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def new_module(self):
''' Make a fresh module to run in.
Returns:
Module
'''
self.reset_run_errors()
if self._code is None:
return None
module_name = 'bk_script_' + make_id().replace('-', '')
module = ModuleType(str(module_name)) # str needed for py2.7
module.__dict__['__file__'] = os.path.abspath(self._path)
return module | 0.007059 |
def cf_dictionary_to_dict(dictionary):
"""
Converts a CFDictionary object into a python dictionary
:param dictionary:
The CFDictionary to convert
:return:
A python dict
"""
dict_length = CoreFoundation.CFDictionaryGetCount(dictionary)
keys = (CFTypeRef * dict_length)()
values = (CFTypeRef * dict_length)()
CoreFoundation.CFDictionaryGetKeysAndValues(
dictionary,
_cast_pointer_p(keys),
_cast_pointer_p(values)
)
output = {}
for index in range(0, dict_length):
output[CFHelpers.native(keys[index])] = CFHelpers.native(values[index])
return output | 0.004121 |
def get_tokens(max_value):
"""Defines tokens.
Args:
max_value: the maximum numeric range for the token.
Returns:
list of string tokens in vocabulary.
"""
vocab = [str(i) for i in range(max_value)]
vocab = set(vocab)
vocab.update(CodeOp.LITERALS)
vocab.update(CodeOp.KEYWORDS)
vocab |= set("".join(vocab))
return sorted(vocab) | 0.022535 |
def get_valid_kwargs(func, potential_kwargs):
"""
Return valid kwargs to function func
"""
kwargs = {}
for name in get_kwarg_names(func):
with suppress(KeyError):
kwargs[name] = potential_kwargs[name]
return kwargs | 0.003876 |
def Reload(self):
"""Call `Reload` on every `EventAccumulator`."""
logger.info('Beginning EventMultiplexer.Reload()')
self._reload_called = True
# Build a list so we're safe even if the list of accumulators is modified
# even while we're reloading.
with self._accumulators_mutex:
items = list(self._accumulators.items())
names_to_delete = set()
for name, accumulator in items:
try:
accumulator.Reload()
except (OSError, IOError) as e:
logger.error("Unable to reload accumulator '%s': %s", name, e)
except directory_watcher.DirectoryDeletedError:
names_to_delete.add(name)
with self._accumulators_mutex:
for name in names_to_delete:
logger.warn("Deleting accumulator '%s'", name)
del self._accumulators[name]
logger.info('Finished with EventMultiplexer.Reload()')
return self | 0.006742 |
def extractFieldsFromResult(data):
'''
Method that parses Infobel textual information to return a series of attributes.
:return: a list of i3visio-like objects.
'''
entities = []
# Defining the objects to extract
fieldsRegExp = {}
fieldsRegExp["i3visio.fullname"] = "<span class=\"fn\">([^<]*)</span>"
fieldsRegExp["i3visio.name"] = " por <strong>[^ ]* ([^<]*)</strong>"
fieldsRegExp["i3visio.surname"] = " por <strong>([^ ]*) "
fieldsRegExp["i3visio.location.address"] = "itemprop=\"streetAddress\">([^<]*)</span>"
fieldsRegExp["i3visio.location.city"] = "addressLocality\">([^<]*)</span>"
fieldsRegExp["i3visio.location.postalcode"] = "postalCode\">([^<]*)</span>"
fieldsRegExp["i3visio.phone"] = "document.write\('([0-9]+)'"
for field in fieldsRegExp.keys():
listRecovered = re.findall(fieldsRegExp[field], data)
if len(listRecovered) >0:
aux = {}
aux["type"]= field
aux["value"] = listRecovered[0].replace('\xa0', ' ')
aux["attributes"] = []
entities.append(aux)
return entities | 0.012521 |
def getColorHSV(name):
"""Retrieve the hue, saturation, value triple of a color name.
Returns:
a triple (degree, percent, percent). If not found (-1, -1, -1) is returned.
"""
try:
x = getColorInfoList()[getColorList().index(name.upper())]
except:
return (-1, -1, -1)
r = x[1] / 255.
g = x[2] / 255.
b = x[3] / 255.
cmax = max(r, g, b)
V = round(cmax * 100, 1)
cmin = min(r, g, b)
delta = cmax - cmin
if delta == 0:
hue = 0
elif cmax == r:
hue = 60. * (((g - b)/delta) % 6)
elif cmax == g:
hue = 60. * (((b - r)/delta) + 2)
else:
hue = 60. * (((r - g)/delta) + 4)
H = int(round(hue))
if cmax == 0:
sat = 0
else:
sat = delta / cmax
S = int(round(sat * 100))
return (H, S, V) | 0.008235 |
def longitude(self, longitude):
"""Setter for longitude."""
if not (-180 <= longitude <= 180):
raise ValueError('longitude was {}, but has to be in [-180, 180]'
.format(longitude))
self._longitude = longitude | 0.007326 |
def get_relationship_form_for_update(self, relationship_id=None):
"""Gets the relationship form for updating an existing relationship.
A new relationship form should be requested for each update
transaction.
arg: relationship_id (osid.id.Id): the ``Id`` of the
``Relationship``
return: (osid.relationship.RelationshipForm) - the relationship
form
raise: NotFound - ``relationship_id`` is not found
raise: NullArgument - ``relationship_id`` is ``null``
raise: OperationFailed - unable to complete request
raise: PermissionDenied - authorization failure
*compliance: mandatory -- This method must be implemented.*
"""
if relationship_id is None:
raise NullArgument()
try:
url_path = ('/handcar/services/relationship/families/' +
self._catalog_idstr + '/relationships/' + str(relationship_id))
relationship = objects.Relationship(self._get_request(url_path))
except Exception:
raise
relationship_form = objects.RelationshipForm(relationship._my_map)
self._forms[relationship_form.get_id().get_identifier()] = not UPDATED
return relationship_form | 0.002322 |
def check(codeString, filename, reporter=None):
"""
Check the Python source given by C{codeString} for flakes.
@param codeString: The Python source to check.
@type codeString: C{str}
@param filename: The name of the file the source came from, used to report
errors.
@type filename: C{str}
@param reporter: A L{Reporter} instance, where errors and warnings will be
reported.
@return: The number of warnings emitted.
@rtype: C{int}
"""
if reporter is None:
reporter = modReporter._makeDefaultReporter()
# First, compile into an AST and handle syntax errors.
try:
tree = ast.parse(codeString, filename=filename)
except SyntaxError:
value = sys.exc_info()[1]
msg = value.args[0]
(lineno, offset, text) = value.lineno, value.offset, value.text
if checker.PYPY:
if text is None:
lines = codeString.splitlines()
if len(lines) >= lineno:
text = lines[lineno - 1]
if sys.version_info >= (3, ) and isinstance(text, bytes):
try:
text = text.decode('ascii')
except UnicodeDecodeError:
text = None
offset -= 1
# If there's an encoding problem with the file, the text is None.
if text is None:
# Avoid using msg, since for the only known case, it contains a
# bogus message that claims the encoding the file declared was
# unknown.
reporter.unexpectedError(filename, 'problem decoding source')
else:
reporter.syntaxError(filename, msg, lineno, offset, text)
return 1
except Exception:
reporter.unexpectedError(filename, 'problem decoding source')
return 1
# Okay, it's syntactically valid. Now check it.
file_tokens = checker.make_tokens(codeString)
w = checker.Checker(tree, file_tokens=file_tokens, filename=filename)
w.messages.sort(key=lambda m: m.lineno)
for warning in w.messages:
reporter.flake(warning)
return len(w.messages) | 0.000456 |
def search_terms(q):
'''Takes a search string and parses it into a list of keywords and
phrases.'''
tokens = parse_search_terms(q)
# iterate through all the tokens and make a list of token values
# (which are the actual words and phrases)
values = []
for t in tokens:
# word/phrase
if t[0] is None:
values.append(t[1])
# incomplete field
elif t[1] is None:
values.append('%s:' % t[0])
# anything else must be a field, value pair
# - if value includes whitespace, wrap in quotes
elif re.search('\s', t[1]):
values.append('%s:"%s"' % t)
# otherwise, leave unquoted
else:
values.append('%s:%s' % t)
return values | 0.002628 |
def get_condition(self, service_id, version_number, name):
"""Gets a specified condition."""
content = self._fetch("/service/%s/version/%d/condition/%s" % (service_id, version_number, name))
return FastlyCondition(self, content) | 0.025641 |
def t_escaped_LINE_FEED_CHAR(self, t):
r'\x6E' # 'n'
t.lexer.pop_state()
t.value = unichr(0x000a)
return t | 0.014388 |
def board_fen(self, *, promoted: Optional[bool] = False) -> str:
"""
Gets the board FEN.
"""
builder = []
empty = 0
for square in SQUARES_180:
piece = self.piece_at(square)
if not piece:
empty += 1
else:
if empty:
builder.append(str(empty))
empty = 0
builder.append(piece.symbol())
if promoted and BB_SQUARES[square] & self.promoted:
builder.append("~")
if BB_SQUARES[square] & BB_FILE_H:
if empty:
builder.append(str(empty))
empty = 0
if square != H1:
builder.append("/")
return "".join(builder) | 0.002436 |
def unparse_qs(qs, sort=False, reverse=False):
"""Reverse conversion for parse_qs"""
result = []
items = qs.items()
if sort:
items = sorted(items, key=lambda x: x[0], reverse=reverse)
for keys, values in items:
query_name = quote(keys)
for value in values:
result.append(query_name + "=" + quote(value))
return "&".join(result) | 0.002584 |
def refresh_plugin(self):
"""Refresh tabwidget."""
nb = None
if self.tabwidget.count():
client = self.tabwidget.currentWidget()
nb = client.notebookwidget
nb.setFocus()
else:
nb = None
self.update_notebook_actions() | 0.00641 |
def get_aggregate_check(self, check, age=None):
"""
Returns the list of aggregates for a given check
"""
data = {}
if age:
data['max_age'] = age
result = self._request('GET', '/aggregates/{}'.format(check),
data=json.dumps(data))
return result.json() | 0.005714 |
def setNreps(self, nreps):
"""Sets the number of reps before the raster plot resets"""
for plot in self.responsePlots.values():
plot.setNreps(nreps) | 0.011364 |
def mean_squared_logarithmic_error(pred:Tensor, targ:Tensor)->Rank0Tensor:
"Mean squared logarithmic error between `pred` and `targ`."
pred,targ = flatten_check(pred,targ)
return F.mse_loss(torch.log(1 + pred), torch.log(1 + targ)) | 0.024691 |
def plot_diode_fold(dio_cross,bothfeeds=True,feedtype='l',min_samp=-500,max_samp=7000,legend=True,**kwargs):
'''
Plots the calculated average power and time sampling of ON (red) and
OFF (blue) for a noise diode measurement over the observation time series
'''
#Get full stokes data of ND measurement
obs = Waterfall(dio_cross,max_load=150)
tsamp = obs.header['tsamp']
data = obs.data
obs = None
I,Q,U,V = get_stokes(data,feedtype)
#Calculate time series, OFF and ON averages, and time samples for each
tseriesI = np.squeeze(np.mean(I,axis=2))
I_OFF,I_ON,OFFints,ONints = foldcal(I,tsamp,inds=True,**kwargs)
if bothfeeds==True:
if feedtype=='l':
tseriesQ = np.squeeze(np.mean(Q,axis=2))
tseriesX = (tseriesI+tseriesQ)/2
tseriesY = (tseriesI-tseriesQ)/2
if feedtype=='c':
tseriesV = np.squeeze(np.mean(V,axis=2))
tseriesR = (tseriesI+tseriesV)/2
tseriesL = (tseriesI-tseriesV)/2
stop = ONints[-1,1]
#Plot time series and calculated average for ON and OFF
if bothfeeds==False:
plt.plot(tseriesI[0:stop],'k-',label='Total Power')
for i in ONints:
plt.plot(np.arange(i[0],i[1]),np.full((i[1]-i[0]),np.mean(I_ON)),'r-')
for i in OFFints:
plt.plot(np.arange(i[0],i[1]),np.full((i[1]-i[0]),np.mean(I_OFF)),'b-')
else:
if feedtype=='l':
diff = np.mean(tseriesX)-np.mean(tseriesY)
plt.plot(tseriesX[0:stop],'b-',label='XX')
plt.plot(tseriesY[0:stop]+diff,'r-',label='YY (shifted)')
if feedtype=='c':
diff = np.mean(tseriesL)-np.mean(tseriesR)
plt.plot(tseriesL[0:stop],'b-',label='LL')
plt.plot(tseriesR[0:stop]+diff,'r-',label='RR (shifted)')
#Calculate plotting limits
if bothfeeds==False:
lowlim = np.mean(I_OFF)-(np.mean(I_ON)-np.mean(I_OFF))/2
hilim = np.mean(I_ON)+(np.mean(I_ON)-np.mean(I_OFF))/2
plt.ylim((lowlim,hilim))
plt.xlim((min_samp,max_samp))
plt.xlabel('Time Sample Number')
plt.ylabel('Power (Counts)')
plt.title('Noise Diode Fold')
if legend==True:
plt.legend() | 0.027342 |
def resolve(self, key):
"""
Resolves the requested key to an object instance, raising a KeyError if the key is missing
"""
registration = self._registrations.get(key)
if registration is None:
raise KeyError("Unknown key: '{0}'".format(key))
return registration.resolve(self, key) | 0.008798 |
def get_args():
"""
Get and parse arguments.
"""
import argparse
parser = argparse.ArgumentParser(
description="Swift Navigation SBP Example.")
parser.add_argument(
"-s",
"--serial-port",
default=[DEFAULT_SERIAL_PORT],
nargs=1,
help="specify the serial port to use.")
parser.add_argument(
"-b",
"--baud",
default=[DEFAULT_SERIAL_BAUD],
nargs=1,
help="specify the baud rate to use.")
parser.add_argument(
"-a",
"--address",
default=[DEFAULT_UDP_ADDRESS],
nargs=1,
help="specify the serial port to use.")
parser.add_argument(
"-p",
"--udp-port",
default=[DEFAULT_UDP_PORT],
nargs=1,
help="specify the baud rate to use.")
return parser.parse_args() | 0.001172 |
def ignored_corner(
intersection, tangent_s, tangent_t, edge_nodes1, edge_nodes2
):
"""Check if an intersection is an "ignored" corner.
.. note::
This is a helper used only by :func:`classify_intersection`.
An "ignored" corner is one where the surfaces just "kiss" at
the point of intersection but their interiors do not meet.
We can determine this by comparing the tangent lines from
the point of intersection.
.. note::
This assumes the ``intersection`` has been shifted to the
beginning of a curve so only checks if ``s == 0.0`` or ``t == 0.0``
(rather than also checking for ``1.0``).
Args:
intersection (.Intersection): An intersection to "diagnose".
tangent_s (numpy.ndarray): The tangent vector (``2 x 1`` array) to
the first curve at the intersection.
tangent_t (numpy.ndarray): The tangent vector (``2 x 1`` array) to
the second curve at the intersection.
edge_nodes1 (Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]): The
nodes of the three edges of the first surface being intersected.
edge_nodes2 (Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]): The
nodes of the three edges of the second surface being intersected.
Returns:
bool: Indicates if the corner is to be ignored.
"""
if intersection.s == 0.0:
if intersection.t == 0.0:
# Double corner.
return ignored_double_corner(
intersection, tangent_s, tangent_t, edge_nodes1, edge_nodes2
)
else:
# s-only corner.
prev_index = (intersection.index_first - 1) % 3
prev_edge = edge_nodes1[prev_index]
return ignored_edge_corner(tangent_t, tangent_s, prev_edge)
elif intersection.t == 0.0:
# t-only corner.
prev_index = (intersection.index_second - 1) % 3
prev_edge = edge_nodes2[prev_index]
return ignored_edge_corner(tangent_s, tangent_t, prev_edge)
else:
# Not a corner.
return False | 0.000475 |
def kill(self, signal=None):
"""
Kill or send a signal to the container.
Args:
signal (str or int): The signal to send. Defaults to ``SIGKILL``
Raises:
:py:class:`docker.errors.APIError`
If the server returns an error.
"""
return self.client.api.kill(self.id, signal=signal) | 0.005479 |
def admin_create_user(self, username, temporary_password='', attr_map=None, **kwargs):
"""
Create a user using admin super privileges.
:param username: User Pool username
:param temporary_password: The temporary password to give the user.
Leave blank to make Cognito generate a temporary password for the user.
:param attr_map: Attribute map to Cognito's attributes
:param kwargs: Additional User Pool attributes
:return response: Response from Cognito
"""
response = self.client.admin_create_user(
UserPoolId=self.user_pool_id,
Username=username,
UserAttributes=dict_to_cognito(kwargs, attr_map),
TemporaryPassword=temporary_password,
)
kwargs.update(username=username)
self._set_attributes(response, kwargs)
response.pop('ResponseMetadata')
return response | 0.003236 |
def plot_irm(fignum, B, M, title):
"""
function to plot IRM backfield curves
Parameters
_________
fignum : matplotlib figure number
B : list or array of field values
M : list or array of magnetizations
title : string title for plot
"""
rpars = {}
Mnorm = []
backfield = 0
X, Y = [], []
for k in range(len(B)):
if M[k] < 0:
break
if k <= 5:
kmin = 0
else:
kmin = k - 5
for k in range(kmin, k + 1):
X.append(B[k])
if B[k] < 0:
backfield = 1
Y.append(M[k])
if backfield == 1:
poly = np.polyfit(X, Y, 1)
if poly[0] != 0:
bcr = (old_div(-poly[1], poly[0]))
else:
bcr = 0
rpars['remanence_mr_moment'] = '%8.3e' % (M[0])
rpars['remanence_bcr'] = '%8.3e' % (-bcr)
rpars['magic_method_codes'] = 'LP-BCR-BF'
if M[0] != 0:
for m in M:
Mnorm.append(old_div(m, M[0])) # normalize to unity Msat
title = title + ':' + '%8.3e' % (M[0])
else:
if M[-1] != 0:
for m in M:
Mnorm.append(old_div(m, M[-1])) # normalize to unity Msat
title = title + ':' + '%8.3e' % (M[-1])
# do plots if desired
if fignum != 0 and M[0] != 0: # skip plot for fignum = 0
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(B, Mnorm)
plt.axhline(0, color='k')
plt.axvline(0, color='k')
plt.xlabel('B (T)')
plt.ylabel('M/Mr')
plt.title(title)
if backfield == 1:
plt.scatter([bcr], [0], marker='s', c='b')
bounds = plt.axis()
n1 = 'Bcr: ' + '%8.2e' % (-bcr) + ' T'
plt.figtext(.2, .5, n1)
n2 = 'Mr: ' + '%8.2e' % (M[0]) + ' Am^2'
plt.figtext(.2, .45, n2)
elif fignum != 0:
plt.figure(num=fignum)
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
print('M[0]=0, skipping specimen')
return rpars | 0.000466 |
def compose(self, *args):
"""
Returns a function that is the composition of a list of functions, each
consuming the return value of the function that follows.
"""
args = list(args)
def composed(*ar, **kwargs):
lastRet = self.obj(*ar, **kwargs)
for i in args:
lastRet = i(lastRet)
return lastRet
return self._wrap(composed) | 0.004619 |
def classify_harmonic(self, partial_labels, use_CMN=True):
'''Harmonic function method for semi-supervised classification,
also known as the Gaussian Mean Fields algorithm.
partial_labels: (n,) array of integer labels, -1 for unlabeled.
use_CMN : when True, apply Class Mass Normalization
From "Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions"
by Zhu, Ghahramani, and Lafferty in 2003.
Based on the matlab code at:
http://pages.cs.wisc.edu/~jerryzhu/pub/harmonic_function.m
'''
# prepare labels
labels = np.array(partial_labels, copy=True)
unlabeled = labels == -1
# convert known labels to one-hot encoding
fl, classes = _onehot(labels[~unlabeled])
L = self.laplacian(normed=False)
if ss.issparse(L):
L = L.tocsr()[unlabeled].toarray()
else:
L = L[unlabeled]
Lul = L[:,~unlabeled]
Luu = L[:,unlabeled]
fu = -np.linalg.solve(Luu, Lul.dot(fl))
if use_CMN:
scale = (1 + fl.sum(axis=0)) / fu.sum(axis=0)
fu *= scale
# assign new labels
labels[unlabeled] = classes[fu.argmax(axis=1)]
return labels | 0.006975 |
def check_child_friendly(self, name):
"""
Check if a module is a container and so can have children
"""
name = name.split()[0]
if name in self.container_modules:
return
root = os.path.dirname(os.path.realpath(__file__))
module_path = os.path.join(root, "modules")
try:
info = imp.find_module(name, [module_path])
except ImportError:
return
if not info:
return
(file, pathname, description) = info
try:
py_mod = imp.load_module(name, file, pathname, description)
except Exception:
# We cannot load the module! We could error out here but then the
# user gets informed that the problem is with their config. This
# is not correct. Better to say that all is well and then the
# config can get parsed and py3status loads. The error about the
# failing module load is better handled at that point, and will be.
return
try:
container = py_mod.Py3status.Meta.container
except AttributeError:
container = False
# delete the module
del py_mod
if container:
self.container_modules.append(name)
else:
self.error("Module `{}` cannot contain others".format(name)) | 0.001443 |
def unassign_authorization_from_vault(self, authorization_id, vault_id):
"""Removes an ``Authorization`` from a ``Vault``.
arg: authorization_id (osid.id.Id): the ``Id`` of the
``Authorization``
arg: vault_id (osid.id.Id): the ``Id`` of the ``Vault``
raise: NotFound - ``authorization_id`` or ``vault_id`` not
found or ``authorization_id`` not assigned to
``vault_id``
raise: NullArgument - ``authorization_id`` or ``vault_id`` is
``null``
raise: OperationFailed - unable to complete request
raise: PermissionDenied - authorization failure
*compliance: mandatory -- This method must be implemented.*
"""
# Implemented from template for
# osid.resource.ResourceBinAssignmentSession.unassign_resource_from_bin
mgr = self._get_provider_manager('AUTHORIZATION', local=True)
lookup_session = mgr.get_vault_lookup_session(proxy=self._proxy)
lookup_session.get_vault(vault_id) # to raise NotFound
self._unassign_object_from_catalog(authorization_id, vault_id) | 0.001741 |
def setup(self, phase=None, quantity='', diffusive_conductance='',
hydraulic_conductance='', pressure='', s_scheme='', **kwargs):
r"""
"""
if phase:
self.settings['phase'] = phase.name
if quantity:
self.settings['quantity'] = quantity
if diffusive_conductance:
self.settings['diffusive_conductance'] = diffusive_conductance
if hydraulic_conductance:
self.settings['hydraulic_conductance'] = hydraulic_conductance
if pressure:
self.settings['pressure'] = pressure
if s_scheme:
self.settings['s_scheme'] = s_scheme
super().setup(**kwargs) | 0.004317 |
def get_schema(frame, name, keys=None, con=None, dtype=None):
"""
Get the SQL db table schema for the given frame.
Parameters
----------
frame : DataFrame
name : string
name of SQL table
keys : string or sequence, default: None
columns to use a primary key
con: an open SQL database connection object or a SQLAlchemy connectable
Using SQLAlchemy makes it possible to use any DB supported by that
library, default: None
If a DBAPI2 object, only sqlite3 is supported.
dtype : dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
"""
pandas_sql = pandasSQL_builder(con=con)
return pandas_sql._create_sql_schema(frame, name, keys=keys, dtype=dtype) | 0.00114 |
def getOption(self, name):
"""
Get the current value of the specified option. If the option does not
exist, returns None.
Args:
name: Option name.
Returns:
Value of the option.
Raises:
InvalidArgumet: if the option name is not valid.
"""
try:
value = lock_and_call(
lambda: self._impl.getOption(name).value(),
self._lock
)
except RuntimeError:
return None
else:
try:
return int(value)
except ValueError:
try:
return float(value)
except ValueError:
return value | 0.002625 |
def loss(self, xs, ys):
"""Computes the loss of the network."""
return float(
self.sess.run(
self.cross_entropy, feed_dict={
self.x: xs,
self.y_: ys
})) | 0.007937 |
def get(obj):
"""
Determines file format and picks suitable file types, extensions and MIME types
Takes:
obj (bytes) -> byte sequence (128 bytes are enough)
Returns:
(<class 'fleep.Info'>) -> Class instance
"""
if not isinstance(obj, bytes):
raise TypeError("object type must be bytes")
info = {
"type": dict(),
"extension": dict(),
"mime": dict()
}
stream = " ".join(['{:02X}'.format(byte) for byte in obj])
for element in data:
for signature in element["signature"]:
offset = element["offset"] * 2 + element["offset"]
if signature == stream[offset:len(signature) + offset]:
for key in ["type", "extension", "mime"]:
info[key][element[key]] = len(signature)
for key in ["type", "extension", "mime"]:
info[key] = [element for element in sorted(info[key], key=info[key].get, reverse=True)]
return Info(info["type"], info["extension"], info["mime"]) | 0.002921 |
def drawBackground(self, painter, rect):
"""When an area of the window is exposed, we just copy out of the
server-side, off-screen pixmap to that area.
"""
if not self.pixmap:
return
x1, y1, x2, y2 = rect.getCoords()
width = x2 - x1 + 1
height = y2 - y1 + 1
# redraw the screen from backing pixmap
rect = QtCore.QRect(x1, y1, width, height)
painter.drawPixmap(rect, self.pixmap, rect) | 0.004193 |
def _ppf(self, q, dist, cache):
"""Point percentile function."""
return -evaluation.evaluate_inverse(dist, 1-q, cache=cache) | 0.014286 |
def HumanReadableStartType(self):
"""Return a human readable string describing the start type value.
Returns:
str: human readable description of the start type value.
"""
if isinstance(self.start_type, py2to3.STRING_TYPES):
return self.start_type
return human_readable_service_enums.SERVICE_ENUMS['Start'].get(
self.start_type, '{0:d}'.format(self.start_type)) | 0.004988 |
def subdict_match(data,
expr,
delimiter=DEFAULT_TARGET_DELIM,
regex_match=False,
exact_match=False):
'''
Check for a match in a dictionary using a delimiter character to denote
levels of subdicts, and also allowing the delimiter character to be
matched. Thus, 'foo:bar:baz' will match data['foo'] == 'bar:baz' and
data['foo']['bar'] == 'baz'. The latter would take priority over the
former, as more deeply-nested matches are tried first.
'''
def _match(target, pattern, regex_match=False, exact_match=False):
# The reason for using six.text_type first and _then_ using
# to_unicode as a fallback is because we want to eventually have
# unicode types for comparison below. If either value is numeric then
# six.text_type will turn it into a unicode string. However, if the
# value is a PY2 str type with non-ascii chars, then the result will be
# a UnicodeDecodeError. In those cases, we simply use to_unicode to
# decode it to unicode. The reason we can't simply use to_unicode to
# begin with is that (by design) to_unicode will raise a TypeError if a
# non-string/bytestring/bytearray value is passed.
try:
target = six.text_type(target).lower()
except UnicodeDecodeError:
target = salt.utils.stringutils.to_unicode(target).lower()
try:
pattern = six.text_type(pattern).lower()
except UnicodeDecodeError:
pattern = salt.utils.stringutils.to_unicode(pattern).lower()
if regex_match:
try:
return re.match(pattern, target)
except Exception:
log.error('Invalid regex \'%s\' in match', pattern)
return False
else:
return target == pattern if exact_match \
else fnmatch.fnmatch(target, pattern)
def _dict_match(target, pattern, regex_match=False, exact_match=False):
wildcard = pattern.startswith('*:')
if wildcard:
pattern = pattern[2:]
if pattern == '*':
# We are just checking that the key exists
return True
elif pattern in target:
# We might want to search for a key
return True
elif subdict_match(target,
pattern,
regex_match=regex_match,
exact_match=exact_match):
return True
if wildcard:
for key in target:
if isinstance(target[key], dict):
if _dict_match(target[key],
pattern,
regex_match=regex_match,
exact_match=exact_match):
return True
elif isinstance(target[key], list):
for item in target[key]:
if _match(item,
pattern,
regex_match=regex_match,
exact_match=exact_match):
return True
elif _match(target[key],
pattern,
regex_match=regex_match,
exact_match=exact_match):
return True
return False
splits = expr.split(delimiter)
num_splits = len(splits)
if num_splits == 1:
# Delimiter not present, this can't possibly be a match
return False
splits = expr.split(delimiter)
num_splits = len(splits)
if num_splits == 1:
# Delimiter not present, this can't possibly be a match
return False
# If we have 4 splits, then we have three delimiters. Thus, the indexes we
# want to use are 3, 2, and 1, in that order.
for idx in range(num_splits - 1, 0, -1):
key = delimiter.join(splits[:idx])
if key == '*':
# We are matching on everything under the top level, so we need to
# treat the match as the entire data being passed in
matchstr = expr
match = data
else:
matchstr = delimiter.join(splits[idx:])
match = traverse_dict_and_list(data, key, {}, delimiter=delimiter)
log.debug("Attempting to match '%s' in '%s' using delimiter '%s'",
matchstr, key, delimiter)
if match == {}:
continue
if isinstance(match, dict):
if _dict_match(match,
matchstr,
regex_match=regex_match,
exact_match=exact_match):
return True
continue
if isinstance(match, (list, tuple)):
# We are matching a single component to a single list member
for member in match:
if isinstance(member, dict):
if _dict_match(member,
matchstr,
regex_match=regex_match,
exact_match=exact_match):
return True
if _match(member,
matchstr,
regex_match=regex_match,
exact_match=exact_match):
return True
continue
if _match(match,
matchstr,
regex_match=regex_match,
exact_match=exact_match):
return True
return False | 0.000176 |
def pykeyword(operation='list', keywordtotest=None):
"""
Check if a keyword exists in the Python keyword dictionary.
:type operation: string
:param operation: Whether to list or check the keywords. Possible options are 'list' and 'in'.
:type keywordtotest: string
:param keywordtotest: The keyword to check.
:return: The list of keywords or if a keyword exists.
:rtype: list or boolean
>>> "True" in pykeyword("list")
True
>>> pykeyword("in", "True")
True
>>> pykeyword("in", "foo")
False
>>> pykeyword("foo", "foo")
Traceback (most recent call last):
...
ValueError: Invalid operation specified.
"""
# If the operation was 'list'
if operation == 'list':
# Return an array of keywords
return str(keyword.kwlist)
# If the operation was 'in'
elif operation == 'in':
# Return a boolean for if the string was a keyword
return keyword.iskeyword(str(keywordtotest))
# Raise a warning
raise ValueError("Invalid operation specified.") | 0.001869 |
def append(self, png, **options):
"""Append one frame.
:arg PNG png: Append a :class:`PNG` as a frame.
:arg dict options: The options for :class:`FrameControl`.
"""
if not isinstance(png, PNG):
raise TypeError("Expect an instance of `PNG` but got `{}`".format(png))
control = FrameControl(**options)
if control.width is None:
control.width = png.width
if control.height is None:
control.height = png.height
self.frames.append((png, control)) | 0.03397 |
def countByValueAndWindow(self, windowDuration, slideDuration, numPartitions=None):
"""
Return a new DStream in which each RDD contains the count of distinct elements in
RDDs in a sliding window over this DStream.
@param windowDuration: width of the window; must be a multiple of this DStream's
batching interval
@param slideDuration: sliding interval of the window (i.e., the interval after which
the new DStream will generate RDDs); must be a multiple of this
DStream's batching interval
@param numPartitions: number of partitions of each RDD in the new DStream.
"""
keyed = self.map(lambda x: (x, 1))
counted = keyed.reduceByKeyAndWindow(operator.add, operator.sub,
windowDuration, slideDuration, numPartitions)
return counted.filter(lambda kv: kv[1] > 0) | 0.009221 |
def convert_list_elements(self):
"""
A sequence of two or more items, which may or may not be ordered.
The <list> element has an optional <label> element and optional <title>
element, followed by one or more <list-item> elements. This is element
is recursive as the <list-item> elements may contain further <list> or
<def-list> elements. Much of the potential complexity in dealing with
lists comes from this recursion.
"""
#I have yet to gather many examples of this element, and may have to
#write a recursive method for the processing of lists depending on how
#PLoS produces their XML, for now this method is ignorant of nesting
#TODO: prefix-words, one possible solution would be to have this method
#edit the CSS to provide formatting support for arbitrary prefixes...
#This is a block level element, so elevate it if found in p
for list_el in self.main.getroot().findall('.//list'):
if list_el.getparent().tag == 'p':
elevate_element(list_el)
#list_el is used instead of list (list is reserved)
for list_el in self.main.getroot().findall('.//list'):
if 'list-type' not in list_el.attrib:
list_el_type = 'order'
else:
list_el_type = list_el.attrib['list-type']
#Unordered lists
if list_el_type in ['', 'bullet', 'simple']:
list_el.tag = 'ul'
#CSS must be used to recognize the class and suppress bullets
if list_el_type == 'simple':
list_el.attrib['class'] = 'simple'
#Ordered lists
else:
list_el.tag = 'ol'
list_el.attrib['class'] = list_el_type
#Convert the list-item element tags to 'li'
for list_item in list_el.findall('list-item'):
list_item.tag = 'li'
remove_all_attributes(list_el, exclude=['id', 'class']) | 0.00636 |
def _startDPDrag(self):
"""Callback for item menu."""
dp = self._dp_menu_on
if dp and dp.archived:
drag = QDrag(self)
mimedata = QMimeData()
mimedata.setUrls([QUrl.fromLocalFile(dp.fullpath)])
drag.setMimeData(mimedata)
drag.exec_(Qt.CopyAction | Qt.LinkAction) | 0.005797 |
def cee_map_name(self, **kwargs):
"""Auto Generated Code
"""
config = ET.Element("config")
cee_map = ET.SubElement(config, "cee-map", xmlns="urn:brocade.com:mgmt:brocade-cee-map")
name = ET.SubElement(cee_map, "name")
name.text = kwargs.pop('name')
callback = kwargs.pop('callback', self._callback)
return callback(config) | 0.007752 |
def propose_live(self):
"""Return a live point/axes to be used by other sampling methods."""
# Copy a random live point.
i = self.rstate.randint(self.nlive)
u = self.live_u[i, :]
# Check for ellipsoid overlap.
ell_idxs = self.mell.within(u)
nidx = len(ell_idxs)
# Automatically trigger an update if we're not in any ellipsoid.
if nidx == 0:
try:
# Expected ln(prior volume) at a given iteration.
expected_vol = math.exp(self.saved_logvol[-1] - self.dlv)
except:
# Expected ln(prior volume) at the first iteration.
expected_vol = math.exp(-self.dlv)
pointvol = expected_vol / self.nlive # minimum point volume
# Update the bounding ellipsoids.
bound = self.update(pointvol)
if self.save_bounds:
self.bound.append(bound)
self.nbound += 1
self.since_update = 0
# Check for ellipsoid overlap (again).
ell_idxs = self.mell.within(u)
nidx = len(ell_idxs)
# Pick a random ellipsoid that encompasses `u`.
ell_idx = ell_idxs[self.rstate.randint(nidx)]
# Choose axes.
if self.sampling in ['rwalk', 'rstagger', 'rslice']:
ax = self.mell.ells[ell_idx].axes
elif self.sampling == 'slice':
ax = self.mell.ells[ell_idx].paxes
else:
ax = np.identity(self.npdim)
return u, ax | 0.001944 |
def _ask_local_config(self):
""" Ask some parameters about the local configuration """
options = {"backend": "local", "local-config": {}}
# Concurrency
while True:
concurrency = self._ask_with_default(
"Maximum concurrency (number of tasks running simultaneously). Leave it empty to use the number of "
"CPU of your host.", "")
if concurrency == "":
break
try:
concurrency = int(concurrency)
except:
self._display_error("Invalid number")
continue
if concurrency <= 0:
self._display_error("Invalid number")
continue
options["local-config"]["concurrency"] = concurrency
break
# Debug hostname
hostname = self._ask_with_default(
"What is the external hostname/address of your machine? You can leave this empty and let INGInious "
"autodetect it.", "")
if hostname != "":
options["local-config"]["debug_host"] = hostname
self._display_info(
"You can now enter the port range for the remote debugging feature of INGInious. Please verify that these "
"ports are open in your firewall. You can leave this parameters empty, the default is 64100-64200")
# Debug port range
port_range = None
while True:
start_port = self._ask_with_default("Beginning of the range", "")
if start_port != "":
try:
start_port = int(start_port)
except:
self._display_error("Invalid number")
continue
end_port = self._ask_with_default("End of the range", str(start_port + 100))
try:
end_port = int(end_port)
except:
self._display_error("Invalid number")
continue
if start_port > end_port:
self._display_error("Invalid range")
continue
port_range = str(start_port) + "-" + str(end_port)
else:
break
if port_range != None:
options["local-config"]["debug_ports"] = port_range
return options | 0.004632 |
def ensure():
"""
Makes sure the current working directory is a Git repository.
"""
LOGGER.debug('checking repository')
if not os.path.exists('.git'):
LOGGER.error('This command is meant to be ran in a Git repository.')
sys.exit(-1)
LOGGER.debug('repository OK') | 0.008982 |
def _expected_reads(run_info_file):
"""Parse the number of expected reads from the RunInfo.xml file.
"""
reads = []
if os.path.exists(run_info_file):
tree = ElementTree()
tree.parse(run_info_file)
read_elem = tree.find("Run/Reads")
reads = read_elem.findall("Read")
return len(reads) | 0.002985 |
def is_alpha_number(number):
"""Checks if the number is a valid vanity (alpha) number such as 800
MICROSOFT. A valid vanity number will start with at least 3 digits and
will have three or more alpha characters. This does not do region-specific
checks - to work out if this number is actually valid for a region, it
should be parsed and methods such as is_possible_number_with_reason() and
is_valid_number() should be used.
Arguments:
number -- the number that needs to be checked
Returns True if the number is a valid vanity number
"""
if not _is_viable_phone_number(number):
# Number is too short, or doesn't match the basic phone number pattern.
return False
extension, stripped_number = _maybe_strip_extension(number)
return bool(fullmatch(_VALID_ALPHA_PHONE_PATTERN, stripped_number)) | 0.001166 |
def haversine(point1, point2, unit='km'):
""" Calculate the great-circle distance between two points on the Earth surface.
:input: two 2-tuples, containing the latitude and longitude of each point
in decimal degrees.
Keyword arguments:
unit -- a string containing the initials of a unit of measurement (i.e. miles = mi)
default 'km' (kilometers).
Example: haversine((45.7597, 4.8422), (48.8567, 2.3508))
:output: Returns the distance between the two points.
The default returned unit is kilometers. The default unit can be changed by
setting the unit parameter to a string containing the initials of the desired unit.
Other available units are miles (mi), nautic miles (nmi), meters (m),
feets (ft) and inches (in).
"""
# mean earth radius - https://en.wikipedia.org/wiki/Earth_radius#Mean_radius
AVG_EARTH_RADIUS_KM = 6371.0088
# Units values taken from http://www.unitconversion.org/unit_converter/length.html
conversions = {'km': 1,
'm': 1000,
'mi': 0.621371192,
'nmi': 0.539956803,
'ft': 3280.839895013,
'in': 39370.078740158}
# get earth radius in required units
avg_earth_radius = AVG_EARTH_RADIUS_KM * conversions[unit]
# unpack latitude/longitude
lat1, lng1 = point1
lat2, lng2 = point2
# convert all latitudes/longitudes from decimal degrees to radians
lat1, lng1, lat2, lng2 = map(radians, (lat1, lng1, lat2, lng2))
# calculate haversine
lat = lat2 - lat1
lng = lng2 - lng1
d = sin(lat * 0.5) ** 2 + cos(lat1) * cos(lat2) * sin(lng * 0.5) ** 2
return 2 * avg_earth_radius * asin(sqrt(d)) | 0.003472 |
def experiments_predictions_create(self, experiment_id, model_id, argument_defs, name, arguments=None, properties=None):
"""Create new model run for given experiment.
Parameters
----------
experiment_id : string
Unique experiment identifier
model_id : string
Unique identifier of model to run
name : string
User-provided name for the model run
argument_defs : list(attribute.AttributeDefinition)
Definition of valid arguments for the given model
arguments : list(dict('name':...,'value:...')), optional
List of attribute instances
properties : Dictionary, optional
Set of model run properties.
Returns
-------
ModelRunHandle
Handle for created model run or None if experiment is unknown
"""
# Get experiment to ensure that it exists
if self.experiments_get(experiment_id) is None:
return None
# Return created model run
return self.predictions.create_object(
name,
experiment_id,
model_id,
argument_defs,
arguments=arguments,
properties=properties
) | 0.002375 |
def create(cls, session, record, imported=False, auto_reply=False):
"""Create a conversation.
Please note that conversation cannot be created with more than 100
threads, if attempted the API will respond with HTTP 412.
Args:
session (requests.sessions.Session): Authenticated session.
record (helpscout.models.Conversation): The conversation
to be created.
imported (bool, optional): The ``imported`` request parameter
enables conversations to be created for historical purposes (i.e.
if moving from a different platform, you can import your
history). When ``imported`` is set to ``True``, no outgoing
emails or notifications will be generated.
auto_reply (bool): The ``auto_reply`` request parameter enables
auto replies to be sent when a conversation is created via the
API. When ``auto_reply`` is set to ``True``, an auto reply will
be sent as long as there is at least one ``customer`` thread in
the conversation.
Returns:
helpscout.models.Conversation: Newly created conversation.
"""
return super(Conversations, cls).create(
session,
record,
imported=imported,
auto_reply=auto_reply,
) | 0.001446 |
def p_route(self, p):
"""route : ROUTE route_name route_version route_io route_deprecation NL \
INDENT docsection attrssection DEDENT
| ROUTE route_name route_version route_io route_deprecation NL"""
p[0] = AstRouteDef(self.path, p.lineno(1), p.lexpos(1), p[2], p[3], p[5], *p[4])
if len(p) > 7:
p[0].set_doc(p[8])
if p[9]:
keys = set()
for attr in p[9]:
if attr.name in keys:
msg = "Attribute '%s' defined more than once." % attr.name
self.errors.append((msg, attr.lineno, attr.path))
keys.add(attr.name)
p[0].set_attrs(p[9]) | 0.007989 |
def free(self):
"""Remove the lock on the connection if the connection is not active
:raises: ConnectionBusyError
"""
LOGGER.debug('Connection %s freeing', self.id)
if self.handle.isexecuting():
raise ConnectionBusyError(self)
with self._lock:
self.used_by = None
LOGGER.debug('Connection %s freed', self.id) | 0.005128 |
def saltpath():
'''
Return the path of the salt module
'''
# Provides:
# saltpath
salt_path = os.path.abspath(os.path.join(__file__, os.path.pardir))
return {'saltpath': os.path.dirname(salt_path)} | 0.004405 |
def can_download(self, dist, force=False):
"""
Can download if location/file does not exist or if force=True
:param dist:
:param force:
:return: True/False
"""
return not os.path.exists(os.path.join(self.output, dist['basename'])) or force | 0.010169 |
def trimRight(self, amount):
"""
Trim this fastqSequence in-place by removing <amount> nucleotides from
the 3' end (right end).
:param amount: the number of nucleotides to trim from the right-side of
this sequence.
"""
if amount == 0:
return
self.sequenceData = self.sequenceData[:-amount]
self.seq_qual = self.seq_qual[:-amount] | 0.005063 |
def update_line(s, bold=False, underline=False, blinking=False, color=None, bgcolor=None):
"""
Overwrites the output of the current line and prints s on the same line
without a new line.
"""
s = get_line(s, bold=bold, underline=underline, blinking=blinking,
color=color, bgcolor=bgcolor, update_line=True)
print(s, end='') | 0.005495 |
def _http_error_handler(http_error):
''' Simple error handler for azure.'''
message = str(http_error)
if http_error.respbody is not None:
message += '\n' + http_error.respbody.decode('utf-8-sig')
raise AzureHttpError(message, http_error.status) | 0.003731 |
def _proxy(self):
"""
Generate an instance context for the instance, the context is capable of
performing various actions. All instance actions are proxied to the context
:returns: ModelBuildContext for this ModelBuildInstance
:rtype: twilio.rest.autopilot.v1.assistant.model_build.ModelBuildContext
"""
if self._context is None:
self._context = ModelBuildContext(
self._version,
assistant_sid=self._solution['assistant_sid'],
sid=self._solution['sid'],
)
return self._context | 0.008143 |
def readOne(stream, validate=False, transform=True, ignoreUnreadable=False,
allowQP=False):
"""
Return the first component from stream.
"""
return next(readComponents(stream, validate, transform, ignoreUnreadable,
allowQP)) | 0.003546 |
def dt2ts(dt, drop_micro=False):
''' convert datetime objects to timestamp seconds (float) '''
is_true(HAS_DATEUTIL, "`pip install python_dateutil` required")
if is_empty(dt, except_=False):
ts = None
elif isinstance(dt, (int, long, float)): # its a ts already
ts = float(dt)
elif isinstance(dt, basestring): # convert to datetime first
try:
parsed_dt = float(dt)
except (TypeError, ValueError):
parsed_dt = dt_parse(dt)
ts = dt2ts(parsed_dt)
else:
assert isinstance(dt, (datetime, date))
# keep micros; see: http://stackoverflow.com/questions/7031031
ts = ((
timegm(dt.timetuple()) * 1000.0) +
(dt.microsecond / 1000.0)) / 1000.0
if ts is None:
pass
elif drop_micro:
ts = float(int(ts))
else:
ts = float(ts)
return ts | 0.001116 |
def sort(records: Sequence[Record]) -> List[Record]:
"Sort records into a canonical order, suitable for comparison."
return sorted(records, key=_record_key) | 0.006098 |
def get_dev_at_mountpoint(mntpoint):
"""
Retrieves the device mounted at mntpoint, or raises
MountError if none.
"""
results = util.subp(['findmnt', '-o', 'SOURCE', mntpoint])
if results.return_code != 0:
raise MountError('No device mounted at %s' % mntpoint)
stdout = results.stdout.decode(sys.getdefaultencoding())
return stdout.replace('SOURCE\n', '').strip().split('\n')[-1] | 0.004396 |
def true_num_genes(model, custom_spont_id=None):
"""Return the number of genes in a model ignoring spontaneously labeled genes.
Args:
model (Model):
custom_spont_id (str): Optional custom spontaneous ID if it does not match the regular expression ``[Ss](_|)0001``
Returns:
int: Number of genes excluding spontaneous genes
"""
true_num = 0
for gene in model.genes:
if not is_spontaneous(gene, custom_id=custom_spont_id):
true_num += 1
return true_num | 0.005725 |
def get_lat_long(self, callsign, timestamp=timestamp_now):
""" Returns Latitude and Longitude for a callsign
Args:
callsign (str): Amateur Radio callsign
timestamp (datetime, optional): datetime in UTC (tzinfo=pytz.UTC)
Returns:
dict: Containing Latitude and Longitude
Raises:
KeyError: No data found for callsign
Example:
The following code returns Latitude & Longitude for "DH1TW"
>>> from pyhamtools import LookupLib, Callinfo
>>> my_lookuplib = LookupLib(lookuptype="countryfile")
>>> cic = Callinfo(my_lookuplib)
>>> cic.get_lat_long("DH1TW")
{
'latitude': 51.0,
'longitude': -10.0
}
Note:
Unfortunately, in most cases the returned Latitude and Longitude are not very precise.
Clublog and Country-files.com use the country's capital coordinates in most cases, if no
dedicated entry in the database exists. Best results will be retrieved with QRZ.com Lookup.
"""
callsign_data = self.get_all(callsign, timestamp=timestamp)
return {
const.LATITUDE: callsign_data[const.LATITUDE],
const.LONGITUDE: callsign_data[const.LONGITUDE]
} | 0.003723 |
def finalize(self):
"""
Finalize the visualization to create an "origin grid" feel instead of
the default matplotlib feel. Set the title, remove spines, and label
the grid with components. This function also adds a legend from the
sizes if required.
"""
# Set the default title if a user hasn't supplied one
self.set_title("{} Intercluster Distance Map (via {})".format(
self.estimator.__class__.__name__, self.embedding.upper()
))
# Create the origin grid and minimalist display
self.ax.set_xticks([0])
self.ax.set_yticks([0])
self.ax.set_xticklabels([])
self.ax.set_yticklabels([])
self.ax.set_xlabel("PC2")
self.ax.set_ylabel("PC1")
# Make the legend by creating an inset axes that shows relative sizing
# based on the scoring metric supplied by the user.
if self.legend:
self._make_size_legend()
return self.ax | 0.001998 |
def continuous_decode_on_train_data(self):
"""Decode from dataset on new checkpoint."""
for _ in next_checkpoint(self._hparams.model_dir,
self._decode_hparams.decode_timeout_mins):
self.decode(dataset_split=tf.estimator.ModeKeys.TRAIN) | 0.007194 |
def _build_units(indep_units, dep_units, op):
"""Build unit math operations."""
if (not dep_units) and (not indep_units):
return ""
if dep_units and (not indep_units):
return dep_units
if (not dep_units) and indep_units:
return (
remove_extra_delims("1{0}({1})".format(op, indep_units))
if op == "/"
else remove_extra_delims("({0})".format(indep_units))
)
return remove_extra_delims("({0}){1}({2})".format(dep_units, op, indep_units)) | 0.003831 |
def safe_index(cls, unique_id):
""" Return a valid elastic index generated from unique_id """
index = unique_id
if unique_id:
index = unique_id.replace("/", "_").lower()
return index | 0.00885 |
def end_of_history(event):
"""
Move to the end of the input history, i.e., the line currently being entered.
"""
event.current_buffer.history_forward(count=10**100)
buff = event.current_buffer
buff.go_to_history(len(buff._working_lines) - 1) | 0.007547 |
def show(fig=None, path='_map.html', **kwargs):
"""
Convert a Matplotlib Figure to a Leaflet map. Open in a browser
Parameters
----------
fig : figure, default gcf()
Figure used to convert to map
path : string, default '_map.html'
Filename where output html will be saved
See fig_to_html() for description of keyword args.
"""
import webbrowser
fullpath = os.path.abspath(path)
with open(fullpath, 'w') as f:
save_html(fig, fileobj=f, **kwargs)
webbrowser.open('file://' + fullpath) | 0.001795 |
def get_next_grade(self):
"""Gets the next ``Grade`` in this list.
return: (osid.grading.Grade) - the next ``Grade`` in this list.
The ``has_next()`` method should be used to test that a
next ``Grade`` is available before calling this method.
raise: IllegalState - no more elements available in this list
raise: OperationFailed - unable to complete request
*compliance: mandatory -- This method must be implemented.*
"""
try:
next_object = next(self)
except StopIteration:
raise IllegalState('no more elements available in this list')
except Exception: # Need to specify exceptions here!
raise OperationFailed()
else:
return next_object | 0.002497 |
def stdio_mgr(in_str=""):
r"""Subsitute temporary text buffers for `stdio` in a managed context.
Context manager.
Substitutes empty :cls:`~io.StringIO`\ s for
:cls:`sys.stdout` and :cls:`sys.stderr`,
and a :cls:`TeeStdin` for :cls:`sys.stdin` within the managed context.
Upon exiting the context, the original stream objects are restored
within :mod:`sys`, and the temporary streams are closed.
Parameters
----------
in_str
|str| *(optional)* -- Initialization text for
the :cls:`TeeStdin` substitution for `stdin`.
Default is an empty string.
Yields
------
in_
:cls:`TeeStdin` -- Temporary stream for `stdin`.
out_
:cls:`~io.StringIO` -- Temporary stream for `stdout`,
initially empty.
err_
:cls:`~io.StringIO` -- Temporary stream for `stderr`,
initially empty.
"""
old_stdin = sys.stdin
old_stdout = sys.stdout
old_stderr = sys.stderr
new_stdout = StringIO()
new_stderr = StringIO()
new_stdin = TeeStdin(new_stdout, in_str)
sys.stdin = new_stdin
sys.stdout = new_stdout
sys.stderr = new_stderr
yield new_stdin, new_stdout, new_stderr
sys.stdin = old_stdin
sys.stdout = old_stdout
sys.stderr = old_stderr
new_stdin.close()
new_stdout.close()
new_stderr.close() | 0.00073 |
def set_session_info(self, info):
'''
:type info: :class:`~kitty.data.data_manager.SessionInfo`
:param info: info to set
'''
if not self.info:
self.info = SessionInfo()
info_d = self.info.as_dict()
ks = []
vs = []
for k, v in info_d.items():
ks.append(k)
vs.append(v)
self.insert(ks, vs)
changed = self.info.copy(info)
if changed:
self.update(self.info.as_dict()) | 0.003738 |
def package_installed(self,
package,
shutit_pexpect_child=None,
note=None,
loglevel=logging.DEBUG):
"""Returns True if we can be sure the package is installed.
@param package: Package as a string, eg 'wget'.
@param shutit_pexpect_child: See send()
@param note: See send()
@rtype: boolean
"""
shutit_pexpect_child = shutit_pexpect_child or self.get_current_shutit_pexpect_session().pexpect_child
shutit_pexpect_session = self.get_shutit_pexpect_session_from_child(shutit_pexpect_child)
return shutit_pexpect_session(package,note=note,loglevel=loglevel) | 0.039474 |
def executeOnController(self, clusterId, script, lang):
"""
Parameters:
- clusterId
- script
- lang
"""
self.send_executeOnController(clusterId, script, lang)
return self.recv_executeOnController() | 0.007576 |
def mapped_read_count(self, force=False):
"""
Counts total reads in a BAM file.
If a file self.bam + '.scale' exists, then just read the first line of
that file that doesn't start with a "#". If such a file doesn't exist,
then it will be created with the number of reads as the first and only
line in the file.
The result is also stored in self._readcount so that the time-consuming
part only runs once; use force=True to force re-count.
Parameters
----------
force : bool
If True, then force a re-count; otherwise use cached data if
available.
"""
# Already run?
if self._readcount and not force:
return self._readcount
if os.path.exists(self.fn + '.mmr') and not force:
for line in open(self.fn + '.mmr'):
if line.startswith('#'):
continue
self._readcount = float(line.strip())
return self._readcount
cmds = ['samtools',
'view',
'-c',
'-F', '0x4',
self.fn]
p = subprocess.Popen(
cmds, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = p.communicate()
if stderr:
sys.stderr.write('samtools says: %s' % stderr)
return None
mapped_reads = int(stdout)
# write to file so the next time you need the lib size you can access
# it quickly
if not os.path.exists(self.fn + '.mmr'):
fout = open(self.fn + '.mmr', 'w')
fout.write(str(mapped_reads) + '\n')
fout.close()
self._readcount = mapped_reads
return self._readcount | 0.001119 |
def _ast_to_code(self, node, **kwargs):
"""Convert an abstract syntax tree to python source code."""
if isinstance(node, OptreeNode):
return self._ast_optree_node_to_code(node, **kwargs)
elif isinstance(node, Identifier):
return self._ast_identifier_to_code(node, **kwargs)
elif isinstance(node, Terminal):
return self._ast_terminal_to_code(node, **kwargs)
elif isinstance(node, OptionGroup):
return self._ast_option_group_to_code(node, **kwargs)
elif isinstance(node, RepetitionGroup):
return self._ast_repetition_group_to_code(node, **kwargs)
elif isinstance(node, SpecialHandling):
return self._ast_special_handling_to_code(node, **kwargs)
elif isinstance(node, Number):
return self._ast_number_to_code(node, **kwargs)
else:
raise Exception("Unhandled ast node: {0}".format(node)) | 0.010381 |
def setup():
""" Returns the attributes of this family if using in a probabilistic model
Notes
----------
- scale notes whether family has a variance parameter (sigma)
- shape notes whether family has a tail thickness parameter (nu)
- skewness notes whether family has a skewness parameter (gamma)
- mean_transform is a function which transforms the location parameter
- cythonized notes whether the family has cythonized routines
Returns
----------
- model name, link function, scale, shape, skewness, mean_transform, cythonized
"""
name = "Cauchy"
link = np.array
scale = True
shape = False
skewness = False
mean_transform = np.array
cythonized = True # used for GAS models
return name, link, scale, shape, skewness, mean_transform, cythonized | 0.006557 |
def user_timeline(self, delegate, user=None, params={}, extra_args=None):
"""Get the most recent updates for a user.
If no user is specified, the statuses for the authenticating user are
returned.
See search for example of how results are returned."""
if user:
params['id'] = user
return self.__get('/statuses/user_timeline.xml', delegate, params,
txml.Statuses, extra_args=extra_args) | 0.004228 |
def trigger(self, events, *args, **kwargs):
"""
Fires the given *events* (string or list of strings). All callbacks
associated with these *events* will be called and if their respective
objects have a *times* value set it will be used to determine when to
remove the associated callback from the event.
If given, callbacks associated with the given *events* will be called
with *args* and *kwargs*.
"""
# Make sure our _on_off_events dict is present (if first invokation)
if not hasattr(self, '_on_off_events'):
self._on_off_events = {}
if not hasattr(self, 'exc_info'):
self.exc_info = None
logging.debug("OnOffMixin triggering event(s): %s" % events)
if isinstance(events, (str, unicode)):
events = [events]
for event in events:
if event in self._on_off_events:
for callback_obj in self._on_off_events[event]:
callback_obj['callback'](*args, **kwargs)
callback_obj['calls'] += 1
if callback_obj['calls'] == callback_obj['times']:
self.off(event, callback_obj['callback']) | 0.001619 |
def _gen_csv_data(self, f, dialect):
"""
Yields (column data, row number) tuples from the given csv file
handler, using the given Dialect named tuple instance. Depends on
self.ipa_col being correctly set.
Helper for the gen_ipa_data method.
"""
reader = self._get_csv_reader(f, dialect)
for line in reader:
try:
datum = line[self.ipa_col]
except IndexError:
mes = 'Could not find IPA data on line: {}'.format(line)
raise ValueError(mes)
yield datum, reader.line_num | 0.031683 |
def infer_x(self, y, sigma=None, k=None, **kwargs):
"""Infer probable x from input y
@param y the desired output for infered x.
@param k how many neighbors to consider for the average
this value override the class provided one on a per
method call basis.
"""
assert len(y) == self.fmodel.dim_y, "Wrong dimension for y. Expected %i, got %i" % (self.fmodel.dim_y, len(y))
k = k or self.k
sigma = sigma or self.sigma
x_guess = self._guess_x(y, k = k)[0]
dists, index = self.fmodel.dataset.nn_x(x_guess, k = k)
w = self._weights(index, dists, sigma*sigma, y)
return [np.sum([wi*self.fmodel.dataset.get_x(idx)
for wi, idx in zip(w, index)], axis = 0)] | 0.011392 |
def get_service_state(self, service_id: str) -> str:
"""Get the state of the service.
Only the manager nodes can retrieve service state
Args:
service_id (str): Service id
Returns:
str, state of the service
"""
# Get service
service = self._client.services.get(service_id)
# Get the state of the service
for service_task in service.tasks():
service_state = service_task['DesiredState']
return service_state | 0.003802 |
def remove_pool_snapshot(service, pool_name, snapshot_name):
"""
Remove a snapshot from a RADOS pool in ceph.
:param service: six.string_types. The Ceph user name to run the command under
:param pool_name: six.string_types
:param snapshot_name: six.string_types
:return: None. Can raise CalledProcessError
"""
cmd = ['ceph', '--id', service, 'osd', 'pool', 'rmsnap', pool_name, snapshot_name]
try:
check_call(cmd)
except CalledProcessError:
raise | 0.005964 |
def _data(self):
"""A deep copy NDArray of the data array associated with the BaseSparseNDArray.
This function blocks. Do not use it in performance critical code.
"""
self.wait_to_read()
hdl = NDArrayHandle()
check_call(_LIB.MXNDArrayGetDataNDArray(self.handle, ctypes.byref(hdl)))
return NDArray(hdl) | 0.011173 |
def easy_train_and_evaluate(hyper_params, Model=None, create_loss=None,
training_data=None, validation_data=None,
inline_plotting=False, session_config=None, log_suffix=None,
continue_training=False, continue_with_specific_checkpointpath=None):
"""
Train and evaluate your model without any boilerplate code.
1) Write your data using the starttf.tfrecords.autorecords.write_data method.
2) Create your hyper parameter file containing all required fields and then load it using
starttf.utils.hyper_params.load_params method.
Minimal Sample Hyperparams File:
{"train": {
"learning_rate": {
"type": "const",
"start_value": 0.001
},
"optimizer": {
"type": "adam"
},
"batch_size": 1024,
"iters": 10000,
"summary_iters": 100,
"checkpoint_path": "checkpoints/mnist",
"tf_records_path": "data/.records/mnist"
}
}
3) Pass everything required to this method and that's it.
:param hyper_params: The hyper parameters obejct loaded via starttf.utils.hyper_params.load_params
:param Model: A keras model.
:param create_loss: A create_loss function like that in starttf.examples.mnist.loss.
:param inline_plotting: When you are using jupyter notebooks you can tell it to plot the loss directly inside the notebook.
:param continue_training: Bool, continue last training in the checkpoint path specified in the hyper parameters.
:param session_config: A configuration for the session.
:param log_suffix: A suffix for the log folder, so you can remember what was special about the run.
:return:
"""
time_stamp = datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d_%H.%M.%S')
chkpt_path = hyper_params.train.checkpoint_path + "/" + time_stamp
if log_suffix is not None:
chkpt_path = chkpt_path + "_" + log_suffix
if session_config is None:
session_config = get_default_config()
if continue_with_specific_checkpointpath:
chkpt_path = hyper_params.train.checkpoint_path + "/" + continue_with_specific_checkpointpath
print("Continue with checkpoint: {}".format(chkpt_path))
elif continue_training:
chkpts = sorted([name for name in os.listdir(hyper_params.train.checkpoint_path)])
chkpt_path = hyper_params.train.checkpoint_path + "/" + chkpts[-1]
print("Latest found checkpoint: {}".format(chkpt_path))
if not os.path.exists(chkpt_path):
os.makedirs(chkpt_path)
# If hyperparam config is used, load and save code
if Model is None:
model_backup = os.path.join(chkpt_path, "model.py")
copyfile(hyperparams["arch"]["model"].replace(".", os.sep), model_backup)
arch_model = __import__(hyperparams["arch"]["model"], fromlist=["Model"])
Model = arch_model.Model
if create_loss is None:
loss_backup = os.path.join(chkpt_path, "loss.py")
copyfile(hyperparams["arch"]["loss"].replace(".", os.sep), loss_backup)
arch_loss = __import__(hyperparams["arch"]["loss"], fromlist=["create_loss"])
create_loss = arch_loss.create_loss
# Load training data
print("Load data")
if training_data is None:
training_data = create_input_fn(os.path.join(hyper_params.train.tf_records_path, PHASE_TRAIN),
hyper_params.train.batch_size)
if validation_data is None:
validation_data = create_input_fn(os.path.join(hyper_params.train.tf_records_path, PHASE_VALIDATION),
hyper_params.train.batch_size)
# Write hyper parameters to be able to track what config you had.
with open(chkpt_path + "/hyperparameters.json", "w") as json_file:
json_file.write(json.dumps(hyper_params.to_dict(), indent=4, sort_keys=True))
estimator_spec = create_tf_estimator_spec(chkpt_path, Model, create_loss, inline_plotting)
# Create a run configuration
config = None
if hyper_params.train.get("distributed", False):
distribution = tf.contrib.distribute.MirroredStrategy()
config = tf.estimator.RunConfig(model_dir=chkpt_path,
save_summary_steps=hyper_params.train.summary_steps,
train_distribute=distribution,
save_checkpoints_steps=hyper_params.train.save_checkpoint_steps,
keep_checkpoint_max=hyper_params.train.keep_checkpoint_max,
keep_checkpoint_every_n_hours=1)
else:
config = tf.estimator.RunConfig(session_config=session_config,
model_dir=chkpt_path,
save_summary_steps=hyper_params.train.summary_steps,
save_checkpoints_steps=hyper_params.train.save_checkpoint_steps,
keep_checkpoint_max=hyper_params.train.keep_checkpoint_max,
keep_checkpoint_every_n_hours=1)
# Create the estimator.
estimator = None
if hyper_params.train.get("warm_start_checkpoint", None) is not None:
warm_start_dir = hyper_params.train.warm_start_checkpoint
estimator = tf.estimator.Estimator(estimator_spec,
config=config,
warm_start_from=warm_start_dir,
params=hyper_params)
else:
estimator = tf.estimator.Estimator(estimator_spec,
config=config,
params=hyper_params)
# Specify training and actually train.
throttle_secs = hyper_params.train.get("throttle_secs", 120)
train_spec = tf.estimator.TrainSpec(input_fn=training_data,
max_steps=hyper_params.train.steps)
eval_spec = tf.estimator.EvalSpec(input_fn=validation_data,
throttle_secs=throttle_secs)
print("Start training")
tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)
return estimator | 0.004344 |
def gg_ipython(plot, data, width=IPYTHON_IMAGE_SIZE, height=None,
*args, **kwargs):
"""Render pygg in an IPython notebook
Allows one to say things like:
import pygg
p = pygg.ggplot('diamonds', pygg.aes(x='carat', y='price', color='clarity'))
p += pygg.geom_point(alpha=0.5, size = 2)
p += pygg.scale_x_log10(limits=[1, 2])
pygg.gg_ipython(p, data=None, quiet=True)
directly in an IPython notebook and see the resulting ggplot2 image
displayed inline. This function is print a warning if the IPython library
cannot be imported. The ggplot2 image is rendered as a PNG and not
as a vectorized graphics object right now.
Note that by default gg_ipython sets the output height and width to
IPYTHON_IMAGE_SIZE pixels as this is a reasonable default size for a
browser-based notebook. Height is by default None, indicating that height
should be set to the same value as width. It is possible to adjust
the aspect ratio of the output by providing non-None values for both
width and height
"""
try:
import IPython.display
tmp_image_filename = tempfile.NamedTemporaryFile(suffix='.jpg').name
# Quiet by default
kwargs['quiet'] = kwargs.get('quiet', True)
if width is None:
raise ValueError("Width cannot be None")
height = height or width
w_in, h_in = size_r_img_inches(width, height)
ggsave(name=tmp_image_filename, plot=plot, data=data,
dpi=600, width=w_in, height=h_in, units=esc('in'),
*args, **kwargs)
return IPython.display.Image(filename=tmp_image_filename,
width=width, height=height)
except ImportError:
print "Could't load IPython library; integration is disabled" | 0.001094 |
def verify_raw_data(raw_data, pubkey_hex, sigb64):
"""
Verify the signature over a string, given the public key
and base64-encode signature.
Return True on success.
Return False on error.
"""
if not isinstance(raw_data, (str, unicode)):
raise ValueError("data is not a string")
raw_data = str(raw_data)
vi = ECVerifier(pubkey_hex, sigb64)
vi.update(raw_data)
return vi.verify() | 0.00232 |
def __on_message(self, client, userdata, msg):
# pylint: disable=W0613
"""
A message has been received from a server
:param client: Client that received the message
:param userdata: User data (unused)
:param msg: A MQTTMessage bean
"""
# Notify the caller, if any
if self.on_message is not None:
try:
self.on_message(self, msg)
except Exception as ex:
_logger.exception("Error notifying MQTT listener: %s", ex) | 0.005566 |
def create(server_context, domain_definition, container_path=None):
# type: (ServerContext, dict, str) -> Domain
"""
Create a domain
:param server_context: A LabKey server context. See utils.create_server_context.
:param domain_definition: A domain definition.
:param container_path: labkey container path if not already set in context
:return: Domain
"""
url = server_context.build_url('property', 'createDomain.api', container_path=container_path)
headers = {
'Content-Type': 'application/json'
}
domain = None
raw_domain = server_context.make_request(url, json_dumps(domain_definition), headers=headers)
if raw_domain is not None:
domain = Domain.from_data(raw_domain)
return domain | 0.005222 |
def set_motion_detect(self, enable):
"""Set motion detection."""
if enable:
return api.request_motion_detection_enable(self.sync.blink,
self.network_id,
self.camera_id)
return api.request_motion_detection_disable(self.sync.blink,
self.network_id,
self.camera_id) | 0.003906 |
def softplus_inverse(x, name=None):
"""Computes the inverse softplus, i.e., x = softplus_inverse(softplus(x)).
Mathematically this op is equivalent to:
```none
softplus_inverse = log(exp(x) - 1.)
```
Args:
x: `Tensor`. Non-negative (not enforced), floating-point.
name: A name for the operation (optional).
Returns:
`Tensor`. Has the same type/shape as input `x`.
"""
with tf.name_scope(name or "softplus_inverse"):
x = tf.convert_to_tensor(value=x, name="x")
# We begin by deriving a more numerically stable softplus_inverse:
# x = softplus(y) = Log[1 + exp{y}], (which means x > 0).
# ==> exp{x} = 1 + exp{y} (1)
# ==> y = Log[exp{x} - 1] (2)
# = Log[(exp{x} - 1) / exp{x}] + Log[exp{x}]
# = Log[(1 - exp{-x}) / 1] + Log[exp{x}]
# = Log[1 - exp{-x}] + x (3)
# (2) is the "obvious" inverse, but (3) is more stable than (2) for large x.
# For small x (e.g. x = 1e-10), (3) will become -inf since 1 - exp{-x} will
# be zero. To fix this, we use 1 - exp{-x} approx x for small x > 0.
#
# In addition to the numerically stable derivation above, we clamp
# small/large values to be congruent with the logic in:
# tensorflow/core/kernels/softplus_op.h
#
# Finally, we set the input to one whenever the input is too large or too
# small. This ensures that no unchosen codepath is +/- inf. This is
# necessary to ensure the gradient doesn't get NaNs. Recall that the
# gradient of `where` behaves like `pred*pred_true + (1-pred)*pred_false`
# thus an `inf` in an unselected path results in `0*inf=nan`. We are careful
# to overwrite `x` with ones only when we will never actually use this
# value. Note that we use ones and not zeros since `log(expm1(0.)) = -inf`.
threshold = np.log(np.finfo(dtype_util.as_numpy_dtype(x.dtype)).eps) + 2.
is_too_small = tf.less(x, np.exp(threshold))
is_too_large = tf.greater(x, -threshold)
too_small_value = tf.math.log(x)
too_large_value = x
# This `where` will ultimately be a NOP because we won't select this
# codepath whenever we used the surrogate `ones_like`.
x = tf.where(tf.logical_or(is_too_small, is_too_large), tf.ones_like(x), x)
y = x + tf.math.log(-tf.math.expm1(-x)) # == log(expm1(x))
return tf.where(is_too_small, too_small_value,
tf.where(is_too_large, too_large_value, y)) | 0.00199 |
def file_matches_regexps(filename, patterns):
"""Does this filename match any of the regular expressions?"""
return any(re.match(pat, filename) for pat in patterns) | 0.005814 |
def email(self, client_id, email, send='link', auth_params=None):
"""Start flow sending an email.
Given the user email address, it will send an email with:
- A link (default, send:"link"). You can then authenticate with
this user opening the link and he will be automatically logged in
to the application. Optionally, you can append/override
parameters to the link (like scope, redirect_uri, protocol,
response_type, etc.) using auth_params dict.
- A verification code (send:"code"). You can then authenticate with
this user using email as username and code as password.
Args:
client_id (str): Client Id of the application.
email (str): Email address.
send (str, optional): Can be: 'link' or 'code'. Defaults to 'link'.
auth_params (dict, optional): Parameters to append or override.
"""
return self.post(
'https://{}/passwordless/start'.format(self.domain),
data={
'client_id': client_id,
'connection': 'email',
'email': email,
'send': send,
'authParams': auth_params
},
headers={'Content-Type': 'application/json'}
) | 0.001504 |
def encode_utf8(s, f):
"""UTF-8 encodes string `s` to file-like object `f` according to
the MQTT Version 3.1.1 specification in section 1.5.3.
The maximum length for the encoded string is 2**16-1 (65535) bytes.
An assertion error will result if the encoded string is longer.
Parameters
----------
s: str
String to be encoded.
f: file
File-like object.
Returns
-------
int
Number of bytes written to f.
"""
encode = codecs.getencoder('utf8')
encoded_str_bytes, num_encoded_chars = encode(s)
num_encoded_str_bytes = len(encoded_str_bytes)
assert 0 <= num_encoded_str_bytes <= 2**16-1
num_encoded_bytes = num_encoded_str_bytes + 2
f.write(FIELD_U8.pack((num_encoded_str_bytes & 0xff00) >> 8))
f.write(FIELD_U8.pack(num_encoded_str_bytes & 0x00ff))
f.write(encoded_str_bytes)
return num_encoded_bytes | 0.001099 |
def match(self, methods, request_method):
"""Check for a method match.
:param methods: A method or tuple of methods to match against.
:param request_method: The method to check for a match.
:returns: An empty :class:`dict` in the case of a match, or ``None``
if there is no matching handler for the given method.
Example:
>>> MethodRouter().match(('GET', 'HEAD'), 'HEAD')
{}
>>> MethodRouter().match('POST', 'DELETE')
"""
if isinstance(methods, basestring):
return {} if request_method == methods else None
return {} if request_method in methods else None | 0.002933 |
def build_lst(a, b):
""" function to be folded over a list (with initial value `None`)
produces one of:
1. `None`
2. A single value
3. A list of all values
"""
if type(a) is list:
return a + [b]
elif a:
return [a, b]
else:
return b | 0.003247 |
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