[s2t] mv dataset into paddlespeech.dataset (#3183)
* mv dataset into paddlespeech.dataset * add aidatatang * fix importpull/3193/head
parent
3ad55a31e7
commit
35d874c532
@ -1,3 +0,0 @@
|
||||
# [Aishell1](http://openslr.elda.org/33/)
|
||||
|
||||
This Open Source Mandarin Speech Corpus, AISHELL-ASR0009-OS1, is 178 hours long. It is a part of AISHELL-ASR0009, of which utterance contains 11 domains, including smart home, autonomous driving, and industrial production. The whole recording was put in quiet indoor environment, using 3 different devices at the same time: high fidelity microphone (44.1kHz, 16-bit,); Android-system mobile phone (16kHz, 16-bit), iOS-system mobile phone (16kHz, 16-bit). Audios in high fidelity were re-sampled to 16kHz to build AISHELL- ASR0009-OS1. 400 speakers from different accent areas in China were invited to participate in the recording. The manual transcription accuracy rate is above 95%, through professional speech annotation and strict quality inspection. The corpus is divided into training, development and testing sets. ( This database is free for academic research, not in the commerce, if without permission. )
|
@ -0,0 +1,14 @@
|
||||
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
from .aidatatang_200zh import main as aidatatang_200zh_main
|
@ -0,0 +1,157 @@
|
||||
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""Prepare aidatatang_200zh mandarin dataset
|
||||
|
||||
Download, unpack and create manifest files.
|
||||
Manifest file is a json-format file with each line containing the
|
||||
meta data (i.e. audio filepath, transcript and audio duration)
|
||||
of each audio file in the data set.
|
||||
"""
|
||||
import argparse
|
||||
import codecs
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
import soundfile
|
||||
|
||||
from paddlespeech.dataset.download import download
|
||||
from paddlespeech.dataset.download import unpack
|
||||
|
||||
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
|
||||
|
||||
URL_ROOT = 'http://www.openslr.org/resources/62'
|
||||
# URL_ROOT = 'https://openslr.magicdatatech.com/resources/62'
|
||||
DATA_URL = URL_ROOT + '/aidatatang_200zh.tgz'
|
||||
MD5_DATA = '6e0f4f39cd5f667a7ee53c397c8d0949'
|
||||
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument(
|
||||
"--target_dir",
|
||||
default=DATA_HOME + "/aidatatang_200zh",
|
||||
type=str,
|
||||
help="Directory to save the dataset. (default: %(default)s)")
|
||||
parser.add_argument(
|
||||
"--manifest_prefix",
|
||||
default="manifest",
|
||||
type=str,
|
||||
help="Filepath prefix for output manifests. (default: %(default)s)")
|
||||
args = parser.parse_args()
|
||||
|
||||
|
||||
def create_manifest(data_dir, manifest_path_prefix):
|
||||
print("Creating manifest %s ..." % manifest_path_prefix)
|
||||
json_lines = []
|
||||
transcript_path = os.path.join(data_dir, 'transcript',
|
||||
'aidatatang_200_zh_transcript.txt')
|
||||
transcript_dict = {}
|
||||
for line in codecs.open(transcript_path, 'r', 'utf-8'):
|
||||
line = line.strip()
|
||||
if line == '':
|
||||
continue
|
||||
audio_id, text = line.split(' ', 1)
|
||||
# remove withespace, charactor text
|
||||
text = ''.join(text.split())
|
||||
transcript_dict[audio_id] = text
|
||||
|
||||
data_types = ['train', 'dev', 'test']
|
||||
for dtype in data_types:
|
||||
del json_lines[:]
|
||||
total_sec = 0.0
|
||||
total_text = 0.0
|
||||
total_num = 0
|
||||
|
||||
audio_dir = os.path.join(data_dir, 'corpus/', dtype)
|
||||
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
|
||||
for fname in filelist:
|
||||
if not fname.endswith('.wav'):
|
||||
continue
|
||||
|
||||
audio_path = os.path.abspath(os.path.join(subfolder, fname))
|
||||
audio_id = os.path.basename(fname)[:-4]
|
||||
utt2spk = Path(audio_path).parent.name
|
||||
|
||||
audio_data, samplerate = soundfile.read(audio_path)
|
||||
duration = float(len(audio_data) / samplerate)
|
||||
text = transcript_dict[audio_id]
|
||||
json_lines.append(
|
||||
json.dumps(
|
||||
{
|
||||
'utt': audio_id,
|
||||
'utt2spk': str(utt2spk),
|
||||
'feat': audio_path,
|
||||
'feat_shape': (duration, ), # second
|
||||
'text': text,
|
||||
},
|
||||
ensure_ascii=False))
|
||||
|
||||
total_sec += duration
|
||||
total_text += len(text)
|
||||
total_num += 1
|
||||
|
||||
manifest_path = manifest_path_prefix + '.' + dtype
|
||||
with codecs.open(manifest_path, 'w', 'utf-8') as fout:
|
||||
for line in json_lines:
|
||||
fout.write(line + '\n')
|
||||
|
||||
manifest_dir = os.path.dirname(manifest_path_prefix)
|
||||
meta_path = os.path.join(manifest_dir, dtype) + '.meta'
|
||||
with open(meta_path, 'w') as f:
|
||||
print(f"{dtype}:", file=f)
|
||||
print(f"{total_num} utts", file=f)
|
||||
print(f"{total_sec / (60*60)} h", file=f)
|
||||
print(f"{total_text} text", file=f)
|
||||
print(f"{total_text / total_sec} text/sec", file=f)
|
||||
print(f"{total_sec / total_num} sec/utt", file=f)
|
||||
|
||||
|
||||
def prepare_dataset(url, md5sum, target_dir, manifest_path, subset):
|
||||
"""Download, unpack and create manifest file."""
|
||||
data_dir = os.path.join(target_dir, subset)
|
||||
if not os.path.exists(data_dir):
|
||||
filepath = download(url, md5sum, target_dir)
|
||||
unpack(filepath, target_dir)
|
||||
# unpack all audio tar files
|
||||
audio_dir = os.path.join(data_dir, 'corpus')
|
||||
for subfolder, dirlist, filelist in sorted(os.walk(audio_dir)):
|
||||
for sub in dirlist:
|
||||
print(f"unpack dir {sub}...")
|
||||
for folder, _, filelist in sorted(
|
||||
os.walk(os.path.join(subfolder, sub))):
|
||||
for ftar in filelist:
|
||||
unpack(os.path.join(folder, ftar), folder, True)
|
||||
else:
|
||||
print("Skip downloading and unpacking. Data already exists in %s." %
|
||||
target_dir)
|
||||
|
||||
create_manifest(data_dir, manifest_path)
|
||||
|
||||
|
||||
def main():
|
||||
print(f"args: {args}")
|
||||
if args.target_dir.startswith('~'):
|
||||
args.target_dir = os.path.expanduser(args.target_dir)
|
||||
|
||||
prepare_dataset(
|
||||
url=DATA_URL,
|
||||
md5sum=MD5_DATA,
|
||||
target_dir=args.target_dir,
|
||||
manifest_path=args.manifest_prefix,
|
||||
subset='aidatatang_200zh')
|
||||
|
||||
print("Data download and manifest prepare done!")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
@ -0,0 +1,58 @@
|
||||
# [Aishell1](http://openslr.elda.org/33/)
|
||||
|
||||
This Open Source Mandarin Speech Corpus, AISHELL-ASR0009-OS1, is 178 hours long. It is a part of AISHELL-ASR0009, of which utterance contains 11 domains, including smart home, autonomous driving, and industrial production. The whole recording was put in quiet indoor environment, using 3 different devices at the same time: high fidelity microphone (44.1kHz, 16-bit,); Android-system mobile phone (16kHz, 16-bit), iOS-system mobile phone (16kHz, 16-bit). Audios in high fidelity were re-sampled to 16kHz to build AISHELL- ASR0009-OS1. 400 speakers from different accent areas in China were invited to participate in the recording. The manual transcription accuracy rate is above 95%, through professional speech annotation and strict quality inspection. The corpus is divided into training, development and testing sets. ( This database is free for academic research, not in the commerce, if without permission. )
|
||||
|
||||
|
||||
## Dataset Architecture
|
||||
|
||||
```bash
|
||||
data_aishell
|
||||
├── transcript # text 目录
|
||||
└── wav # wav 目录
|
||||
├── dev # dev 目录
|
||||
│ ├── S0724 # spk 目录
|
||||
│ ├── S0725
|
||||
│ ├── S0726
|
||||
├── train
|
||||
│ ├── S0724
|
||||
│ ├── S0725
|
||||
│ ├── S0726
|
||||
├── test
|
||||
│ ├── S0724
|
||||
│ ├── S0725
|
||||
│ ├── S0726
|
||||
|
||||
|
||||
data_aishell
|
||||
├── transcript
|
||||
│ └── aishell_transcript_v0.8.txt # 文本标注文件
|
||||
└── wav
|
||||
├── dev
|
||||
│ ├── S0724
|
||||
│ │ ├── BAC009S0724W0121.wav # S0724 的音频
|
||||
│ │ ├── BAC009S0724W0122.wav
|
||||
│ │ ├── BAC009S0724W0123.wav
|
||||
├── test
|
||||
│ ├── S0724
|
||||
│ │ ├── BAC009S0724W0121.wav
|
||||
│ │ ├── BAC009S0724W0122.wav
|
||||
│ │ ├── BAC009S0724W0123.wav
|
||||
├── train
|
||||
│ ├── S0724
|
||||
│ │ ├── BAC009S0724W0121.wav
|
||||
│ │ ├── BAC009S0724W0122.wav
|
||||
│ │ ├── BAC009S0724W0123.wav
|
||||
|
||||
标注文件格式: <utt> <tokens>
|
||||
> head data_aishell/transcript/aishell_transcript_v0.8.txt
|
||||
BAC009S0002W0122 而 对 楼市 成交 抑制 作用 最 大 的 限 购
|
||||
BAC009S0002W0123 也 成为 地方 政府 的 眼中 钉
|
||||
BAC009S0002W0124 自 六月 底 呼和浩特 市 率先 宣布 取消 限 购 后
|
||||
BAC009S0002W0125 各地 政府 便 纷纷 跟进
|
||||
BAC009S0002W0126 仅 一 个 多 月 的 时间 里
|
||||
BAC009S0002W0127 除了 北京 上海 广州 深圳 四 个 一 线 城市 和 三亚 之外
|
||||
BAC009S0002W0128 四十六 个 限 购 城市 当中
|
||||
BAC009S0002W0129 四十一 个 已 正式 取消 或 变相 放松 了 限 购
|
||||
BAC009S0002W0130 财政 金融 政策 紧随 其后 而来
|
||||
BAC009S0002W0131 显示 出 了 极 强 的 威力
|
||||
```
|
@ -0,0 +1,18 @@
|
||||
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
from .aishell import check_dataset
|
||||
from .aishell import create_manifest
|
||||
from .aishell import download_dataset
|
||||
from .aishell import main as aishell_main
|
||||
from .aishell import prepare_dataset
|
@ -0,0 +1,229 @@
|
||||
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
"""Prepare Aishell mandarin dataset
|
||||
|
||||
Download, unpack and create manifest files.
|
||||
Manifest file is a json-format file with each line containing the
|
||||
meta data (i.e. audio filepath, transcript and audio duration)
|
||||
of each audio file in the data set.
|
||||
"""
|
||||
import argparse
|
||||
import codecs
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
import soundfile
|
||||
|
||||
from paddlespeech.dataset.download import download
|
||||
from paddlespeech.dataset.download import unpack
|
||||
|
||||
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
|
||||
|
||||
URL_ROOT = 'http://openslr.elda.org/resources/33'
|
||||
# URL_ROOT = 'https://openslr.magicdatatech.com/resources/33'
|
||||
DATA_URL = URL_ROOT + '/data_aishell.tgz'
|
||||
MD5_DATA = '2f494334227864a8a8fec932999db9d8'
|
||||
RESOURCE_URL = URL_ROOT + '/resource_aishell.tgz'
|
||||
MD5_RESOURCE = '957d480a0fcac85fc18e550756f624e5'
|
||||
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument(
|
||||
"--target_dir",
|
||||
default=DATA_HOME + "/Aishell",
|
||||
type=str,
|
||||
help="Directory to save the dataset. (default: %(default)s)")
|
||||
parser.add_argument(
|
||||
"--manifest_prefix",
|
||||
default="manifest",
|
||||
type=str,
|
||||
help="Filepath prefix for output manifests. (default: %(default)s)")
|
||||
args = parser.parse_args()
|
||||
|
||||
|
||||
def create_manifest(data_dir, manifest_path_prefix):
|
||||
print("Creating manifest %s ..." % os.path.join(data_dir,
|
||||
manifest_path_prefix))
|
||||
json_lines = []
|
||||
transcript_path = os.path.join(data_dir, 'transcript',
|
||||
'aishell_transcript_v0.8.txt')
|
||||
transcript_dict = {}
|
||||
for line in codecs.open(transcript_path, 'r', 'utf-8'):
|
||||
line = line.strip()
|
||||
if line == '':
|
||||
continue
|
||||
audio_id, text = line.split(' ', 1)
|
||||
# remove withespace, charactor text
|
||||
text = ''.join(text.split())
|
||||
transcript_dict[audio_id] = text
|
||||
|
||||
data_metas = dict()
|
||||
data_types = ['train', 'dev', 'test']
|
||||
for dtype in data_types:
|
||||
del json_lines[:]
|
||||
total_sec = 0.0
|
||||
total_text = 0.0
|
||||
total_num = 0
|
||||
|
||||
audio_dir = os.path.join(data_dir, 'wav', dtype)
|
||||
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
|
||||
for fname in filelist:
|
||||
audio_path = os.path.abspath(os.path.join(subfolder, fname))
|
||||
audio_id = os.path.basename(fname)[:-4]
|
||||
# if no transcription for audio then skipped
|
||||
if audio_id not in transcript_dict:
|
||||
continue
|
||||
|
||||
utt2spk = Path(audio_path).parent.name
|
||||
audio_data, samplerate = soundfile.read(audio_path)
|
||||
duration = float(len(audio_data) / samplerate)
|
||||
text = transcript_dict[audio_id]
|
||||
json_lines.append(
|
||||
json.dumps(
|
||||
{
|
||||
'utt': audio_id,
|
||||
'utt2spk': str(utt2spk),
|
||||
'feat': audio_path,
|
||||
'feat_shape': (duration, ), # second
|
||||
'text': text
|
||||
},
|
||||
ensure_ascii=False))
|
||||
|
||||
total_sec += duration
|
||||
total_text += len(text)
|
||||
total_num += 1
|
||||
|
||||
manifest_path = manifest_path_prefix + '.' + dtype
|
||||
with codecs.open(manifest_path, 'w', 'utf-8') as fout:
|
||||
for line in json_lines:
|
||||
fout.write(line + '\n')
|
||||
|
||||
meta = dict()
|
||||
meta["dtype"] = dtype # train, dev, test
|
||||
meta["utts"] = total_num
|
||||
meta["hours"] = total_sec / (60 * 60)
|
||||
meta["text"] = total_text
|
||||
meta["text/sec"] = total_text / total_sec
|
||||
meta["sec/utt"] = total_sec / total_num
|
||||
data_metas[dtype] = meta
|
||||
|
||||
manifest_dir = os.path.dirname(manifest_path_prefix)
|
||||
meta_path = os.path.join(manifest_dir, dtype) + '.meta'
|
||||
with open(meta_path, 'w') as f:
|
||||
for key, val in meta.items():
|
||||
print(f"{key}: {val}", file=f)
|
||||
|
||||
return data_metas
|
||||
|
||||
|
||||
def download_dataset(url, md5sum, target_dir):
|
||||
"""Download, unpack and create manifest file."""
|
||||
data_dir = os.path.join(target_dir, 'data_aishell')
|
||||
if not os.path.exists(data_dir):
|
||||
filepath = download(url, md5sum, target_dir)
|
||||
unpack(filepath, target_dir)
|
||||
# unpack all audio tar files
|
||||
audio_dir = os.path.join(data_dir, 'wav')
|
||||
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
|
||||
for ftar in filelist:
|
||||
unpack(os.path.join(subfolder, ftar), subfolder, True)
|
||||
else:
|
||||
print("Skip downloading and unpacking. Data already exists in %s." %
|
||||
os.path.abspath(target_dir))
|
||||
return os.path.abspath(data_dir)
|
||||
|
||||
|
||||
def check_dataset(data_dir):
|
||||
print(f"check dataset {os.path.abspath(data_dir)} ...")
|
||||
|
||||
transcript_path = os.path.join(data_dir, 'transcript',
|
||||
'aishell_transcript_v0.8.txt')
|
||||
if not os.path.exists(transcript_path):
|
||||
raise FileNotFoundError(f"no transcript file found in {data_dir}.")
|
||||
|
||||
transcript_dict = {}
|
||||
for line in codecs.open(transcript_path, 'r', 'utf-8'):
|
||||
line = line.strip()
|
||||
if line == '':
|
||||
continue
|
||||
audio_id, text = line.split(' ', 1)
|
||||
# remove withespace, charactor text
|
||||
text = ''.join(text.split())
|
||||
transcript_dict[audio_id] = text
|
||||
|
||||
no_label = 0
|
||||
data_types = ['train', 'dev', 'test']
|
||||
for dtype in data_types:
|
||||
audio_dir = os.path.join(data_dir, 'wav', dtype)
|
||||
if not os.path.exists(audio_dir):
|
||||
raise IOError(f"{audio_dir} does not exist.")
|
||||
|
||||
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
|
||||
for fname in filelist:
|
||||
audio_path = os.path.abspath(os.path.join(subfolder, fname))
|
||||
audio_id = os.path.basename(fname)[:-4]
|
||||
# if no transcription for audio then skipped
|
||||
if audio_id not in transcript_dict:
|
||||
print(f"Warning: {audio_id} not has transcript.")
|
||||
no_label += 1
|
||||
continue
|
||||
|
||||
utt2spk = Path(audio_path).parent.name
|
||||
audio_data, samplerate = soundfile.read(audio_path)
|
||||
assert samplerate == 16000, f"{audio_path} sample rate is {samplerate} not 16k, please check."
|
||||
|
||||
print(f"Warning: {dtype} has {no_label} audio does not has transcript.")
|
||||
|
||||
|
||||
def prepare_dataset(url, md5sum, target_dir, manifest_path=None, check=False):
|
||||
"""Download, unpack and create manifest file."""
|
||||
data_dir = download_dataset(url, md5sum, target_dir)
|
||||
|
||||
if check:
|
||||
try:
|
||||
check_dataset(data_dir)
|
||||
except Exception as e:
|
||||
raise ValueError(
|
||||
f"{data_dir} dataset format not right, please check it.")
|
||||
|
||||
meta = None
|
||||
if manifest_path:
|
||||
meta = create_manifest(data_dir, manifest_path)
|
||||
|
||||
return data_dir, meta
|
||||
|
||||
|
||||
def main():
|
||||
print(f"args: {args}")
|
||||
if args.target_dir.startswith('~'):
|
||||
args.target_dir = os.path.expanduser(args.target_dir)
|
||||
|
||||
data_dir, meta = prepare_dataset(
|
||||
url=DATA_URL,
|
||||
md5sum=MD5_DATA,
|
||||
target_dir=args.target_dir,
|
||||
manifest_path=args.manifest_prefix,
|
||||
check=True)
|
||||
|
||||
resource_dir, _ = prepare_dataset(
|
||||
url=RESOURCE_URL,
|
||||
md5sum=MD5_RESOURCE,
|
||||
target_dir=args.target_dir,
|
||||
manifest_path=None)
|
||||
|
||||
print("Data download and manifest prepare done!")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
@ -0,0 +1,98 @@
|
||||
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
import hashlib
|
||||
import os
|
||||
import sys
|
||||
from typing import Text
|
||||
|
||||
__all__ = ["print_arguments", "add_arguments", "get_commandline_args"]
|
||||
|
||||
|
||||
def get_commandline_args():
|
||||
extra_chars = [
|
||||
" ",
|
||||
";",
|
||||
"&",
|
||||
"(",
|
||||
")",
|
||||
"|",
|
||||
"^",
|
||||
"<",
|
||||
">",
|
||||
"?",
|
||||
"*",
|
||||
"[",
|
||||
"]",
|
||||
"$",
|
||||
"`",
|
||||
'"',
|
||||
"\\",
|
||||
"!",
|
||||
"{",
|
||||
"}",
|
||||
]
|
||||
|
||||
# Escape the extra characters for shell
|
||||
argv = [
|
||||
arg.replace("'", "'\\''") if all(char not in arg
|
||||
for char in extra_chars) else
|
||||
"'" + arg.replace("'", "'\\''") + "'" for arg in sys.argv
|
||||
]
|
||||
|
||||
return sys.executable + " " + " ".join(argv)
|
||||
|
||||
|
||||
def print_arguments(args, info=None):
|
||||
"""Print argparse's arguments.
|
||||
|
||||
Usage:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("name", default="Jonh", type=str, help="User name.")
|
||||
args = parser.parse_args()
|
||||
print_arguments(args)
|
||||
|
||||
:param args: Input argparse.Namespace for printing.
|
||||
:type args: argparse.Namespace
|
||||
"""
|
||||
filename = ""
|
||||
if info:
|
||||
filename = info["__file__"]
|
||||
filename = os.path.basename(filename)
|
||||
print(f"----------- {filename} Configuration Arguments -----------")
|
||||
for arg, value in sorted(vars(args).items()):
|
||||
print("%s: %s" % (arg, value))
|
||||
print("-----------------------------------------------------------")
|
||||
|
||||
|
||||
def add_arguments(argname, type, default, help, argparser, **kwargs):
|
||||
"""Add argparse's argument.
|
||||
|
||||
Usage:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
add_argument("name", str, "Jonh", "User name.", parser)
|
||||
args = parser.parse_args()
|
||||
"""
|
||||
type = distutils.util.strtobool if type == bool else type
|
||||
argparser.add_argument(
|
||||
"--" + argname,
|
||||
default=default,
|
||||
type=type,
|
||||
help=help + ' Default: %(default)s.',
|
||||
**kwargs)
|
Loading…
Reference in new issue