Datasets:
thisisanshgupta
/
Pycode

Dataset card Data Studio Files
xet
 Community
text
stringlengths
0
828
for candidate_cls in getmro(cls):
if is_backup_class(cls):
# Note that we don't keep recursing on base classes
added += self.add_class(candidate_cls, include_bases=False)
return added"
1129,"def log(self, entry, *args):
""""""Append the string supplied to the log (a list of strings). If
additional arguments are supplied, then first string is assumed to be
a format string and the other args are used for string interpolation.
For instance `backup.log(""%d + %d == %d"", 1, 1, 2)` would result in the
string `'1 + 1 == 2'` being logged""""""
if args:
entry = entry % args
self.backup_log.append(entry)"
1130,"def run_backup(self):
""""""The actual backup is performed. The data for all added classes is
extracted and written to a file per class where each line (terminated
by a line feed character) is the JSON representing a single object.
Those files are all archived in a single gzip'ed tarball which is
stored in the AWS S3 bucket specified when the current instance of
Backup was created""""""
self.log(""Starting backup at %s"", now_field())
self.log(""Backup config object created at %s"", self.timestamp)
# Make sure we're good to go
for fld in ['aws_access_key', 'aws_secret_key', 'bucketname']:
val = getattr(self, fld, None)
if not val:
self.log(""Backup cannot start: %s is a required field"", fld)
raise ValueError(self.backup_log[-1])
# Start the compressed tarball our data is stored in
backup_file = NamedTemporaryFile(suffix="".tar.gz"")
backup_tarfile = tarfile.open(fileobj=backup_file, mode='w:gz')
for cls_name, cls in self.classes.items():
self.log(""Backing up %s"", cls_name)
rec_count = 0
with NamedTemporaryFile() as record_file:
for rec in cls.find_all():
write_line(record_file, rec.to_data())
rec_count += 1
record_file.flush()
backup_tarfile.add(record_file.name, arcname=cls_name+'.json')
self.log(""%s => %d records backed up"", cls_name, rec_count)
# Finalize archive
backup_tarfile.close()
backup_file.flush()
backup_size = os.stat(backup_file.name)[6]
# Figure out key name for archived file
key_name = ('Backup_' + now_field() + '.tar.gz').replace(':', '_')
# upload archive to s3
if os.environ.get('DEBUG', False) or os.environ.get('travis', False):
# Local or CI - connect to our mock s3 service
conn = S3Connection(
'', '',
is_secure=False, port=8888, host='localhost',
calling_format=OrdinaryCallingFormat()
)
else:
conn = S3Connection(self.aws_access_key, self.aws_secret_key)
bucket = conn.get_bucket(self.bucketname)
key = Key(bucket)
key.key = key_name
self.log(
""Sending %s [size=%d bytes] with key name %s"",
backup_file.name,
backup_size,
key_name
)
# TODO: should probably look into a multi-part upload for larger backup
key.set_contents_from_filename(backup_file.name)
self.log(""Sent %s"", backup_file.name)
# All done
backup_file.close()
self.log(""Backup completed"")
# return the bucket name and key name for the completed backup
return self.bucketname, key_name"
1131,"def list_dir(sourceDir, include_source=None, include_file=True):
""""""与 :func:`os.listdir()` 类似，但提供一些筛选功能，且返回生成器对象。
:param str sourceDir: 待处理的文件夹。
:param bool include_source: 遍历结果中是否包含源文件夹的路径。
:param bool include_file: 是否包含文件。True 表示返回的内容中既包含文件，又
包含文件夹；Flase 代表仅包含文件夹。
:return: 一个生成器对象。