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dhermes/bezier | scripts/check_doc_templates.py | https://github.com/dhermes/bezier/blob/4f941f82637a8e70a5b159a9203132192e23406b/scripts/check_doc_templates.py#L229-L242 | def doc_replace(match, sphinx_docs):
"""Convert Sphinx ``:doc:`` to plain reST link.
Args:
match (_sre.SRE_Match): A match (from ``re``) to be used
in substitution.
sphinx_docs (list): List to be track the documents that have been
encountered.
Returns:
str: The ``match`` converted to a link.
"""
sphinx_docs.append(match.group("path"))
return "`{}`_".format(match.group("value")) | [
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bwohlberg/sporco | sporco/admm/ccmodmd.py | https://github.com/bwohlberg/sporco/blob/8946a04331106f4e39904fbdf2dc7351900baa04/sporco/admm/ccmodmd.py#L978-L1032 | def compute_residuals(self):
"""Compute residuals and stopping thresholds. The parent class
method is overridden to ensure that the residual calculations
include the additional variables introduced in the modification
to the baseline algorithm.
"""
# The full primary residual is straightforward to compute from
# the primary residuals for the baseline algorithm and for the
# additional variables
r0 = self.rsdl_r(self.AXnr, self.Y)
r1 = self.AX1nr - self.Y1 - self.S
r = np.sqrt(np.sum(r0**2) + np.sum(r1**2))
# The full dual residual is more complicated to compute than the
# full primary residual
ATU = self.swapaxes(self.U) + sl.irfftn(
np.conj(self.Zf) * sl.rfftn(self.U1, self.cri.Nv, self.cri.axisN),
self.cri.Nv, self.cri.axisN)
s = self.rho * np.linalg.norm(ATU)
# The normalisation factor for the full primal residual is also not
# straightforward
nAX = np.sqrt(np.linalg.norm(self.AXnr)**2 +
np.linalg.norm(self.AX1nr)**2)
nY = np.sqrt(np.linalg.norm(self.Y)**2 +
np.linalg.norm(self.Y1)**2)
rn = max(nAX, nY, np.linalg.norm(self.S))
# The normalisation factor for the full dual residual is
# straightforward to compute
sn = self.rho * np.sqrt(np.linalg.norm(self.U)**2 +
np.linalg.norm(self.U1)**2)
# Final residual values and stopping tolerances depend on
# whether standard or normalised residuals are specified via the
# options object
if self.opt['AutoRho', 'StdResiduals']:
epri = np.sqrt(self.Nc)*self.opt['AbsStopTol'] + \
rn*self.opt['RelStopTol']
edua = np.sqrt(self.Nx)*self.opt['AbsStopTol'] + \
sn*self.opt['RelStopTol']
else:
if rn == 0.0:
rn = 1.0
if sn == 0.0:
sn = 1.0
r /= rn
s /= sn
epri = np.sqrt(self.Nc)*self.opt['AbsStopTol']/rn + \
self.opt['RelStopTol']
edua = np.sqrt(self.Nx)*self.opt['AbsStopTol']/sn + \
self.opt['RelStopTol']
return r, s, epri, edua | [
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qubell/contrib-python-qubell-client | qubell/api/private/platform.py | https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/platform.py#L62-L72 | def connect_to_another_user(self, user, password, token=None, is_public=False):
"""
Authenticates user with the same tenant as current platform using and returns new platform to user.
:rtype: QubellPlatform
:param str user: user email
:param str password: user password
:param str token: session token
:param bool is_public: either to use public or private api (public is not fully supported use with caution)
:return: New Platform instance
"""
return QubellPlatform.connect(self._router.base_url, user, password, token, is_public) | [
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PedalPi/Application | application/controller/current_controller.py | https://github.com/PedalPi/Application/blob/3fdf6f97cfef97a7f1d90a5881dd04324c229f9d/application/controller/current_controller.py#L217-L247 | def set_bank(self, bank, try_preserve_index=False):
"""
Set the current :class:`Bank` for the bank
only if the ``bank != current_bank``
The current pedalboard will be the first pedalboard of the new current bank
**if it contains any pedalboard**, else will be ``None``.
.. warning::
If the current :attr:`.pedalboard` is ``None``, a :class:`.CurrentPedalboardError` is raised.
:param Bank bank: Bank that will be the current
:param bool try_preserve_index: Tries to preserve the index of the current pedalboard
when changing the bank. That is, if the current pedalboard is the fifth,
when updating the bank, it will attempt to place the fifth pedalboard
of the new bank as the current one. If it does not get
(``len(bank.pedalboards) < 6``) the current pedalboard will be the
first pedalboard.
"""
if bank not in self._manager:
raise CurrentPedalboardError('Bank {} has not added in banks manager'.format(bank))
if self.bank == bank:
return
if bank.pedalboards:
pedalboard = self._equivalent_pedalboard(bank) if try_preserve_index else bank.pedalboards[0]
self.set_pedalboard(pedalboard)
else:
self.set_pedalboard(None) | [
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HewlettPackard/python-hpOneView | hpOneView/image_streamer/resources/golden_images.py | https://github.com/HewlettPackard/python-hpOneView/blob/3c6219723ef25e6e0c83d44a89007f89bc325b89/hpOneView/image_streamer/resources/golden_images.py#L108-L121 | def download_archive(self, id_or_uri, file_path):
"""
Download the details of the Golden Image capture logs, which has been archived based on the specific attribute
ID.
Args:
id_or_uri: ID or URI of the Golden Image.
file_path (str): File name to save the archive.
Returns:
bool: Success.
"""
uri = self.URI + "/archive/" + extract_id_from_uri(id_or_uri)
return self._client.download(uri, file_path) | [
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sosy-lab/benchexec | benchexec/util.py | https://github.com/sosy-lab/benchexec/blob/44428f67f41384c03aea13e7e25f884764653617/benchexec/util.py#L174-L190 | def parse_int_list(s):
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Parse a comma-separated list of strings.
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"""
result = []
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item = item.strip().split('-')
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RonenNess/Fileter | fileter/files_iterator.py | https://github.com/RonenNess/Fileter/blob/5372221b4049d5d46a9926573b91af17681c81f3/fileter/files_iterator.py#L121-L130 | def add_filter(self, files_filter, filter_type=DefaultFilterType):
"""
Add a files filter to this iterator.
For a file to be processed, it must match ALL filters, eg they are added with ADD, not OR.
:param files_filter: filter to apply, must be an object inheriting from filters.FilterAPI.
:param filter_type: filter behavior, see FilterType for details.
"""
self.__filters.append((files_filter, filter_type))
return self | [
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Shizmob/pydle | pydle/features/rfc1459/client.py | https://github.com/Shizmob/pydle/blob/7ec7d65d097318ed0bcdc5d8401470287d8c7cf7/pydle/features/rfc1459/client.py#L974-L978 | async def on_raw_422(self, message):
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await self._registration_completed(message)
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await self.on_connect() | [
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] | python | train |
saltstack/salt | salt/modules/keystone.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/keystone.py#L867-L907 | def project_update(project_id=None, name=None, description=None,
enabled=None, profile=None, **connection_args):
'''
Update a tenant's information (keystone project-update)
The following fields may be updated: name, description, enabled.
Can only update name if targeting by ID
Overrides keystone tenant_update form api V2.
For keystone api V3 only.
.. versionadded:: 2016.11.0
project_id
The project id.
name
The project name, which must be unique within the owning domain.
description
The project description.
enabled
Enables or disables the project.
profile
Configuration profile - if configuration for multiple openstack accounts required.
CLI Examples:
.. code-block:: bash
salt '*' keystone.project_update name=admin enabled=True
salt '*' keystone.project_update c965f79c4f864eaaa9c3b41904e67082 name=admin email=admin@domain.com
'''
auth(profile, **connection_args)
if _OS_IDENTITY_API_VERSION > 2:
return tenant_update(tenant_id=project_id, name=name, description=description,
enabled=enabled, profile=profile, **connection_args)
else:
return False | [
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.. versionadded:: 2016.11.0
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.. code-block:: bash
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darkfeline/mir.anidb | mir/anidb/api.py | https://github.com/darkfeline/mir.anidb/blob/a0d25908f85fb1ff4bc595954bfc3f223f1b5acc/mir/anidb/api.py#L65-L68 | def _check_for_errors(etree: ET.ElementTree):
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davedoesdev/python-jwt | bench/generate_token_bench.py | https://github.com/davedoesdev/python-jwt/blob/5c753a26955cc666f00f6ff8e601406d95071368/bench/generate_token_bench.py#L24-L30 | def make_bench_generate_token(alg):
""" Return function which will generate token for particular algorithm """
def f(_):
""" Generate token """
privk = priv_keys[alg].get('default', priv_key)
jwt.generate_jwt(payload, privk, alg, timedelta(seconds=5))
return f | [
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adrn/gala | gala/coordinates/greatcircle.py | https://github.com/adrn/gala/blob/ea95575a0df1581bb4b0986aebd6eea8438ab7eb/gala/coordinates/greatcircle.py#L299-L322 | def sph_midpoint(coord1, coord2):
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Coordinate of one point on a great circle.
coord2 : `~astropy.coordinates.SkyCoord`
Coordinate of the other point on a great circle.
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midpt = 0.5 * (c1 + c2)
usph = midpt.represent_as(coord.UnitSphericalRepresentation)
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Coordinate of the other point on a great circle.
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blockstack/blockstack-core | blockstack/lib/nameset/db.py | https://github.com/blockstack/blockstack-core/blob/1dcfdd39b152d29ce13e736a6a1a0981401a0505/blockstack/lib/nameset/db.py#L840-L854 | def namedb_namespace_fields_check( namespace_rec ):
"""
Given a namespace record, make sure the following fields are present:
* namespace_id
* buckets
Makes the record suitable for insertion/update.
NOTE: MODIFIES namespace_rec
"""
assert namespace_rec.has_key('namespace_id'), "BUG: namespace record has no ID"
assert namespace_rec.has_key('buckets'), 'BUG: missing price buckets'
assert isinstance(namespace_rec['buckets'], str), 'BUG: namespace data is not in canonical form'
return namespace_rec | [
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Chilipp/psy-simple | psy_simple/widgets/colors.py | https://github.com/Chilipp/psy-simple/blob/7d916406a6d3c3c27c0b7102f98fef07a4da0a61/psy_simple/widgets/colors.py#L76-L83 | def headerData(self, section, orientation, role=Qt.DisplayRole):
"""Set header data"""
if role != Qt.DisplayRole:
return None
if orientation == Qt.Vertical:
return six.text_type(self.color_da.cmap[section].values)
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kislyuk/aegea | aegea/deploy.py | https://github.com/kislyuk/aegea/blob/94957e9dba036eae3052e2662c208b259c08399a/aegea/deploy.py#L138-L162 | def grant(args):
"""
Given an IAM role or instance name, attach an IAM policy granting
appropriate permissions to subscribe to deployments. Given a
GitHub repo URL, create and record deployment keys for the repo
and any of its private submodules, making the keys accessible to
the IAM role.
"""
try:
role = resources.iam.Role(args.iam_role_or_instance)
role.load()
except ClientError:
role = get_iam_role_for_instance(args.iam_role_or_instance)
role.attach_policy(PolicyArn=ensure_deploy_iam_policy().arn)
for private_repo in [args.repo] + list(private_submodules(args.repo)):
gh_owner_name, gh_repo_name = parse_repo_name(private_repo)
secret = secrets.put(argparse.Namespace(secret_name="deploy.{}.{}".format(gh_owner_name, gh_repo_name),
iam_role=role.name,
instance_profile=None,
iam_group=None,
iam_user=None,
generate_ssh_key=True))
get_repo(private_repo).create_key(__name__ + "." + role.name, secret["ssh_public_key"])
logger.info("Created deploy key %s for IAM role %s to access GitHub repo %s",
secret["ssh_key_fingerprint"], role.name, private_repo) | [
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Apstra/aeon-venos | pylib/aeon/nxos/autoload/install_os.py | https://github.com/Apstra/aeon-venos/blob/4d4f73d5904831ddc78c30922a8a226c90cf7d90/pylib/aeon/nxos/autoload/install_os.py#L56-L76 | def copy_from(self, location, timeout=10 * 60):
"""
This method will fetch the image; the fetch will happen from the
device-side using the 'copy' command. Note that the NXAPI appears to
be single-threaded, so the code needs to wait until this operation has
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value is set very high (10min)
:param location: URL to the location of the file. This URL must be a valid source
field to the NXOS 'copy' command
:keyword timeout: Timeout in seconds
:return:
"""
cmd = 'copy {location} {dir}: vrf {vrf_name}'.format(
location=location, dir=self.DESTDIR, vrf_name=self.VRF_NAME)
run = self.device.api.exec_opcmd
run(cmd, msg_type='cli_show_ascii', timeout=timeout) | [
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guaix-ucm/pyemir | emirdrp/processing/wavecal/slitlet2d.py | https://github.com/guaix-ucm/pyemir/blob/fef6bbabcb13f80123cafd1800a0f508a3c21702/emirdrp/processing/wavecal/slitlet2d.py#L316-L351 | def extract_slitlet2d(self, image_2k2k):
"""Extract slitlet 2d image from image with original EMIR dimensions.
Parameters
----------
image_2k2k : numpy array
Original image (dimensions EMIR_NAXIS1 * EMIR_NAXIS2)
Returns
-------
slitlet2d : numpy array
Image corresponding to the slitlet region defined by its
bounding box.
"""
# protections
naxis2, naxis1 = image_2k2k.shape
if naxis1 != EMIR_NAXIS1:
raise ValueError('Unexpected naxis1')
if naxis2 != EMIR_NAXIS2:
raise ValueError('Unexpected naxis2')
# extract slitlet region
slitlet2d = image_2k2k[(self.bb_ns1_orig - 1):self.bb_ns2_orig,
(self.bb_nc1_orig - 1):self.bb_nc2_orig]
# transform to float
slitlet2d = slitlet2d.astype(np.float)
# display slitlet2d with boundaries and middle spectrum trail
if abs(self.debugplot) in [21, 22]:
self.ximshow_unrectified(slitlet2d)
# return slitlet image
return slitlet2d | [
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slitlet2d : numpy array
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Erotemic/ubelt | ubelt/util_dict.py | https://github.com/Erotemic/ubelt/blob/db802f3ad8abba025db74b54f86e6892b8927325/ubelt/util_dict.py#L415-L448 | def dict_isect(*args):
"""
Constructs a dictionary that contains keys common between all inputs.
The returned values will only belong to the first dictionary.
Args:
*args : a sequence of dictionaries (or sets of keys)
Returns:
Dict | OrderedDict :
OrderedDict if the first argument is an OrderedDict, otherwise dict
Notes:
This function can be used as an alternative to `dict_subset` where any
key not in the dictionary is ignored. See the following example:
>>> dict_isect({'a': 1, 'b': 2, 'c': 3}, ['a', 'c', 'd'])
{'a': 1, 'c': 3}
Example:
>>> dict_isect({'a': 1, 'b': 1}, {'b': 2, 'c': 2})
{'b': 1}
>>> dict_isect(odict([('a', 1), ('b', 2)]), odict([('c', 3)]))
OrderedDict()
>>> dict_isect()
{}
"""
if not args:
return {}
else:
dictclass = OrderedDict if isinstance(args[0], OrderedDict) else dict
common_keys = set.intersection(*map(set, args))
first_dict = args[0]
return dictclass((k, first_dict[k]) for k in common_keys) | [
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The returned values will only belong to the first dictionary.
Args:
*args : a sequence of dictionaries (or sets of keys)
Returns:
Dict | OrderedDict :
OrderedDict if the first argument is an OrderedDict, otherwise dict
Notes:
This function can be used as an alternative to `dict_subset` where any
key not in the dictionary is ignored. See the following example:
>>> dict_isect({'a': 1, 'b': 2, 'c': 3}, ['a', 'c', 'd'])
{'a': 1, 'c': 3}
Example:
>>> dict_isect({'a': 1, 'b': 1}, {'b': 2, 'c': 2})
{'b': 1}
>>> dict_isect(odict([('a', 1), ('b', 2)]), odict([('c', 3)]))
OrderedDict()
>>> dict_isect()
{} | [
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ctuning/ck | ck/kernel.py | https://github.com/ctuning/ck/blob/7e009814e975f8742790d3106340088a46223714/ck/kernel.py#L7932-L8019 | def compare_dicts(i):
"""
Input: {
dict1 - dictionary 1
dict2 - dictionary 2
(ignore_case) - ignore case of letters
Note that if dict1 and dict2 has lists, the results will be as follows:
* dict1={"key":['a','b','c']}
dict2={"key":['a','b']}
EQUAL
* dict1={"key":['a','b']}
dict2={"key":['a','b','c']}
NOT EQUAL
}
Output: {
return - return code = 0, if successful
> 0, if error
(error) - error text if return > 0
equal - if 'yes' dictionaries are equal
}
"""
d1=i.get('dict1',{})
d2=i.get('dict2',{})
equal='yes'
bic=False
ic=i.get('ignore_case','')
if ic=='yes': bic=True
for q2 in d2:
v2=d2[q2]
if type(v2)==dict:
if q2 not in d1:
equal='no'
break
v1=d1[q2]
rx=compare_dicts({'dict1':v1,'dict2':v2, 'ignore_case':ic})
if rx['return']>0: return rx
equal=rx['equal']
if equal=='no':
break
elif type(v2)==list:
# For now can check only values in list
if q2 not in d1:
equal='no'
break
v1=d1[q2]
if type(v1)!=list:
equal='no'
break
for m in v2:
if m not in v1:
equal='no'
break
if equal=='no':
break
else:
if q2 not in d1:
equal='no'
break
if equal=='no':
break
v1=d1[q2]
if bic and type(v1)!=int and type(v1)!=float and type(v1)!=bool:
v1=v1.lower()
v2=v2.lower()
if v2!=v1:
equal='no'
break
return {'return':0, 'equal':equal} | [
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dict2 - dictionary 2
(ignore_case) - ignore case of letters
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* dict1={"key":['a','b','c']}
dict2={"key":['a','b']}
EQUAL
* dict1={"key":['a','b']}
dict2={"key":['a','b','c']}
NOT EQUAL
}
Output: {
return - return code = 0, if successful
> 0, if error
(error) - error text if return > 0
equal - if 'yes' dictionaries are equal
} | [
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] | python | train |
google/prettytensor | prettytensor/replay_queue.py | https://github.com/google/prettytensor/blob/75daa0b11252590f548da5647addc0ea610c4c45/prettytensor/replay_queue.py#L26-L39 | def _make_tuple(x):
"""TF has an obnoxious habit of being lenient with single vs tuple."""
if isinstance(x, prettytensor.PrettyTensor):
if x.is_sequence():
return tuple(x.sequence)
else:
return (x.tensor,)
elif isinstance(x, tuple):
return x
elif (isinstance(x, collections.Sequence) and
not isinstance(x, six.string_types)):
return tuple(x)
else:
return (x,) | [
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saltstack/salt | salt/daemons/__init__.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/daemons/__init__.py#L200-L240 | def parse_hostname(hostname, default_port):
'''
Parse hostname string and return a tuple of (host, port)
If port missing in hostname string then use default_port
If anything is not a valid then return None
hostname should contain a host and an option space delimited port
host port
As an attempt to prevent foolish mistakes the parser also tries to identify
the port when it is colon delimited not space delimited. As in host:port.
This is problematic since IPV6 addresses may have colons in them.
Consequently the use of colon delimited ports is strongly discouraged.
An ipv6 address must have at least 2 colons.
'''
try:
host, sep, port = hostname.strip().rpartition(' ')
if not port: # invalid nothing there
return None
if not host: # no space separated port, only host as port use default port
host = port
port = default_port
# ipv6 must have two or more colons
if host.count(':') == 1: # only one so may be using colon delimited port
host, sep, port = host.rpartition(':')
if not host: # colon but not host so invalid
return None
if not port: # colon but no port so use default
port = default_port
host = host.strip()
try:
port = int(port)
except ValueError:
return None
except AttributeError:
return None
return (host, port) | [
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As an attempt to prevent foolish mistakes the parser also tries to identify
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Consequently the use of colon delimited ports is strongly discouraged.
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GoogleCloudPlatform/google-cloud-datastore | python/googledatastore/helper.py | https://github.com/GoogleCloudPlatform/google-cloud-datastore/blob/a23940d0634d7f537faf01ad9e60598046bcb40a/python/googledatastore/helper.py#L422-L432 | def micros_to_timestamp(micros, timestamp):
"""Convert microseconds from utc epoch to google.protobuf.timestamp.
Args:
micros: a long, number of microseconds since utc epoch.
timestamp: a google.protobuf.timestamp.Timestamp to populate.
"""
seconds = long(micros / _MICROS_PER_SECOND)
micro_remainder = micros % _MICROS_PER_SECOND
timestamp.seconds = seconds
timestamp.nanos = micro_remainder * _NANOS_PER_MICRO | [
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hyperledger/indy-crypto | wrappers/python/indy_crypto/bls.py | https://github.com/hyperledger/indy-crypto/blob/1675e29a2a5949b44899553d3d128335cf7a61b3/wrappers/python/indy_crypto/bls.py#L229-L250 | def sign(message: bytes, sign_key: SignKey) -> Signature:
"""
Signs the message and returns signature.
:param: message - Message to sign
:param: sign_key - Sign key
:return: Signature
"""
logger = logging.getLogger(__name__)
logger.debug("Bls::sign: >>> message: %r, sign_key: %r", message, sign_key)
c_instance = c_void_p()
do_call('indy_crypto_bls_sign',
message, len(message),
sign_key.c_instance,
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res = Signature(c_instance)
logger.debug("Bls::sign: <<< res: %r", res)
return res | [
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googleapis/google-auth-library-python | google/auth/compute_engine/_metadata.py | https://github.com/googleapis/google-auth-library-python/blob/2c6ad78917e936f38f87c946209c8031166dc96e/google/auth/compute_engine/_metadata.py#L92-L140 | def get(request, path, root=_METADATA_ROOT, recursive=False):
"""Fetch a resource from the metadata server.
Args:
request (google.auth.transport.Request): A callable used to make
HTTP requests.
path (str): The resource to retrieve. For example,
``'instance/service-accounts/default'``.
root (str): The full path to the metadata server root.
recursive (bool): Whether to do a recursive query of metadata. See
https://cloud.google.com/compute/docs/metadata#aggcontents for more
details.
Returns:
Union[Mapping, str]: If the metadata server returns JSON, a mapping of
the decoded JSON is return. Otherwise, the response content is
returned as a string.
Raises:
google.auth.exceptions.TransportError: if an error occurred while
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"""
base_url = urlparse.urljoin(root, path)
query_params = {}
if recursive:
query_params['recursive'] = 'true'
url = _helpers.update_query(base_url, query_params)
response = request(url=url, method='GET', headers=_METADATA_HEADERS)
if response.status == http_client.OK:
content = _helpers.from_bytes(response.data)
if response.headers['content-type'] == 'application/json':
try:
return json.loads(content)
except ValueError as caught_exc:
new_exc = exceptions.TransportError(
'Received invalid JSON from the Google Compute Engine'
'metadata service: {:.20}'.format(content))
six.raise_from(new_exc, caught_exc)
else:
return content
else:
raise exceptions.TransportError(
'Failed to retrieve {} from the Google Compute Engine'
'metadata service. Status: {} Response:\n{}'.format(
url, response.status, response.data), response) | [
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Returns:
Union[Mapping, str]: If the metadata server returns JSON, a mapping of
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Raises:
google.auth.exceptions.TransportError: if an error occurred while
retrieving metadata. | [
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] | python | train |
saltstack/salt | salt/utils/virt.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/virt.py#L32-L64 | def accept(self, pub):
'''
Accept the provided key
'''
try:
with salt.utils.files.fopen(self.path, 'r') as fp_:
expiry = int(fp_.read())
except (OSError, IOError):
log.error(
'Request to sign key for minion \'%s\' on hyper \'%s\' '
'denied: no authorization', self.id, self.hyper
)
return False
except ValueError:
log.error('Invalid expiry data in %s', self.path)
return False
# Limit acceptance window to 10 minutes
# TODO: Move this value to the master config file
if (time.time() - expiry) > 600:
log.warning(
'Request to sign key for minion "%s" on hyper "%s" denied: '
'authorization expired', self.id, self.hyper
)
return False
pubfn = os.path.join(self.opts['pki_dir'],
'minions',
self.id)
with salt.utils.files.fopen(pubfn, 'w+') as fp_:
fp_.write(pub)
self.void()
return True | [
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albertz/py_better_exchook | better_exchook.py | https://github.com/albertz/py_better_exchook/blob/3d524a027d7fc4e83e47e39a1978849561da69b3/better_exchook.py#L736-L743 | def hide_button_span(self, mode, file=sys.stdout):
"""
:param int mode: 1 or 2
:param io.TextIOBase|io.StringIO file:
"""
file.write("\033[83;%iu" % mode)
yield
file.write("\033[83;0u") | [
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jobovy/galpy | galpy/df/evolveddiskdf.py | https://github.com/jobovy/galpy/blob/9c5b9fe65d58835624dffe432be282060918ee08/galpy/df/evolveddiskdf.py#L339-L482 | def vmomentsurfacemass(self,R,n,m,t=0.,nsigma=None,deg=False,
epsrel=1.e-02,epsabs=1.e-05,phi=0.,
grid=None,gridpoints=101,returnGrid=False,
hierarchgrid=False,nlevels=2,
print_progress=False,
integrate_method='dopr54_c',
deriv=None):
"""
NAME:
vmomentsurfacemass
PURPOSE:
calculate the an arbitrary moment of the velocity distribution at (R,phi) times the surfacmass
INPUT:
R - radius at which to calculate the moment (in natural units)
phi= azimuth (rad unless deg=True)
n - vR^n
m - vT^m
t= time at which to evaluate the DF (can be a list or ndarray; if this is the case, list needs to be in descending order and equally spaced)
nsigma - number of sigma to integrate the velocities over (based on an estimate, so be generous, but not too generous)
deg= azimuth is in degree (default=False)
epsrel, epsabs - scipy.integrate keywords (the integration calculates the ratio of this vmoment to that of the initial DF)
grid= if set to True, build a grid and use that to evaluate integrals; if set to a grid-objects (such as returned by this procedure), use this grid; if this was created for a list of times, moments are calculated for each time
gridpoints= number of points to use for the grid in 1D (default=101)
returnGrid= if True, return the grid object (default=False)
hierarchgrid= if True, use a hierarchical grid (default=False)
nlevels= number of hierarchical levels for the hierarchical grid
print_progress= if True, print progress updates
integrate_method= orbit.integrate method argument
deriv= None, 'R', or 'phi': calculates derivative of the moment wrt R or phi **onnly with grid options**
OUTPUT:
<vR^n vT^m x surface-mass> at R,phi (no support for units)
COMMENT:
grid-based calculation is the only one that is heavily tested (although the test suite also tests the direct calculation)
HISTORY:
2011-03-30 - Written - Bovy (NYU)
"""
#if we have already precalculated a grid, use that
if not grid is None and isinstance(grid,evolveddiskdfGrid):
if returnGrid:
return (self._vmomentsurfacemassGrid(n,m,grid),grid)
else:
return self._vmomentsurfacemassGrid(n,m,grid)
elif not grid is None \
and isinstance(grid,evolveddiskdfHierarchicalGrid):
if returnGrid:
return (self._vmomentsurfacemassHierarchicalGrid(n,m,grid),
grid)
else:
return self._vmomentsurfacemassHierarchicalGrid(n,m,grid)
#Otherwise we need to do some more work
if deg: az= phi*_DEGTORAD
else: az= phi
if nsigma is None: nsigma= _NSIGMA
if _PROFILE: #pragma: no cover
start= time_module.time()
if hasattr(self._initdf,'_estimatemeanvR') \
and hasattr(self._initdf,'_estimatemeanvT') \
and hasattr(self._initdf,'_estimateSigmaR2') \
and hasattr(self._initdf,'_estimateSigmaT2'):
sigmaR1= nu.sqrt(self._initdf._estimateSigmaR2(R,phi=az))
sigmaT1= nu.sqrt(self._initdf._estimateSigmaT2(R,phi=az))
meanvR= self._initdf._estimatemeanvR(R,phi=az)
meanvT= self._initdf._estimatemeanvT(R,phi=az)
else:
warnings.warn("No '_estimateSigmaR2' etc. functions found for initdf in evolveddf; thus using potentially slow sigmaR2 etc functions",
galpyWarning)
sigmaR1= nu.sqrt(self._initdf.sigmaR2(R,phi=az,use_physical=False))
sigmaT1= nu.sqrt(self._initdf.sigmaT2(R,phi=az,use_physical=False))
meanvR= self._initdf.meanvR(R,phi=az,use_physical=False)
meanvT= self._initdf.meanvT(R,phi=az,use_physical=False)
if _PROFILE: #pragma: no cover
setup_time= (time_module.time()-start)
if not grid is None and isinstance(grid,bool) and grid:
if not hierarchgrid:
if _PROFILE: #pragma: no cover
start= time_module.time()
grido= self._buildvgrid(R,az,nsigma,t,
sigmaR1,sigmaT1,meanvR,meanvT,
gridpoints,print_progress,
integrate_method,deriv)
if _PROFILE: #pragma: no cover
grid_time= (time_module.time()-start)
print(setup_time/(setup_time+grid_time), \
grid_time/(setup_time+grid_time), \
setup_time+grid_time)
if returnGrid:
return (self._vmomentsurfacemassGrid(n,m,grido),grido)
else:
return self._vmomentsurfacemassGrid(n,m,grido)
else: #hierarchical grid
grido= evolveddiskdfHierarchicalGrid(self,R,az,nsigma,t,
sigmaR1,sigmaT1,meanvR,
meanvT,
gridpoints,nlevels,deriv,
print_progress=print_progress)
if returnGrid:
return (self._vmomentsurfacemassHierarchicalGrid(n,m,
grido),
grido)
else:
return self._vmomentsurfacemassHierarchicalGrid(n,m,grido)
#Calculate the initdf moment and then calculate the ratio
initvmoment= self._initdf.vmomentsurfacemass(R,n,m,nsigma=nsigma,
phi=phi)
if initvmoment == 0.: initvmoment= 1.
norm= sigmaR1**(n+1)*sigmaT1**(m+1)*initvmoment
if isinstance(t,(list,nu.ndarray)):
raise IOError("list of times is only supported with grid-based calculation")
return dblquad(_vmomentsurfaceIntegrand,
meanvT/sigmaT1-nsigma,
meanvT/sigmaT1+nsigma,
lambda x: meanvR/sigmaR1
-nu.sqrt(nsigma**2.-(x-meanvT/sigmaT1)**2.),
lambda x: meanvR/sigmaR1
+nu.sqrt(nsigma**2.-(x-meanvT/sigmaT1)**2.),
(R,az,self,n,m,sigmaR1,sigmaT1,t,initvmoment),
epsrel=epsrel,epsabs=epsabs)[0]*norm | [
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] | NAME:
vmomentsurfacemass
PURPOSE:
calculate the an arbitrary moment of the velocity distribution at (R,phi) times the surfacmass
INPUT:
R - radius at which to calculate the moment (in natural units)
phi= azimuth (rad unless deg=True)
n - vR^n
m - vT^m
t= time at which to evaluate the DF (can be a list or ndarray; if this is the case, list needs to be in descending order and equally spaced)
nsigma - number of sigma to integrate the velocities over (based on an estimate, so be generous, but not too generous)
deg= azimuth is in degree (default=False)
epsrel, epsabs - scipy.integrate keywords (the integration calculates the ratio of this vmoment to that of the initial DF)
grid= if set to True, build a grid and use that to evaluate integrals; if set to a grid-objects (such as returned by this procedure), use this grid; if this was created for a list of times, moments are calculated for each time
gridpoints= number of points to use for the grid in 1D (default=101)
returnGrid= if True, return the grid object (default=False)
hierarchgrid= if True, use a hierarchical grid (default=False)
nlevels= number of hierarchical levels for the hierarchical grid
print_progress= if True, print progress updates
integrate_method= orbit.integrate method argument
deriv= None, 'R', or 'phi': calculates derivative of the moment wrt R or phi **onnly with grid options**
OUTPUT:
<vR^n vT^m x surface-mass> at R,phi (no support for units)
COMMENT:
grid-based calculation is the only one that is heavily tested (although the test suite also tests the direct calculation)
HISTORY:
2011-03-30 - Written - Bovy (NYU) | [
"NAME",
":"
] | python | train |
saltstack/salt | salt/modules/pagerduty_util.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/pagerduty_util.py#L371-L407 | def resource_absent(resource, identifier_fields, profile='pagerduty', subdomain=None, api_key=None, **kwargs):
'''
Generic resource.absent state method. Pagerduty state modules should be a thin wrapper over this method,
with a custom diff function.
This method calls delete_resource() and formats the result as a salt state return value.
example:
resource_absent("users", ["id","name","email"])
'''
ret = {'name': kwargs['name'],
'changes': {},
'result': None,
'comment': ''}
for k, v in kwargs.items():
if k not in identifier_fields:
continue
result = delete_resource(resource,
v,
identifier_fields,
profile=profile,
subdomain=subdomain,
api_key=api_key)
if result is None:
ret['result'] = True
ret['comment'] = '{0} deleted'.format(v)
return ret
elif result is True:
continue
elif __opts__['test']:
ret['comment'] = result
return ret
elif 'error' in result:
ret['result'] = False
ret['comment'] = result
return ret
return ret | [
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JdeRobot/base | src/drivers/MAVLinkServer/MAVProxy/pymavlink/mavwp.py | https://github.com/JdeRobot/base/blob/303b18992785b2fe802212f2d758a60873007f1f/src/drivers/MAVLinkServer/MAVProxy/pymavlink/mavwp.py#L599-L604 | def polygon(self):
'''return a polygon for the fence'''
points = []
for fp in self.points[1:]:
points.append((fp.lat, fp.lng))
return points | [
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DarkEnergySurvey/ugali | ugali/scratch/simulation/survey_selection_function.py | https://github.com/DarkEnergySurvey/ugali/blob/21e890b4117fc810afb6fb058e8055d564f03382/ugali/scratch/simulation/survey_selection_function.py#L425-L449 | def predict(self, lon, lat, **kwargs):
"""
distance, abs_mag, r_physical
"""
assert self.classifier is not None, 'ERROR'
pred = np.zeros(len(lon))
cut_geometry, flags_geometry = self.applyGeometry(lon, lat)
x_test = []
for key, operation in self.config['operation']['params_intrinsic']:
assert operation.lower() in ['linear', 'log'], 'ERROR'
if operation.lower() == 'linear':
x_test.append(kwargs[key])
else:
x_test.append(np.log10(kwargs[key]))
x_test = np.vstack(x_test).T
#import pdb; pdb.set_trace()
pred[cut_geometry] = self.classifier.predict_proba(x_test[cut_geometry])[:,1]
self.validatePredict(pred, flags_geometry, lon, lat, kwargs['r_physical'], kwargs['abs_mag'], kwargs['distance'])
return pred, flags_geometry | [
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"r_physical"
] | python | train |
wavefrontHQ/python-client | wavefront_api_client/api/search_api.py | https://github.com/wavefrontHQ/python-client/blob/b0f1046a8f68c2c7d69e395f7167241f224c738a/wavefront_api_client/api/search_api.py#L4431-L4451 | def search_user_entities(self, **kwargs): # noqa: E501
"""Search over a customer's users # noqa: E501
# noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.search_user_entities(async_req=True)
>>> result = thread.get()
:param async_req bool
:param SortableSearchRequest body:
:return: ResponseContainerPagedCustomerFacingUserObject
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.search_user_entities_with_http_info(**kwargs) # noqa: E501
else:
(data) = self.search_user_entities_with_http_info(**kwargs) # noqa: E501
return data | [
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# noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.search_user_entities(async_req=True)
>>> result = thread.get()
:param async_req bool
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raiden-network/raiden | raiden/network/rpc/client.py | https://github.com/raiden-network/raiden/blob/407ba15c72074e9de88771d6b9661ff4dc36bef5/raiden/network/rpc/client.py#L145-L151 | def parity_discover_next_available_nonce(
web3: Web3,
address: AddressHex,
) -> Nonce:
"""Returns the next available nonce for `address`."""
next_nonce_encoded = web3.manager.request_blocking('parity_nextNonce', [address])
return Nonce(int(next_nonce_encoded, 16)) | [
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mikicz/arca | arca/backend/vagrant.py | https://github.com/mikicz/arca/blob/e67fdc00be473ecf8ec16d024e1a3f2c47ca882c/arca/backend/vagrant.py#L87-L106 | def validate_configuration(self):
""" Runs :meth:`arca.DockerBackend.validate_configuration` and checks extra:
* ``box`` format
* ``provider`` format
* ``use_registry_name`` is set and ``registry_pull_only`` is not enabled.
"""
super().validate_configuration()
if self.use_registry_name is None:
raise ArcaMisconfigured("Use registry name setting is required for VagrantBackend")
if not re.match(r"^[a-z]+/[a-zA-Z0-9\-_]+$", self.box):
raise ArcaMisconfigured("Provided Vagrant box is not valid")
if not re.match(r"^[a-z_]+$", self.provider):
raise ArcaMisconfigured("Provided Vagrant provider is not valid")
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adeel/timed | timed/client.py | https://github.com/adeel/timed/blob/9f85e004de491cd4863d31b09991a1e2591b1b66/timed/client.py#L52-L63 | def start(project, logfile, time_format):
"start tracking for <project>"
records = read(logfile, time_format)
if records and not records[-1][1][1]:
print "error: there is a project already active"
return
write(server.start(project, records), logfile, time_format)
print "starting work on %s" % colored(project, attrs=['bold'])
print " at %s" % colored(server.date_to_txt(now(), time_format), 'green') | [
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gwastro/pycbc-glue | pycbc_glue/pipeline.py | https://github.com/gwastro/pycbc-glue/blob/a3e906bae59fbfd707c3ff82e5d008d939ec5e24/pycbc_glue/pipeline.py#L3440-L3469 | def invert(self):
"""
Inverts the ScienceSegments in the class (i.e. set NOT). Returns the
number of ScienceSegments after inversion.
"""
# check for an empty list
if len(self) == 0:
# return a segment representing all time
self.__sci_segs = ScienceSegment(tuple([0,0,1999999999,1999999999]))
# go through the list checking for validity as we go
outlist = []
ostart = 0
for seg in self:
start = seg.start()
stop = seg.end()
if start < 0 or stop < start or start < ostart:
raise SegmentError, "Invalid list"
if start > 0:
x = ScienceSegment(tuple([0,ostart,start,start-ostart]))
outlist.append(x)
ostart = stop
if ostart < 1999999999:
x = ScienceSegment(tuple([0,ostart,1999999999,1999999999-ostart]))
outlist.append(x)
self.__sci_segs = outlist
return len(self) | [
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Feneric/doxypypy | doxypypy/doxypypy.py | https://github.com/Feneric/doxypypy/blob/a8555b15fa2a758ea8392372de31c0f635cc0d93/doxypypy/doxypypy.py#L616-L656 | def visit_Assign(self, node, **kwargs):
"""
Handles assignments within code.
Variable assignments in Python are used to represent interface
attributes in addition to basic variables. If an assignment appears
to be an attribute, it gets labeled as such for Doxygen. If a variable
name uses Python mangling or is just a bed lump, it is labeled as
private for Doxygen.
"""
lineNum = node.lineno - 1
# Assignments have one Doxygen-significant special case:
# interface attributes.
match = AstWalker.__attributeRE.match(self.lines[lineNum])
if match:
self.lines[lineNum] = '{0}## @property {1}{2}{0}# {3}{2}' \
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match.group(1),
match.group(2),
linesep,
match.group(3),
self.lines[lineNum].rstrip()
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if self.options.debug:
stderr.write("# Attribute {0.id}{1}".format(node.targets[0],
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if isinstance(node.targets[0], Name):
match = AstWalker.__indentRE.match(self.lines[lineNum])
indentStr = match and match.group(1) or ''
restrictionLevel = self._checkMemberName(node.targets[0].id)
if restrictionLevel:
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restrictionLevel,
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# Visit any contained nodes.
self.generic_visit(node, containingNodes=kwargs['containingNodes']) | [
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spyder-ide/conda-manager | conda_manager/api/conda_api.py | https://github.com/spyder-ide/conda-manager/blob/89a2126cbecefc92185cf979347ccac1c5ee5d9d/conda_manager/api/conda_api.py#L603-L621 | def update(self, *pkgs, **kwargs):
"""Update package(s) (in an environment) by name."""
cmd_list = ['update', '--json', '--yes']
if not pkgs and not kwargs.get('all'):
raise TypeError("Must specify at least one package to update, or "
"all=True.")
cmd_list.extend(
self._setup_install_commands_from_kwargs(
kwargs,
('dry_run', 'no_deps', 'override_channels',
'no_pin', 'force', 'all', 'use_index_cache', 'use_local',
'alt_hint')))
cmd_list.extend(pkgs)
return self._call_and_parse(cmd_list, abspath=kwargs.get('abspath',
True)) | [
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elastic/apm-agent-python | elasticapm/processors.py | https://github.com/elastic/apm-agent-python/blob/2975663d7bd22282dc39336b2c37b37c12c7a774/elasticapm/processors.py#L174-L187 | def sanitize_http_wsgi_env(client, event):
"""
Sanitizes WSGI environment variables
:param client: an ElasticAPM client
:param event: a transaction or error event
:return: The modified event
"""
try:
env = event["context"]["request"]["env"]
event["context"]["request"]["env"] = varmap(_sanitize, env)
except (KeyError, TypeError):
pass
return event | [
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rigetti/pyquil | pyquil/pyqvm.py | https://github.com/rigetti/pyquil/blob/ec98e453084b0037d69d8c3245f6822a5422593d/pyquil/pyqvm.py#L502-L526 | def execute(self, program: Program):
"""
Execute a program on the QVM.
Note that the QAM is stateful. Subsequent calls to :py:func:`execute` will not
automatically reset the wavefunction or the classical RAM. If this is desired,
consider starting your program with ``RESET``.
:return: ``self`` to support method chaining.
"""
# TODO: why are DEFGATEs not just included in the list of instructions?
for dg in program.defined_gates:
if dg.parameters is not None:
raise NotImplementedError("PyQVM does not support parameterized DEFGATEs")
self.defined_gates[dg.name] = dg.matrix
# initialize program counter
self.program = program
self.program_counter = 0
halted = len(program) == 0
while not halted:
halted = self.transition()
return self | [
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googledatalab/pydatalab | datalab/bigquery/_api.py | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/datalab/bigquery/_api.py#L465-L477 | def table_delete(self, table_name):
"""Issues a request to delete a table.
Args:
table_name: the name of the table as a tuple of components.
Returns:
A parsed result object.
Raises:
Exception if there is an error performing the operation.
"""
url = Api._ENDPOINT + (Api._TABLES_PATH % table_name)
return datalab.utils.Http.request(url, method='DELETE', credentials=self._credentials,
raw_response=True) | [
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pkkid/python-plexapi | plexapi/library.py | https://github.com/pkkid/python-plexapi/blob/9efbde96441c2bfbf410eacfb46e811e108e8bbc/plexapi/library.py#L868-L870 | def searchAlbums(self, title, **kwargs):
""" Search for an album. See :func:`~plexapi.library.LibrarySection.search()` for usage. """
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widdowquinn/pyani | pyani/anim.py | https://github.com/widdowquinn/pyani/blob/2b24ec971401e04024bba896e4011984fe3f53f0/pyani/anim.py#L101-L143 | def construct_nucmer_cmdline(
fname1,
fname2,
outdir=".",
nucmer_exe=pyani_config.NUCMER_DEFAULT,
filter_exe=pyani_config.FILTER_DEFAULT,
maxmatch=False,
):
"""Returns a tuple of NUCmer and delta-filter commands
The split into a tuple was made necessary by changes to SGE/OGE. The
delta-filter command must now be run as a dependency of the NUCmer
command, and be wrapped in a Python script to capture STDOUT.
NOTE: This command-line writes output data to a subdirectory of the passed
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- fname1 - query FASTA filepath
- fname2 - subject FASTA filepath
- outdir - path to output directory
- maxmatch - Boolean flag indicating whether to use NUCmer's -maxmatch
option. If not, the -mum option is used instead
"""
outsubdir = os.path.join(outdir, pyani_config.ALIGNDIR["ANIm"])
outprefix = os.path.join(
outsubdir,
"%s_vs_%s"
% (
os.path.splitext(os.path.split(fname1)[-1])[0],
os.path.splitext(os.path.split(fname2)[-1])[0],
),
)
if maxmatch:
mode = "--maxmatch"
else:
mode = "--mum"
nucmercmd = "{0} {1} -p {2} {3} {4}".format(
nucmer_exe, mode, outprefix, fname1, fname2
)
filtercmd = "delta_filter_wrapper.py " + "{0} -1 {1} {2}".format(
filter_exe, outprefix + ".delta", outprefix + ".filter"
)
return (nucmercmd, filtercmd) | [
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django-danceschool/django-danceschool | danceschool/core/constants.py | https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/constants.py#L15-L29 | def getConstant(name):
'''
This is a convenience function that makes it easy to access the value of a preference/constant
without needing to check if the django_dynamic_preferences app has been set up and without
needing to load from that model directly.
'''
# We instantiate a manager for our global preferences
if 'dynamic_preferences_globalpreferencemodel' in connection.introspection.table_names() and not isPreliminaryRun():
params = global_preferences_registry.manager()
try:
return params.get(name)
except NotFoundInRegistry as e:
logger.error('Error in getting constant: %s' % e)
return None | [
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v1k45/python-qBittorrent | qbittorrent/client.py | https://github.com/v1k45/python-qBittorrent/blob/04f9482a022dcc78c56b0b9acb9ca455f855ae24/qbittorrent/client.py#L309-L330 | def download_from_file(self, file_buffer, **kwargs):
"""
Download torrent using a file.
:param file_buffer: Single file() buffer or list of.
:param save_path: Path to download the torrent.
:param label: Label of the torrent(s).
:return: Empty JSON data.
"""
if isinstance(file_buffer, list):
torrent_files = {}
for i, f in enumerate(file_buffer):
torrent_files.update({'torrents%s' % i: f})
else:
torrent_files = {'torrents': file_buffer}
data = kwargs.copy()
if data.get('save_path'):
data.update({'savepath': data['save_path']})
return self._post('command/upload', data=data, files=torrent_files) | [
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michaeljohnbarr/django-timezone-utils | timezone_utils/fields.py | https://github.com/michaeljohnbarr/django-timezone-utils/blob/61c8b50c59049cb7eccd4e3892f332f88b890f00/timezone_utils/fields.py#L349-L364 | def _get_time_override(self):
"""
Retrieves the datetime.time or None from the `time_override` attribute.
"""
if callable(self.time_override):
time_override = self.time_override()
else:
time_override = self.time_override
if not isinstance(time_override, datetime_time):
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bitesofcode/projexui | projexui/widgets/xchartwidget/xchartwidgetitem.py | https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xchartwidget/xchartwidgetitem.py#L225-L234 | def keyColor( self, key ):
"""
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:return <QColor>
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self._keyColors.setdefault(nativestring(key), self.color())
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inveniosoftware/invenio-files-rest | invenio_files_rest/tasks.py | https://github.com/inveniosoftware/invenio-files-rest/blob/59a950da61cc8d5882a03c6fde6db2e2ed10befd/invenio_files_rest/tasks.py#L256-L267 | def remove_expired_multipartobjects():
"""Remove expired multipart objects."""
delta = current_app.config['FILES_REST_MULTIPART_EXPIRES']
expired_dt = datetime.utcnow() - delta
file_ids = []
for mp in MultipartObject.query_expired(expired_dt):
file_ids.append(str(mp.file_id))
mp.delete()
for fid in file_ids:
remove_file_data.delay(fid) | [
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opencobra/cobrapy | cobra/flux_analysis/gapfilling.py | https://github.com/opencobra/cobrapy/blob/9d1987cdb3a395cf4125a3439c3b002ff2be2009/cobra/flux_analysis/gapfilling.py#L164-L200 | def add_switches_and_objective(self):
""" Update gapfilling model with switches and the indicator objective.
"""
constraints = list()
big_m = max(max(abs(b) for b in r.bounds)
for r in self.model.reactions)
prob = self.model.problem
for rxn in self.model.reactions:
if not hasattr(rxn, 'gapfilling_type'):
continue
indicator = prob.Variable(
name='indicator_{}'.format(rxn.id), lb=0, ub=1, type='binary')
if rxn.id in self.penalties:
indicator.cost = self.penalties[rxn.id]
else:
indicator.cost = self.penalties[rxn.gapfilling_type]
indicator.rxn_id = rxn.id
self.indicators.append(indicator)
# if z = 1 v_i is allowed non-zero
# v_i - Mz <= 0 and v_i + Mz >= 0
constraint_lb = prob.Constraint(
rxn.flux_expression - big_m * indicator, ub=0,
name='constraint_lb_{}'.format(rxn.id), sloppy=True)
constraint_ub = prob.Constraint(
rxn.flux_expression + big_m * indicator, lb=0,
name='constraint_ub_{}'.format(rxn.id), sloppy=True)
constraints.extend([constraint_lb, constraint_ub])
self.model.add_cons_vars(self.indicators)
self.model.add_cons_vars(constraints, sloppy=True)
self.model.objective = prob.Objective(
Zero, direction='min', sloppy=True)
self.model.objective.set_linear_coefficients({
i: 1 for i in self.indicators})
self.update_costs() | [
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alerta/python-alerta-client | alertaclient/commands/cmd_heartbeat.py | https://github.com/alerta/python-alerta-client/blob/7eb367b5fe87d5fc20b54dea8cddd7f09e251afa/alertaclient/commands/cmd_heartbeat.py#L17-L28 | def cli(obj, origin, tags, timeout, customer, delete):
"""Send or delete a heartbeat."""
client = obj['client']
if delete:
client.delete_heartbeat(delete)
else:
try:
heartbeat = client.heartbeat(origin=origin, tags=tags, timeout=timeout, customer=customer)
except Exception as e:
click.echo('ERROR: {}'.format(e))
sys.exit(1)
click.echo(heartbeat.id) | [
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slightlynybbled/tk_tools | tk_tools/groups.py | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/groups.py#L71-L83 | def remove_row(self, row_number: int=-1):
"""
Removes a specified row of data
:param row_number: the row to remove (defaults to the last row)
:return: None
"""
if len(self._rows) == 0:
return
row = self._rows.pop(row_number)
for widget in row:
widget.destroy() | [
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aparsons/threadfix_api | threadfix_api/threadfix.py | https://github.com/aparsons/threadfix_api/blob/76fd1bd26e9ac863636112cd30d733543807ff7d/threadfix_api/threadfix.py#L263-L332 | def get_vulnerabilities(self, teams=None, applications=None, channel_types=None, start_date=None, end_date=None,
generic_severities=None, generic_vulnerabilities=None, number_merged=None,
number_vulnerabilities=None, parameter=None, path=None, show_open=None, show_closed=None,
show_defect_open=None, show_defect_closed=None, show_defect_present=None,
show_defect_not_present=None, show_false_positive=None, show_hidden=None):
"""
Returns filtered list of vulnerabilities.
:param teams: List of team ids.
:param applications: List of application ids.
:param channel_types: List of scanner names.
:param start_date: Lower bound on scan dates.
:param end_date: Upper bound on scan dates.
:param generic_severities: List of generic severity values.
:param generic_vulnerabilities: List of generic vulnerability ids.
:param number_merged: Number of vulnerabilities merged from different scans.
:param number_vulnerabilities: Number of vulnerabilities to return.
:param parameter: Application input that the vulnerability affects.
:param path: Path to the web page where the vulnerability was found.
:param show_open: Flag to show all open vulnerabilities.
:param show_closed: Flag to show all closed vulnerabilities.
:param show_defect_open: Flag to show any vulnerabilities with open defects.
:param show_defect_closed: Flag to show any vulnerabilities with closed defects.
:param show_defect_present: Flag to show any vulnerabilities with a defect.
:param show_defect_not_present: Flag to show any vulnerabilities without a defect.
:param show_false_positive: Flag to show any false positives from vulnerabilities.
:param show_hidden: Flag to show all hidden vulnerabilities.
"""
params = {}
# Build parameter list
if teams:
params.update(self._build_list_params('teams', 'id', teams))
if applications:
params.update(self._build_list_params('applications', 'id', applications))
if channel_types:
params.update(self._build_list_params('channelTypes', 'name', channel_types))
if start_date:
params['startDate'] = start_date
if end_date:
params['endDate'] = end_date
if generic_severities:
params.update(self._build_list_params('genericSeverities', 'intValue', generic_severities))
if generic_vulnerabilities:
params.update(self._build_list_params('genericVulnerabilities', 'id', generic_vulnerabilities))
if number_merged:
params['numberMerged'] = number_merged
if number_vulnerabilities:
params['numberVulnerabilities'] = number_vulnerabilities
if parameter:
params['parameter'] = parameter
if path:
params['path'] = path
if show_open:
params['showOpen'] = show_open
if show_closed:
params['showClosed'] = show_closed
if show_defect_open:
params['showDefectOpen'] = show_defect_open
if show_defect_closed:
params['showDefectClosed'] = show_defect_closed
if show_defect_present:
params['showDefectPresent'] = show_defect_present
if show_defect_not_present:
params['showDefectNotPresent'] = show_defect_not_present
if show_false_positive:
params['showFalsePositive'] = show_false_positive
if show_hidden:
params['showHidden'] = show_hidden
return self._request('POST', 'rest/vulnerabilities', params) | [
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tk0miya/tk.phpautodoc | src/phply/phpparse.py | https://github.com/tk0miya/tk.phpautodoc/blob/cf789f64abaf76351485cee231a075227e665fb6/src/phply/phpparse.py#L1126-L1128 | def p_expr_require_once(p):
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apache/spark | python/pyspark/sql/streaming.py | https://github.com/apache/spark/blob/618d6bff71073c8c93501ab7392c3cc579730f0b/python/pyspark/sql/streaming.py#L546-L572 | def text(self, path, wholetext=False, lineSep=None):
"""
Loads a text file stream and returns a :class:`DataFrame` whose schema starts with a
string column named "value", and followed by partitioned columns if there
are any.
The text files must be encoded as UTF-8.
By default, each line in the text file is a new row in the resulting DataFrame.
.. note:: Evolving.
:param paths: string, or list of strings, for input path(s).
:param wholetext: if true, read each file from input path(s) as a single row.
:param lineSep: defines the line separator that should be used for parsing. If None is
set, it covers all ``\\r``, ``\\r\\n`` and ``\\n``.
>>> text_sdf = spark.readStream.text(tempfile.mkdtemp())
>>> text_sdf.isStreaming
True
>>> "value" in str(text_sdf.schema)
True
"""
self._set_opts(wholetext=wholetext, lineSep=lineSep)
if isinstance(path, basestring):
return self._df(self._jreader.text(path))
else:
raise TypeError("path can be only a single string") | [
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evhub/coconut | coconut/exceptions.py | https://github.com/evhub/coconut/blob/ff97177344e7604e89a0a98a977a87ed2a56fc6d/coconut/exceptions.py#L121-L139 | def message(self, message, source, point, ln):
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Jayin/ETipsService | service/wyulibrary.py | https://github.com/Jayin/ETipsService/blob/1a42612a5e5d11bec0ec1a26c99dec6fe216fca4/service/wyulibrary.py#L51-L89 | def search_book(self, anywords, page=1):
"""
检索图书
:param anywords: 检索关键字
:param page: 页码
:return: 图书列表
"""
result = []
html = self.__search_book_html(anywords, page)
soup = BeautifulSoup(html)
tds = soup.select(selector='tbody')[0].select('td')
cursor = 1
while cursor < len(tds) / 9:
s = (cursor - 1) * 9
num = tds[s].get_text()
ctrlno = tds[s].input.attrs['value']
name = tds[s + 1].get_text()
author = tds[s + 2].get_text()
press = tds[s + 3].get_text()
press_time = tds[s + 4].get_text()
index_num = tds[s + 5].get_text()
total = tds[s + 6].get_text()
left = tds[s + 7].get_text()
addtion = tds[s + 8].get_text().strip('\r\n') # 相关资源
book = {
'num': num, # 序号
'ctrlno': ctrlno, # 图书馆系统控制号(在图书馆的唯一编号)
'name': name, # 名称
'author': author, # 作者
'press': press, # 出版社
'press_time': press_time, # 出版时间
'index_num': index_num, # 索取号
'total': total, # 馆藏
'left': left, # 剩余
}
result.append(book)
cursor += 1
return result | [
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OpenTreeOfLife/peyotl | peyotl/nexson_proxy.py | https://github.com/OpenTreeOfLife/peyotl/blob/5e4e52a0fdbd17f490aa644ad79fda6ea2eda7c0/peyotl/nexson_proxy.py#L52-L64 | def tree_iter_nexson_proxy(nexson_proxy):
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nexml_el = nexson_proxy._nexml_el
tg_order = nexml_el['^ot:treesElementOrder']
tgd = nexml_el['treesById']
for tg_id in tg_order:
tg = tgd[tg_id]
tree_order = tg['^ot:treeElementOrder']
tbid = tg['treeById']
otus = tg['@otus']
for k in tree_order:
v = tbid[k]
yield nexson_proxy._create_tree_proxy(tree_id=k, tree=v, otus=otus) | [
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mojaie/chorus | chorus/mcsdr.py | https://github.com/mojaie/chorus/blob/fc7fe23a0272554c67671645ab07830b315eeb1b/chorus/mcsdr.py#L117-L126 | def node_desc(self, atoms):
"""default 9 bits descriptor
7 bits of atomic number (0-127) and 2 bits of pi electrons (0-3)
"""
a1 = self.mol.atom(atoms[0])
a2 = self.mol.atom(atoms[1])
a1t = a1.number << 2 | a1.pi
a2t = a2.number << 2 | a2.pi
pair = sorted((a1t, a2t))
return pair[0] << 9 | pair[1] | [
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wummel/linkchecker | linkcheck/logger/text.py | https://github.com/wummel/linkchecker/blob/c2ce810c3fb00b895a841a7be6b2e78c64e7b042/linkcheck/logger/text.py#L177-L181 | def write_dltime (self, url_data):
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self.writeln(_("%.3f seconds") % url_data.dltime,
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pycontribs/pyrax | pyrax/object_storage.py | https://github.com/pycontribs/pyrax/blob/9ddfd5064b3a292d7337906f3b2d5dce95b50b99/pyrax/object_storage.py#L1295-L1306 | def list_object_names(self, container, marker=None, limit=None, prefix=None,
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boriel/zxbasic | symbols/boundlist.py | https://github.com/boriel/zxbasic/blob/23b28db10e41117805bdb3c0f78543590853b132/symbols/boundlist.py#L35-L49 | def make_node(cls, node, *args):
''' Creates an array BOUND LIST.
'''
if node is None:
return cls.make_node(SymbolBOUNDLIST(), *args)
if node.token != 'BOUNDLIST':
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for arg in args:
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ChrisBeaumont/soupy | soupy.py | https://github.com/ChrisBeaumont/soupy/blob/795f2f61f711f574d5218fc8a3375d02bda1104f/soupy.py#L629-L643 | def dropwhile(self, func=None):
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func : function(Node) -> Node
Returns:
A new Collection, discarding all items
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Julius2342/pyvlx | pyvlx/heartbeat.py | https://github.com/Julius2342/pyvlx/blob/ee78e1324bcb1be5b8d1a9d05ab5496b72eae848/pyvlx/heartbeat.py#L30-L35 | async def stop(self):
"""Stop heartbeat."""
self.stopped = True
self.loop_event.set()
# Waiting for shutdown of loop()
await self.stopped_event.wait() | [
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kurtbrose/pyjks | jks/jks.py | https://github.com/kurtbrose/pyjks/blob/1cbe7f060e2ad076b6462f3273f11d635771ea3d/jks/jks.py#L229-L253 | def encrypt(self, key_password):
"""
Encrypts the private key, so that it can be saved to a keystore.
This will make it necessary to decrypt it again if it is going to be used later.
Has no effect if the entry is already encrypted.
:param str key_password: The password to encrypt the entry with.
"""
if not self.is_decrypted():
return
encrypted_private_key = sun_crypto.jks_pkey_encrypt(self.pkey_pkcs8, key_password)
a = AlgorithmIdentifier()
a.setComponentByName('algorithm', sun_crypto.SUN_JKS_ALGO_ID)
a.setComponentByName('parameters', '\x05\x00')
epki = rfc5208.EncryptedPrivateKeyInfo()
epki.setComponentByName('encryptionAlgorithm',a)
epki.setComponentByName('encryptedData', encrypted_private_key)
self._encrypted = encoder.encode(epki)
self._pkey = None
self._pkey_pkcs8 = None
self._algorithm_oid = None | [
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prometheus/client_python | prometheus_client/metrics.py | https://github.com/prometheus/client_python/blob/31f5557e2e84ca4ffa9a03abf6e3f4d0c8b8c3eb/prometheus_client/metrics.py#L160-L169 | def remove(self, *labelvalues):
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"""Remove the given labelset from the metric."""
if len(labelvalues) != len(self._labelnames):
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with self._lock:
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xeroc/python-graphenelib | graphenecommon/chain.py | https://github.com/xeroc/python-graphenelib/blob/8bb5396bc79998ee424cf3813af478304173f3a6/graphenecommon/chain.py#L144-L227 | def finalizeOp(self, ops, account, permission, **kwargs):
""" This method obtains the required private keys if present in
the wallet, finalizes the transaction, signs it and
broadacasts it
:param operation ops: The operation (or list of operaions) to
broadcast
:param operation account: The account that authorizes the
operation
:param string permission: The required permission for
signing (active, owner, posting)
:param object append_to: This allows to provide an instance of
ProposalsBuilder (see :func:`new_proposal`) or
TransactionBuilder (see :func:`new_tx()`) to specify
where to put a specific operation.
... note:: ``append_to`` is exposed to every method used in the
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... note::
If ``ops`` is a list of operation, they all need to be
signable by the same key! Thus, you cannot combine ops
that require active permission with ops that require
posting permission. Neither can you use different
accounts for different operations!
... note:: This uses ``txbuffer`` as instance of
:class:`transactionbuilder.TransactionBuilder`.
You may want to use your own txbuffer
"""
if "append_to" in kwargs and kwargs["append_to"]:
if self.proposer:
log.warning(
"You may not use append_to and self.proposer at "
"the same time. Append new_proposal(..) instead"
)
# Append to the append_to and return
append_to = kwargs["append_to"]
parent = append_to.get_parent()
assert isinstance(
append_to, (self.transactionbuilder_class, self.proposalbuilder_class)
)
append_to.appendOps(ops)
# Add the signer to the buffer so we sign the tx properly
if isinstance(append_to, self.proposalbuilder_class):
parent.appendSigner(append_to.proposer, permission)
else:
parent.appendSigner(account, permission)
# This returns as we used append_to, it does NOT broadcast, or sign
return append_to.get_parent()
elif self.proposer:
# Legacy proposer mode!
proposal = self.proposal()
proposal.set_proposer(self.proposer)
proposal.set_expiration(self.proposal_expiration)
proposal.set_review(self.proposal_review)
proposal.appendOps(ops)
# Go forward to see what the other options do ...
else:
# Append tot he default buffer
self.txbuffer.appendOps(ops)
# The API that obtains the fee only allows to specify one particular
# fee asset for all operations in that transaction even though the
# blockchain itself could allow to pay multiple operations with
# different fee assets.
if "fee_asset" in kwargs and kwargs["fee_asset"]:
self.txbuffer.set_fee_asset(kwargs["fee_asset"])
# Add signing information, signer, sign and optionally broadcast
if self.unsigned:
# In case we don't want to sign anything
self.txbuffer.addSigningInformation(account, permission)
return self.txbuffer
elif self.bundle:
# In case we want to add more ops to the tx (bundle)
self.txbuffer.appendSigner(account, permission)
return self.txbuffer.json()
else:
# default behavior: sign + broadcast
self.txbuffer.appendSigner(account, permission)
self.txbuffer.sign()
return self.txbuffer.broadcast() | [
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:param operation account: The account that authorizes the
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:param string permission: The required permission for
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:param object append_to: This allows to provide an instance of
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... note:: ``append_to`` is exposed to every method used in the
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ldomic/lintools | lintools/ligand_description.py | https://github.com/ldomic/lintools/blob/d825a4a7b35f3f857d3b81b46c9aee72b0ec697a/lintools/ligand_description.py#L57-L66 | def get_rotatable_bonds(self,mol):
"""Determines rotatable bonds in a ligand molecule
Takes:
* mol * - mol file in rdkit environment
Output:
* bonds * - tuples of atom ids
"""
RotatableBondSmarts = Chem.MolFromSmarts('[!$(*#*)&!D1]-&!@[!$(*#*)&!D1]')
bonds = mol.GetSubstructMatches(RotatableBondSmarts,uniquify=1)
return bonds | [
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Opentrons/opentrons | api/src/opentrons/util/linal.py | https://github.com/Opentrons/opentrons/blob/a7c15cc2636ecb64ab56c7edc1d8a57163aaeadf/api/src/opentrons/util/linal.py#L117-L133 | def apply_transform(
t: Union[List[List[float]], np.ndarray],
pos: Tuple[float, float, float],
with_offsets=True) -> Tuple[float, float, float]:
"""
Change of base using a transform matrix. Primarily used to render a point
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:param pos: XYZ point in space A
:param with_offsets: Whether to apply the transform as an affine transform
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with_offsets=False
:return: corresponding XYZ point in space B
"""
extended = 1 if with_offsets else 0
return tuple(dot(t, list(pos) + [extended])[:3]) | [
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fossasia/knittingpattern | knittingpattern/Parser.py | https://github.com/fossasia/knittingpattern/blob/8e608896b0ab82fea1ca9fbfa2b4ee023d8c8027/knittingpattern/Parser.py#L247-L254 | def _create_pattern_set(self, pattern, values):
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type_ = self._get_type(values)
version = self._get_version(values)
comment = values.get(COMMENT)
self._pattern_set = self._spec.new_pattern_set(
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ska-sa/katcp-python | katcp/client.py | https://github.com/ska-sa/katcp-python/blob/9127c826a1d030c53b84d0e95743e20e5c5ea153/katcp/client.py#L550-L569 | def handle_reply(self, msg):
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Parameters
----------
msg : Message object
The reply message to dispatch.
"""
method = self.__class__.unhandled_reply
if msg.name in self._reply_handlers:
method = self._reply_handlers[msg.name]
try:
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e_type, e_value, trace = sys.exc_info()
reason = "\n".join(traceback.format_exception(
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self._logger.error("Reply %s FAIL: %s" % (msg.name, reason)) | [
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quiltdata/quilt | compiler/quilt/nodes.py | https://github.com/quiltdata/quilt/blob/651853e7e89a8af86e0ff26167e752efa5878c12/compiler/quilt/nodes.py#L184-L220 | def _data(self, asa=None):
"""
Merges all child dataframes. Only works for dataframes stored on disk - not in memory.
"""
hash_list = []
stack = [self]
alldfs = True
store = None
while stack:
node = stack.pop()
if isinstance(node, GroupNode):
stack.extend(child for _, child in sorted(node._items(), reverse=True))
else:
if node._target() != TargetType.PANDAS:
alldfs = False
if node._store is None or node._hashes is None:
msg = "Can only merge built dataframes. Build this package and try again."
raise NotImplementedError(msg)
node_store = node._store
if store is None:
store = node_store
if node_store != store:
raise NotImplementedError("Can only merge dataframes from the same store")
hash_list += node._hashes
if asa is None:
if not hash_list:
return None
if not alldfs:
raise ValueError("Group contains non-dataframe nodes")
return store.load_dataframe(hash_list)
else:
if hash_list:
assert store is not None
return asa(self, [store.object_path(obj) for obj in hash_list])
else:
return asa(self, []) | [
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shidenggui/easytrader | easytrader/xqtrader.py | https://github.com/shidenggui/easytrader/blob/e5ae4daeda4ea125763a95b280dd694c7f68257d/easytrader/xqtrader.py#L143-L165 | def get_balance(self):
"""
获取账户资金状况
:return:
"""
portfolio_code = self.account_config.get("portfolio_code", "ch")
portfolio_info = self._get_portfolio_info(portfolio_code)
asset_balance = self._virtual_to_balance(
float(portfolio_info["net_value"])
) # 总资产
position = portfolio_info["view_rebalancing"] # 仓位结构
cash = asset_balance * float(position["cash"]) / 100
market = asset_balance - cash
return [
{
"asset_balance": asset_balance,
"current_balance": cash,
"enable_balance": cash,
"market_value": market,
"money_type": u"人民币",
"pre_interest": 0.25,
}
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TorkamaniLab/metapipe | metapipe/models/command_template_factory.py | https://github.com/TorkamaniLab/metapipe/blob/15592e5b0c217afb00ac03503f8d0d7453d4baf4/metapipe/models/command_template_factory.py#L15-L30 | def get_command_templates(command_tokens, file_tokens=[], path_tokens=[],
job_options=[]):
""" Given a list of tokens from the grammar, return a
list of commands.
"""
files = get_files(file_tokens)
paths = get_paths(path_tokens)
job_options = get_options(job_options)
templates = _get_command_templates(command_tokens, files, paths,
job_options)
for command_template in templates:
command_template._dependencies = _get_prelim_dependencies(
command_template, templates)
return templates | [
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spyder-ide/spyder | spyder/plugins/profiler/widgets/profilergui.py | https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/plugins/profiler/widgets/profilergui.py#L637-L699 | def populate_tree(self, parentItem, children_list):
"""Recursive method to create each item (and associated data) in the tree."""
for child_key in children_list:
self.item_depth += 1
(filename, line_number, function_name, file_and_line, node_type
) = self.function_info(child_key)
((total_calls, total_calls_dif), (loc_time, loc_time_dif), (cum_time,
cum_time_dif)) = self.format_output(child_key)
child_item = TreeWidgetItem(parentItem)
self.item_list.append(child_item)
self.set_item_data(child_item, filename, line_number)
# FIXME: indexes to data should be defined by a dictionary on init
child_item.setToolTip(0, _('Function or module name'))
child_item.setData(0, Qt.DisplayRole, function_name)
child_item.setIcon(0, self.icon_list[node_type])
child_item.setToolTip(1, _('Time in function '\
'(including sub-functions)'))
child_item.setData(1, Qt.DisplayRole, cum_time)
child_item.setTextAlignment(1, Qt.AlignRight)
child_item.setData(2, Qt.DisplayRole, cum_time_dif[0])
child_item.setForeground(2, QColor(cum_time_dif[1]))
child_item.setTextAlignment(2, Qt.AlignLeft)
child_item.setToolTip(3, _('Local time in function '\
'(not in sub-functions)'))
child_item.setData(3, Qt.DisplayRole, loc_time)
child_item.setTextAlignment(3, Qt.AlignRight)
child_item.setData(4, Qt.DisplayRole, loc_time_dif[0])
child_item.setForeground(4, QColor(loc_time_dif[1]))
child_item.setTextAlignment(4, Qt.AlignLeft)
child_item.setToolTip(5, _('Total number of calls '\
'(including recursion)'))
child_item.setData(5, Qt.DisplayRole, total_calls)
child_item.setTextAlignment(5, Qt.AlignRight)
child_item.setData(6, Qt.DisplayRole, total_calls_dif[0])
child_item.setForeground(6, QColor(total_calls_dif[1]))
child_item.setTextAlignment(6, Qt.AlignLeft)
child_item.setToolTip(7, _('File:line '\
'where function is defined'))
child_item.setData(7, Qt.DisplayRole, file_and_line)
#child_item.setExpanded(True)
if self.is_recursive(child_item):
child_item.setData(7, Qt.DisplayRole, '(%s)' % _('recursion'))
child_item.setDisabled(True)
else:
callees = self.find_callees(child_key)
if self.item_depth < 3:
self.populate_tree(child_item, callees)
elif callees:
child_item.setChildIndicatorPolicy(child_item.ShowIndicator)
self.items_to_be_shown[id(child_item)] = callees
self.item_depth -= 1 | [
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hyperledger/indy-plenum | plenum/server/replica_freshness_checker.py | https://github.com/hyperledger/indy-plenum/blob/dcd144e238af7f17a869ffc9412f13dc488b7020/plenum/server/replica_freshness_checker.py#L21-L48 | def check_freshness(self, ts):
'''
Get all ledger IDs for which
A) not updated for more than Freshness Timeout
B) hasn't been attempted to update (returned from this method) for more than Freshness Timeout
Should be called whenever we need to decide if ledgers need to be updated.
:param ts: the current time check the freshness against
:return: an ordered dict of outdated ledgers sorted by the time from the last update (from oldest to newest)
and then by ledger ID (in case of equal update time)
'''
outdated_ledgers = {}
for ledger_id, freshness_state in self._ledger_freshness.items():
if ts - freshness_state.last_updated <= self.freshness_timeout:
continue
if ts - freshness_state.last_marked_as_outdated <= self.freshness_timeout:
continue
outdated_ledgers[ledger_id] = ts - freshness_state.last_updated
freshness_state.last_marked_as_outdated = ts
# sort by last update time and then by ledger_id
return OrderedDict(
sorted(
outdated_ledgers.items(),
key=lambda item: (-item[1], item[0])
)
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urinieto/msaf | msaf/pymf/cnmf.py | https://github.com/urinieto/msaf/blob/9dbb57d77a1310465a65cc40f1641d083ca74385/msaf/pymf/cnmf.py#L108-L187 | def factorize(self, niter=10, compute_w=True, compute_h=True,
compute_err=True, show_progress=False):
""" Factorize s.t. WH = data
Parameters
----------
niter : int
number of iterations.
show_progress : bool
print some extra information to stdout.
compute_h : bool
iteratively update values for H.
compute_w : bool
iteratively update values for W.
compute_err : bool
compute Frobenius norm |data-WH| after each update and store
it to .ferr[k].
Updated Values
--------------
.W : updated values for W.
.H : updated values for H.
.ferr : Frobenius norm |data-WH| for each iteration.
"""
if not hasattr(self,'W'):
self.init_w()
if not hasattr(self,'H'):
self.init_h()
def separate_positive(m):
return (np.abs(m) + m)/2.0
def separate_negative(m):
return (np.abs(m) - m)/2.0
if show_progress:
self._logger.setLevel(logging.INFO)
else:
self._logger.setLevel(logging.ERROR)
XtX = np.dot(self.data[:,:].T, self.data[:,:])
XtX_pos = separate_positive(XtX)
XtX_neg = separate_negative(XtX)
self.ferr = np.zeros(niter)
# iterate over W and H
for i in range(niter):
# update H
XtX_neg_x_W = np.dot(XtX_neg, self.G)
XtX_pos_x_W = np.dot(XtX_pos, self.G)
if compute_h:
H_x_WT = np.dot(self.H.T, self.G.T)
ha = XtX_pos_x_W + np.dot(H_x_WT, XtX_neg_x_W)
hb = XtX_neg_x_W + np.dot(H_x_WT, XtX_pos_x_W) + 10**-9
self.H = (self.H.T*np.sqrt(ha/hb)).T
# update W
if compute_w:
HT_x_H = np.dot(self.H, self.H.T)
wa = np.dot(XtX_pos, self.H.T) + np.dot(XtX_neg_x_W, HT_x_H)
wb = np.dot(XtX_neg, self.H.T) + np.dot(XtX_pos_x_W, HT_x_H) + 10**-9
self.G *= np.sqrt(wa/wb)
self.W = np.dot(self.data[:,:], self.G)
if compute_err:
self.ferr[i] = self.frobenius_norm()
self._logger.info('Iteration ' + str(i+1) + '/' + str(niter) +
' FN:' + str(self.ferr[i]))
else:
self._logger.info('Iteration ' + str(i+1) + '/' + str(niter))
if i > 1 and compute_err:
if self.converged(i):
self.ferr = self.ferr[:i]
break | [
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] | Factorize s.t. WH = data
Parameters
----------
niter : int
number of iterations.
show_progress : bool
print some extra information to stdout.
compute_h : bool
iteratively update values for H.
compute_w : bool
iteratively update values for W.
compute_err : bool
compute Frobenius norm |data-WH| after each update and store
it to .ferr[k].
Updated Values
--------------
.W : updated values for W.
.H : updated values for H.
.ferr : Frobenius norm |data-WH| for each iteration. | [
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markovmodel/msmtools | msmtools/estimation/sparse/transition_matrix.py | https://github.com/markovmodel/msmtools/blob/54dc76dd2113a0e8f3d15d5316abab41402941be/msmtools/estimation/sparse/transition_matrix.py#L27-L37 | def transition_matrix_non_reversible(C):
"""implementation of transition_matrix"""
if not scipy.sparse.issparse(C):
C = scipy.sparse.csr_matrix(C)
rowsum = C.tocsr().sum(axis=1)
# catch div by zero
if np.min(rowsum) == 0.0:
raise ValueError("matrix C contains rows with sum zero.")
rowsum = np.array(1. / rowsum).flatten()
norm = scipy.sparse.diags(rowsum, 0)
return norm * C | [
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apache/incubator-heron | heron/tools/tracker/src/python/handlers/metricstimelinehandler.py | https://github.com/apache/incubator-heron/blob/ad10325a0febe89ad337e561ebcbe37ec5d9a5ac/heron/tools/tracker/src/python/handlers/metricstimelinehandler.py#L57-L79 | def get(self):
""" get method """
try:
cluster = self.get_argument_cluster()
role = self.get_argument_role()
environ = self.get_argument_environ()
topology_name = self.get_argument_topology()
component = self.get_argument_component()
metric_names = self.get_required_arguments_metricnames()
start_time = self.get_argument_starttime()
end_time = self.get_argument_endtime()
self.validateInterval(start_time, end_time)
instances = self.get_arguments(constants.PARAM_INSTANCE)
topology = self.tracker.getTopologyByClusterRoleEnvironAndName(
cluster, role, environ, topology_name)
metrics = yield tornado.gen.Task(metricstimeline.getMetricsTimeline,
topology.tmaster, component, metric_names,
instances, int(start_time), int(end_time))
self.write_success_response(metrics)
except Exception as e:
Log.debug(traceback.format_exc())
self.write_error_response(e) | [
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has2k1/plotnine | plotnine/facets/facet_wrap.py | https://github.com/has2k1/plotnine/blob/566e579af705367e584fb27a74e6c5199624ca89/plotnine/facets/facet_wrap.py#L302-L318 | def n2mfrow(nr_plots):
"""
Compute the rows and columns given the number
of plots.
This is a port of grDevices::n2mfrow from R
"""
if nr_plots <= 3:
nrow, ncol = nr_plots, 1
elif nr_plots <= 6:
nrow, ncol = (nr_plots + 1) // 2, 2
elif nr_plots <= 12:
nrow, ncol = (nr_plots + 2) // 3, 3
else:
nrow = int(np.ceil(np.sqrt(nr_plots)))
ncol = int(np.ceil(nr_plots/nrow))
return (nrow, ncol) | [
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adamziel/python_translate | python_translate/operations.py | https://github.com/adamziel/python_translate/blob/0aee83f434bd2d1b95767bcd63adb7ac7036c7df/python_translate/operations.py#L70-L82 | def get_new_messages(self, domain):
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Returns new valid messages after operation.
@type domain: str
@rtype: dict
"""
if domain not in self.domains:
raise ValueError('Invalid domain: {0}'.format(domain))
if domain not in self.messages or 'new' not in self.messages[domain]:
self._process_domain(domain)
return self.messages[domain]['new'] | [
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ioam/lancet | lancet/core.py | https://github.com/ioam/lancet/blob/1fbbf88fa0e8974ff9ed462e3cb11722ddebdd6e/lancet/core.py#L210-L221 | def _collect_by_key(self,specs):
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"""
# Collect (key, value) tuples as list of lists, flatten with chain
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collection = defaultdict(list)
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return collection | [
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zqfang/GSEApy | gseapy/enrichr.py | https://github.com/zqfang/GSEApy/blob/673e9ec1391e3b14d3e8a4353117151fd2cb9345/gseapy/enrichr.py#L154-L170 | def get_results(self, gene_list):
"""Enrichr API"""
ADDLIST_URL = 'http://amp.pharm.mssm.edu/%sEnrichr/addList'%self._organism
job_id = self.send_genes(gene_list, ADDLIST_URL)
user_list_id = job_id['userListId']
RESULTS_URL = 'http://amp.pharm.mssm.edu/%sEnrichr/export'%self._organism
query_string = '?userListId=%s&filename=%s&backgroundType=%s'
# set max retries num =5
s = retry(num=5)
filename = "%s.%s.reports" % (self._gs, self.descriptions)
url = RESULTS_URL + query_string % (user_list_id, filename, self._gs)
response = s.get(url, stream=True, timeout=None)
# response = requests.get(RESULTS_URL + query_string % (user_list_id, gene_set))
sleep(1)
res = pd.read_csv(StringIO(response.content.decode('utf-8')),sep="\t")
return [job_id['shortId'], res] | [
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spry-group/python-vultr | vultr/v1_server.py | https://github.com/spry-group/python-vultr/blob/bad1448f1df7b5dba70fd3d11434f32580f0b850/vultr/v1_server.py#L107-L116 | def neighbors(self, subid, params=None):
''' v1/server/neighbors
GET - account
Determine what other subscriptions are hosted on the same physical
host as a given subscription.
Link: https://www.vultr.com/api/#server_neighbors
'''
params = update_params(params, {'SUBID': subid})
return self.request('/v1/server/neighbors', params, 'GET') | [
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Chilipp/funcargparse | funcargparse/__init__.py | https://github.com/Chilipp/funcargparse/blob/398ce8e7fa5aa35c465215446bda151cf1ecf7ad/funcargparse/__init__.py#L333-L398 | def setup_subparser(
self, func=None, setup_as=None, insert_at=None, interprete=True,
epilog_sections=None, overwrite=False, append_epilog=True,
return_parser=False, name=None, **kwargs):
"""
Create a subparser with the name of the given function
Parameters are the same as for the :meth:`setup_args` function, other
parameters are parsed to the :meth:`add_subparsers` method if (and only
if) this method has not already been called.
Parameters
----------
%(FuncArgParser.setup_args.parameters)s
return_parser: bool
If True, the create parser is returned instead of the function
name: str
The name of the created parser. If None, the function name is used
and underscores (``'_'``) are replaced by minus (``'-'``)
``**kwargs``
Any other parameter that is passed to the add_parser method that
creates the parser
Other Parameters
----------------
Returns
-------
FuncArgParser or %(FuncArgParser.setup_args.returns)s
If return_parser is True, the created subparser is returned
Examples
--------
Use this method as a decorator::
>>> from funcargparser import FuncArgParser
>>> parser = FuncArgParser()
>>> @parser.setup_subparser
... def my_func(my_argument=None):
... pass
>>> args = parser.parse_args('my-func -my-argument 1'.split())
"""
def setup(func):
if self._subparsers_action is None:
raise RuntimeError(
"No subparsers have yet been created! Run the "
"add_subparsers method first!")
# replace underscore by '-'
name2use = name
if name2use is None:
name2use = func.__name__.replace('_', '-')
kwargs.setdefault('help', docstrings.get_summary(
docstrings.dedents(inspect.getdoc(func))))
parser = self._subparsers_action.add_parser(name2use, **kwargs)
parser.setup_args(
func, setup_as=setup_as, insert_at=insert_at,
interprete=interprete, epilog_sections=epilog_sections,
overwrite=overwrite, append_epilog=append_epilog)
return func, parser
if func is None:
return lambda f: setup(f)[0]
else:
return setup(func)[int(return_parser)] | [
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Parameters
----------
%(FuncArgParser.setup_args.parameters)s
return_parser: bool
If True, the create parser is returned instead of the function
name: str
The name of the created parser. If None, the function name is used
and underscores (``'_'``) are replaced by minus (``'-'``)
``**kwargs``
Any other parameter that is passed to the add_parser method that
creates the parser
Other Parameters
----------------
Returns
-------
FuncArgParser or %(FuncArgParser.setup_args.returns)s
If return_parser is True, the created subparser is returned
Examples
--------
Use this method as a decorator::
>>> from funcargparser import FuncArgParser
>>> parser = FuncArgParser()
>>> @parser.setup_subparser
... def my_func(my_argument=None):
... pass
>>> args = parser.parse_args('my-func -my-argument 1'.split()) | [
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openstack/networking-cisco | networking_cisco/apps/saf/server/dfa_server.py | https://github.com/openstack/networking-cisco/blob/aa58a30aec25b86f9aa5952b0863045975debfa9/networking_cisco/apps/saf/server/dfa_server.py#L1651-L1667 | def listener_delete_event(self, listener_info):
"""Process listener delete event.
This is lbaas v2
vif will be plugged into ovs when first
listener is created and unpluged from ovs
when last listener is deleted.
as the data only contains listener id, we will
scan all loadbalancers from db and delete the vdp
if their admin state is down in that loadbalancer
"""
lb_list = self.neutronclient.list_loadbalancers()
for lb in lb_list.get('loadbalancers'):
if not lb.get("listeners"):
lb_id = lb.get('id')
LOG.info("Deleting lb %s port" % lb_id)
self.delete_lbaas_port(lb_id) | [
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MIT-LCP/wfdb-python | wfdb/processing/qrs.py | https://github.com/MIT-LCP/wfdb-python/blob/cc8c9e9e44f10af961b7a9d8ae03708b31ac8a8c/wfdb/processing/qrs.py#L603-L648 | def xqrs_detect(sig, fs, sampfrom=0, sampto='end', conf=None,
learn=True, verbose=True):
"""
Run the 'xqrs' qrs detection algorithm on a signal. See the
docstring of the XQRS class for algorithm details.
Parameters
----------
sig : numpy array
The input ecg signal to apply the qrs detection on.
fs : int or float
The sampling frequency of the input signal.
sampfrom : int, optional
The starting sample number to run the detection on.
sampto :
The final sample number to run the detection on. Set as 'end' to
run on the entire signal.
conf : XQRS.Conf object, optional
The configuration object specifying signal configuration
parameters. See the docstring of the XQRS.Conf class.
learn : bool, optional
Whether to apply learning on the signal before running the main
detection. If learning fails or is not conducted, the default
configuration parameters will be used to initialize these
variables.
verbose : bool, optional
Whether to display the stages and outcomes of the detection
process.
Returns
-------
qrs_inds : numpy array
The indices of the detected qrs complexes
Examples
--------
>>> import wfdb
>>> from wfdb import processing
>>> sig, fields = wfdb.rdsamp('sample-data/100', channels=[0])
>>> qrs_inds = processing.xqrs_detect(sig=sig[:,0], fs=fields['fs'])
"""
xqrs = XQRS(sig=sig, fs=fs, conf=conf)
xqrs.detect(sampfrom=sampfrom, sampto=sampto, verbose=verbose)
return xqrs.qrs_inds | [
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Parameters
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sig : numpy array
The input ecg signal to apply the qrs detection on.
fs : int or float
The sampling frequency of the input signal.
sampfrom : int, optional
The starting sample number to run the detection on.
sampto :
The final sample number to run the detection on. Set as 'end' to
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conf : XQRS.Conf object, optional
The configuration object specifying signal configuration
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learn : bool, optional
Whether to apply learning on the signal before running the main
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verbose : bool, optional
Whether to display the stages and outcomes of the detection
process.
Returns
-------
qrs_inds : numpy array
The indices of the detected qrs complexes
Examples
--------
>>> import wfdb
>>> from wfdb import processing
>>> sig, fields = wfdb.rdsamp('sample-data/100', channels=[0])
>>> qrs_inds = processing.xqrs_detect(sig=sig[:,0], fs=fields['fs']) | [
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Autodesk/aomi | aomi/helpers.py | https://github.com/Autodesk/aomi/blob/84da2dfb0424837adf9c4ddc1aa352e942bb7a4a/aomi/helpers.py#L44-L53 | def hard_path(path, prefix_dir):
"""Returns an absolute path to either the relative or absolute file."""
relative = abspath("%s/%s" % (prefix_dir, path))
a_path = abspath(path)
if os.path.exists(relative):
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return relative
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ga4gh/ga4gh-client | ga4gh/client/client.py | https://github.com/ga4gh/ga4gh-client/blob/d23b00b89112ef0930d45ee75aa3c6de3db615c5/ga4gh/client/client.py#L802-L812 | def search_rna_quantification_sets(self, dataset_id):
"""
Returns an iterator over the RnaQuantificationSet objects from the
server
"""
request = protocol.SearchRnaQuantificationSetsRequest()
request.dataset_id = dataset_id
request.page_size = pb.int(self._page_size)
return self._run_search_request(
request, "rnaquantificationsets",
protocol.SearchRnaQuantificationSetsResponse) | [
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saltstack/salt | salt/modules/pip.py | https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/pip.py#L1466-L1563 | def list_all_versions(pkg,
bin_env=None,
include_alpha=False,
include_beta=False,
include_rc=False,
user=None,
cwd=None,
index_url=None,
extra_index_url=None):
'''
.. versionadded:: 2017.7.3
List all available versions of a pip package
pkg
The package to check
bin_env
Path to pip (or to a virtualenv). This can be used to specify the path
to the pip to use when more than one Python release is installed (e.g.
``/usr/bin/pip-2.7`` or ``/usr/bin/pip-2.6``. If a directory path is
specified, it is assumed to be a virtualenv.
include_alpha
Include alpha versions in the list
include_beta
Include beta versions in the list
include_rc
Include release candidates versions in the list
user
The user under which to run pip
cwd
Directory from which to run pip
index_url
Base URL of Python Package Index
.. versionadded:: 2019.2.0
extra_index_url
Additional URL of Python Package Index
.. versionadded:: 2019.2.0
CLI Example:
.. code-block:: bash
salt '*' pip.list_all_versions <package name>
'''
cmd = _get_pip_bin(bin_env)
cmd.extend(['install', '{0}==versions'.format(pkg)])
if index_url:
if not salt.utils.url.validate(index_url, VALID_PROTOS):
raise CommandExecutionError(
'\'{0}\' is not a valid URL'.format(index_url)
)
cmd.extend(['--index-url', index_url])
if extra_index_url:
if not salt.utils.url.validate(extra_index_url, VALID_PROTOS):
raise CommandExecutionError(
'\'{0}\' is not a valid URL'.format(extra_index_url)
)
cmd.extend(['--extra-index-url', extra_index_url])
cmd_kwargs = dict(cwd=cwd, runas=user, output_loglevel='quiet', redirect_stderr=True)
if bin_env and os.path.isdir(bin_env):
cmd_kwargs['env'] = {'VIRTUAL_ENV': bin_env}
result = __salt__['cmd.run_all'](cmd, **cmd_kwargs)
filtered = []
if not include_alpha:
filtered.append('a')
if not include_beta:
filtered.append('b')
if not include_rc:
filtered.append('rc')
if filtered:
excludes = re.compile(r'^((?!{0}).)*$'.format('|'.join(filtered)))
else:
excludes = re.compile(r'')
versions = []
for line in result['stdout'].splitlines():
match = re.search(r'\s*Could not find a version.* \(from versions: (.*)\)', line)
if match:
versions = [v for v in match.group(1).split(', ') if v and excludes.match(v)]
versions.sort(key=pkg_resources.parse_version)
break
if not versions:
return None
return versions | [
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List all available versions of a pip package
pkg
The package to check
bin_env
Path to pip (or to a virtualenv). This can be used to specify the path
to the pip to use when more than one Python release is installed (e.g.
``/usr/bin/pip-2.7`` or ``/usr/bin/pip-2.6``. If a directory path is
specified, it is assumed to be a virtualenv.
include_alpha
Include alpha versions in the list
include_beta
Include beta versions in the list
include_rc
Include release candidates versions in the list
user
The user under which to run pip
cwd
Directory from which to run pip
index_url
Base URL of Python Package Index
.. versionadded:: 2019.2.0
extra_index_url
Additional URL of Python Package Index
.. versionadded:: 2019.2.0
CLI Example:
.. code-block:: bash
salt '*' pip.list_all_versions <package name> | [
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latchset/jwcrypto | jwcrypto/jwt.py | https://github.com/latchset/jwcrypto/blob/961df898dc08f63fe3d900f2002618740bc66b4a/jwcrypto/jwt.py#L416-L428 | def make_signed_token(self, key):
"""Signs the payload.
Creates a JWS token with the header as the JWS protected header and
the claims as the payload. See (:class:`jwcrypto.jws.JWS`) for
details on the exceptions that may be reaised.
:param key: A (:class:`jwcrypto.jwk.JWK`) key.
"""
t = JWS(self.claims)
t.add_signature(key, protected=self.header)
self.token = t | [
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psss/did | did/plugins/sentry.py | https://github.com/psss/did/blob/04e4ee6f1aa14c0cae3ba9f9803871f3f98279cb/did/plugins/sentry.py#L81-L85 | def issues(self, kind, email):
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openstack/proliantutils | proliantutils/redfish/redfish.py | https://github.com/openstack/proliantutils/blob/86ef3b47b4eca97c221577e3570b0240d6a25f22/proliantutils/redfish/redfish.py#L1133-L1170 | def set_bios_settings(self, data=None, only_allowed_settings=True):
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sushy_system = self._get_sushy_system(PROLIANT_SYSTEM_ID)
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unsupported_settings = [key for key in data if key not in (
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if unsupported_settings:
msg = ("Could not apply settings as one or more settings are"
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" Supported settings are %s." % (
unsupported_settings,
ilo_cons.SUPPORTED_REDFISH_BIOS_PROPERTIES))
raise exception.IloError(msg)
try:
settings_required = sushy_system.bios_settings.pending_settings
settings_required.update_bios_data_by_patch(data)
except sushy.exceptions.SushyError as e:
msg = (self._('The pending BIOS Settings resource not found.'
' Error %(error)s') %
{'error': str(e)})
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cloud9ers/gurumate | environment/lib/python2.7/site-packages/IPython/core/inputsplitter.py | https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/core/inputsplitter.py#L816-L821 | def transform_cell(self, cell):
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self.reset()
self.push(cell)
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brocade/pynos | pynos/versions/ver_6/ver_6_0_1/yang/brocade_nameserver.py | https://github.com/brocade/pynos/blob/bd8a34e98f322de3fc06750827d8bbc3a0c00380/pynos/versions/ver_6/ver_6_0_1/yang/brocade_nameserver.py#L103-L117 | def get_nameserver_detail_output_show_nameserver_nameserver_portsymb(self, **kwargs):
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dropbox/stone | stone/backends/obj_c_types.py | https://github.com/dropbox/stone/blob/2e95cbcd1c48e05cca68c919fd8d24adec6b0f58/stone/backends/obj_c_types.py#L497-L517 | def _generate_struct_cstor_default(self, struct):
"""Emits struct convenience constructor. Default arguments are omitted."""
if not self._struct_has_defaults(struct):
return
fields_no_default = [
f for f in struct.all_fields
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with self.block_func(
func=self._cstor_name_from_fields(fields_no_default),
args=fmt_func_args_from_fields(fields_no_default),
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args = ([(fmt_var(f.name), fmt_var(f.name) if not f.has_default and
not is_nullable_type(f.data_type) else 'nil')
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cstor_args = fmt_func_args(args)
self.emit('return [self {}:{}];'.format(
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dalloriam/engel | engel/application.py | https://github.com/dalloriam/engel/blob/f3477cd546e885bc53e755b3eb1452ce43ef5697/engel/application.py#L82-L90 | def unregister(self, event, callback, selector=None):
"""
Unregisters an event that was being monitored.
:param event: Name of the event to monitor
:param callback: Callback function for when the event is received (Params: event, interface).
:param selector: `(Optional)` CSS selector for the element(s) you want to monitor
"""
self.processor.unregister(event, callback, selector) | [
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sassoftware/saspy | saspy/sasets.py | https://github.com/sassoftware/saspy/blob/e433f71990f249d3a6c3db323ceb11cb2d462cf9/saspy/sasets.py#L87-L121 | def timeseries(self, data: ['SASdata', str] = None,
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Python method to call the TIMESERIES procedure
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http://support.sas.com/documentation/cdl//en/etsug/68148/HTML/default/viewer.htm#etsug_timeseries_syntax.htm
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:parm crosscorr: The crosscorr variable can only be a string type.
:parm crossvar: The crossvar variable can only be a string type.
:parm decomp: The decomp variable can only be a string type.
:parm id: The id variable can only be a string type.
:parm out: The out variable can be a string or SASdata type.
:parm season: The season variable can only be a string type.
:parm trend: The trend variable can only be a string type.
:parm var: The var variable can only be a string type.
:parm procopts: The procopts variable is a generic option available for advanced use. It can only be a string type.
:parm stmtpassthrough: The stmtpassthrough variable is a generic option available for advanced use. It can only be a string type.
:return: SAS Result Object
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pantsbuild/pants | src/python/pants/option/options.py | https://github.com/pantsbuild/pants/blob/b72e650da0df685824ffdcc71988b8c282d0962d/src/python/pants/option/options.py#L292-L298 | def register(self, scope, *args, **kwargs):
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MillionIntegrals/vel | vel/rl/buffers/backend/prioritized_vec_buffer_backend.py | https://github.com/MillionIntegrals/vel/blob/e0726e1f63742b728966ccae0c8b825ea0ba491a/vel/rl/buffers/backend/prioritized_vec_buffer_backend.py#L72-L75 | def update_priority(self, tree_idx_list, priority_list):
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MKLab-ITI/reveal-graph-embedding | reveal_graph_embedding/learning/holdout.py | https://github.com/MKLab-ITI/reveal-graph-embedding/blob/eda862687aa5a64b79c6b12de1b4dca6ce986dc8/reveal_graph_embedding/learning/holdout.py#L202-L270 | def iterative_stratification(node_label_matrix, training_set_size, number_of_categories, random_seed=0):
"""
Iterative data fold stratification/balancing for two folds.
Based on: Sechidis, K., Tsoumakas, G., & Vlahavas, I. (2011).
On the stratification of multi-label data.
In Machine Learning and Knowledge Discovery in Databases (pp. 145-158).
Springer Berlin Heidelberg.
Inputs: - node_label_matrix: The node-label ground truth in a SciPy sparse matrix format.
- training_set_size: The minimum required size for the training set.
- number_of_categories: The number of categories/classes in the learning.
- random_seed: A seed for numpy random.
Outputs: - train_set: A NumPy array containing the training set node ids.
- test_set: A NumPy array containing the testing set node ids.
"""
number_of_labelled_nodes = node_label_matrix.shape[0]
testing_set_size = number_of_labelled_nodes - training_set_size
training_set_proportion = training_set_size/number_of_labelled_nodes
testing_set_proportion = testing_set_size/number_of_labelled_nodes
# Calculate the desired number of examples of each label at each subset.
desired_label_number = np.zeros((2, number_of_categories), dtype=np.int64)
node_label_matrix = node_label_matrix.tocsc()
for j in range(number_of_categories):
category_label_number = node_label_matrix.getcol(j).indices.size
desired_label_number[0, j] = math.ceil(category_label_number*training_set_proportion)
desired_label_number[1, j] = category_label_number - desired_label_number[0, j]
train_ids = list()
test_ids = list()
append_train_id = train_ids.append
append_test_id = test_ids.append
# Randomize process
np.random.seed(random_seed)
while True:
if len(train_ids) + len(test_ids) >= number_of_labelled_nodes:
break
# Find the label with the fewest (but at least one) remaining examples, breaking the ties randomly
remaining_label_distribution = desired_label_number.sum(axis=0)
min_label = np.min(remaining_label_distribution[np.where(remaining_label_distribution > 0)[0]])
label_indices = np.where(remaining_label_distribution == min_label)[0]
chosen_label = int(np.random.choice(label_indices, 1)[0])
# Find the subset with the largest number of desired examples for this label,
# breaking ties by considering the largest number of desired examples, breaking further ties randomly.
fold_max_remaining_labels = np.max(desired_label_number[:, chosen_label])
fold_indices = np.where(desired_label_number[:, chosen_label] == fold_max_remaining_labels)[0]
chosen_fold = int(np.random.choice(fold_indices, 1)[0])
# Choose a random example for the selected label.
relevant_nodes = node_label_matrix.getcol(chosen_label).indices
chosen_node = int(np.random.choice(np.setdiff1d(relevant_nodes,
np.union1d(np.array(train_ids),
np.array(test_ids))),
1)[0])
if chosen_fold == 0:
append_train_id(chosen_node)
desired_label_number[0, node_label_matrix.getrow(chosen_node).indices] -= 1
elif chosen_fold == 1:
append_test_id(chosen_node)
desired_label_number[1, node_label_matrix.getrow(chosen_node).indices] -= 1
else:
raise RuntimeError
return np.array(train_ids), np.array(test_ids) | [
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Based on: Sechidis, K., Tsoumakas, G., & Vlahavas, I. (2011).
On the stratification of multi-label data.
In Machine Learning and Knowledge Discovery in Databases (pp. 145-158).
Springer Berlin Heidelberg.
Inputs: - node_label_matrix: The node-label ground truth in a SciPy sparse matrix format.
- training_set_size: The minimum required size for the training set.
- number_of_categories: The number of categories/classes in the learning.
- random_seed: A seed for numpy random.
Outputs: - train_set: A NumPy array containing the training set node ids.
- test_set: A NumPy array containing the testing set node ids. | [
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gwastro/pycbc | pycbc/conversions.py | https://github.com/gwastro/pycbc/blob/7a64cdd104d263f1b6ea0b01e6841837d05a4cb3/pycbc/conversions.py#L226-L266 | def _mass_from_knownmass_eta(known_mass, eta, known_is_secondary=False,
force_real=True):
r"""Returns the other component mass given one of the component masses
and the symmetric mass ratio.
This requires finding the roots of the quadratic equation:
.. math::
\eta m_2^2 + (2\eta - 1)m_1 m_2 + \eta m_1^2 = 0.
This has two solutions which correspond to :math:`m_1` being the heavier
mass or it being the lighter mass. By default, `known_mass` is assumed to
be the heavier (primary) mass, and the smaller solution is returned. Use
the `other_is_secondary` to invert.
Parameters
----------
known_mass : float
The known component mass.
eta : float
The symmetric mass ratio.
known_is_secondary : {False, bool}
Whether the known component mass is the primary or the secondary. If
True, `known_mass` is assumed to be the secondary (lighter) mass and
the larger solution is returned. Otherwise, the smaller solution is
returned. Default is False.
force_real : {True, bool}
Force the returned mass to be real.
Returns
-------
float
The other component mass.
"""
roots = numpy.roots([eta, (2*eta - 1)*known_mass, eta*known_mass**2.])
if force_real:
roots = numpy.real(roots)
if known_is_secondary:
return roots[roots.argmax()]
else:
return roots[roots.argmin()] | [
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The known component mass.
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The symmetric mass ratio.
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Whether the known component mass is the primary or the secondary. If
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