twine/5.0.0 CPython/3.11.17
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Release files / kaldi_native_io-1.23.0-cp311-cp311-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-macosx_11_0_arm64.whl |
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| Size | 968.9 kB |
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No |
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twine/5.0.0 CPython/3.11.9
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Release files / kaldi_native_io-1.23.0-cp311-cp311-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-macosx_10_15_x86_64.whl |
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| Size | 1.1 MB |
| Tags | CPython 3.11 macOS 10.15+ x86-64 |
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No |
| Uploaded via |
twine/5.0.0 CPython/3.11.9
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Release files / kaldi_native_io-1.23.0-cp311-cp311-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp311-cp311-macosx_10_15_universal2.whl |
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| Size | 2.1 MB |
| Tags | CPython 3.11 macOS 10.15+ universal2 (ARM64, x86-64) |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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twine/5.0.0 CPython/3.11.9
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Release files / kaldi_native_io-1.23.0-cp310-cp310-win_amd64.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-win_amd64.whl |
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| Size | 790.2 kB |
| Tags | CPython 3.10 Windows x86-64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.11
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Release files / kaldi_native_io-1.23.0-cp310-cp310-win32.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-win32.whl |
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| Size | 713.6 kB |
| Tags | CPython 3.10 Windows x86-32 |
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No |
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twine/5.0.0 CPython/3.10.11
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Release files / kaldi_native_io-1.23.0-cp310-cp310-manylinux_2_31_armv7l.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-manylinux_2_31_armv7l.whl |
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| Size | 1.1 MB |
| Tags | CPython 3.10 Linux glibc 2.31+ ARMv7l |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.3
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Release files / kaldi_native_io-1.23.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
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| Size | 1.3 MB |
| Tags | CPython 3.10 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.22
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Release files / kaldi_native_io-1.23.0-cp310-cp310-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
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| Size | 1.2 MB |
| Tags | CPython 3.10 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 |
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No |
| Uploaded via |
twine/5.0.0 CPython/3.10.22
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Release files / kaldi_native_io-1.23.0-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-macosx_11_0_arm64.whl |
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| Size | 968.0 kB |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/5.0.0 CPython/3.10.11
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Release files / kaldi_native_io-1.23.0-cp310-cp310-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-macosx_10_15_x86_64.whl |
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| Size | 1.1 MB |
| Tags | CPython 3.10 macOS 10.15+ x86-64 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.21
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Release files / kaldi_native_io-1.23.0-cp310-cp310-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp310-cp310-macosx_10_15_universal2.whl |
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| Size | 2.1 MB |
| Tags | CPython 3.10 macOS 10.15+ universal2 (ARM64, x86-64) |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.11
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Release files / kaldi_native_io-1.23.0-cp39-cp39-win_amd64.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-win_amd64.whl |
|---|---|
| Size | 790.9 kB |
| Tags | CPython 3.9 Windows x86-64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.13
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Release files / kaldi_native_io-1.23.0-cp39-cp39-win32.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-win32.whl |
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| Size | 714.4 kB |
| Tags | CPython 3.9 Windows x86-32 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.13
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Release files / kaldi_native_io-1.23.0-cp39-cp39-manylinux_2_31_armv7l.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-manylinux_2_31_armv7l.whl |
|---|---|
| Size | 1.1 MB |
| Tags | CPython 3.9 Linux glibc 2.31+ ARMv7l |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.12.3
|
Release files / kaldi_native_io-1.23.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 1.3 MB |
| Tags | CPython 3.9 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.25
|
Release files / kaldi_native_io-1.23.0-cp39-cp39-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
|---|---|
| Size | 1.2 MB |
| Tags | CPython 3.9 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.25
|
Release files / kaldi_native_io-1.23.0-cp39-cp39-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-macosx_11_0_arm64.whl |
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| Size | 967.9 kB |
| Tags | CPython 3.9 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.13
|
Release files / kaldi_native_io-1.23.0-cp39-cp39-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-macosx_10_15_x86_64.whl |
|---|---|
| Size | 1.1 MB |
| Tags | CPython 3.9 macOS 10.15+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.25
|
Release files / kaldi_native_io-1.23.0-cp39-cp39-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp39-cp39-macosx_10_15_universal2.whl |
|---|---|
| Size | 2.1 MB |
| Tags | CPython 3.9 macOS 10.15+ universal2 (ARM64, x86-64) |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.13
|
Release files / kaldi_native_io-1.23.0-cp38-cp38-win_amd64.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-win_amd64.whl |
|---|---|
| Size | 789.9 kB |
| Tags | CPython 3.8 Windows x86-64 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.8.10
|
Release files / kaldi_native_io-1.23.0-cp38-cp38-win32.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-win32.whl |
|---|---|
| Size | 714.0 kB |
| Tags | CPython 3.8 Windows x86-32 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.8.10
|
Release files / kaldi_native_io-1.23.0-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.8.18
|
Release files / kaldi_native_io-1.23.0-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-manylinux2014_aarch64.manylinux_2_17_aarch64.whl |
|---|---|
| Size | 1.3 MB |
| Tags | CPython 3.8 Linux glibc 2.17+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.8.18
|
Release files / kaldi_native_io-1.23.0-cp38-cp38-macosx_11_0_arm64.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-macosx_11_0_arm64.whl |
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| Size | 967.8 kB |
| Tags | CPython 3.8 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.8.10
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Release files / kaldi_native_io-1.23.0-cp38-cp38-macosx_10_15_x86_64.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-macosx_10_15_x86_64.whl |
|---|---|
| Size | 1.1 MB |
| Tags | CPython 3.8 macOS 10.15+ x86-64 |
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SHA-256 checksum How to use checksums |
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No |
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twine/5.0.0 CPython/3.8.18
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Release files / kaldi_native_io-1.23.0-cp38-cp38-macosx_10_15_universal2.whl
| Download URL | kaldi_native_io-1.23.0-cp38-cp38-macosx_10_15_universal2.whl |
|---|---|
| Size | 2.1 MB |
| Tags | CPython 3.8 macOS 10.15+ universal2 (ARM64, x86-64) |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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twine/5.0.0 CPython/3.8.10
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