28 ví dụ mã Python được tìm thấy liên quan đến "chuyển đổi tệp". Bạn có thể bỏ phiếu cho những người bạn thích hoặc bỏ phiếu cho những người bạn không thích và đi đến dự án gốc hoặc tệp nguồn bằng cách theo các liên kết trên mỗi ví dụ. convert files". You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Show ví dụ 1 def convert_and_rename_subcortical_files(fol, new_fol, lookup):
obj_files = glob.glob(op.join(fol, '*.srf'))
utils.delete_folder_files(new_fol)
for obj_file in obj_files:
num = int(op.basename(obj_file)[:-4].split('_')[-1])
new_name = lookup.get(num, '')
if new_name != '':
utils.srf2ply(obj_file, op.join(new_fol, '{}.ply'.format(new_name)))
verts, faces = utils.read_ply_file(op.join(new_fol, '{}.ply'.format(new_name)))
np.savez(op.join(new_fol, '{}.npz'.format(new_name)), verts=verts, faces=faces)
# copy_subcorticals_to_mmvt(new_fol, subject, mmvt_subcorticals_fol_name)
# def copy_subcorticals_to_mmvt(subcorticals_fol, subject, mmvt_subcorticals_fol_name='subcortical'):
# blender_fol = op.join(MMVT_DIR, subject, mmvt_subcorticals_fol_name)
# if op.isdir(blender_fol):
# shutil.rmtree(blender_fol)
# utils.copy_filetree(subcorticals_fol, blender_fol) Ví dụ 2 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs Ví dụ 3 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) Ví dụ 4 def convert_skin_files(self):
# get list of skins to convert
skin_dirs = [d for d in os.listdir(self.skin_path) if os.path.isdir(os.path.join(self.skin_path, d))]
for skin_dir in skin_dirs:
if skin_dir != 'Default':
target_dir = os.path.join(self.skin_path, skin_dir, '720p')
skin_files = os.listdir(self.source_file_dir)
convert_file = os.path.join(self.skin_path, skin_dir, 'convert.xml')
if not os.path.exists(convert_file):
print ('convert file does not exist: %s' %convert_file)
continue
for skin_file in skin_files:
source_file = os.path.join(self.source_file_dir, skin_file)
target_file = os.path.join(target_dir, skin_file)
self.convert_skin_file(source_file, target_file, convert_file) Ví dụ 5 def convert_examples_to_features_and_output_to_files(
examples: List[str],
max_seq_length: int,
tokenizer: tx.data.GPT2Tokenizer,
output_file: str,
feature_types: Dict[str, Any],
append_eos_token: bool = True):
r"""Converts a set of examples to a `pickle` file."""
with tx.data.RecordData.writer(output_file, feature_types) as writer:
for (_, example) in enumerate(examples):
text_ids, length = tokenizer.encode_text(
text=example, max_seq_length=max_seq_length,
append_eos_token=append_eos_token)
features = {
"text_ids": text_ids,
"length": length
}
writer.write(features) Ví dụ 6 def convertSourceFiles(filenames):
"Helper function - makes minimal PDF document"
from reportlab.platypus import Paragraph, SimpleDocTemplate, Spacer, XPreformatted
from reportlab.lib.styles import getSampleStyleSheet
styT=getSampleStyleSheet()["Title"]
styC=getSampleStyleSheet()["Code"]
doc = SimpleDocTemplate("pygments2xpre.pdf")
S = [].append
for filename in filenames:
S(Paragraph(filename,style=styT))
src = open(filename, 'r').read()
fmt = pygments2xpre(src)
S(XPreformatted(fmt, style=styC))
doc.build(S.__self__)
print 'saved pygments2xpre.pdf' Ví dụ 7 def convert_examples_to_features_and_output_to_files(
examples: List[str],
max_seq_length: int,
tokenizer: tx.data.GPT2Tokenizer,
output_file: str,
feature_types: Dict[str, Any],
append_eos_token: bool = True):
r"""Converts a set of examples to a `pickle` file."""
with tx.data.RecordData.writer(output_file, feature_types) as writer:
for (_, example) in enumerate(examples):
text_ids, length = tokenizer.encode_text(
text=example, max_seq_length=max_seq_length,
append_eos_token=append_eos_token)
features = {
"text_ids": text_ids,
"length": length
}
writer.write(features) # type: ignore Ví dụ 8 def convertToMultipleFiles(fileDir, targetDir):
destDir = genDestDir(targetDir)
for _, dirnames, _ in os.walk(fileDir):
valuesDirs = [di for di in dirnames if di.startswith("values")]
for dirname in valuesDirs:
workbook = pyExcelerator.Workbook()
for _, _, filenames in os.walk(fileDir+'/'+dirname):
xmlFiles = [fi for fi in filenames if fi.endswith(".xml")]
for xmlfile in xmlFiles:
ws = workbook.add_sheet(xmlfile)
path = fileDir+'/'+dirname+'/' + xmlfile
(keys, values) = XmlFileUtil.getKeysAndValues(path)
for keyIndex in range(len(keys)):
key = keys[keyIndex]
value = values[keyIndex]
ws.write(keyIndex, 0, key)
ws.write(keyIndex, 1, value)
filePath = destDir + "/" + getCountryCode(dirname) + ".xls"
workbook.save(filePath)
print "Convert %s successfully! you can see xls file in %s" % (
fileDir, destDir) Ví dụ 9 def convertSourceFiles(filenames):
"Helper function - makes minimal PDF document"
from reportlab.platypus import Paragraph, SimpleDocTemplate, Spacer, XPreformatted
from reportlab.lib.styles import getSampleStyleSheet
styT=getSampleStyleSheet()["Title"]
styC=getSampleStyleSheet()["Code"]
doc = SimpleDocTemplate("pygments2xpre.pdf")
S = [].append
for filename in filenames:
S(Paragraph(filename,style=styT))
src = open(filename, 'r').read()
fmt = pygments2xpre(src)
S(XPreformatted(fmt, style=styC))
doc.build(S.__self__)
print('saved pygments2xpre.pdf') Ví dụ 10 def convertFiles(self):
files = [x for x in self.jsonFiles.getItems() if x[2] is True]
outPath = self.exportPath.text().strip() if not len(self.outputPath.text().strip()) else self.outputPath.text().strip()
if not os.path.exists(outPath):
os.mkdir(outPath)
parPool = mp.Pool(mp.cpu_count() - 1)
inFiles = [file[1] for file in files]
outFiles = [os.path.join(outPath, file[0] + '.obj') for file in files]
progressBar = QtGui.QProgressDialog("Converting Files...", "Cancel", 0, len(outFiles), self)
progressBar.setWindowModality(QtCore.Qt.WindowModal)
progressBar.show()
for i, _ in enumerate(parPool.imap_unordered(functools.partial(convert_to_obj.convertFile,
cooked=self.cooked.isChecked()),
zip(inFiles, outFiles))):
progressBar.setValue(i)
progressBar.setValue(len(outFiles)) Ví dụ 11 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 0Ví dụ 12 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 1Ví dụ 13 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 2Ví dụ 14 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 3Ví dụ 15 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 4Ví dụ 16 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 5Ví dụ 17 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 6Ví dụ 18 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 7Ví dụ 19 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 8Ví dụ 20 def convert_files(self, paths, source=None, target=None, lang_chain=None,
output=None, output_dir=None):
"""Convert a file by passing it through a chain of conversion functions."""
objs = []
for i, path in enumerate(paths):
# Create the context object.
context = self._create_context(path=path, source=source, target=target,
lang_chain=lang_chain,
output=output, output_dir=output_dir,
)
logger.debug("Converting `%s` from %s to %s.", op.basename(context.path),
context.source, context.target)
obj = self._convert_from_context(context.path, context,
is_path=True, do_append=i >= 1)
objs.append(obj)
return objs[0] if objs and len(objs) else objs 9Ví dụ 21 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 0Ví dụ 22 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 1Ví dụ 23 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 2Ví dụ 24 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 3Ví dụ 25 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 4Ví dụ 26 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 5Ví dụ 27 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 6Ví dụ 28 def convert_examples_to_features_and_output_to_files(
examples, label_list, max_seq_length, tokenizer, output_file):
"""Convert a set of `InputExample`s to a TFRecord file."""
writer = tf.python_io.TFRecordWriter(output_file)
for (ex_index, example) in enumerate(examples):
feature = convert_single_example(ex_index, example, label_list,
max_seq_length, tokenizer)
def create_int_feature(values):
return tf.train.Feature(
int64_list=tf.train.Int64List(value=list(values)))
features = collections.OrderedDict()
features["input_ids"] = create_int_feature(feature.input_ids)
features["input_mask"] = create_int_feature(feature.input_mask)
features["segment_ids"] = create_int_feature(feature.segment_ids)
features["label_ids"] = create_int_feature([feature.label_id])
tf_example = tf.train.Example(
features=tf.train.Features(feature=features))
writer.write(tf_example.SerializeToString()) 7
Làm thế nào để bạn thay đổi một loại tệp trong Python?Các bước để chuyển đổi tệp văn bản thành CSV bằng Python.. Bước 1: Cài đặt gói Pandas. Nếu bạn chưa làm như vậy, hãy cài đặt gói Pandas. .... Bước 2: Chụp đường dẫn nơi lưu trữ tệp văn bản của bạn. .... Bước 3: Chỉ định đường dẫn nơi tệp CSV mới sẽ được lưu. .... Bước 4: Chuyển đổi tệp văn bản thành CSV bằng Python .. Làm cách nào để chuyển đổi một tệp thành Python?Bắt đầu tập lệnh.. Lặp lại thông qua tất cả các tệp với tiện ích mở rộng đã cho - trong trường hợp của chúng tôi.PNG - và lặp lại tất cả những điều sau đây:. Mở tệp hình ảnh (dưới dạng tệp hình ảnh). Chuyển đổi tệp hình ảnh thành một định dạng khác (RGB). Cuối cùng lưu tệp - với tiện ích mở rộng mới.jpg .. Làm thế nào để bạn chuyển đổi một định dạng tệp?Đây là cách sử dụng nó:.. Chỉ trình trình duyệt của bạn để chuyển đổi trực tuyến .. Chọn loại tệp bạn muốn chuyển đổi và loại tệp bạn muốn sử dụng từ các menu thả xuống..... Bạn có hai tùy chọn để chọn tệp để chuyển đổi..... Thay đổi cài đặt tùy chọn, nếu bạn thích, sau đó nhấp vào "Chuyển đổi tệp" để bắt đầu quá trình .. Làm cách nào để chuyển đổi tệp văn bản thành Python?Python Python chuyển đổi tệp PY sang tệp TXT.. File = Open ("Text.txt", "W"). tập tin..... tập tin..... 'R' Mở để đọc (mặc định). 'W' Mở để viết, cắt ngắn tệp trước .. 'X' Mở để tạo độc quyền, không thành công nếu tệp đã tồn tại .. 'A' Mở để viết, nối vào cuối tệp nếu nó tồn tại .. |
