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bastula/dicompyler | 2643e0ee145cb7c699b3d36e3e4f07ac9dc7b1f2 | dicompyler/main.py | python | MainFrame.OnPreferences | (self, evt) | Load and show the Preferences dialog box. | Load and show the Preferences dialog box. | [
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] | def OnPreferences(self, evt):
"""Load and show the Preferences dialog box."""
self.prefmgr.Show() | [
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||
SteveDoyle2/pyNastran | eda651ac2d4883d95a34951f8a002ff94f642a1a | pyNastran/bdf/cards/params.py | python | PARAM.__init__ | (self, key, values, comment='') | Creates a PARAM card
Parameters
----------
key : str
the name of the PARAM
values : int/float/str/List
varies depending on the type of PARAM
comment : str; default=''
a comment for the card | Creates a PARAM card | [
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] | def __init__(self, key, values, comment=''):
"""
Creates a PARAM card
Parameters
----------
key : str
the name of the PARAM
values : int/float/str/List
varies depending on the type of PARAM
comment : str; default=''
a comment for the card
"""
if comment:
self.comment = comment
self.key = key
if isinstance(values, list):
pass
elif isinstance(values, (integer_types, float_types, str)):
values = [values]
self.values = values
if isinstance(self.values, tuple) or isinstance(self.values[0], (list, tuple)):
raise TypeError((key, self.values)) | [
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NordicSemiconductor/pc-nrfutil | d08e742128f2a3dac522601bc6b9f9b2b63952df | nordicsemi/lister/unix/unix_lister.py | python | create_id_string | (sno, PID, VID) | return "{}-{}-{}".format(sno, PID, VID) | [] | def create_id_string(sno, PID, VID):
return "{}-{}-{}".format(sno, PID, VID) | [
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|||
securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/lib-python/3/xml/sax/xmlreader.py | python | XMLReader.setFeature | (self, name, state) | Sets the state of a SAX2 feature. | Sets the state of a SAX2 feature. | [
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||
hydroshare/hydroshare | 7ba563b55412f283047fb3ef6da367d41dec58c6 | hs_core/views/__init__.py | python | MyResourcesView.dispatch | (self, *args, **kwargs) | return super(MyResourcesView, self).dispatch(*args, **kwargs) | [] | def dispatch(self, *args, **kwargs):
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|||
openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/celery/celery/task/base.py | python | PeriodicTask.remaining_estimate | (self, last_run_at) | return self.run_every.remaining_estimate(last_run_at) | Returns when the periodic task should run next as a timedelta. | Returns when the periodic task should run next as a timedelta. | [
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|
morganstanley/treadmill | f18267c665baf6def4374d21170198f63ff1cde4 | lib/python/treadmill/api/state.py | python | watch_finished_history | (zkclient, cell_state) | Watch finished historical snapshots. | Watch finished historical snapshots. | [
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] | def watch_finished_history(zkclient, cell_state):
"""Watch finished historical snapshots."""
loaded_snapshots = {}
@zkclient.ChildrenWatch(z.FINISHED_HISTORY)
@utils.exit_on_unhandled
def _watch_finished_snapshots(snapshots):
"""Watch /finished.history nodes."""
start_time = time.time()
updated_finished_history = cell_state.finished_history.copy()
for db_node in sorted(set(loaded_snapshots) - set(snapshots)):
_LOGGER.info('Unloading snapshot: %s', db_node)
for instance in loaded_snapshots.pop(db_node):
updated_finished_history.pop(instance, None)
for db_node in sorted(set(snapshots) - set(loaded_snapshots)):
_LOGGER.info('Loading snapshot: %s', db_node)
loading_start_time = time.time()
loaded_snapshots[db_node] = []
data, _stat = zkclient.get(z.path.finished_history(db_node))
with tempfile.NamedTemporaryFile(delete=False, mode='wb') as f:
f.write(zlib.decompress(data))
try:
conn = sqlite3.connect(f.name)
cur = conn.cursor()
sql = 'SELECT name, data FROM finished ORDER BY timestamp'
for row in cur.execute(sql):
instance, data = row
if data:
data = yaml.load(data)
updated_finished_history[instance] = data
loaded_snapshots[db_node].append(instance)
conn.close()
finally:
os.unlink(f.name)
_LOGGER.debug('Loading time: %s', time.time() - loading_start_time)
cell_state.finished_history = updated_finished_history
_LOGGER.debug(
'Loaded snapshots: %d, finished: %d, finished history: %d, '
'time: %s', len(loaded_snapshots), len(cell_state.finished),
len(cell_state.finished_history), time.time() - start_time
)
return True
_LOGGER.info('Loaded finished snapshots.') | [
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||
sympy/sympy | d822fcba181155b85ff2b29fe525adbafb22b448 | sympy/physics/secondquant.py | python | simplify_index_permutations | (expr, permutation_operators) | return expr | Performs simplification by introducing PermutationOperators where appropriate.
Explanation
===========
Schematically:
[abij] - [abji] - [baij] + [baji] -> P(ab)*P(ij)*[abij]
permutation_operators is a list of PermutationOperators to consider.
If permutation_operators=[P(ab),P(ij)] we will try to introduce the
permutation operators P(ij) and P(ab) in the expression. If there are other
possible simplifications, we ignore them.
>>> from sympy import symbols, Function
>>> from sympy.physics.secondquant import simplify_index_permutations
>>> from sympy.physics.secondquant import PermutationOperator
>>> p,q,r,s = symbols('p,q,r,s')
>>> f = Function('f')
>>> g = Function('g')
>>> expr = f(p)*g(q) - f(q)*g(p); expr
f(p)*g(q) - f(q)*g(p)
>>> simplify_index_permutations(expr,[PermutationOperator(p,q)])
f(p)*g(q)*PermutationOperator(p, q)
>>> PermutList = [PermutationOperator(p,q),PermutationOperator(r,s)]
>>> expr = f(p,r)*g(q,s) - f(q,r)*g(p,s) + f(q,s)*g(p,r) - f(p,s)*g(q,r)
>>> simplify_index_permutations(expr,PermutList)
f(p, r)*g(q, s)*PermutationOperator(p, q)*PermutationOperator(r, s) | Performs simplification by introducing PermutationOperators where appropriate. | [
"Performs",
"simplification",
"by",
"introducing",
"PermutationOperators",
"where",
"appropriate",
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] | def simplify_index_permutations(expr, permutation_operators):
"""
Performs simplification by introducing PermutationOperators where appropriate.
Explanation
===========
Schematically:
[abij] - [abji] - [baij] + [baji] -> P(ab)*P(ij)*[abij]
permutation_operators is a list of PermutationOperators to consider.
If permutation_operators=[P(ab),P(ij)] we will try to introduce the
permutation operators P(ij) and P(ab) in the expression. If there are other
possible simplifications, we ignore them.
>>> from sympy import symbols, Function
>>> from sympy.physics.secondquant import simplify_index_permutations
>>> from sympy.physics.secondquant import PermutationOperator
>>> p,q,r,s = symbols('p,q,r,s')
>>> f = Function('f')
>>> g = Function('g')
>>> expr = f(p)*g(q) - f(q)*g(p); expr
f(p)*g(q) - f(q)*g(p)
>>> simplify_index_permutations(expr,[PermutationOperator(p,q)])
f(p)*g(q)*PermutationOperator(p, q)
>>> PermutList = [PermutationOperator(p,q),PermutationOperator(r,s)]
>>> expr = f(p,r)*g(q,s) - f(q,r)*g(p,s) + f(q,s)*g(p,r) - f(p,s)*g(q,r)
>>> simplify_index_permutations(expr,PermutList)
f(p, r)*g(q, s)*PermutationOperator(p, q)*PermutationOperator(r, s)
"""
def _get_indices(expr, ind):
"""
Collects indices recursively in predictable order.
"""
result = []
for arg in expr.args:
if arg in ind:
result.append(arg)
else:
if arg.args:
result.extend(_get_indices(arg, ind))
return result
def _choose_one_to_keep(a, b, ind):
# we keep the one where indices in ind are in order ind[0] < ind[1]
return min(a, b, key=lambda x: default_sort_key(_get_indices(x, ind)))
expr = expr.expand()
if isinstance(expr, Add):
terms = set(expr.args)
for P in permutation_operators:
new_terms = set()
on_hold = set()
while terms:
term = terms.pop()
permuted = P.get_permuted(term)
if permuted in terms | on_hold:
try:
terms.remove(permuted)
except KeyError:
on_hold.remove(permuted)
keep = _choose_one_to_keep(term, permuted, P.args)
new_terms.add(P*keep)
else:
# Some terms must get a second chance because the permuted
# term may already have canonical dummy ordering. Then
# substitute_dummies() does nothing. However, the other
# term, if it exists, will be able to match with us.
permuted1 = permuted
permuted = substitute_dummies(permuted)
if permuted1 == permuted:
on_hold.add(term)
elif permuted in terms | on_hold:
try:
terms.remove(permuted)
except KeyError:
on_hold.remove(permuted)
keep = _choose_one_to_keep(term, permuted, P.args)
new_terms.add(P*keep)
else:
new_terms.add(term)
terms = new_terms | on_hold
return Add(*terms)
return expr | [
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] | https://github.com/sympy/sympy/blob/d822fcba181155b85ff2b29fe525adbafb22b448/sympy/physics/secondquant.py#L3046-L3136 |
|
IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/lzma.py | python | LZMAFile._rewind | (self) | [] | def _rewind(self):
self._fp.seek(0, 0)
self._mode = _MODE_READ
self._pos = 0
self._decompressor = LZMADecompressor(**self._init_args)
self._buffer = b""
self._buffer_offset = 0 | [
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||||
makerbot/ReplicatorG | d6f2b07785a5a5f1e172fb87cb4303b17c575d5d | skein_engines/skeinforge-35/fabmetheus_utilities/intercircle.py | python | getInsetLoopsFromLoop | (inset, loop, thresholdRatio=0.9) | return insetLoops | Get the inset loops, which might overlap. | Get the inset loops, which might overlap. | [
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] | def getInsetLoopsFromLoop(inset, loop, thresholdRatio=0.9):
"Get the inset loops, which might overlap."
isInset = inset > 0
insetLoops = []
isLoopWiddershins = euclidean.isWiddershins(loop)
arounds = getAroundsFromLoop( loop, inset, thresholdRatio )
for around in arounds:
leftPoint = euclidean.getLeftPoint(around)
shouldBeWithin = (isInset == isLoopWiddershins)
if euclidean.isPointInsideLoop(loop, leftPoint) == shouldBeWithin:
if isLoopWiddershins != euclidean.isWiddershins(around):
around.reverse()
insetLoops.append(around)
return insetLoops | [
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SteveDoyle2/pyNastran | eda651ac2d4883d95a34951f8a002ff94f642a1a | pyNastran/bdf/bdf_interface/write_mesh.py | python | WriteMesh._write_constraints | (self, bdf_file: Any, size: int=8, is_double: bool=False,
is_long_ids: Optional[bool]=None) | Writes the constraint cards sorted by ID | Writes the constraint cards sorted by ID | [
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] | def _write_constraints(self, bdf_file: Any, size: int=8, is_double: bool=False,
is_long_ids: Optional[bool]=None) -> None:
"""Writes the constraint cards sorted by ID"""
size, is_long_ids = self._write_mesh_long_ids_size(size, is_long_ids)
if self.suport or self.suport1:
bdf_file.write('$CONSTRAINTS\n')
for suport in self.suport:
bdf_file.write(suport.write_card(size, is_double))
for unused_suport_id, suport in sorted(self.suport1.items()):
bdf_file.write(suport.write_card(size, is_double))
if self.spcs or self.spcadds or self.spcoffs:
#bdf_file.write('$SPCs\n')
#str_spc = str(self.spcObject) # old
#if str_spc:
#bdf_file.write(str_spc)
#else:
bdf_file.write('$SPCs\n')
for (unused_id, spcadds) in sorted(self.spcadds.items()):
for spcadd in spcadds:
bdf_file.write(str(spcadd))
for (unused_id, spcs) in sorted(self.spcs.items()):
for spc in spcs:
bdf_file.write(str(spc))
for (unused_id, spcoffs) in sorted(self.spcoffs.items()):
for spc in spcoffs:
bdf_file.write(str(spc))
if self.mpcs or self.mpcadds:
bdf_file.write('$MPCs\n')
for (unused_id, mpcadds) in sorted(self.mpcadds.items()):
for mpcadd in mpcadds:
bdf_file.write(str(mpcadd))
for (unused_id, mpcs) in sorted(self.mpcs.items()):
for mpc in mpcs:
bdf_file.write(mpc.write_card(size, is_double)) | [
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||
SteveDoyle2/pyNastran | eda651ac2d4883d95a34951f8a002ff94f642a1a | pyNastran/bdf/cards/optimization.py | python | DVMREL1.uncross_reference | (self) | Removes cross-reference links | Removes cross-reference links | [
"Removes",
"cross",
"-",
"reference",
"links"
] | def uncross_reference(self) -> None:
"""Removes cross-reference links"""
self.mid = self.Mid()
self.dvids = self.desvar_ids
self.mid_ref = None
self.dvids_ref = None | [
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||
Parsely/pykafka | e7665bf36bfe521050fdcb017c68e92365bd89ed | pykafka/utils/__init__.py | python | deserialize_utf8 | (value, partition_key) | return value, partition_key | A deserializer accepting bytes arguments and returning utf-8 strings
Can be used as `pykafka.simpleconsumer.SimpleConsumer(deserializer=deserialize_utf8)`,
or similarly in other consumer classes | A deserializer accepting bytes arguments and returning utf-8 strings | [
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"deserializer",
"accepting",
"bytes",
"arguments",
"and",
"returning",
"utf",
"-",
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] | def deserialize_utf8(value, partition_key):
"""A deserializer accepting bytes arguments and returning utf-8 strings
Can be used as `pykafka.simpleconsumer.SimpleConsumer(deserializer=deserialize_utf8)`,
or similarly in other consumer classes
"""
# allow UnicodeError to be raised here if the decoding fails
if value is not None:
value = value.decode('utf-8')
if partition_key is not None:
partition_key = partition_key.decode('utf-8')
return value, partition_key | [
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|
IntelAI/models | 1d7a53ccfad3e6f0e7378c9e3c8840895d63df8c | models/language_translation/tensorflow/transformer_mlperf/training/bfloat16/transformer/utils/tokenizer.py | python | _save_vocab_file | (vocab_file, subtoken_list) | Save subtokens to file. | Save subtokens to file. | [
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"to",
"file",
"."
] | def _save_vocab_file(vocab_file, subtoken_list):
"""Save subtokens to file."""
with tf.io.gfile.GFile(vocab_file, mode="w") as f:
for subtoken in subtoken_list:
f.write("'%s'\n" % _unicode_to_native(subtoken)) | [
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apple/coremltools | 141a83af482fcbdd5179807c9eaff9a7999c2c49 | deps/protobuf/python/google/protobuf/internal/encoder.py | python | MapEncoder | (field_descriptor) | return EncodeField | Encoder for extensions of MessageSet.
Maps always have a wire format like this:
message MapEntry {
key_type key = 1;
value_type value = 2;
}
repeated MapEntry map = N; | Encoder for extensions of MessageSet. | [
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] | def MapEncoder(field_descriptor):
"""Encoder for extensions of MessageSet.
Maps always have a wire format like this:
message MapEntry {
key_type key = 1;
value_type value = 2;
}
repeated MapEntry map = N;
"""
# Can't look at field_descriptor.message_type._concrete_class because it may
# not have been initialized yet.
message_type = field_descriptor.message_type
encode_message = MessageEncoder(field_descriptor.number, False, False)
def EncodeField(write, value):
for key in value:
entry_msg = message_type._concrete_class(key=key, value=value[key])
encode_message(write, entry_msg)
return EncodeField | [
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|
nathanlopez/Stitch | 8e22e91c94237959c02d521aab58dc7e3d994cea | Application/stitch_winshell.py | python | st_winshell.help_keylogger | (self) | [] | def help_keylogger(self): st_help_keylogger() | [
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||||
etetoolkit/ete | 2b207357dc2a40ccad7bfd8f54964472c72e4726 | ete3/nexml/_nexml.py | python | RestrictionMatrixObsRow.get_cell | (self) | return self.cell | [] | def get_cell(self): return self.cell | [
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|||
pyserial/pyserial | 31fa4807d73ed4eb9891a88a15817b439c4eea2d | serial/rfc2217.py | python | PortManager.check_modem_lines | (self, force_notification=False) | \
read control lines from serial port and compare the last value sent to remote.
send updates on changes. | \
read control lines from serial port and compare the last value sent to remote.
send updates on changes. | [
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"""\
read control lines from serial port and compare the last value sent to remote.
send updates on changes.
"""
modemstate = (
(self.serial.cts and MODEMSTATE_MASK_CTS) |
(self.serial.dsr and MODEMSTATE_MASK_DSR) |
(self.serial.ri and MODEMSTATE_MASK_RI) |
(self.serial.cd and MODEMSTATE_MASK_CD))
# check what has changed
deltas = modemstate ^ (self.last_modemstate or 0) # when last is None -> 0
if deltas & MODEMSTATE_MASK_CTS:
modemstate |= MODEMSTATE_MASK_CTS_CHANGE
if deltas & MODEMSTATE_MASK_DSR:
modemstate |= MODEMSTATE_MASK_DSR_CHANGE
if deltas & MODEMSTATE_MASK_RI:
modemstate |= MODEMSTATE_MASK_RI_CHANGE
if deltas & MODEMSTATE_MASK_CD:
modemstate |= MODEMSTATE_MASK_CD_CHANGE
# if new state is different and the mask allows this change, send
# notification. suppress notifications when client is not rfc2217
if modemstate != self.last_modemstate or force_notification:
if (self._client_is_rfc2217 and (modemstate & self.modemstate_mask)) or force_notification:
self.rfc2217_send_subnegotiation(
SERVER_NOTIFY_MODEMSTATE,
to_bytes([modemstate & self.modemstate_mask]))
if self.logger:
self.logger.info("NOTIFY_MODEMSTATE: {}".format(modemstate))
# save last state, but forget about deltas.
# otherwise it would also notify about changing deltas which is
# probably not very useful
self.last_modemstate = modemstate & 0xf0 | [
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kubeflow/pipelines | bea751c9259ff0ae85290f873170aae89284ba8e | sdk/python/kfp/components/_component_store.py | python | ComponentStore.load_component_from_file | (self, path) | return comp.load_component_from_file(path) | Loads a component from a path.
Args:
path: The path of the component specification.
Returns:
A factory function with a strongly-typed signature. | Loads a component from a path. | [
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] | def load_component_from_file(self, path):
"""Loads a component from a path.
Args:
path: The path of the component specification.
Returns:
A factory function with a strongly-typed signature.
"""
return comp.load_component_from_file(path) | [
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ctxis/canape | 5f0e03424577296bcc60c2008a60a98ec5307e4b | CANAPE.Scripting/Lib/warnings.py | python | catch_warnings.__init__ | (self, record=False, module=None) | Specify whether to record warnings and if an alternative module
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/bsddb/dbtables.py | python | Cond.__call__ | (self, s) | return 1 | [] | def __call__(self, s):
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skelsec/msldap | ed3134135ddf9e13c74a4d7208ef3e48ec898192 | msldap/client.py | python | MSLDAPClient.get_all_users | (self) | Fetches all user objects available in the LDAP tree and yields them as MSADUser object.
:return: Async generator which yields (`MSADUser`, None) tuple on success or (None, `Exception`) on error
:rtype: Iterator[(:class:`MSADUser`, :class:`Exception`)] | Fetches all user objects available in the LDAP tree and yields them as MSADUser object.
:return: Async generator which yields (`MSADUser`, None) tuple on success or (None, `Exception`) on error
:rtype: Iterator[(:class:`MSADUser`, :class:`Exception`)] | [
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"""
logger.debug('Polling AD for all user objects')
ldap_filter = r'(sAMAccountType=805306368)'
async for entry, err in self.pagedsearch(ldap_filter, MSADUser_ATTRS):
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yield None, err
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ipython/ipython | c0abea7a6dfe52c1f74c9d0387d4accadba7cc14 | IPython/core/oinspect.py | python | Inspector._mime_format | (self, text:str, formatter=None) | Return a mime bundle representation of the input text.
- if `formatter` is None, the returned mime bundle has
a `text/plain` field, with the input text.
a `text/html` field with a `<pre>` tag containing the input text.
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input text into a mime bundle. Default values for `text/plain` and
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Formatters returning strings are supported but this behavior is deprecated. | Return a mime bundle representation of the input text. | [
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"""Return a mime bundle representation of the input text.
- if `formatter` is None, the returned mime bundle has
a `text/plain` field, with the input text.
a `text/html` field with a `<pre>` tag containing the input text.
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input text into a mime bundle. Default values for `text/plain` and
`text/html` representations are the ones described above.
Note:
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"""
defaults = {
'text/plain': text,
'text/html': '<pre>' + text + '</pre>'
}
if formatter is None:
return defaults
else:
formatted = formatter(text)
if not isinstance(formatted, dict):
# Handle the deprecated behavior of a formatter returning
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return {
'text/plain': formatted,
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}
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return dict(defaults, **formatted) | [
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jet-admin/jet-django | 9bd4536e02d581d39890d56190e8cc966e2714a4 | jet_django/deps/rest_framework/serializers.py | python | ModelSerializer.build_standard_field | (self, field_name, model_field) | return field_class, field_kwargs | Create regular model fields. | Create regular model fields. | [
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] | def build_standard_field(self, field_name, model_field):
"""
Create regular model fields.
"""
field_mapping = ClassLookupDict(self.serializer_field_mapping)
field_class = field_mapping[model_field]
field_kwargs = get_field_kwargs(field_name, model_field)
# Special case to handle when a OneToOneField is also the primary key
if model_field.one_to_one and model_field.primary_key:
field_class = self.serializer_related_field
field_kwargs['queryset'] = model_field.related_model.objects
if 'choices' in field_kwargs:
# Fields with choices get coerced into `ChoiceField`
# instead of using their regular typed field.
field_class = self.serializer_choice_field
# Some model fields may introduce kwargs that would not be valid
# for the choice field. We need to strip these out.
# Eg. models.DecimalField(max_digits=3, decimal_places=1, choices=DECIMAL_CHOICES)
valid_kwargs = {
'read_only', 'write_only',
'required', 'default', 'initial', 'source',
'label', 'help_text', 'style',
'error_messages', 'validators', 'allow_null', 'allow_blank',
'choices'
}
for key in list(field_kwargs):
if key not in valid_kwargs:
field_kwargs.pop(key)
if not issubclass(field_class, ModelField):
# `model_field` is only valid for the fallback case of
# `ModelField`, which is used when no other typed field
# matched to the model field.
field_kwargs.pop('model_field', None)
if not issubclass(field_class, CharField) and not issubclass(field_class, ChoiceField):
# `allow_blank` is only valid for textual fields.
field_kwargs.pop('allow_blank', None)
if postgres_fields and isinstance(model_field, postgres_fields.ArrayField):
# Populate the `child` argument on `ListField` instances generated
# for the PostgreSQL specific `ArrayField`.
child_model_field = model_field.base_field
child_field_class, child_field_kwargs = self.build_standard_field(
'child', child_model_field
)
field_kwargs['child'] = child_field_class(**child_field_kwargs)
return field_class, field_kwargs | [
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haiwen/seahub | e92fcd44e3e46260597d8faa9347cb8222b8b10d | seahub/api2/permissions.py | python | IsRepoAccessible.has_permission | (self, request, view, obj=None) | return True if check_permission(repo_id, user) else False | [] | def has_permission(self, request, view, obj=None):
repo_id = view.kwargs.get('repo_id', '')
user = request.user.username if request.user else ''
return True if check_permission(repo_id, user) else False | [
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|||
coinbase/coinbase-python | 497c28158f529e8c7d0228521b4386a890baf088 | coinbase/wallet/client.py | python | Client.get_buy_price | (self, **params) | return self._make_api_object(response, APIObject) | https://developers.coinbase.com/api/v2#get-buy-price | https://developers.coinbase.com/api/v2#get-buy-price | [
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"""https://developers.coinbase.com/api/v2#get-buy-price"""
currency_pair = params.get('currency_pair', 'BTC-USD')
response = self._get('v2', 'prices', currency_pair, 'buy', params=params)
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CouchPotato/CouchPotatoServer | 7260c12f72447ddb6f062367c6dfbda03ecd4e9c | libs/suds/xsd/schema.py | python | Schema.custom | (self, ref, context=None) | Get whether the specified reference is B{not} an (xs) builtin.
@param ref: A str or qref.
@type ref: (str|qref)
@return: True if B{not} a builtin, else False.
@rtype: bool | Get whether the specified reference is B{not} an (xs) builtin. | [
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"""
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@type ref: (str|qref)
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if ref is None:
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sibblegp/b2blaze | 5976bdefa4816f8d7586df0c5612bb6ce8d286b6 | b2blaze/models/b2_file.py | python | B2File.__init__ | (self, connector, parent_list, fileId, fileName, contentSha1, contentLength, contentType,
fileInfo, action, uploadTimestamp, *args, **kwargs) | :param connector:
:param parent_list:
:param fileId:
:param fileName:
:param contentSha1:
:param contentLength:
:param contentType:
:param fileInfo:
:param action:
:param uploadTimestamp:
:param args:
:param kwargs: | [] | def __init__(self, connector, parent_list, fileId, fileName, contentSha1, contentLength, contentType,
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"""
:param connector:
:param parent_list:
:param fileId:
:param fileName:
:param contentSha1:
:param contentLength:
:param contentType:
:param fileInfo:
:param action:
:param uploadTimestamp:
:param args:
:param kwargs:
"""
self.file_id = fileId
# self.file_name_decoded = b2_url_decode(fileName)
#TODO: Find out if this is necessary
self.file_name = fileName
self.content_sha1 = contentSha1
self.content_length = contentLength
self.content_type = contentType
self.file_info = fileInfo
self.action = action
self.uploadTimestamp = uploadTimestamp
self.connector = connector
self.parent_list = parent_list
self.deleted = False | [
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|||
wnma3mz/wechat_articles_spider | 77704ffe454a5f7cf287f7ccd07a005ea85ee066 | wechatarticles/ArticlesInfo.py | python | ArticlesInfo.comments | (self, article_url) | 获取文章评论
Parameters
----------
article_url: str
文章链接
Returns
-------
json::
{
"base_resp": {
"errmsg": "ok",
"ret": 0
},
"elected_comment": [
{
"content": 用户评论文字,
"content_id": "6846263421277569047",
"create_time": 1520098511,
"id": 3,
"is_from_friend": 0,
"is_from_me": 0,
"is_top": 0, 是否被置顶
"like_id": 10001,
"like_num": 3,
"like_status": 0,
"logo_url": "http://wx.qlogo.cn/mmhead/OibRNdtlJdkFLMHYLMR92Lvq0PicDpJpbnaicP3Z6kVcCicLPVjCWbAA9w/132",
"my_id": 23,
"nick_name": 评论用户的名字,
"reply": {
"reply_list": [ ]
}
}
],
"elected_comment_total_cnt": 3, 评论总数
"enabled": 1,
"friend_comment": [ ],
"is_fans": 1,
"logo_url": "http://wx.qlogo.cn/mmhead/Q3auHgzwzM6GAic0FAHOu9Gtv5lEu5kUqO6y6EjEFjAhuhUNIS7Y2AQ/132",
"my_comment": [ ],
"nick_name": 当前用户名,
"only_fans_can_comment": false
} | 获取文章评论 | [
"获取文章评论"
] | def comments(self, article_url):
"""
获取文章评论
Parameters
----------
article_url: str
文章链接
Returns
-------
json::
{
"base_resp": {
"errmsg": "ok",
"ret": 0
},
"elected_comment": [
{
"content": 用户评论文字,
"content_id": "6846263421277569047",
"create_time": 1520098511,
"id": 3,
"is_from_friend": 0,
"is_from_me": 0,
"is_top": 0, 是否被置顶
"like_id": 10001,
"like_num": 3,
"like_status": 0,
"logo_url": "http://wx.qlogo.cn/mmhead/OibRNdtlJdkFLMHYLMR92Lvq0PicDpJpbnaicP3Z6kVcCicLPVjCWbAA9w/132",
"my_id": 23,
"nick_name": 评论用户的名字,
"reply": {
"reply_list": [ ]
}
}
],
"elected_comment_total_cnt": 3, 评论总数
"enabled": 1,
"friend_comment": [ ],
"is_fans": 1,
"logo_url": "http://wx.qlogo.cn/mmhead/Q3auHgzwzM6GAic0FAHOu9Gtv5lEu5kUqO6y6EjEFjAhuhUNIS7Y2AQ/132",
"my_comment": [ ],
"nick_name": 当前用户名,
"only_fans_can_comment": false
}
"""
__biz, _, idx, _ = self.__get_params(article_url)
getcomment_url = "https://mp.weixin.qq.com/mp/appmsg_comment?action=getcomment&__biz={}&idx={}&comment_id={}&limit=100"
try:
comment_id = self.__get_comment_id(article_url)
if comment_id == "":
return {}
url = getcomment_url.format(__biz, idx, comment_id)
return self.s.get(url, headers=self.headers, proxies=self.proxies).json()
except Exception as e:
print(e)
return {} | [
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||
crowdresearch/daemo | 36e3b70d4e2c06b4853e9209a4916f8301ed6464 | csp/utils.py | python | authenticate | (request) | Returns two-tuple of (user, token) if authentication succeeds,
or None otherwise. | Returns two-tuple of (user, token) if authentication succeeds,
or None otherwise. | [
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] | def authenticate(request):
"""
Returns two-tuple of (user, token) if authentication succeeds,
or None otherwise.
"""
oauthlib_core = get_oauthlib_core()
valid, r = oauthlib_core.verify_request(request, scopes=[])
if valid:
return r.user, r.access_token
else:
return None, None | [
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||
getsentry/sentry | 83b1f25aac3e08075e0e2495bc29efaf35aca18a | src/sentry_plugins/trello/client.py | python | TrelloApiClient.get_organization_options | (self) | return [(org["id"], org["name"]) for org in organizations] | Return organization options to use in a Django form | Return organization options to use in a Django form | [
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] | def get_organization_options(self):
"""
Return organization options to use in a Django form
"""
organizations = self.get_organization_list(fields="name")
return [(org["id"], org["name"]) for org in organizations] | [
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|
mediacloud/backend | d36b489e4fbe6e44950916a04d9543a1d6cd5df0 | apps/common/src/python/mediawords/db/locks.py | python | list_session_locks | (db: mediawords.db.DatabaseHandler, lock_type: str) | return db.query(
"select objid from pg_locks where locktype = 'advisory' and classid = %(a)s",
{'a': lock_type_id}).flat() | Return a list of all locked ids for the given lock_type. | Return a list of all locked ids for the given lock_type. | [
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] | def list_session_locks(db: mediawords.db.DatabaseHandler, lock_type: str) -> list:
"""Return a list of all locked ids for the given lock_type."""
lock_type = str(decode_object_from_bytes_if_needed(lock_type))
if lock_type not in LOCK_TYPES:
raise McDBLocksException("lock type not in LOCK_TYPES: %s" % lock_type)
lock_type_id = LOCK_TYPES[lock_type]
# noinspection SqlResolve
return db.query(
"select objid from pg_locks where locktype = 'advisory' and classid = %(a)s",
{'a': lock_type_id}).flat() | [
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|
whoosh-community/whoosh | 5421f1ab3bb802114105b3181b7ce4f44ad7d0bb | src/whoosh/util/times.py | python | adatetime.floor | (self) | return datetime(y, m, d, h, mn, s, ms) | Returns a ``datetime`` version of this object with all unspecified
(None) attributes replaced by their lowest values.
This method raises an error if the ``adatetime`` object has no year.
>>> adt = adatetime(year=2009, month=5)
>>> adt.floor()
datetime.datetime(2009, 5, 1, 0, 0, 0, 0) | Returns a ``datetime`` version of this object with all unspecified
(None) attributes replaced by their lowest values. | [
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] | def floor(self):
"""Returns a ``datetime`` version of this object with all unspecified
(None) attributes replaced by their lowest values.
This method raises an error if the ``adatetime`` object has no year.
>>> adt = adatetime(year=2009, month=5)
>>> adt.floor()
datetime.datetime(2009, 5, 1, 0, 0, 0, 0)
"""
y, m, d, h, mn, s, ms = (self.year, self.month, self.day, self.hour,
self.minute, self.second, self.microsecond)
if y is None:
raise ValueError("Date has no year")
if m is None:
m = 1
if d is None:
d = 1
if h is None:
h = 0
if mn is None:
mn = 0
if s is None:
s = 0
if ms is None:
ms = 0
return datetime(y, m, d, h, mn, s, ms) | [
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|
mwouts/jupytext | f8e8352859cc22e17b11154d0770fd946c4a430a | jupytext/config.py | python | find_global_jupytext_configuration_file | () | return None | Return the global Jupytext configuration file, if any | Return the global Jupytext configuration file, if any | [
"Return",
"the",
"global",
"Jupytext",
"configuration",
"file",
"if",
"any"
] | def find_global_jupytext_configuration_file():
"""Return the global Jupytext configuration file, if any"""
for config_dir in global_jupytext_configuration_directories():
config_file = find_jupytext_configuration_file(config_dir, False)
if config_file:
return config_file
return None | [
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|
apple/ccs-calendarserver | 13c706b985fb728b9aab42dc0fef85aae21921c3 | twistedcaldav/directorybackedaddressbook.py | python | DirectoryBackedAddressBookResource.makeChild | (self, name) | return self.directory | [] | def makeChild(self, name):
from twistedcaldav.simpleresource import SimpleCalDAVResource
return SimpleCalDAVResource(principalCollections=self.principalCollections())
return self.directory | [
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|||
has2k1/plotnine | 6c82cdc20d6f81c96772da73fc07a672a0a0a6ef | plotnine/stats/stat.py | python | stat.compute_layer | (cls, data, params, layout) | return groupby_apply(data, 'PANEL', fn) | Calculate statistics for this layers
This is the top-most computation method for the
stat. It does not do any computations, but it
knows how to verify the data, partition it call the
next computation method and merge results.
stats should not override this method.
Parameters
----------
data : panda.DataFrame
Data points for all objects in a layer.
params : dict
Stat parameters
layout : plotnine.layout.Layout
Panel layout information | Calculate statistics for this layers | [
"Calculate",
"statistics",
"for",
"this",
"layers"
] | def compute_layer(cls, data, params, layout):
"""
Calculate statistics for this layers
This is the top-most computation method for the
stat. It does not do any computations, but it
knows how to verify the data, partition it call the
next computation method and merge results.
stats should not override this method.
Parameters
----------
data : panda.DataFrame
Data points for all objects in a layer.
params : dict
Stat parameters
layout : plotnine.layout.Layout
Panel layout information
"""
check_required_aesthetics(
cls.REQUIRED_AES,
list(data.columns) + list(params.keys()),
cls.__name__)
data = remove_missing(
data,
na_rm=params.get('na_rm', False),
vars=list(cls.REQUIRED_AES | cls.NON_MISSING_AES),
name=cls.__name__,
finite=True)
def fn(pdata):
"""
Helper compute function
"""
# Given data belonging to a specific panel, grab
# the corresponding scales and call the method
# that does the real computation
if len(pdata) == 0:
return pdata
pscales = layout.get_scales(pdata['PANEL'].iat[0])
return cls.compute_panel(pdata, pscales, **params)
return groupby_apply(data, 'PANEL', fn) | [
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|
awslabs/sockeye | ec2d13f7beb42d8c4f389dba0172250dc9154d5a | sockeye/model.py | python | SockeyeModel.save_version | (folder: str) | Saves version to <folder>/version.
:param folder: Destination folder. | Saves version to <folder>/version. | [
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"version",
"to",
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">",
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] | def save_version(folder: str):
"""
Saves version to <folder>/version.
:param folder: Destination folder.
"""
fname = os.path.join(folder, C.VERSION_NAME)
with open(fname, "w") as out:
out.write(__version__) | [
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||
fluentpython/example-code-2e | 80f7f84274a47579e59c29a4657691525152c9d5 | 09-closure-deco/fibo_demo.py | python | fibonacci | (n) | return fibonacci(n - 2) + fibonacci(n - 1) | [] | def fibonacci(n):
if n < 2:
return n
return fibonacci(n - 2) + fibonacci(n - 1) | [
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|||
jupyter-incubator/sparkmagic | ac0852cbe88a41faa368cf1e1c89045a2de973bf | sparkmagic/sparkmagic/utils/dataframe_parser.py | python | cell_components_iter | (cell) | Provides spans for each dataframe in a cell.
1. Determines if the evaluated output of a cell contains a Spark DF
2. Splits the cell output on Dataframes
3. Alternates yielding Plain Text and DF spans of evaluated cell output
For example if our cell looked like this with provided line numbers:
0
1 Random stuff at the start
45 +---+------+
| id|animal|
+---+------+
| 1| bat|
| 2| mouse|
| 3| horse|
247 +---+------+
Random stuff in the middle
293
The cell components are
(CellComponent.TEXT, 0, 45)
(CellComponentType.DF, 45, 247)
(CellComponentType.TEXT, 247, 293) | Provides spans for each dataframe in a cell.
1. Determines if the evaluated output of a cell contains a Spark DF
2. Splits the cell output on Dataframes
3. Alternates yielding Plain Text and DF spans of evaluated cell output
For example if our cell looked like this with provided line numbers: | [
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"numbers",
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] | def cell_components_iter(cell):
"""Provides spans for each dataframe in a cell.
1. Determines if the evaluated output of a cell contains a Spark DF
2. Splits the cell output on Dataframes
3. Alternates yielding Plain Text and DF spans of evaluated cell output
For example if our cell looked like this with provided line numbers:
0
1 Random stuff at the start
45 +---+------+
| id|animal|
+---+------+
| 1| bat|
| 2| mouse|
| 3| horse|
247 +---+------+
Random stuff in the middle
293
The cell components are
(CellComponent.TEXT, 0, 45)
(CellComponentType.DF, 45, 247)
(CellComponentType.TEXT, 247, 293)
"""
if not cell:
return
df_spans = dataframe_pattern_r.finditer(cell)
if cell_contains_dataframe(cell):
df_start, df_end = next(df_spans).span()
if(df_start > 0):
# Some text before the first Dataframe
yield (CellComponentType.TEXT, 0, df_start)
while df_start < len(cell):
yield (CellComponentType.DF, df_start, df_end)
try:
start, end = next(df_spans).span()
if start > df_end:
# Some text before the next Dataframe
yield (CellComponentType.TEXT, df_end, start)
df_start, df_end = start, end
except StopIteration:
yield (CellComponentType.TEXT, df_end, len(cell))
return
else:
# Cell does not contain a DF. The whole cell is text.
yield (CellComponentType.TEXT, 0, len(cell)) | [
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||
openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_openshift/library/oc_adm_registry.py | python | Service.add_portal_ip | (self, pip) | add cluster ip | add cluster ip | [
"add",
"cluster",
"ip"
] | def add_portal_ip(self, pip):
'''add cluster ip'''
self.put(Service.portal_ip, pip) | [
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||
kivymd/KivyMD | 1cb82f7d2437770f71be7c5a4f7de4b8da61f352 | kivymd/uix/button/button.py | python | MDFloatingActionButtonSpeedDial.open_stack | (
self, instance_floating_root_button: MDFloatingRootButton
) | Opens a button stack. | Opens a button stack. | [
"Opens",
"a",
"button",
"stack",
"."
] | def open_stack(
self, instance_floating_root_button: MDFloatingRootButton
) -> NoReturn:
"""Opens a button stack."""
for widget in self.children:
if isinstance(widget, MDFloatingLabel):
Animation.cancel_all(widget)
if self.state != "open":
y = 0
label_position = dp(56)
anim_buttons_data = {}
anim_labels_data = {}
for widget in self.children:
if isinstance(widget, MDFloatingBottomButton):
# Sets new button positions.
y += dp(56)
widget.y = widget.y * 2 + y
if not self._anim_buttons_data:
anim_buttons_data[widget] = Animation(
opacity=1,
d=self.opening_time,
t=self.opening_transition,
)
elif isinstance(widget, MDFloatingLabel):
# Sets new labels positions.
label_position += dp(56)
# Sets the position of signatures only once.
if not self._label_pos_y_set:
widget.y = widget.y * 2 + label_position
widget.x = Window.width - widget.width - dp(86)
if not self._anim_labels_data:
anim_labels_data[widget] = Animation(
opacity=1, d=self.opening_time
)
elif (
isinstance(widget, MDFloatingRootButton)
and self.root_button_anim
):
# Rotates the root button 45 degrees.
Animation(
_angle=-45,
d=self.opening_time_button_rotation,
t=self.opening_transition_button_rotation,
).start(widget)
if anim_buttons_data:
self._anim_buttons_data = anim_buttons_data
if anim_labels_data and not self.hint_animation:
self._anim_labels_data = anim_labels_data
self.state = "open"
self.dispatch("on_open")
self.do_animation_open_stack(self._anim_buttons_data)
self.do_animation_open_stack(self._anim_labels_data)
if not self._label_pos_y_set:
self._label_pos_y_set = True
else:
self.close_stack() | [
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||
biocore/qiime | 76d633c0389671e93febbe1338b5ded658eba31f | qiime/rarefaction.py | python | RarefactionMaker.rarefy_to_files | (self, output_dir, small_included=False,
include_full=False, include_lineages=False,
empty_otus_removed=False, subsample_f=subsample) | computes rarefied otu tables and writes them, one at a time
this prevents large memory usage | computes rarefied otu tables and writes them, one at a time | [
"computes",
"rarefied",
"otu",
"tables",
"and",
"writes",
"them",
"one",
"at",
"a",
"time"
] | def rarefy_to_files(self, output_dir, small_included=False,
include_full=False, include_lineages=False,
empty_otus_removed=False, subsample_f=subsample):
""" computes rarefied otu tables and writes them, one at a time
this prevents large memory usage"""
if not include_lineages:
for (val, id, meta) in self.otu_table.iter(axis='observation'):
try:
del meta['taxonomy']
except (TypeError, KeyError) as e:
# no meta or just no taxonomy present
pass
self.output_dir = output_dir
for depth in self.rare_depths:
for rep in range(self.num_reps):
sub_otu_table = get_rare_data(self.otu_table,
depth,
small_included,
subsample_f=subsample_f)
if empty_otus_removed:
sub_otu_table = filter_otus_from_otu_table(
sub_otu_table, sub_otu_table.ids(axis='observation'),
1, inf, 0, inf)
self._write_rarefaction(depth, rep, sub_otu_table)
if include_full:
self._write_rarefaction('full', 0, self.otu_table) | [
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] | https://github.com/biocore/qiime/blob/76d633c0389671e93febbe1338b5ded658eba31f/qiime/rarefaction.py#L96-L125 |
||
edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/python_clients/venv/lib/python2.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py | python | TarInfo._apply_pax_info | (self, pax_headers, encoding, errors) | Replace fields with supplemental information from a previous
pax extended or global header. | Replace fields with supplemental information from a previous
pax extended or global header. | [
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"with",
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"information",
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"previous",
"pax",
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"or",
"global",
"header",
"."
] | def _apply_pax_info(self, pax_headers, encoding, errors):
"""Replace fields with supplemental information from a previous
pax extended or global header.
"""
for keyword, value in pax_headers.items():
if keyword == "GNU.sparse.name":
setattr(self, "path", value)
elif keyword == "GNU.sparse.size":
setattr(self, "size", int(value))
elif keyword == "GNU.sparse.realsize":
setattr(self, "size", int(value))
elif keyword in PAX_FIELDS:
if keyword in PAX_NUMBER_FIELDS:
try:
value = PAX_NUMBER_FIELDS[keyword](value)
except ValueError:
value = 0
if keyword == "path":
value = value.rstrip("/")
setattr(self, keyword, value)
self.pax_headers = pax_headers.copy() | [
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||
maurosoria/dirsearch | b83e68c8fdf360ab06be670d7b92b263262ee5b1 | thirdparty/requests/auth.py | python | HTTPDigestAuth.handle_redirect | (self, r, **kwargs) | Reset num_401_calls counter on redirects. | Reset num_401_calls counter on redirects. | [
"Reset",
"num_401_calls",
"counter",
"on",
"redirects",
"."
] | def handle_redirect(self, r, **kwargs):
"""Reset num_401_calls counter on redirects."""
if r.is_redirect:
self._thread_local.num_401_calls = 1 | [
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||
ctallec/world-models | d6abd9ce97409734a766eb67ccf0d1967ba9bf0c | envs/simulated_carracing.py | python | SimulatedCarracing.render | (self) | Rendering | Rendering | [
"Rendering"
] | def render(self): # pylint: disable=arguments-differ
""" Rendering """
import matplotlib.pyplot as plt
if not self.monitor:
self.figure = plt.figure()
self.monitor = plt.imshow(
np.zeros((RED_SIZE, RED_SIZE, 3),
dtype=np.uint8))
self.monitor.set_data(self._visual_obs)
plt.pause(.01) | [
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||
nyu-dl/dl4marco-bert | f1d18d63271d9e53cd23fc27bd7cc911f89b89db | tokenization.py | python | convert_tokens_to_ids | (vocab, tokens) | return [vocab[token] for token in tokens] | Converts a sequence of tokens into ids using the vocab. | Converts a sequence of tokens into ids using the vocab. | [
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"""Converts a sequence of tokens into ids using the vocab."""
return [vocab[token] for token in tokens] | [
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|
SaltieRL/Saltie | a491ecfa5c77583ec370a0a378d27865dbd8da63 | framework/self_evolving_car/genetic_algorithm.py | python | GeneticAlgorithm.mutate | (self, list, mut_rate) | Randomizes a certain amount of the first five models' parameters based on mutation rate
:param list contains the parameters to be mutated
:param mut_rate is the mutation rate | Randomizes a certain amount of the first five models' parameters based on mutation rate
:param list contains the parameters to be mutated
:param mut_rate is the mutation rate | [
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"""Randomizes a certain amount of the first five models' parameters based on mutation rate
:param list contains the parameters to be mutated
:param mut_rate is the mutation rate"""
for i, bot in enumerate(list):
new_genes = self.Model()
for param, param_new in zip(bot.parameters(), new_genes.parameters()):
mask = self.torch.rand(param.data.size()) < mut_rate / (i + 1)
param.data[mask] = param_new.data[mask] | [
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||
zsdonghao/text-to-image | c1fbfa4349f5aa1c74c9fe17743cc0cff34f1aab | tensorlayer/cost.py | python | dice_coe | (output, target, epsilon=1e-10) | Sørensen–Dice coefficient for comparing the similarity of two distributions,
usually be used for binary image segmentation i.e. labels are binary.
The coefficient = [0, 1], 1 if totally match.
Parameters
-----------
output : tensor
A distribution with shape: [batch_size, ....], (any dimensions).
target : tensor
A distribution with shape: [batch_size, ....], (any dimensions).
epsilon : float
An optional name to attach to this layer.
Examples
---------
>>> outputs = tl.act.pixel_wise_softmax(network.outputs)
>>> dice_loss = 1 - tl.cost.dice_coe(outputs, y_, epsilon=1e-5)
References
-----------
- `wiki-dice <https://en.wikipedia.org/wiki/Sørensen–Dice_coefficient>`_ | Sørensen–Dice coefficient for comparing the similarity of two distributions,
usually be used for binary image segmentation i.e. labels are binary.
The coefficient = [0, 1], 1 if totally match. | [
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"""Sørensen–Dice coefficient for comparing the similarity of two distributions,
usually be used for binary image segmentation i.e. labels are binary.
The coefficient = [0, 1], 1 if totally match.
Parameters
-----------
output : tensor
A distribution with shape: [batch_size, ....], (any dimensions).
target : tensor
A distribution with shape: [batch_size, ....], (any dimensions).
epsilon : float
An optional name to attach to this layer.
Examples
---------
>>> outputs = tl.act.pixel_wise_softmax(network.outputs)
>>> dice_loss = 1 - tl.cost.dice_coe(outputs, y_, epsilon=1e-5)
References
-----------
- `wiki-dice <https://en.wikipedia.org/wiki/Sørensen–Dice_coefficient>`_
"""
# inse = tf.reduce_sum( tf.mul(output, target) )
# l = tf.reduce_sum( tf.mul(output, output) )
# r = tf.reduce_sum( tf.mul(target, target) )
inse = tf.reduce_sum( output * target )
l = tf.reduce_sum( output * output )
r = tf.reduce_sum( target * target )
dice = 2 * (inse) / (l + r)
if epsilon == 0:
return dice
else:
return tf.clip_by_value(dice, 0, 1.0-epsilon) | [
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||
ansible/ansible-modules-core | 00911a75ad6635834b6d28eef41f197b2f73c381 | source_control/subversion.py | python | Subversion.get_revision | (self) | return rev, url | Revision and URL of subversion working directory. | Revision and URL of subversion working directory. | [
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] | def get_revision(self):
'''Revision and URL of subversion working directory.'''
text = '\n'.join(self._exec(["info", self.dest]))
rev = re.search(r'^Revision:.*$', text, re.MULTILINE).group(0)
url = re.search(r'^URL:.*$', text, re.MULTILINE).group(0)
return rev, url | [
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|
aws/aws-parallelcluster | f1fe5679a01c524e7ea904c329bd6d17318c6cd9 | api/client/src/pcluster_client/model/image_builder_image_status.py | python | ImageBuilderImageStatus.openapi_types | () | return {
'value': (str,),
} | This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type. | This must be a method because a model may have properties that are
of type self, this must run after the class is loaded | [
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"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type.
"""
return {
'value': (str,),
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|
pytorch/fairseq | 1575f30dd0a9f7b3c499db0b4767aa4e9f79056c | fairseq/optim/fairseq_optimizer.py | python | FairseqOptimizer.clip_grad_norm | (self, max_norm, aggregate_norm_fn=None) | return utils.clip_grad_norm_(self.params, max_norm, aggregate_norm_fn) | Clips gradient norm. | Clips gradient norm. | [
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] | def clip_grad_norm(self, max_norm, aggregate_norm_fn=None):
"""Clips gradient norm."""
return utils.clip_grad_norm_(self.params, max_norm, aggregate_norm_fn) | [
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|
emesene/emesene | 4548a4098310e21b16437bb36223a7f632a4f7bc | emesene/gui/gtkui/Dialog.py | python | InviteWindow.__init__ | (self, session, callback, l_buddy_exclude) | constructor | constructor | [
"constructor"
] | def __init__(self, session, callback, l_buddy_exclude):
"""
constructor
"""
gtk.Window.__init__(self)
global dialogs
dialogs.append(self)
self.set_border_width(1)
self.set_title(_('Invite friend'))
self.set_default_size(300, 250)
self.session = session
self.callback = callback
ContactList = extension.get_default('contact list')
self.contact_list = ContactList(session)
sel = self.contact_list.get_selection()
sel.set_mode(gtk.SELECTION_MULTIPLE)
self.contact_list.destroy_on_filtering = True
self.contact_list.nick_template = \
'[$DISPLAY_NAME][$NL][$small][$ACCOUNT][$/small]'
order_by_group = self.contact_list.session.config.b_order_by_group
show_blocked = self.contact_list.session.config.b_show_blocked
show_offline = self.contact_list.session.config.b_show_offline
self.contact_list.order_by_group = False
self.contact_list.show_blocked = False
self.contact_list.show_offline = False
self.contact_list.hide_on_filtering = True
self.contact_list.session.config.b_order_by_group = order_by_group
self.contact_list.session.config.b_show_blocked = show_blocked
self.contact_list.session.config.b_show_offline = show_offline
self.set_type_hint(gtk.gdk.WINDOW_TYPE_HINT_DIALOG)
self.set_position(gtk.WIN_POS_CENTER)
vbox = gtk.VBox()
vbox.set_spacing(1)
bbox = gtk.HButtonBox()
bbox.set_spacing(1)
bbox.set_layout(gtk.BUTTONBOX_END)
badd = gtk.Button(stock=gtk.STOCK_ADD)
bclose = gtk.Button(stock=gtk.STOCK_CLOSE)
search = SearchEntry.SearchEntry()
search.connect('changed', self._on_search_changed)
scroll = gtk.ScrolledWindow()
scroll.set_policy(gtk.POLICY_NEVER, gtk.POLICY_AUTOMATIC)
scroll.set_shadow_type(gtk.SHADOW_IN)
scroll.set_border_width(1)
scroll.add(self.contact_list)
bbox.pack_start(bclose)
bbox.pack_start(badd)
vbox.pack_start(scroll, True, True)
vbox.pack_start(search, False)
vbox.pack_start(bbox, False)
self.add(vbox)
badd.connect('clicked', self._on_add_clicked)
bclose.connect('clicked', lambda *args: self.destroy())
self.connect('key-press-event', self._on_key_press)
self.connect('delete-event', lambda *args: self.destroy())
self.contact_list.contact_selected.subscribe(
self._on_contact_selected)
self.contact_list.fill()
l_buddy_exclude.append(self.session.account.account)
for buddy in l_buddy_exclude:
self.contact_list.remove_contact(e3.Contact(buddy))
self.set_modal(True)
self.show()
vbox.show_all() | [
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||
9miao/Firefly | fd2795b8c26de6ab63bbec23d11f18c3dfb39a50 | gfirefly/utils/interfaces.py | python | IDataPackProtoc.getHeadlength | () | 获取数据包的长度 | 获取数据包的长度 | [
"获取数据包的长度"
] | def getHeadlength():
"""获取数据包的长度
"""
pass | [
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||
siznax/wptools | 788cdc2078696dacb14652d5f2ad098a585e4763 | wptools/query.py | python | WPToolsQuery.labels | (self, qids) | return query | Returns Wikidata labels query string | Returns Wikidata labels query string | [
"Returns",
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"string"
] | def labels(self, qids):
"""
Returns Wikidata labels query string
"""
if len(qids) > 50:
raise ValueError("The limit is 50.")
self.domain = 'www.wikidata.org'
self.uri = self.wiki_uri(self.domain)
query = self.WIKIDATA.substitute(
WIKI=self.uri,
ENDPOINT=self.endpoint,
LANG=self.variant or self.lang,
PROPS='labels')
qids = '|'.join(qids)
query += "&ids=%s" % qids
self.set_status('labels', qids)
return query | [
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|
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/rigged_configurations/rigged_configuration_element.py | python | RCNonSimplyLacedElement.to_virtual_configuration | (self) | return self.parent().to_virtual(self) | Return the corresponding rigged configuration in the virtual crystal.
EXAMPLES::
sage: RC = RiggedConfigurations(['C',2,1], [[1,2],[1,1],[2,1]])
sage: elt = RC(partition_list=[[3],[2]]); elt
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0[ ][ ][ ]0
<BLANKLINE>
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sage: elt.to_virtual_configuration()
<BLANKLINE>
0[ ][ ][ ]0
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0[ ][ ][ ][ ]0
<BLANKLINE>
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] | def to_virtual_configuration(self):
"""
Return the corresponding rigged configuration in the virtual crystal.
EXAMPLES::
sage: RC = RiggedConfigurations(['C',2,1], [[1,2],[1,1],[2,1]])
sage: elt = RC(partition_list=[[3],[2]]); elt
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return self.parent().to_virtual(self) | [
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|
fluentpython/example-code-2e | 80f7f84274a47579e59c29a4657691525152c9d5 | 24-class-metaprog/metabunch/pre3.6/bunch.py | python | MetaBunch.__prepare__ | (name, *bases, **kwargs) | return collections.OrderedDict() | [] | def __prepare__(name, *bases, **kwargs):
return collections.OrderedDict() | [
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|||
kylebebak/Requester | 4a9f9f051fa5fc951a8f7ad098a328261ca2db97 | deps/graphql/parser.py | python | GraphQLParser.p_selection | (self, p) | selection : field
| fragment_spread
| inline_fragment | selection : field
| fragment_spread
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"""
selection : field
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||
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/kombu/transport/virtual/base.py | python | AbstractChannel._get_and_deliver | (self, queue, callback) | [] | def _get_and_deliver(self, queue, callback):
message = self._get(queue)
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||||
mtianyan/OnlineMooc | 51a910e27c8d2808a8a5198b4db31f463e646bf6 | app_api/models.py | python | EmailVerifyRecord.__str__ | (self) | return self.code + ":" + self.email | [] | def __str__(self):
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|||
edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/tagging/models.py | python | TagManager.update_tags | (self, obj, tag_names) | Update tags associated with an object. | Update tags associated with an object. | [
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] | def update_tags(self, obj, tag_names):
"""
Update tags associated with an object.
"""
ctype = ContentType.objects.get_for_model(obj)
current_tags = list(self.filter(items__content_type__pk=ctype.pk,
items__object_id=obj.pk))
updated_tag_names = parse_tag_input(tag_names)
if settings.FORCE_LOWERCASE_TAGS:
updated_tag_names = [t.lower() for t in updated_tag_names]
# Remove tags which no longer apply
tags_for_removal = [tag for tag in current_tags \
if tag.name not in updated_tag_names]
if len(tags_for_removal):
TaggedItem._default_manager.filter(content_type__pk=ctype.pk,
object_id=obj.pk,
tag__in=tags_for_removal).delete()
# Add new tags
current_tag_names = [tag.name for tag in current_tags]
for tag_name in updated_tag_names:
if tag_name not in current_tag_names:
tag, created = self.get_or_create(name=tag_name)
TaggedItem._default_manager.create(tag=tag, object=obj) | [
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||
slush0/stratum-mining | b2a24d7424784cada95010232cdb79cfed481da6 | lib/util.py | python | ser_uint256_be | (u) | return rs | ser_uint256 to big endian | ser_uint256 to big endian | [
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"to",
"big",
"endian"
] | def ser_uint256_be(u):
'''ser_uint256 to big endian'''
rs = ""
for i in xrange(8):
rs += struct.pack(">I", u & 0xFFFFFFFFL)
u >>= 32
return rs | [
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|
fake-name/ReadableWebProxy | ed5c7abe38706acc2684a1e6cd80242a03c5f010 | WebMirror/management/rss_parser_funcs/feed_parse_extractCcKhatUs.py | python | extractCcKhatUs | (item) | return False | Parser for 'cc.khat.us' | Parser for 'cc.khat.us' | [
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] | def extractCcKhatUs(item):
'''
Parser for 'cc.khat.us'
'''
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol) or "preview" in item['title'].lower():
return None
tagmap = [
('PRC', 'PRC', 'translated'),
('Loiterous', 'Loiterous', 'oel'),
]
for tagname, name, tl_type in tagmap:
if tagname in item['tags']:
return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type)
return False | [
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|
wrobstory/vincent | c5a06e50179015fbb788a7a42e4570ff4467a9e9 | vincent/marks.py | python | Mark.scales | (value) | list or KeyedList: For grouped marks, you can define a set of scales
for within the mark groups | list or KeyedList: For grouped marks, you can define a set of scales
for within the mark groups | [
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"""list or KeyedList: For grouped marks, you can define a set of scales
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||
Mindwerks/worldengine | 64dff8eb7824ce46b5b6cb8006bcef21822ef144 | worldengine/drawing_functions.py | python | _draw_tropical_dry_forest | (pixels, x, y, w, h) | [] | def _draw_tropical_dry_forest(pixels, x, y, w, h):
c = (51, 36, 3, 255)
c2 = (139, 204, 58, 255)
_draw_forest_pattern2(pixels, x, y, c, c2) | [
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dropbox/dropbox-sdk-python | 015437429be224732990041164a21a0501235db1 | dropbox/team.py | python | RevokeDeviceSessionArg.mobile_client | (cls, val) | return cls('mobile_client', val) | Create an instance of this class set to the ``mobile_client`` tag with
value ``val``.
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"""
Create an instance of this class set to the ``mobile_client`` tag with
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wummel/linkchecker | c2ce810c3fb00b895a841a7be6b2e78c64e7b042 | linkcheck/fileutil.py | python | get_mtime | (filename) | Return modification time of filename or zero on errors. | Return modification time of filename or zero on errors. | [
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UlionTse/translators | af661ebb7b797e0e9493f1a1c8d30a1ea2edef90 | translators/apis.py | python | Alibaba.alibaba_api | (self, query_text:str, from_language:str='auto', to_language:str='en', **kwargs) | return data if is_detail_result else data['listTargetText'][0] | https://translate.alibaba.com
:param query_text: str, must.
:param from_language: str, default 'auto'.
:param to_language: str, default 'en'.
:param **kwargs:
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:param if_ignore_limit_of_length: boolean, default False.
:param is_detail_result: boolean, default False.
:param timeout: float, default None.
:param proxies: dict, default None.
:param sleep_seconds: float, default `random.random()`.
:return: str or dict | https://translate.alibaba.com
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:param to_language: str, default 'en'.
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:param is_detail_result: boolean, default False.
:param timeout: float, default None.
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:param query_text: str, must.
:param from_language: str, default 'auto'.
:param to_language: str, default 'en'.
:param **kwargs:
:param professional_field: str, default 'message', choose from ("general","message","offer")
:param if_ignore_limit_of_length: boolean, default False.
:param is_detail_result: boolean, default False.
:param timeout: float, default None.
:param proxies: dict, default None.
:param sleep_seconds: float, default `random.random()`.
:return: str or dict
"""
use_domain = kwargs.get('professional_field', 'message')
assert use_domain in ("general", "message", "offer")
is_detail_result = kwargs.get('is_detail_result', False)
timeout = kwargs.get('timeout', None)
proxies = kwargs.get('proxies', None)
sleep_seconds = kwargs.get('sleep_seconds', random.random())
if_ignore_limit_of_length = kwargs.get('if_ignore_limit_of_length', False)
query_text = self.check_query_text(query_text, if_ignore_limit_of_length)
with requests.Session() as ss:
host_response = ss.get(self.host_url, headers=self.host_headers, timeout=timeout, proxies=proxies)
dmtrack_pageid = self.get_dmtrack_pageid(host_response)
if not self.language_map:
self.language_map = self.get_language_map(ss, use_domain, dmtrack_pageid, timeout, proxies)
from_language, to_language = self.check_language(from_language, to_language, self.language_map, output_zh=self.output_zh)
form_data = {
"srcLanguage": from_language,
"tgtLanguage": to_language,
"srcText": query_text,
"viewType": "",
"source": "",
"bizType": use_domain,
}
params = {"dmtrack_pageid":dmtrack_pageid}
r = ss.post(self.api_url, headers=self.api_headers, params=params, data=form_data, timeout=timeout, proxies=proxies)
r.raise_for_status()
data = r.json()
time.sleep(sleep_seconds)
self.query_count += 1
return data if is_detail_result else data['listTargetText'][0] | [
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|
pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/poplib.py | python | POP3.uidl | (self, which=None) | return self._longcmd('UIDL') | Return message digest (unique id) list.
If 'which', result contains unique id for that message
in the form 'response mesgnum uid', otherwise result is
the list ['response', ['mesgnum uid', ...], octets] | Return message digest (unique id) list. | [
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] | def uidl(self, which=None):
"""Return message digest (unique id) list.
If 'which', result contains unique id for that message
in the form 'response mesgnum uid', otherwise result is
the list ['response', ['mesgnum uid', ...], octets]
"""
if which is not None:
return self._shortcmd('UIDL %s' % which)
return self._longcmd('UIDL') | [
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|
PaddlePaddle/PaddleSpeech | 26524031d242876b7fdb71582b0b3a7ea45c7d9d | third_party/python_kaldi_features/python_speech_features/sigproc.py | python | powspec | (frames, NFFT) | return numpy.square(magspec(frames, NFFT)) | Compute the power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1).
:param frames: the array of frames. Each row is a frame.
:param NFFT: the FFT length to use. If NFFT > frame_len, the frames are zero-padded.
:returns: If frames is an NxD matrix, output will be Nx(NFFT/2+1). Each row will be the power spectrum of the corresponding frame. | Compute the power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1). | [
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"""Compute the power spectrum of each frame in frames. If frames is an NxD matrix, output will be Nx(NFFT/2+1).
:param frames: the array of frames. Each row is a frame.
:param NFFT: the FFT length to use. If NFFT > frame_len, the frames are zero-padded.
:returns: If frames is an NxD matrix, output will be Nx(NFFT/2+1). Each row will be the power spectrum of the corresponding frame.
"""
return numpy.square(magspec(frames, NFFT)) | [
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|
onaio/onadata | 89ad16744e8f247fb748219476f6ac295869a95f | onadata/libs/utils/openid_connect_tools.py | python | OpenIDHandler.end_openid_provider_session | (self) | return response | Clears the SSO cookie set at authentication and redirects the User
to the end_session endpoint provided by the provider configuration | Clears the SSO cookie set at authentication and redirects the User
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"""
Clears the SSO cookie set at authentication and redirects the User
to the end_session endpoint provided by the provider configuration
"""
end_session_endpoint = self.provider_configuration.get(
'end_session_endpoint')
target_url_after_logout = self.provider_configuration.get(
'target_url_after_logout')
response = HttpResponseRedirect(
end_session_endpoint +
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response.delete_cookie('SSO')
return response | [
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|
jparkhill/TensorMol | d52104dc7ee46eec8301d332a95d672270ac0bd1 | TensorMol/TFNetworks/TFMolInstanceDirect.py | python | MolInstance_DirectBP_EE_ChargeEncode_Update_vdw_DSF_elu_Normalize_Dropout_Conv.energy_inference | (self, inp, indexs, cc_energy, xyzs, Zs, eles, c6, R_vdw, Reep, EE_cuton, EE_cutoff, keep_prob) | return total_energy_with_vdw, bp_energy, vdw_energy, energy_vars, output | Builds a Behler-Parinello graph
Args:
inp: a list of (num_of atom type X flattened input shape) matrix of input cases.
index: a list of (num_of atom type X batchsize) array which linearly combines the elements
Returns:
The BP graph output | Builds a Behler-Parinello graph | [
"Builds",
"a",
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] | def energy_inference(self, inp, indexs, cc_energy, xyzs, Zs, eles, c6, R_vdw, Reep, EE_cuton, EE_cutoff, keep_prob):
"""
Builds a Behler-Parinello graph
Args:
inp: a list of (num_of atom type X flattened input shape) matrix of input cases.
index: a list of (num_of atom type X batchsize) array which linearly combines the elements
Returns:
The BP graph output
"""
# convert the index matrix from bool to float
xyzsInBohr = tf.multiply(xyzs,BOHRPERA)
Ebranches=[]
output = tf.zeros([self.batch_size, self.MaxNAtoms], dtype=self.tf_prec)
atom_outputs = []
with tf.name_scope("EnergyNet"):
for e in range(len(self.eles)):
Ebranches.append([])
inputs = inp[e]
shp_in = tf.shape(inputs)
index = tf.cast(indexs[e], tf.int64)
for i in range(len(self.filters)):
if i == 0:
with tf.name_scope(str(self.eles[e])+'_conv_hidden1_energy'):
conv = tf.layers.conv2d(tf.reshape(tf.cast(inputs, dtype=tf.float32),[-1, self.inshape, 1, 1]), filters=self.filters[i], kernel_size=self.kernel_size[i], strides=self.strides[i], padding="valid", activation=tf.nn.relu)
Ebranches[-1].append(conv)
else:
with tf.name_scope(str(self.eles[e])+'_conv_hidden'+str(i+1)+"_energy"):
conv = tf.layers.conv2d(Ebranches[-1][-1], filters=self.filters[i], kernel_size=self.kernel_size[i], strides=self.strides[i], padding="valid", activation=tf.nn.relu)
Ebranches[-1].append(conv)
for i in range(len(self.HiddenLayers)):
if i == 0:
with tf.name_scope(str(self.eles[e])+'_hidden1_energy'):
Ebranches[-1][-1] = tf.reshape(tf.cast(Ebranches[-1][-1], dtype=tf.float64), [shp_in[0], -1])
weights = self._variable_with_weight_decay(var_name='weights', var_shape=[512 , self.HiddenLayers[i]], var_stddev=1.0/(10+math.sqrt(float(512.0))), var_wd=0.001)
biases = tf.Variable(tf.zeros([self.HiddenLayers[i]], dtype=self.tf_prec), name='biases')
Ebranches[-1].append(self.activation_function(tf.matmul(Ebranches[-1][-1], weights) + biases))
else:
with tf.name_scope(str(self.eles[e])+'_hidden'+str(i+1)+"_energy"):
weights = self._variable_with_weight_decay(var_name='weights', var_shape=[self.HiddenLayers[i-1], self.HiddenLayers[i]], var_stddev=1.0/(10+math.sqrt(float(self.HiddenLayers[i-1]))), var_wd=0.001)
biases = tf.Variable(tf.zeros([self.HiddenLayers[i]], dtype=self.tf_prec), name='biases')
Ebranches[-1].append(self.activation_function(tf.matmul(Ebranches[-1][-1], weights) + biases))
with tf.name_scope(str(self.eles[e])+'_regression_linear'):
shp = tf.shape(inputs)
weights = self._variable_with_weight_decay(var_name='weights', var_shape=[self.HiddenLayers[-1], 1], var_stddev=1.0/(10+math.sqrt(float(self.HiddenLayers[-1]))), var_wd=None)
biases = tf.Variable(tf.zeros([1], dtype=self.tf_prec), name='biases')
Ebranches[-1].append(tf.matmul(tf.nn.dropout(Ebranches[-1][-1], keep_prob), weights) + biases)
shp_out = tf.shape(Ebranches[-1][-1])
cut = tf.slice(Ebranches[-1][-1],[0,0],[shp_out[0],1])
rshp = tf.reshape(cut,[1,shp_out[0]])
atom_outputs.append(rshp)
rshpflat = tf.reshape(cut,[shp_out[0]])
atom_indice = tf.slice(index, [0,1], [shp_out[0],1])
ToAdd = tf.reshape(tf.scatter_nd(atom_indice, rshpflat, [self.batch_size*self.MaxNAtoms]),[self.batch_size, self.MaxNAtoms])
output = tf.add(output, ToAdd)
tf.verify_tensor_all_finite(output,"Nan in output!!!")
bp_energy = tf.reshape(tf.reduce_sum(output, axis=1), [self.batch_size])
total_energy = tf.add(bp_energy, cc_energy)
vdw_energy = TFVdwPolyLR(xyzsInBohr, Zs, eles, c6, R_vdw, EE_cuton*BOHRPERA, Reep)
total_energy_with_vdw = tf.add(total_energy, vdw_energy)
energy_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope="EnergyNet")
return total_energy_with_vdw, bp_energy, vdw_energy, energy_vars, output | [
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pytoolz/toolz | 294e981edad035a7ac6f0e2b48f1738368fa4b34 | toolz/_signatures.py | python | _is_partial_args | (func, args, kwargs) | return any(check_partial(sig, args, kwargs) for sig in sigs) | Like ``is_partial_args`` for builtins in our ``signatures`` registry | Like ``is_partial_args`` for builtins in our ``signatures`` registry | [
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""" Like ``is_partial_args`` for builtins in our ``signatures`` registry"""
if func not in signatures:
return None
sigs = signatures[func]
return any(check_partial(sig, args, kwargs) for sig in sigs) | [
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conda/conda | 09cb6bdde68e551852c3844fd2b59c8ba4cafce2 | conda/common/configuration.py | python | PrimitiveParameter.__init__ | (self, default, element_type=None, validation=None) | Args:
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element_type (type or Tuple[type]): Type-validation of parameter's value. If None,
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seopbo/nlp_classification | 21ea6e3f5737e7074bdd8dd190e5f5172f86f6bf | Efficient_Character-level_Document_Classification_by_Combining_Convolution_and_Recurrent_Layers/utils.py | python | Config.update | (self, json_path_or_dict) | Updating Config instance
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"""
if isinstance(json_path_or_dict, dict):
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svenkreiss/pysparkling | f0e8e8d039f3313c2693b7c7576cb1b7ba5a6d78 | pysparkling/sql/functions.py | python | month | (e) | return col(Month(ensure_column(e))) | :rtype: Column | :rtype: Column | [
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"""
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/whoosh/src/whoosh/classify.py | python | Bo1Model.score | (self, weight_in_top, weight_in_collection, top_total) | return weight_in_top * log((1.0 + f) / f, 2) + log(1.0 + f, 2) | [] | def score(self, weight_in_top, weight_in_collection, top_total):
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pycontribs/pyrax | a0c022981f76a4cba96a22ecc19bb52843ac4fbe | pyrax/client.py | python | BaseClient.get | (self, item) | return self._manager.get(item) | Gets a specific resource. | Gets a specific resource. | [
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Azure/azure-devops-cli-extension | 11334cd55806bef0b99c3bee5a438eed71e44037 | azure-devops/azext_devops/dev/repos/policy.py | python | create_policy_approver_count | (repository_id, branch, blocking, enabled,
minimum_approver_count, creator_vote_counts, allow_downvotes, reset_on_source_push,
branch_match_type='exact',
organization=None, project=None, detect=None) | return policy_client.create_policy_configuration(configuration=configuration, project=project) | Create approver count policy | Create approver count policy | [
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organization=None, project=None, detect=None):
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"""
organization, project = resolve_instance_and_project(
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param_name_array = ['minimumApproverCount', 'creatorVoteCounts', 'allowDownvotes', 'resetOnSourcePush']
param_value_array = [minimum_approver_count, creator_vote_counts, allow_downvotes, reset_on_source_push]
configuration = create_configuration_object(repository_id, branch, blocking, enabled,
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|
biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/unsupervised/owdistancemap.py | python | DistanceMapItem.__elastic_band_select | (self, area, command) | [] | def __elastic_band_select(self, area, command):
if command & self.Clear and self.__dragging:
item, area = self.__dragging
_remove_item(item)
self.__dragging = None
if command & self.Select:
if self.__dragging:
item, _ = self.__dragging
else:
item = DistanceMapItem.SelectionRect(self)
item.setPen(QPen(Qt.red, 0))
# intersection with existing regions
intersection = [(item, selarea)
for item, selarea in self.__selections
if area.intersects(selarea)]
fullarea = reduce(
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area
)
visualarea = self.__visualRectForSelection(fullarea)
item.setRect(visualarea)
self.__dragging = item, area
if command & self.Commit and self.__dragging:
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||||
jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/matplotlib/__init__.py | python | get_home | () | Return the user's home directory.
If the user's home directory cannot be found, return None. | Return the user's home directory. | [
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"user",
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"home",
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] | def get_home():
"""
Return the user's home directory.
If the user's home directory cannot be found, return None.
"""
try:
return str(Path.home())
except Exception:
return None | [
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||
eirannejad/pyRevit | 49c0b7eb54eb343458ce1365425e6552d0c47d44 | pyrevitlib/pyrevit/coreutils/__init__.py | python | format_hex_rgb | (rgb_value) | Formats rgb value as #RGB value string. | Formats rgb value as #RGB value string. | [
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"""Formats rgb value as #RGB value string."""
if isinstance(rgb_value, str):
if not rgb_value.startswith('#'):
return '#%s' % rgb_value
else:
return rgb_value
elif isinstance(rgb_value, int):
return '#%x' % rgb_value | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/organization/v20181225/organization_client.py | python | OrganizationClient.QuitOrganization | (self, request) | 退出企业组织
:param request: Request instance for QuitOrganization.
:type request: :class:`tencentcloud.organization.v20181225.models.QuitOrganizationRequest`
:rtype: :class:`tencentcloud.organization.v20181225.models.QuitOrganizationResponse` | 退出企业组织 | [
"退出企业组织"
] | def QuitOrganization(self, request):
"""退出企业组织
:param request: Request instance for QuitOrganization.
:type request: :class:`tencentcloud.organization.v20181225.models.QuitOrganizationRequest`
:rtype: :class:`tencentcloud.organization.v20181225.models.QuitOrganizationResponse`
"""
try:
params = request._serialize()
body = self.call("QuitOrganization", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.QuitOrganizationResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
else:
raise TencentCloudSDKException(e.message, e.message) | [
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||
PokemonGoF/PokemonGo-Bot-Desktop | 4bfa94f0183406c6a86f93645eff7abd3ad4ced8 | build/pywin/Lib/mhlib.py | python | MH.getcontext | (self) | return context | Return the name of the current folder. | Return the name of the current folder. | [
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] | def getcontext(self):
"""Return the name of the current folder."""
context = pickline(os.path.join(self.getpath(), 'context'),
'Current-Folder')
if not context: context = 'inbox'
return context | [
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|
osmr/imgclsmob | f2993d3ce73a2f7ddba05da3891defb08547d504 | chainer_/chainercv2/models/pspnet.py | python | pspnet_resnetd50b_cityscapes | (pretrained_backbone=False, classes=19, aux=True, **kwargs) | return get_pspnet(backbone=backbone, classes=classes, aux=aux, model_name="pspnet_resnetd50b_cityscapes",
**kwargs) | PSPNet model on the base of ResNet(D)-50b for Cityscapes from 'Pyramid Scene Parsing Network,'
https://arxiv.org/abs/1612.01105.
Parameters:
----------
pretrained_backbone : bool, default False
Whether to load the pretrained weights for feature extractor.
classes : int, default 19
Number of segmentation classes.
aux : bool, default True
Whether to output an auxiliary result.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters. | PSPNet model on the base of ResNet(D)-50b for Cityscapes from 'Pyramid Scene Parsing Network,'
https://arxiv.org/abs/1612.01105. | [
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"""
PSPNet model on the base of ResNet(D)-50b for Cityscapes from 'Pyramid Scene Parsing Network,'
https://arxiv.org/abs/1612.01105.
Parameters:
----------
pretrained_backbone : bool, default False
Whether to load the pretrained weights for feature extractor.
classes : int, default 19
Number of segmentation classes.
aux : bool, default True
Whether to output an auxiliary result.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
backbone = resnetd50b(pretrained=pretrained_backbone, ordinary_init=False, bends=(3,)).features
del backbone.final_pool
return get_pspnet(backbone=backbone, classes=classes, aux=aux, model_name="pspnet_resnetd50b_cityscapes",
**kwargs) | [
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|
locationtech-labs/geopyspark | 97bcb17a56ed4b4059e2f0dbab97706562cac692 | geopyspark/geotrellis/catalog.py | python | ValueReader.__init__ | (self, uri, layer_name, zoom=None) | [] | def __init__(self, uri, layer_name, zoom=None):
self.layer_name = layer_name
self.zoom = zoom
pysc = get_spark_context()
ValueReaderWrapper = pysc._gateway.jvm.geopyspark.geotrellis.io.ValueReaderWrapper
self.wrapper = ValueReaderWrapper(uri) | [
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||||
rpmuller/pyquante2 | 6e34cb4480ae7dbd8c5e44d221d8b27584890c83 | pyquante2/ints/one.py | python | nuclear_attraction | (alpha1,lmn1,A,alpha2,lmn2,B,C) | return val | Full form of the nuclear attraction integral
>>> isclose(nuclear_attraction(1,(0,0,0),array((0,0,0),'d'),1,(0,0,0),array((0,0,0),'d'),array((0,0,0),'d')),-3.141593)
True | Full form of the nuclear attraction integral
>>> isclose(nuclear_attraction(1,(0,0,0),array((0,0,0),'d'),1,(0,0,0),array((0,0,0),'d'),array((0,0,0),'d')),-3.141593)
True | [
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"""
Full form of the nuclear attraction integral
>>> isclose(nuclear_attraction(1,(0,0,0),array((0,0,0),'d'),1,(0,0,0),array((0,0,0),'d'),array((0,0,0),'d')),-3.141593)
True
"""
l1,m1,n1 = lmn1
l2,m2,n2 = lmn2
gamma = alpha1+alpha2
P = gaussian_product_center(alpha1,A,alpha2,B)
rab2 = norm2(A-B)
rcp2 = norm2(C-P)
dPA = P-A
dPB = P-B
dPC = P-C
Ax = A_array(l1,l2,dPA[0],dPB[0],dPC[0],gamma)
Ay = A_array(m1,m2,dPA[1],dPB[1],dPC[1],gamma)
Az = A_array(n1,n2,dPA[2],dPB[2],dPC[2],gamma)
total = 0.
for I in range(l1+l2+1):
for J in range(m1+m2+1):
for K in range(n1+n2+1):
total += Ax[I]*Ay[J]*Az[K]*Fgamma(I+J+K,rcp2*gamma)
val= -2*pi/gamma*exp(-alpha1*alpha2*rab2/gamma)*total
return val | [
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|
1012598167/flask_mongodb_game | 60c7e0351586656ec38f851592886338e50b4110 | python_flask/venv/Lib/site-packages/pymongo/pool.py | python | PoolOptions.event_listeners | (self) | return self.__event_listeners | An instance of pymongo.monitoring._EventListeners. | An instance of pymongo.monitoring._EventListeners. | [
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".",
"monitoring",
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] | def event_listeners(self):
"""An instance of pymongo.monitoring._EventListeners.
"""
return self.__event_listeners | [
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|
ANSSI-FR/polichombr | e2dc3874ae3d78c3b496e9656c9a6d1b88ae91e1 | polichombr/views/api_sample.py | python | api_get_iat_matches | (sid) | return jsonify({'result': result}) | TODO : Get IAT hashes | TODO : Get IAT hashes | [
"TODO",
":",
"Get",
"IAT",
"hashes"
] | def api_get_iat_matches(sid):
"""
TODO : Get IAT hashes
"""
sample = api.get_elem_by_type("sample", sid)
result = None
return jsonify({'result': result}) | [
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|
kengz/SLM-Lab | 667ba73349ad00c6f4b3e428dcd10eebbdab4c70 | slm_lab/spec/random_baseline.py | python | gen_random_return | (env_name, seed) | return total_reward | Generate a single-episode random policy return for an environment | Generate a single-episode random policy return for an environment | [
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"random",
"policy",
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"environment"
] | def gen_random_return(env_name, seed):
'''Generate a single-episode random policy return for an environment'''
# TODO generalize for unity too once it has a gym wrapper
env = gym.make(env_name)
env.seed(seed)
env.reset()
done = False
total_reward = 0
while not done:
_, reward, done, _ = env.step(env.action_space.sample())
total_reward += reward
return total_reward | [
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|
riffnshred/nhl-led-scoreboard | 14baa7f0691ca507e4c6f7f2ec02e50ccd1ed9e1 | src/nhl_api/data.py | python | get_standings_wildcard | () | [] | def get_standings_wildcard():
try:
data = requests.get(STANDINGS_WILD_CARD, timeout=REQUEST_TIMEOUT)
return data
except requests.exceptions.RequestException as e:
raise ValueError(e) | [
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||||
Epistimio/orion | 732e739d99561020dbe620760acf062ade746006 | src/orion/core/cli/db/upgrade.py | python | ask_question | (question, default=None) | return answer | Ask a question to the user and receive an answer.
Parameters
----------
question: str
The question to be asked.
default: str
The default value to use if the user enters nothing.
Returns
-------
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The answer provided by the user. | Ask a question to the user and receive an answer. | [
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"""Ask a question to the user and receive an answer.
Parameters
----------
question: str
The question to be asked.
default: str
The default value to use if the user enters nothing.
Returns
-------
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The answer provided by the user.
"""
if default is not None:
question = question + " (default: {}) ".format(default)
answer = input(question)
if answer.strip() == "":
return default
return answer | [
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|
qhduan/just_another_seq2seq | ac9be1b1599c05e0802824afa8a351dcb9ba936e | threadedgenerator.py | python | ThreadedGenerator.__repr__ | (self) | return 'ThreadedGenerator({!r})'.format(self._iterator) | [] | def __repr__(self):
return 'ThreadedGenerator({!r})'.format(self._iterator) | [
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|||
HumanCompatibleAI/adversarial-policies | bba910b89149f1274bb9652a6f378b22c3c9b6c5 | src/aprl/multi/score.py | python | extract_data | (path_generator, out_dir, experiment_dirs, ray_upload_dir) | Helper method to extract data from multiple_score experiments. | Helper method to extract data from multiple_score experiments. | [
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"""Helper method to extract data from multiple_score experiments."""
for experiment, experiment_dir in experiment_dirs.items():
experiment_root = osp.join(ray_upload_dir, experiment_dir)
# video_root contains one directory for each score_agent trial.
# These directories have names of form score-<hash>_<id_num>_<k=v>...
for dir_entry in os.scandir(experiment_root):
if not dir_entry.is_dir():
continue
trial_name = dir_entry.name
# Each trial contains the Sacred output from score_agent.
# Note Ray Tune is running with a fresh working directory per trial, so Sacred
# output will always be at score/1.
trial_root = osp.join(experiment_root, trial_name)
sacred_config = osp.join(trial_root, "data", "sacred", "score", "1", "config.json")
with open(sacred_config, "r") as f:
cfg = json.load(f)
def agent_key(agent):
return cfg[agent + "_type"], cfg[agent + "_path"]
env_name = cfg["env_name"]
victim_index = VICTIM_INDEX[env_name]
if victim_index == 0:
victim_type, victim_path = agent_key("agent_a")
opponent_type, opponent_path = agent_key("agent_b")
else:
victim_type, victim_path = agent_key("agent_b")
opponent_type, opponent_path = agent_key("agent_a")
if "multicomp" in cfg["env_name"]:
env_name = env_name_to_canonical(env_name)
env_name = env_name.replace("/", "-") # sanitize
src_path, new_name, suffix = path_generator(
trial_root=trial_root,
cfg=cfg,
env_sanitized=env_name,
victim_index=victim_index,
victim_type=victim_type,
victim_path=victim_path,
opponent_type=opponent_type,
opponent_path=opponent_path,
)
dst_path = osp.join(out_dir, f"{new_name}.{suffix}")
shutil.copy(src_path, dst_path)
dst_config = osp.join(out_dir, f"{new_name}_sacred.json")
shutil.copy(sacred_config, dst_config) | [
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||
Pyomo/pyomo | dbd4faee151084f343b893cc2b0c04cf2b76fd92 | pyomo/core/kernel/base.py | python | ICategorizedObject.name | (self) | return self.getname(fully_qualified=True) | The object's fully qualified name. Alias for
`obj.getname(fully_qualified=True)`. | The object's fully qualified name. Alias for
`obj.getname(fully_qualified=True)`. | [
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] | def name(self):
"""The object's fully qualified name. Alias for
`obj.getname(fully_qualified=True)`."""
return self.getname(fully_qualified=True) | [
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|
apache/tvm | 6eb4ed813ebcdcd9558f0906a1870db8302ff1e0 | python/tvm/relay/op/nn/_nn.py | python | convert_global_avg_pool2d | (attrs, inputs, tinfos, desired_layouts) | return relay.nn.global_avg_pool2d(*inputs, **new_attrs) | Convert Layout pass registration for global_avg_pool2d op.
Parameters
----------
attrs : tvm.ir.Attrs
Attributes of current pooling
inputs : list of tvm.relay.Expr
The args of the Relay expr to be legalized
tinfos : list of types
List of input and output types
desired_layouts : list of one layout string
layout string defining our desired layout for input and output.
Returns
-------
result : tvm.relay.Expr
The transformed expr | Convert Layout pass registration for global_avg_pool2d op.
Parameters
----------
attrs : tvm.ir.Attrs
Attributes of current pooling
inputs : list of tvm.relay.Expr
The args of the Relay expr to be legalized
tinfos : list of types
List of input and output types
desired_layouts : list of one layout string
layout string defining our desired layout for input and output.
Returns
-------
result : tvm.relay.Expr
The transformed expr | [
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"""Convert Layout pass registration for global_avg_pool2d op.
Parameters
----------
attrs : tvm.ir.Attrs
Attributes of current pooling
inputs : list of tvm.relay.Expr
The args of the Relay expr to be legalized
tinfos : list of types
List of input and output types
desired_layouts : list of one layout string
layout string defining our desired layout for input and output.
Returns
-------
result : tvm.relay.Expr
The transformed expr
"""
new_attrs = dict(attrs)
new_attrs["layout"] = str(desired_layouts[0])
new_attrs["out_layout"] = str(desired_layouts[0])
return relay.nn.global_avg_pool2d(*inputs, **new_attrs) | [
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|
viewflow/viewflow | 2389bd379a2ab22cc277585df7c09514e273541d | viewflow/fields.py | python | import_flow_by_ref | (flow_strref) | return import_string('{}.{}'.format(get_app_package(app_label), flow_path)) | Return flow class by flow string reference. | Return flow class by flow string reference. | [
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] | def import_flow_by_ref(flow_strref):
"""Return flow class by flow string reference."""
app_label, flow_path = flow_strref.split('/')
return import_string('{}.{}'.format(get_app_package(app_label), flow_path)) | [
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|
tanghaibao/goatools | 647e9dd833695f688cd16c2f9ea18f1692e5c6bc | goatools/wr_tbl_class.py | python | WrXlsx.wr_row_mergeall | (self, worksheet, txtstr, fmt, row_idx) | return row_idx + 1 | Merge all columns and place text string in widened cell. | Merge all columns and place text string in widened cell. | [
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"""Merge all columns and place text string in widened cell."""
hdridxval = len(self.hdrs) - 1
worksheet.merge_range(row_idx, 0, row_idx, hdridxval, txtstr, fmt)
return row_idx + 1 | [
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|
makelove/OpenCV-Python-Tutorial | e428d648f7aa50d6a0fb4f4d0fb1bd1a600fef41 | 官方samples/gabor_threads.py | python | process_threaded | (img, filters, threadn = 8) | return accum | [] | def process_threaded(img, filters, threadn = 8):
accum = np.zeros_like(img)
def f(kern):
return cv2.filter2D(img, cv2.CV_8UC3, kern)
pool = ThreadPool(processes=threadn)
for fimg in pool.imap_unordered(f, filters):
np.maximum(accum, fimg, accum)
return accum | [
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|||
spesmilo/electrum | bdbd59300fbd35b01605e66145458e5f396108e8 | electrum/interface.py | python | Interface._search_headers_binary | (self, height, bad, bad_header, chain) | return good, bad, bad_header | [] | async def _search_headers_binary(self, height, bad, bad_header, chain):
assert bad == bad_header['block_height']
_assert_header_does_not_check_against_any_chain(bad_header)
self.blockchain = chain if isinstance(chain, Blockchain) else self.blockchain
good = height
while True:
assert good < bad, (good, bad)
height = (good + bad) // 2
self.logger.info(f"binary step. good {good}, bad {bad}, height {height}")
header = await self.get_block_header(height, 'binary')
chain = blockchain.check_header(header) if 'mock' not in header else header['mock']['check'](header)
if chain:
self.blockchain = chain if isinstance(chain, Blockchain) else self.blockchain
good = height
else:
bad = height
bad_header = header
if good + 1 == bad:
break
mock = 'mock' in bad_header and bad_header['mock']['connect'](height)
real = not mock and self.blockchain.can_connect(bad_header, check_height=False)
if not real and not mock:
raise Exception('unexpected bad header during binary: {}'.format(bad_header))
_assert_header_does_not_check_against_any_chain(bad_header)
self.logger.info(f"binary search exited. good {good}, bad {bad}")
return good, bad, bad_header | [
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|||
wonderworks-software/PyFlow | 57e2c858933bf63890d769d985396dfad0fca0f0 | .vscode/.ropeproject/config.py | python | project_opened | (project) | This function is called after opening the project | This function is called after opening the project | [
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] | https://github.com/wonderworks-software/PyFlow/blob/57e2c858933bf63890d769d985396dfad0fca0f0/.vscode/.ropeproject/config.py#L112-L113 |