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rwl/pylon
pyreto/continuous/task.py
https://github.com/rwl/pylon/blob/916514255db1ae1661406f0283df756baf960d14/pyreto/continuous/task.py#L87-L104
def _getActorLimits(self): """ Returns a list of 2-tuples, e.g. [(-3.14, 3.14), (-0.001, 0.001)], one tuple per parameter, giving min and max for that parameter. """ actorLimits = [] for _ in range(self.env.numOffbids): for _ in self.env.generators: actorLimits.append((0.0, self.env.maxMarkup)) for _ in range(self.env.numOffbids): for _ in self.env.generators: if self.env.maxWithhold is not None: actorLimits.append((0.0, self.env.maxWithhold)) logger.debug("Actor limits: %s" % actorLimits) return actorLimits
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Returns a list of 2-tuples, e.g. [(-3.14, 3.14), (-0.001, 0.001)], one tuple per parameter, giving min and max for that parameter.
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python
train
chainer/chainerui
chainerui/models/result.py
https://github.com/chainer/chainerui/blob/87ad25e875bc332bfdad20197fd3d0cb81a078e8/chainerui/models/result.py#L48-L58
def create(cls, path_name=None, name=None, project_id=None, log_modified_at=None, crawlable=True): """Initialize an instance and save it to db.""" result = cls(path_name, name, project_id, log_modified_at, crawlable) db.session.add(result) db.session.commit() crawl_result(result, True) return result
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Initialize an instance and save it to db.
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python
train
secdev/scapy
scapy/contrib/automotive/someip.py
https://github.com/secdev/scapy/blob/3ffe757c184017dd46464593a8f80f85abc1e79a/scapy/contrib/automotive/someip.py#L190-L216
def fragment(self, fragsize=1392): """Fragment SOME/IP-TP""" fnb = 0 fl = self lst = list() while fl.underlayer is not None: fnb += 1 fl = fl.underlayer for p in fl: s = raw(p[fnb].payload) nb = (len(s) + fragsize) // fragsize for i in range(nb): q = p.copy() del q[fnb].payload q[fnb].len = SOMEIP.LEN_OFFSET_TP + \ len(s[i * fragsize:(i + 1) * fragsize]) q[fnb].more_seg = 1 if i == nb - 1: q[fnb].more_seg = 0 q[fnb].offset += i * fragsize // 16 r = conf.raw_layer(load=s[i * fragsize:(i + 1) * fragsize]) r.overload_fields = p[fnb].payload.overload_fields.copy() q.add_payload(r) lst.append(q) return lst
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Fragment SOME/IP-TP
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python
train
aws/sagemaker-python-sdk
src/sagemaker/chainer/estimator.py
https://github.com/aws/sagemaker-python-sdk/blob/a9e724c7d3f5572b68c3903548c792a59d99799a/src/sagemaker/chainer/estimator.py#L99-L111
def hyperparameters(self): """Return hyperparameters used by your custom Chainer code during training.""" hyperparameters = super(Chainer, self).hyperparameters() additional_hyperparameters = {Chainer._use_mpi: self.use_mpi, Chainer._num_processes: self.num_processes, Chainer._process_slots_per_host: self.process_slots_per_host, Chainer._additional_mpi_options: self.additional_mpi_options} # remove unset keys. additional_hyperparameters = {k: v for k, v in additional_hyperparameters.items() if v} hyperparameters.update(Framework._json_encode_hyperparameters(additional_hyperparameters)) return hyperparameters
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Return hyperparameters used by your custom Chainer code during training.
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python
train
crgwbr/asymmetric-jwt-auth
src/asymmetric_jwt_auth/__init__.py
https://github.com/crgwbr/asymmetric-jwt-auth/blob/eae1a6474b6141edce4d6be2dc1746e18bbf5318/src/asymmetric_jwt_auth/__init__.py#L21-L49
def generate_key_pair(size=2048, public_exponent=65537, as_string=True): """ Generate a public/private key pair. :param size: Optional. Describes how many bits long the key should be, larger keys provide more security, currently 1024 and below are considered breakable, and 2048 or 4096 are reasonable default key sizes for new keys. Defaults to 2048. :param public_exponent: Optional. Indicates what one mathematical property of the key generation will be. 65537 is the default and should almost always be used. :param as_string: Optional. If True, return tuple of strings. If false, return tuple of RSA key objects. Defaults to True. :return: (PrivateKey<string>, PublicKey<string>) :return: ( `RSAPrivateKey <https://cryptography.io/en/latest/hazmat/primitives/asymmetric/rsa/#cryptography.hazmat.primitives.asymmetric.rsa.RSAPrivateKey>`_, `RSAPublicKey <https://cryptography.io/en/latest/hazmat/primitives/asymmetric/rsa/#cryptography.hazmat.primitives.asymmetric.rsa.RSAPublicKey>`_) """ private = rsa.generate_private_key( public_exponent=public_exponent, key_size=size, backend=default_backend() ) public = private.public_key() if not as_string: return private, public pem_private = private.private_bytes(Encoding.PEM, PrivateFormat.PKCS8, NoEncryption()).decode(ENCODING) pem_public = public.public_bytes(Encoding.PEM, PublicFormat.SubjectPublicKeyInfo).decode(ENCODING) return pem_private, pem_public
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Generate a public/private key pair. :param size: Optional. Describes how many bits long the key should be, larger keys provide more security, currently 1024 and below are considered breakable, and 2048 or 4096 are reasonable default key sizes for new keys. Defaults to 2048. :param public_exponent: Optional. Indicates what one mathematical property of the key generation will be. 65537 is the default and should almost always be used. :param as_string: Optional. If True, return tuple of strings. If false, return tuple of RSA key objects. Defaults to True. :return: (PrivateKey<string>, PublicKey<string>) :return: ( `RSAPrivateKey <https://cryptography.io/en/latest/hazmat/primitives/asymmetric/rsa/#cryptography.hazmat.primitives.asymmetric.rsa.RSAPrivateKey>`_, `RSAPublicKey <https://cryptography.io/en/latest/hazmat/primitives/asymmetric/rsa/#cryptography.hazmat.primitives.asymmetric.rsa.RSAPublicKey>`_)
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python
train
maljovec/topopy
topopy/MergeTree.py
https://github.com/maljovec/topopy/blob/4be598d51c4e4043b73d4ad44beed6d289e2f088/topopy/MergeTree.py#L103-L133
def build(self, X, Y, w=None, edges=None): """ Assigns data to this object and builds the Merge Tree @ In, X, an m-by-n array of values specifying m n-dimensional samples @ In, Y, a m vector of values specifying the output responses corresponding to the m samples specified by X @ In, w, an optional m vector of values specifying the weights associated to each of the m samples used. Default of None means all points will be equally weighted @ In, edges, an optional list of custom edges to use as a starting point for pruning, or in place of a computed graph. """ super(MergeTree, self).build(X, Y, w, edges) if self.debug: sys.stdout.write("Merge Tree Computation: ") start = time.clock() self.__tree = MergeTreeFloat( vectorFloat(self.Xnorm.flatten()), vectorFloat(self.Y), str(self.gradient), self.graph_rep.full_graph(), self.debug, ) self._internal_build() if self.debug: end = time.clock() sys.stdout.write("%f s\n" % (end - start))
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Assigns data to this object and builds the Merge Tree @ In, X, an m-by-n array of values specifying m n-dimensional samples @ In, Y, a m vector of values specifying the output responses corresponding to the m samples specified by X @ In, w, an optional m vector of values specifying the weights associated to each of the m samples used. Default of None means all points will be equally weighted @ In, edges, an optional list of custom edges to use as a starting point for pruning, or in place of a computed graph.
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python
train
Azure/msrestazure-for-python
msrestazure/tools.py
https://github.com/Azure/msrestazure-for-python/blob/5f99262305692525d03ca87d2c5356b05c5aa874/msrestazure/tools.py#L149-L162
def _populate_alternate_kwargs(kwargs): """ Translates the parsed arguments into a format used by generic ARM commands such as the resource and lock commands. """ resource_namespace = kwargs['namespace'] resource_type = kwargs.get('child_type_{}'.format(kwargs['last_child_num'])) or kwargs['type'] resource_name = kwargs.get('child_name_{}'.format(kwargs['last_child_num'])) or kwargs['name'] _get_parents_from_parts(kwargs) kwargs['resource_namespace'] = resource_namespace kwargs['resource_type'] = resource_type kwargs['resource_name'] = resource_name return kwargs
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Translates the parsed arguments into a format used by generic ARM commands such as the resource and lock commands.
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python
train
Yipit/eventlib
eventlib/core.py
https://github.com/Yipit/eventlib/blob/0cf29e5251a59fcbfc727af5f5157a3bb03832e2/eventlib/core.py#L124-L155
def process(event_name, data): """Iterates over the event handler registry and execute each found handler. It takes the event name and its its `data`, passing the return of `ejson.loads(data)` to the found handlers. """ deserialized = loads(data) event_cls = find_event(event_name) event = event_cls(event_name, deserialized) try: event.clean() except ValidationError as exc: if os.environ.get('EVENTLIB_RAISE_ERRORS'): raise else: logger.warning( "The event system just got an exception while cleaning " "data for the event '{}'\ndata: {}\nexc: {}".format( event_name, data, str(exc))) return for handler in find_handlers(event_name): try: handler(deserialized) except Exception as exc: logger.warning( (u'One of the handlers for the event "{}" has failed with the ' u'following exception: {}').format(event_name, str(exc))) if getsetting('DEBUG'): raise exc event._broadcast()
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Iterates over the event handler registry and execute each found handler. It takes the event name and its its `data`, passing the return of `ejson.loads(data)` to the found handlers.
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python
train
Erotemic/utool
utool/util_dict.py
https://github.com/Erotemic/utool/blob/3b27e1f4e6e6fb23cd8744af7b7195b57d99e03a/utool/util_dict.py#L1060-L1064
def dict_assign(dict_, keys, vals): """ simple method for assigning or setting values with a similar interface to dict_take """ for key, val in zip(keys, vals): dict_[key] = val
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simple method for assigning or setting values with a similar interface to dict_take
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python
train
RudolfCardinal/pythonlib
cardinal_pythonlib/django/fields/helpers.py
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/django/fields/helpers.py#L36-L53
def valid_choice(strvalue: str, choices: Iterable[Tuple[str, str]]) -> bool: """ Checks that value is one of the valid option in choices, where choices is a list/tuple of 2-tuples (option, description). Note that parameters sent by URLconf are always strings (https://docs.djangoproject.com/en/1.8/topics/http/urls/) but Python is happy with a string-to-integer-PK lookup, e.g. .. code-block:: python Study.objects.get(pk=1) Study.objects.get(pk="1") # also works Choices can be non-string, though, so we compare against a string version of the choice. """ return strvalue in [str(x[0]) for x in choices]
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Checks that value is one of the valid option in choices, where choices is a list/tuple of 2-tuples (option, description). Note that parameters sent by URLconf are always strings (https://docs.djangoproject.com/en/1.8/topics/http/urls/) but Python is happy with a string-to-integer-PK lookup, e.g. .. code-block:: python Study.objects.get(pk=1) Study.objects.get(pk="1") # also works Choices can be non-string, though, so we compare against a string version of the choice.
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python
train
tonioo/sievelib
sievelib/managesieve.py
https://github.com/tonioo/sievelib/blob/88822d1f1daf30ef3dd9ac74911301b0773ef3c8/sievelib/managesieve.py#L183-L217
def __read_response(self, nblines=-1): """Read a response from the server. In the usual case, we read lines until we find one that looks like a response (OK|NO|BYE\s*(.+)?). If *nblines* > 0, we read excactly nblines before returning. :param nblines: number of lines to read (default : -1) :rtype: tuple :return: a tuple of the form (code, data, response). If nblines is provided, code and data can be equal to None. """ resp, code, data = (b"", None, None) cpt = 0 while True: try: line = self.__read_line() except Response as inst: code = inst.code data = inst.data break except Literal as inst: resp += self.__read_block(inst.value) if not resp.endswith(CRLF): resp += self.__read_line() + CRLF continue if not len(line): continue resp += line + CRLF cpt += 1 if nblines != -1 and cpt == nblines: break return (code, data, resp)
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Read a response from the server. In the usual case, we read lines until we find one that looks like a response (OK|NO|BYE\s*(.+)?). If *nblines* > 0, we read excactly nblines before returning. :param nblines: number of lines to read (default : -1) :rtype: tuple :return: a tuple of the form (code, data, response). If nblines is provided, code and data can be equal to None.
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python
train
fastai/fastai
fastai/vision/learner.py
https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/vision/learner.py#L53-L62
def create_body(arch:Callable, pretrained:bool=True, cut:Optional[Union[int, Callable]]=None): "Cut off the body of a typically pretrained `model` at `cut` (int) or cut the model as specified by `cut(model)` (function)." model = arch(pretrained) cut = ifnone(cut, cnn_config(arch)['cut']) if cut is None: ll = list(enumerate(model.children())) cut = next(i for i,o in reversed(ll) if has_pool_type(o)) if isinstance(cut, int): return nn.Sequential(*list(model.children())[:cut]) elif isinstance(cut, Callable): return cut(model) else: raise NamedError("cut must be either integer or a function")
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Cut off the body of a typically pretrained `model` at `cut` (int) or cut the model as specified by `cut(model)` (function).
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python
train
J535D165/recordlinkage
recordlinkage/algorithms/nb_sklearn.py
https://github.com/J535D165/recordlinkage/blob/87a5f4af904e0834047cd07ff1c70146b1e6d693/recordlinkage/algorithms/nb_sklearn.py#L298-L302
def _count(self, X, Y): """Count and smooth feature occurrences.""" self.feature_count_ += safe_sparse_dot(Y.T, X) self.class_count_ += Y.sum(axis=0)
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Count and smooth feature occurrences.
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python
train
jaraco/jaraco.util
jaraco/util/numbers.py
https://github.com/jaraco/jaraco.util/blob/f21071c64f165a5cf844db15e39356e1a47f4b02/jaraco/util/numbers.py#L10-L37
def coerce(value): """ coerce takes a value and attempts to convert it to a float, or int. If none of the conversions are successful, the original value is returned. >>> coerce('3') 3 >>> coerce('3.0') 3.0 >>> coerce('foo') 'foo' >>> coerce({}) {} >>> coerce('{}') '{}' """ with contextlib2.suppress(Exception): loaded = json.loads(value) assert isinstance(loaded, numbers.Number) return loaded return value
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coerce takes a value and attempts to convert it to a float, or int. If none of the conversions are successful, the original value is returned. >>> coerce('3') 3 >>> coerce('3.0') 3.0 >>> coerce('foo') 'foo' >>> coerce({}) {} >>> coerce('{}') '{}'
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python
test
CodyKochmann/strict_functions
strict_functions/trace3.py
https://github.com/CodyKochmann/strict_functions/blob/adaf78084c66929552d80c95f980e7e0c4331478/strict_functions/trace3.py#L42-L44
def get_locals(f:Frame) -> str: ''' returns a formatted view of the local variables in a frame ''' return pformat({i:f.f_locals[i] for i in f.f_locals if not i.startswith('__')})
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returns a formatted view of the local variables in a frame
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python
train
numenta/htmresearch
htmresearch/frameworks/layers/sequence_object_machine.py
https://github.com/numenta/htmresearch/blob/70c096b09a577ea0432c3f3bfff4442d4871b7aa/htmresearch/frameworks/layers/sequence_object_machine.py#L199-L239
def _getSDRPairs(self, pairs, noise=None, includeRandomLocation=False): """ This method takes a list of (location, feature) index pairs (one pair per cortical column), and returns a sensation dict in the correct format, adding noise if necessary. """ sensations = {} for col in xrange(self.numColumns): locationID, featureID = pairs[col] # generate random location if requested if includeRandomLocation: locationID = random.randint(0, self.numLocations-1) location = self.locations[col][locationID] # generate union of locations if requested elif isinstance(locationID, tuple): location = set() for idx in list(locationID): location = location | self.locations[col][idx] else: location = self.locations[col][locationID] # generate empty feature if requested if featureID == -1: feature = set() # generate union of features if requested elif isinstance(featureID, tuple): feature = set() for idx in list(featureID): feature = feature | self.features[col][idx] else: feature = self.features[col][featureID] if noise is not None: location = self._addNoise(location, noise, self.externalInputSize) feature = self._addNoise(feature, noise, self.sensorInputSize) sensations[col] = (location, feature) return sensations
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This method takes a list of (location, feature) index pairs (one pair per cortical column), and returns a sensation dict in the correct format, adding noise if necessary.
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python
train
InQuest/python-sandboxapi
sandboxapi/falcon.py
https://github.com/InQuest/python-sandboxapi/blob/9bad73f453e25d7d23e7b4b1ae927f44a35a5bc3/sandboxapi/falcon.py#L45-L71
def analyze(self, handle, filename): """Submit a file for analysis. :type handle: File handle :param handle: Handle to file to upload for analysis. :type filename: str :param filename: File name. :rtype: str :return: File hash as a string """ # multipart post files. files = {"file" : (filename, handle)} # ensure the handle is at offset 0. handle.seek(0) response = self._request("/submit/file", method='POST', files=files) try: if response.status_code == 201: # good response return response.json()['job_id'] else: raise sandboxapi.SandboxError("api error in analyze: {r}".format(r=response.content.decode('utf-8'))) except (ValueError, KeyError) as e: raise sandboxapi.SandboxError("error in analyze: {e}".format(e=e))
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Submit a file for analysis. :type handle: File handle :param handle: Handle to file to upload for analysis. :type filename: str :param filename: File name. :rtype: str :return: File hash as a string
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python
train
sdispater/orator
orator/query/builder.py
https://github.com/sdispater/orator/blob/bd90bf198ee897751848f9a92e49d18e60a74136/orator/query/builder.py#L107-L125
def select_raw(self, expression, bindings=None): """ Add a new raw select expression to the query :param expression: The raw expression :type expression: str :param bindings: The expression bindings :type bindings: list :return: The current QueryBuilder instance :rtype: QueryBuilder """ self.add_select(QueryExpression(expression)) if bindings: self.add_binding(bindings, "select") return self
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Add a new raw select expression to the query :param expression: The raw expression :type expression: str :param bindings: The expression bindings :type bindings: list :return: The current QueryBuilder instance :rtype: QueryBuilder
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python
train
neithere/argh
argh/constants.py
https://github.com/neithere/argh/blob/dcd3253f2994400a6a58a700c118c53765bc50a4/argh/constants.py#L55-L91
def _expand_help(self, action): """ This method is copied verbatim from ArgumentDefaultsHelpFormatter with a couple of lines added just before the end. Reason: we need to `repr()` default values instead of simply inserting them as is. This helps notice, for example, an empty string as the default value; moreover, it prevents breaking argparse due to logical quirks inside of its formatters. Ideally this could be achieved by simply defining :attr:`DEFAULT_ARGUMENT_TEMPLATE` as ``{default!r}`` but unfortunately argparse only supports the old printf syntax. """ params = dict(vars(action), prog=self._prog) for name in list(params): if params[name] is argparse.SUPPRESS: del params[name] for name in list(params): if hasattr(params[name], '__name__'): params[name] = params[name].__name__ if params.get('choices') is not None: choices_str = ', '.join([str(c) for c in params['choices']]) params['choices'] = choices_str # XXX this is added in Argh vs. argparse.ArgumentDefaultsHelpFormatter # (avoiding empty strings, otherwise Argparse would die with # an IndexError in _format_action) # if 'default' in params: if params['default'] is None: params['default'] = '-' else: params['default'] = repr(params['default']) # # / return self._get_help_string(action) % params
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This method is copied verbatim from ArgumentDefaultsHelpFormatter with a couple of lines added just before the end. Reason: we need to `repr()` default values instead of simply inserting them as is. This helps notice, for example, an empty string as the default value; moreover, it prevents breaking argparse due to logical quirks inside of its formatters. Ideally this could be achieved by simply defining :attr:`DEFAULT_ARGUMENT_TEMPLATE` as ``{default!r}`` but unfortunately argparse only supports the old printf syntax.
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python
test
bykof/billomapy
billomapy/billomapy.py
https://github.com/bykof/billomapy/blob/a28ba69fd37654fa145d0411d52c200e7f8984ab/billomapy/billomapy.py#L837-L850
def get_all_tags_of_article(self, article_id): """ Get all tags of article This will iterate over all pages until it gets all elements. So if the rate limit exceeded it will throw an Exception and you will get nothing :param article_id: the article id :return: list """ return self._iterate_through_pages( get_function=self.get_tags_of_article_per_page, resource=ARTICLE_TAGS, **{'article_id': article_id} )
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Get all tags of article This will iterate over all pages until it gets all elements. So if the rate limit exceeded it will throw an Exception and you will get nothing :param article_id: the article id :return: list
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python
train
timothydmorton/VESPA
vespa/transit_basic.py
https://github.com/timothydmorton/VESPA/blob/0446b54d48009f3655cfd1a3957ceea21d3adcaa/vespa/transit_basic.py#L745-L753
def fit_traptransit(ts,fs,p0): """ Fits trapezoid model to provided ts,fs """ pfit,success = leastsq(traptransit_resid,p0,args=(ts,fs)) if success not in [1,2,3,4]: raise NoFitError #logging.debug('success = {}'.format(success)) return pfit
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Fits trapezoid model to provided ts,fs
[ "Fits", "trapezoid", "model", "to", "provided", "ts", "fs" ]
python
train
jmgilman/Neolib
neolib/pyamf/util/pure.py
https://github.com/jmgilman/Neolib/blob/228fafeaed0f3195676137732384a14820ae285c/neolib/pyamf/util/pure.py#L477-L485
def read_utf8_string(self, length): """ Reads a UTF-8 string from the stream. @rtype: C{unicode} """ s = struct.unpack("%s%ds" % (self.endian, length), self.read(length))[0] return s.decode('utf-8')
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Reads a UTF-8 string from the stream. @rtype: C{unicode}
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python
train
ChristianTremblay/BAC0
BAC0/sql/sql.py
https://github.com/ChristianTremblay/BAC0/blob/8d95b065ea068524a08f5b0c34322ebeeba95d06/BAC0/sql/sql.py#L147-L153
def his_from_sql(self, db_name, point): """ Retrive point histories from SQL database """ his = self._read_from_sql('select * from "%s"' % "history", db_name) his.index = his["index"].apply(Timestamp) return his.set_index("index")[point]
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Retrive point histories from SQL database
[ "Retrive", "point", "histories", "from", "SQL", "database" ]
python
train
ffcalculator/fantasydata-python
fantasy_data/FantasyData.py
https://github.com/ffcalculator/fantasydata-python/blob/af90cac1e80d8356cffaa80621ee513201f6c661/fantasy_data/FantasyData.py#L161-L166
def get_projected_player_game_stats_by_player(self, season, week, player_id): """ Projected Player Game Stats by Player """ result = self._method_call("PlayerGameProjectionStatsByPlayerID/{season}/{week}/{player_id}", "projections", season=season, week=week, player_id=player_id) return result
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Projected Player Game Stats by Player
[ "Projected", "Player", "Game", "Stats", "by", "Player" ]
python
train
nickmckay/LiPD-utilities
Python/lipd/timeseries.py
https://github.com/nickmckay/LiPD-utilities/blob/5dab6bbeffc5effd68e3a6beaca6b76aa928e860/Python/lipd/timeseries.py#L340-L369
def _extract_table(table_data, current, pc, ts, tt): """ Use the given table data to create a time series entry for each column in the table. :param dict table_data: Table data :param dict current: LiPD root data :param str pc: paleoData or chronData :param list ts: Time series (so far) :param bool summary: Summary Table or not :return list ts: Time series (so far) """ current["tableType"] = tt # Get root items for this table current = _extract_table_root(table_data, current, pc) # Add in modelNumber and tableNumber if this is "ens" or "summ" table current = _extract_table_model(table_data, current, tt) # Add age, depth, and year columns to root if available _table_tmp = _extract_special(current, table_data) try: # Start creating entries using dictionary copies. for _col_name, _col_data in table_data["columns"].items(): # Add column data onto root items. Copy so we don't ruin original data _col_tmp = _extract_columns(_col_data, copy.deepcopy(_table_tmp), pc) try: ts.append(_col_tmp) except Exception as e: logger_ts.warn("extract_table: Unable to create ts entry, {}".format(e)) except Exception as e: logger_ts.error("extract_table: {}".format(e)) return ts
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Use the given table data to create a time series entry for each column in the table. :param dict table_data: Table data :param dict current: LiPD root data :param str pc: paleoData or chronData :param list ts: Time series (so far) :param bool summary: Summary Table or not :return list ts: Time series (so far)
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python
train
hasgeek/coaster
coaster/sqlalchemy/statemanager.py
https://github.com/hasgeek/coaster/blob/07f7eb5d5f516e22fa14fdf4dc70e0ae13ee398d/coaster/sqlalchemy/statemanager.py#L709-L738
def add_conditional_state(self, name, state, validator, class_validator=None, cache_for=None, label=None): """ Add a conditional state that combines an existing state with a validator that must also pass. The validator receives the object on which the property is present as a parameter. :param str name: Name of the new state :param ManagedState state: Existing state that this is based on :param validator: Function that will be called with the host object as a parameter :param class_validator: Function that will be called when the state is queried on the class instead of the instance. Falls back to ``validator`` if not specified. Receives the class as the parameter :param cache_for: Integer or function that indicates how long ``validator``'s result can be cached (not applicable to ``class_validator``). ``None`` implies no cache, ``0`` implies indefinite cache (until invalidated by a transition) and any other integer is the number of seconds for which to cache the assertion :param label: Label for this state (string or 2-tuple) TODO: `cache_for`'s implementation is currently pending a test case demonstrating how it will be used. """ # We'll accept a ManagedState with grouped values, but not a ManagedStateGroup if not isinstance(state, ManagedState): raise TypeError("Not a managed state: %s" % repr(state)) elif state.statemanager != self: raise ValueError("State %s is not associated with this state manager" % repr(state)) if isinstance(label, tuple) and len(label) == 2: label = NameTitle(*label) self._add_state_internal(name, state.value, label=label, validator=validator, class_validator=class_validator, cache_for=cache_for)
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Add a conditional state that combines an existing state with a validator that must also pass. The validator receives the object on which the property is present as a parameter. :param str name: Name of the new state :param ManagedState state: Existing state that this is based on :param validator: Function that will be called with the host object as a parameter :param class_validator: Function that will be called when the state is queried on the class instead of the instance. Falls back to ``validator`` if not specified. Receives the class as the parameter :param cache_for: Integer or function that indicates how long ``validator``'s result can be cached (not applicable to ``class_validator``). ``None`` implies no cache, ``0`` implies indefinite cache (until invalidated by a transition) and any other integer is the number of seconds for which to cache the assertion :param label: Label for this state (string or 2-tuple) TODO: `cache_for`'s implementation is currently pending a test case demonstrating how it will be used.
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python
train
JdeRobot/base
src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v20/ardupilotmega.py
https://github.com/JdeRobot/base/blob/303b18992785b2fe802212f2d758a60873007f1f/src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v20/ardupilotmega.py#L10652-L10662
def remote_log_data_block_send(self, target_system, target_component, seqno, data, force_mavlink1=False): ''' Send a block of log data to remote location target_system : System ID (uint8_t) target_component : Component ID (uint8_t) seqno : log data block sequence number (uint32_t) data : log data block (uint8_t) ''' return self.send(self.remote_log_data_block_encode(target_system, target_component, seqno, data), force_mavlink1=force_mavlink1)
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Send a block of log data to remote location target_system : System ID (uint8_t) target_component : Component ID (uint8_t) seqno : log data block sequence number (uint32_t) data : log data block (uint8_t)
[ "Send", "a", "block", "of", "log", "data", "to", "remote", "location" ]
python
train
05bit/peewee-async
peewee_async.py
https://github.com/05bit/peewee-async/blob/d15f4629da1d9975da4ec37306188e68d288c862/peewee_async.py#L193-L204
async def get_or_create(self, model_, defaults=None, **kwargs): """Try to get an object or create it with the specified defaults. Return 2-tuple containing the model instance and a boolean indicating whether the instance was created. """ try: return (await self.get(model_, **kwargs)), False except model_.DoesNotExist: data = defaults or {} data.update({k: v for k, v in kwargs.items() if '__' not in k}) return (await self.create(model_, **data)), True
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Try to get an object or create it with the specified defaults. Return 2-tuple containing the model instance and a boolean indicating whether the instance was created.
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python
train
RedHatQE/Sentaku
examples/todo_example/ux.py
https://github.com/RedHatQE/Sentaku/blob/b336cef5b6ee2db4e8dff28dcdb2be35a1f3d01c/examples/todo_example/ux.py#L44-L50
def get_by(self, name): """ find a todo list element by name """ item = self.controlled_list.get_by(name) if item: return TodoElementUX(parent=self, controlled_element=item)
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find a todo list element by name
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python
train
ontio/ontology-python-sdk
ontology/smart_contract/native_contract/ontid.py
https://github.com/ontio/ontology-python-sdk/blob/ac88bdda941896c5d2ced08422a9c5179d3f9b19/ontology/smart_contract/native_contract/ontid.py#L110-L146
def parse_ddo(ont_id: str, serialized_ddo: str or bytes) -> dict: """ This interface is used to deserialize a hexadecimal string into a DDO object in the from of dict. :param ont_id: the unique ID for identity. :param serialized_ddo: an serialized description object of ONT ID in form of str or bytes. :return: a description object of ONT ID in the from of dict. """ if len(serialized_ddo) == 0: return dict() if isinstance(serialized_ddo, str): stream = StreamManager.get_stream(bytearray.fromhex(serialized_ddo)) elif isinstance(serialized_ddo, bytes): stream = StreamManager.get_stream(serialized_ddo) else: raise SDKException(ErrorCode.params_type_error('bytes or str parameter is required.')) reader = BinaryReader(stream) try: public_key_bytes = reader.read_var_bytes() except SDKException: public_key_bytes = b'' try: attribute_bytes = reader.read_var_bytes() except SDKException: attribute_bytes = b'' try: recovery_bytes = reader.read_var_bytes() except SDKException: recovery_bytes = b'' if len(recovery_bytes) != 0: b58_recovery = Address(recovery_bytes).b58encode() else: b58_recovery = '' pub_keys = OntId.parse_pub_keys(ont_id, public_key_bytes) attribute_list = OntId.parse_attributes(attribute_bytes) ddo = dict(Owners=pub_keys, Attributes=attribute_list, Recovery=b58_recovery, OntId=ont_id) return ddo
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This interface is used to deserialize a hexadecimal string into a DDO object in the from of dict. :param ont_id: the unique ID for identity. :param serialized_ddo: an serialized description object of ONT ID in form of str or bytes. :return: a description object of ONT ID in the from of dict.
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python
train
swisscom/cleanerversion
versions/admin.py
https://github.com/swisscom/cleanerversion/blob/becadbab5d7b474a0e9a596b99e97682402d2f2c/versions/admin.py#L211-L224
def will_not_clone(self, request, *args, **kwargs): """ Add save but not clone capability in the changeview """ paths = request.path_info.split('/') index_of_object_id = paths.index("will_not_clone") - 1 object_id = paths[index_of_object_id] self.change_view(request, object_id) admin_wordInUrl = index_of_object_id - 3 # This gets the adminsite for the app, and the model name and joins # together with / path = '/' + '/'.join(paths[admin_wordInUrl:index_of_object_id]) return HttpResponseRedirect(path)
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Add save but not clone capability in the changeview
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python
train
vatlab/SoS
src/sos/eval.py
https://github.com/vatlab/SoS/blob/6b60ed0770916d135e17322e469520d778e9d4e7/src/sos/eval.py#L96-L98
def SoS_eval(expr: str, extra_dict: dict = {}) -> Any: '''Evaluate an expression with sos dict.''' return eval(expr, env.sos_dict.dict(), extra_dict)
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Evaluate an expression with sos dict.
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python
train
Arkq/flake8-requirements
src/flake8_requirements/checker.py
https://github.com/Arkq/flake8-requirements/blob/d7cb84af2429a63635528b531111a5da527bf2d1/src/flake8_requirements/checker.py#L322-L385
def run(self): """Run checker.""" def split(module): """Split module into submodules.""" return tuple(module.split(".")) def modcmp(lib=(), test=()): """Compare import modules.""" if len(lib) > len(test): return False return all(a == b for a, b in zip(lib, test)) mods_1st_party = set() mods_3rd_party = set() # Get 1st party modules (used for absolute imports). modules = [project2module(self.setup.keywords.get('name', ""))] if modules[0] in self.known_modules: modules = self.known_modules[modules[0]] mods_1st_party.update(split(x) for x in modules) requirements = self.requirements if self.setup.redirected: # Use requirements from setup if available. requirements = self.setup.get_requirements( setup=self.processing_setup_py, tests=True, ) # Get 3rd party module names based on requirements. for requirement in requirements: modules = [project2module(requirement.project_name)] if modules[0] in KNOWN_3RD_PARTIES: modules = KNOWN_3RD_PARTIES[modules[0]] if modules[0] in self.known_modules: modules = self.known_modules[modules[0]] mods_3rd_party.update(split(x) for x in modules) # When processing setup.py file, forcefully add setuptools to the # project requirements. Setuptools might be required to build the # project, even though it is not listed as a requirement - this # package is required to run setup.py, so listing it as a setup # requirement would be pointless. if self.processing_setup_py: mods_3rd_party.add(split("setuptools")) for node in ImportVisitor(self.tree).imports: _mod = split(node.mod) _alt = split(node.alt) if any([_mod[0] == x for x in STDLIB]): continue if any([modcmp(x, _mod) or modcmp(x, _alt) for x in mods_1st_party]): continue if any([modcmp(x, _mod) or modcmp(x, _alt) for x in mods_3rd_party]): continue yield ( node.line, node.offset, ERRORS['I900'].format(pkg=node.mod), Flake8Checker, )
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Run checker.
[ "Run", "checker", "." ]
python
train
rwl/godot
godot/xdot_parser.py
https://github.com/rwl/godot/blob/013687c9e8983d2aa2ceebb8a76c5c4f1e37c90f/godot/xdot_parser.py#L378-L384
def _proc_bspline(self, tokens, filled): """ Returns the components of a B-spline (Bezier curve). """ pts = [(p["x"], p["y"]) for p in tokens["points"]] component = BSpline(pen=self.pen, points=pts, filled=filled) return component
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Returns the components of a B-spline (Bezier curve).
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python
test
aouyar/PyMunin
pysysinfo/postgresql.py
https://github.com/aouyar/PyMunin/blob/4f58a64b6b37c85a84cc7e1e07aafaa0321b249d/pysysinfo/postgresql.py#L88-L101
def _createStatsDict(self, headers, rows): """Utility method that returns database stats as a nested dictionary. @param headers: List of columns in query result. @param rows: List of rows in query result. @return: Nested dictionary of values. First key is the database name and the second key is the statistics counter name. """ dbstats = {} for row in rows: dbstats[row[0]] = dict(zip(headers[1:], row[1:])) return dbstats
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Utility method that returns database stats as a nested dictionary. @param headers: List of columns in query result. @param rows: List of rows in query result. @return: Nested dictionary of values. First key is the database name and the second key is the statistics counter name.
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python
train
Unidata/MetPy
metpy/io/_nexrad_msgs/parse_spec.py
https://github.com/Unidata/MetPy/blob/16f68a94919b9a82dcf9cada2169cf039129e67b/metpy/io/_nexrad_msgs/parse_spec.py#L126-L135
def fix_var_name(var_name): """Clean up and apply standard formatting to variable names.""" name = var_name.strip() for char in '(). /#,': name = name.replace(char, '_') name = name.replace('+', 'pos_') name = name.replace('-', 'neg_') if name.endswith('_'): name = name[:-1] return name
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Clean up and apply standard formatting to variable names.
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python
train
Chilipp/psy-simple
psy_simple/colors.py
https://github.com/Chilipp/psy-simple/blob/7d916406a6d3c3c27c0b7102f98fef07a4da0a61/psy_simple/colors.py#L155-L198
def get_cmap(name, lut=None): """ Returns the specified colormap. Parameters ---------- name: str or :class:`matplotlib.colors.Colormap` If a colormap, it returned unchanged. %(cmap_note)s lut: int An integer giving the number of entries desired in the lookup table Returns ------- matplotlib.colors.Colormap The colormap specified by `name` See Also -------- show_colormaps: A function to display all available colormaps Notes ----- Different from the :func::`matpltolib.pyplot.get_cmap` function, this function changes the number of colors if `name` is a :class:`matplotlib.colors.Colormap` instance to match the given `lut`.""" if name in rcParams['colors.cmaps']: colors = rcParams['colors.cmaps'][name] lut = lut or len(colors) return FixedColorMap.from_list(name=name, colors=colors, N=lut) elif name in _cmapnames: colors = _cmapnames[name] lut = lut or len(colors) return FixedColorMap.from_list(name=name, colors=colors, N=lut) else: cmap = mpl_get_cmap(name) # Note: we could include the `lut` in the call of mpl_get_cmap, but # this raises a ValueError for colormaps like 'viridis' in mpl version # 1.5. Besides the mpl_get_cmap function does not modify the lut if # it does not match if lut is not None and cmap.N != lut: cmap = FixedColorMap.from_list( name=cmap.name, colors=cmap(np.linspace(0, 1, lut)), N=lut) return cmap
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Returns the specified colormap. Parameters ---------- name: str or :class:`matplotlib.colors.Colormap` If a colormap, it returned unchanged. %(cmap_note)s lut: int An integer giving the number of entries desired in the lookup table Returns ------- matplotlib.colors.Colormap The colormap specified by `name` See Also -------- show_colormaps: A function to display all available colormaps Notes ----- Different from the :func::`matpltolib.pyplot.get_cmap` function, this function changes the number of colors if `name` is a :class:`matplotlib.colors.Colormap` instance to match the given `lut`.
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python
train
bioasp/iggy
src/sif_parser.py
https://github.com/bioasp/iggy/blob/451dee74f277d822d64cf8f3859c94b2f2b6d4db/src/sif_parser.py#L99-L118
def p_identlist(self, t): '''identlist : IDENT | NOT IDENT | IDENT AND identlist | NOT IDENT AND identlist ''' if len(t)==5 : #print(t[1],t[2],t[3],t[4]) t[0] = t[1]+t[2]+t[3]+t[4] elif len(t)==4 : #print(t[1],t[2],t[3]) t[0] = t[1]+t[2]+t[3] elif len(t)==3 : #print(t[1],t[2]) t[0] = t[1]+t[2] elif len(t)==2 : #print(t[0],t[1]) t[0]=t[1] else: print("Syntax error at '",str(t),"'")
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identlist : IDENT | NOT IDENT | IDENT AND identlist | NOT IDENT AND identlist
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python
train
ihgazni2/elist
elist/elist.py
https://github.com/ihgazni2/elist/blob/8c07b5029bda34ead60ce10335ceb145f209263c/elist/elist.py#L3318-L3370
def remove_many(ol,values,seqs,**kwargs): ''' from elist.elist import * ol = [1,'a',3,'b',5,'a',6,'a',7,'b',8,'b',9] id(ol) new = remove_many(ol,['a','b'],[1,2]) ol new id(ol) id(new) #### ol = [1,'a',3,'b',5,'a',6,'a',7,'b',8,'b',9] id(ol) rslt = remove_many(ol,['a','b'],[1,2],mode="original") ol rslt id(ol) id(rslt) ''' if('mode' in kwargs): mode = kwargs["mode"] else: mode = "new" values = copy.deepcopy(values) seqs = copy.deepcopy(seqs) cursors = [-1] * values.__len__() new = [] length = ol.__len__() cpol = copy.deepcopy(ol) for i in range(0,length): label = True for j in range(0,cursors.__len__()): which = seqs[j] value = values[j] if(cpol[i] == value): cursors[j] = cursors[j] + 1 if(cursors[j] == which): label = False break else: pass else: pass if(label): new.append(cpol[i]) else: pass if(mode == "new"): return(new) else: ol.clear() ol.extend(new) return(ol)
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from elist.elist import * ol = [1,'a',3,'b',5,'a',6,'a',7,'b',8,'b',9] id(ol) new = remove_many(ol,['a','b'],[1,2]) ol new id(ol) id(new) #### ol = [1,'a',3,'b',5,'a',6,'a',7,'b',8,'b',9] id(ol) rslt = remove_many(ol,['a','b'],[1,2],mode="original") ol rslt id(ol) id(rslt)
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python
valid
woolfson-group/isambard
isambard/optimisation/optimizer.py
https://github.com/woolfson-group/isambard/blob/ebc33b48a28ad217e18f93b910dfba46e6e71e07/isambard/optimisation/optimizer.py#L47-L67
def buff_internal_eval(params): """Builds and evaluates BUFF internal energy of a model in parallelization Parameters ---------- params: list Tuple containing the specification to be built, the sequence and the parameters for model building. Returns ------- model.bude_score: float BUFF internal energy score to be assigned to particle fitness value. """ specification, sequence, parsed_ind = params model = specification(*parsed_ind) model.build() model.pack_new_sequences(sequence) return model.buff_internal_energy.total_energy
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Builds and evaluates BUFF internal energy of a model in parallelization Parameters ---------- params: list Tuple containing the specification to be built, the sequence and the parameters for model building. Returns ------- model.bude_score: float BUFF internal energy score to be assigned to particle fitness value.
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python
train
hugapi/hug
hug/output_format.py
https://github.com/hugapi/hug/blob/080901c81576657f82e2432fd4a82f1d0d2f370c/hug/output_format.py#L233-L250
def video(video_type, video_mime, doc=None): """Dynamically creates a video type handler for the specified video type""" @on_valid(video_mime) def video_handler(data, **kwargs): if hasattr(data, 'read'): return data elif hasattr(data, 'save'): output = stream() data.save(output, format=video_type.upper()) output.seek(0) return output elif hasattr(data, 'render'): return data.render() elif os.path.isfile(data): return open(data, 'rb') video_handler.__doc__ = doc or "{0} formatted video".format(video_type) return video_handler
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Dynamically creates a video type handler for the specified video type
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python
train
bitesofcode/projexui
projexui/widgets/xwalkthroughwidget/xwalkthroughscene.py
https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xwalkthroughwidget/xwalkthroughscene.py#L66-L81
def findReference(self, name, cls=QtGui.QWidget): """ Looks up a reference from the widget based on its object name. :param name | <str> cls | <subclass of QtGui.QObject> :return <QtGui.QObject> || None """ ref_widget = self._referenceWidget if not ref_widget: return None if ref_widget.objectName() == name: return ref_widget return ref_widget.findChild(cls, name)
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Looks up a reference from the widget based on its object name. :param name | <str> cls | <subclass of QtGui.QObject> :return <QtGui.QObject> || None
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python
train
agoragames/kairos
kairos/cassandra_backend.py
https://github.com/agoragames/kairos/blob/0b062d543b0f4a46df460fa0eb6ec281232ab179/kairos/cassandra_backend.py#L175-L185
def _insert(self, name, value, timestamp, intervals, **kwargs): ''' Insert the new value. ''' if self._value_type in QUOTE_TYPES and not QUOTE_MATCH.match(value): value = "'%s'"%(value) for interval,config in self._intervals.items(): timestamps = self._normalize_timestamps(timestamp, intervals, config) for tstamp in timestamps: self._insert_data(name, value, tstamp, interval, config, **kwargs)
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Insert the new value.
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python
train
google/grr
grr/server/grr_response_server/client_index.py
https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/client_index.py#L375-L406
def LookupClients(self, keywords): """Returns a list of client URNs associated with keywords. Args: keywords: The list of keywords to search by. Returns: A list of client URNs. Raises: ValueError: A string (single keyword) was passed instead of an iterable. """ if isinstance(keywords, string_types): raise ValueError( "Keywords should be an iterable, not a string (got %s)." % keywords) start_time, filtered_keywords = self._AnalyzeKeywords(keywords) keyword_map = data_store.REL_DB.ListClientsForKeywords( list(map(self._NormalizeKeyword, filtered_keywords)), start_time=start_time) results = itervalues(keyword_map) relevant_set = set(next(results)) for hits in results: relevant_set &= set(hits) if not relevant_set: return [] return sorted(relevant_set)
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Returns a list of client URNs associated with keywords. Args: keywords: The list of keywords to search by. Returns: A list of client URNs. Raises: ValueError: A string (single keyword) was passed instead of an iterable.
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python
train
fossasia/knittingpattern
knittingpattern/Row.py
https://github.com/fossasia/knittingpattern/blob/8e608896b0ab82fea1ca9fbfa2b4ee023d8c8027/knittingpattern/Row.py#L46-L54
def _instructions_changed(self, change): """Call when there is a change in the instructions.""" if change.adds(): for index, instruction in change.items(): if isinstance(instruction, dict): in_row = self._parser.instruction_in_row(self, instruction) self.instructions[index] = in_row else: instruction.transfer_to_row(self)
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Call when there is a change in the instructions.
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python
valid
greenbone/ospd
ospd/misc.py
https://github.com/greenbone/ospd/blob/cef773166b15a19c17764721d3fe404fa0e107bf/ospd/misc.py#L742-L759
def port_list_compress(port_list): """ Compress a port list and return a string. """ if not port_list or len(port_list) == 0: LOGGER.info("Invalid or empty port list.") return '' port_list = sorted(set(port_list)) compressed_list = [] for key, group in itertools.groupby(enumerate(port_list), lambda t: t[1] - t[0]): group = list(group) if group[0][1] == group[-1][1]: compressed_list.append(str(group[0][1])) else: compressed_list.append(str(group[0][1]) + '-' + str(group[-1][1])) return ','.join(compressed_list)
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Compress a port list and return a string.
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python
train
ellmetha/django-machina
machina/apps/forum_conversation/views.py
https://github.com/ellmetha/django-machina/blob/89ac083c1eaf1cfdeae6686ee094cc86362e8c69/machina/apps/forum_conversation/views.py#L209-L226
def get_post_form_kwargs(self): """ Returns the keyword arguments for instantiating the post form. """ kwargs = { 'user': self.request.user, 'forum': self.get_forum(), 'topic': self.get_topic(), } post = self.get_post() if post: kwargs.update({'instance': post}) if self.request.method in ('POST', 'PUT'): kwargs.update({ 'data': self.request.POST, 'files': self.request.FILES, }) return kwargs
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Returns the keyword arguments for instantiating the post form.
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python
train
ralphje/imagemounter
imagemounter/parser.py
https://github.com/ralphje/imagemounter/blob/86213781c366cad65096447d91f522f0a3fb4b93/imagemounter/parser.py#L152-L160
def get_volumes(self): """Gets a list of all volumes of all disks, concatenating :func:`Disk.get_volumes` of all disks. :rtype: list""" volumes = [] for disk in self.disks: volumes.extend(disk.get_volumes()) return volumes
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Gets a list of all volumes of all disks, concatenating :func:`Disk.get_volumes` of all disks. :rtype: list
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python
train
lebinh/aq
aq/engines.py
https://github.com/lebinh/aq/blob/eb366dd063db25598daa70a216170776e83383f4/aq/engines.py#L75-L89
def load_table(self, table): """ Load resources as specified by given table into our db. """ region = table.database if table.database else self.default_region resource_name, collection_name = table.table.split('_', 1) # we use underscore "_" instead of dash "-" for region name but boto3 need dash boto_region_name = region.replace('_', '-') resource = self.boto3_session.resource(resource_name, region_name=boto_region_name) if not hasattr(resource, collection_name): raise QueryError( 'Unknown collection <{0}> of resource <{1}>'.format(collection_name, resource_name)) self.attach_region(region) self.refresh_table(region, table.table, resource, getattr(resource, collection_name))
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Load resources as specified by given table into our db.
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python
train
hannes-brt/hebel
hebel/pycuda_ops/cublas.py
https://github.com/hannes-brt/hebel/blob/1e2c3a9309c2646103901b26a55be4e312dd5005/hebel/pycuda_ops/cublas.py#L2363-L2374
def cublasSger(handle, m, n, alpha, x, incx, y, incy, A, lda): """ Rank-1 operation on real general matrix. """ status = _libcublas.cublasSger_v2(handle, m, n, ctypes.byref(ctypes.c_float(alpha)), int(x), incx, int(y), incy, int(A), lda) cublasCheckStatus(status)
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Rank-1 operation on real general matrix.
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python
train
RLBot/RLBot
src/main/python/rlbot/agents/base_agent.py
https://github.com/RLBot/RLBot/blob/3f9b6bec8b9baf4dcfff0f6cf3103c8744ac6234/src/main/python/rlbot/agents/base_agent.py#L96-L105
def send_quick_chat(self, team_only, quick_chat): """ Sends a quick chat to the other bots. If it is QuickChats.CHAT_NONE or None it does not send a quick chat to other bots. :param team_only: either True or False, this says if the quick chat should only go to team members. :param quick_chat: The quick chat selection, available chats are defined in quick_chats.py """ if quick_chat == QuickChats.CHAT_NONE or quick_chat is None: return self.__quick_chat_func(team_only, quick_chat)
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Sends a quick chat to the other bots. If it is QuickChats.CHAT_NONE or None it does not send a quick chat to other bots. :param team_only: either True or False, this says if the quick chat should only go to team members. :param quick_chat: The quick chat selection, available chats are defined in quick_chats.py
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python
train
ftao/python-ifcfg
src/ifcfg/__init__.py
https://github.com/ftao/python-ifcfg/blob/724a4a103088fee7dc2bc2f63b0b9006a614e1d0/src/ifcfg/__init__.py#L18-L39
def get_parser_class(): """ Returns the parser according to the system platform """ global distro if distro == 'Linux': Parser = parser.LinuxParser if not os.path.exists(Parser.get_command()[0]): Parser = parser.UnixIPParser elif distro in ['Darwin', 'MacOSX']: Parser = parser.MacOSXParser elif distro == 'Windows': # For some strange reason, Windows will always be win32, see: # https://stackoverflow.com/a/2145582/405682 Parser = parser.WindowsParser else: Parser = parser.NullParser Log.error("Unknown distro type '%s'." % distro) Log.debug("Distro detected as '%s'" % distro) Log.debug("Using '%s'" % Parser) return Parser
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Returns the parser according to the system platform
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python
train
GeorgeArgyros/symautomata
symautomata/pdacnf.py
https://github.com/GeorgeArgyros/symautomata/blob/f5d66533573b27e155bec3f36b8c00b8e3937cb3/symautomata/pdacnf.py#L106-L117
def get(self, statediag): """ Args: statediag (list): The states of the PDA Returns: list: A reduced list of states using BFS """ if len(statediag) < 1: print 'PDA is empty and can not be reduced' return statediag newstatediag = self.bfs(statediag, statediag[0]) return newstatediag
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Args: statediag (list): The states of the PDA Returns: list: A reduced list of states using BFS
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python
train
twisted/axiom
benchmark/benchlib.py
https://github.com/twisted/axiom/blob/7de70bc8fe1bb81f9c2339fba8daec9eb2e92b68/benchmark/benchlib.py#L13-L22
def itemTypeWithSomeAttributes(attributeTypes): """ Create a new L{Item} subclass with L{numAttributes} integers in its schema. """ class SomeItem(Item): typeName = 'someitem_' + str(typeNameCounter()) for i, attributeType in enumerate(attributeTypes): locals()['attr_' + str(i)] = attributeType() return SomeItem
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Create a new L{Item} subclass with L{numAttributes} integers in its schema.
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python
train
deepmind/pysc2
pysc2/lib/stopwatch.py
https://github.com/deepmind/pysc2/blob/df4cc4b00f07a2242be9ba153d4a7f4ad2017897/pysc2/lib/stopwatch.py#L242-L252
def parse(s): """Parse the output below to create a new StopWatch.""" stopwatch = StopWatch() for line in s.splitlines(): if line.strip(): parts = line.split(None) name = parts[0] if name != "%": # ie not the header line rest = (float(v) for v in parts[2:]) stopwatch.times[parts[0]].merge(Stat.build(*rest)) return stopwatch
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Parse the output below to create a new StopWatch.
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python
train
danielhrisca/asammdf
benchmarks/gen_images.py
https://github.com/danielhrisca/asammdf/blob/3c7a1fd19c957ceebe4dcdbb2abf00806c2bdb66/benchmarks/gen_images.py#L8-L94
def generate_graphs(result, topic, aspect, for_doc=False): """ genrate graphs from result file Parameters ---------- result : str path to result file topic : str benchmark topic; for example "Open file" or "Save file" aspect : str performance indiitemsor; can be "ram" (RAM memory usage) or "time" (elapsed time) for_doc : bool wether the source code is used inside the documentation """ result = result topic = topic aspect = aspect for_doc = for_doc with open(result, 'r') as f: lines = f.readlines() platform = 'x86' if '32 bit' in lines[2] else 'x64' idx = [i for i, line in enumerate(lines) if line.startswith('==')] table_spans = {'open': [idx[1] + 1, idx[2]], 'save': [idx[4] + 1, idx[5]], 'get': [idx[7] + 1, idx[8]], 'convert' : [idx[10] + 1, idx[11]], 'merge' : [idx[13] + 1, idx[14]]} start, stop = table_spans[topic.lower()] items = [l[:50].strip(' \t\r\n\0*') for l in lines[start: stop]] time = np.array([int(l[50:61].strip(' \t\r\n\0*')) for l in lines[start: stop]]) ram = np.array([int(l[61:].strip(' \t\r\n\0*')) for l in lines[start: stop]]) if aspect == 'ram': array = ram else: array = time y_pos = list(range(len(items))) fig, ax = plt.subplots() fig.set_size_inches(15, 3.8 / 12 * len(items) + 1.2) asam_pos = [i for i, c in enumerate(items) if c.startswith('asam')] mdfreader_pos = [i for i, c in enumerate(items) if c.startswith('mdfreader')] ax.barh(asam_pos, array[asam_pos], color='green', ecolor='green') ax.barh(mdfreader_pos, array[mdfreader_pos], color='blue', ecolor='black') ax.set_yticks(y_pos) ax.set_yticklabels(items) ax.invert_yaxis() ax.set_xlabel('Time [ms]' if aspect == 'time' else 'RAM [MB]') if topic == 'Get': ax.set_title('Get all channels (36424 calls) - {}' .format('time' if aspect == 'time' else 'ram usage')) else: ax.set_title('{} test file - {}' .format(topic, 'time' if aspect == 'time' else 'ram usage')) ax.xaxis.grid() fig.subplots_adjust(bottom=0.72/fig.get_figheight(), top=1-0.48/fig.get_figheight(), left=0.4, right=0.9) if aspect == 'time': if topic == 'Get': name = '{}_get_all_channels.png'.format(platform) else: name = '{}_{}.png'.format(platform, topic.lower()) else: if topic == 'Get': name = '{}_get_all_channels_ram_usage.png'.format(platform) else: name = '{}_{}_ram_usage.png'.format(platform, topic.lower()) if for_doc: plt.show() else: plt.savefig(name, dpi=300)
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genrate graphs from result file Parameters ---------- result : str path to result file topic : str benchmark topic; for example "Open file" or "Save file" aspect : str performance indiitemsor; can be "ram" (RAM memory usage) or "time" (elapsed time) for_doc : bool wether the source code is used inside the documentation
[ "genrate", "graphs", "from", "result", "file" ]
python
train
hubo1016/vlcp
vlcp/event/core.py
https://github.com/hubo1016/vlcp/blob/239055229ec93a99cc7e15208075724ccf543bd1/vlcp/event/core.py#L303-L518
def main(self, installsignal = True, sendinit = True): ''' Start main loop ''' if installsignal: sigterm = signal(SIGTERM, self._quitsignal) sigint = signal(SIGINT, self._quitsignal) try: from signal import SIGUSR1 sigusr1 = signal(SIGUSR1, self._tracesignal) except Exception: pass try: if sendinit: self.queue.append(SystemControlEvent(SystemControlEvent.INIT), True) def processSyscall(): while self.syscallfunc is not None: r = getattr(self, 'syscallrunnable', None) if r is None: self.syscallfunc = None break try: try: retvalue = self.syscallfunc(self, processEvent) except Exception: (t, v, tr) = sys.exc_info() self.syscallfunc = None self.syscallrunnable = None r.send((SyscallReturnEvent(exception=(t, v, tr)), self.syscallmatcher)) else: self.syscallfunc = None self.syscallrunnable = None r.send((SyscallReturnEvent(retvalue=retvalue), self.syscallmatcher)) except StopIteration: self.unregisterall(r) except QuitException: self.unregisterall(r) except Exception: self.logger.exception('processing syscall failed with exception') self.unregisterall(r) def processEvent(event, emptys = ()): if self.debugging: self.logger.debug('Processing event %s', repr(event)) runnables = self.matchtree.matchesWithMatchers(event) for r, m in runnables: try: self.syscallfunc = None self.syscallrunnable = None if self.debugging: self.logger.debug('Send event to %r, matched with %r', r, m) r.send((event, m)) except StopIteration: self.unregisterall(r) except QuitException: self.unregisterall(r) except Exception: self.logger.exception('processing event %s failed with exception', repr(event)) self.unregisterall(r) processSyscall() if not event.canignore and not event.canignorenow(): self.eventtree.insert(event) self.queue.block(event, emptys) else: for e in emptys: processEvent(e) def processQueueEvent(event): """ Optimized with queue events """ if self.debugging: self.logger.debug('Processing event %s', repr(event)) is_valid = event.is_valid() if is_valid is None: processEvent(event) else: while event.is_valid(): result = self.matchtree.matchfirstwithmatcher(event) if result is None: break r, m = result try: self.syscallfunc = None self.syscallrunnable = None if self.debugging: self.logger.debug('Send event to %r, matched with %r', r, m) r.send((event, m)) except StopIteration: self.unregisterall(r) except QuitException: self.unregisterall(r) except Exception: self.logger.exception('processing event %s failed with exception', repr(event)) self.unregisterall(r) processSyscall() def processYields(): while self._pending_runnables: i = 0 while i < len(self._pending_runnables): r = self._pending_runnables[i] try: next(r) except StopIteration: self.unregisterall(r) except QuitException: self.unregisterall(r) except Exception: self.logger.exception('Resuming %r failed with exception', r) self.unregisterall(r) processSyscall() i += 1 del self._pending_runnables[:i] canquit = False self.logger.info('Main loop started') current_time = self.current_time = time() processYields() quitMatcher = SystemControlEvent.createMatcher(type=SystemControlEvent.QUIT) while len(self.registerIndex) > len(self.daemons): if self.debugging: self.logger.debug('Blocked events: %d', len(self.queue.blockEvents)) self.logger.debug('Blocked events list: %r', list(self.queue.blockEvents.keys())) if self.quitting: self.logger.debug('Routines still not quit: %r', list(self.registerIndex.keys())) if self.quitsignal: self.quit() if canquit and not self.queue.canPop() and not self.timers: if self.quitting: break else: self.quit(True) self.queue.append(SystemControlLowPriorityEvent(SystemControlLowPriorityEvent.LOOP), True) processedEvents = 0 while self.queue.canPop() and (self.processevents is None or processedEvents < self.processevents): e, qes, emptys = self.queue.pop() # Queue events will not enqueue again if not e.canignore and not e.canignorenow(): # The event might block, must process it first processEvent(e, emptys) for qe in qes: processQueueEvent(qe) else: for qe in qes: processQueueEvent(qe) processEvent(e, emptys) processYields() if quitMatcher.isMatch(e): if e.daemononly: runnables = list(self.daemons) else: runnables = list(self.registerIndex.keys()) for r in runnables: try: r.throw(QuitException) except StopIteration: self.unregisterall(r) except QuitException: self.unregisterall(r) except Exception: self.logger.exception('Runnable quit failed with exception') self.unregisterall(r) processSyscall() processYields() if self.quitsignal: self.quit() processedEvents += 1 if len(self.registerIndex) <= len(self.daemons): break end_time = time() if end_time - current_time > 1: self.logger.warning("An iteration takes %r seconds to process", end_time - current_time) if self.generatecontinue or self.queue.canPop(): wait = 0 elif not self.timers: wait = None else: wait = self.timers.top().timestamp - end_time if wait < 0: wait = 0 events, canquit = self.polling.pollEvents(wait) for e in events: self.queue.append(e, True) current_time = self.current_time = time() now = current_time + 0.1 while self.timers and self.timers.topPriority() < now: t = self.timers.top() if t.interval is not None: t.timestamp += t.interval self.timers.setpriority(t, t.timestamp) else: self.timers.pop() self.queue.append(TimerEvent(t), True) if self.generatecontinue: self.queue.append(SystemControlEvent(SystemControlEvent.CONTINUE), True) self.generatecontinue = False if self.registerIndex: if len(self.registerIndex) > len(self.daemons): self.logger.warning('Some runnables are not quit, doing cleanup') self.logger.warning('Runnables list: %r', set(self.registerIndex.keys()).difference(self.daemons)) for r in list(self.registerIndex.keys()): try: r.close() except Exception: self.logger.exception('Runnable quit failed with exception') finally: self.unregisterall(r) self.logger.info('Main loop quit normally') finally: if installsignal: signal(SIGTERM, sigterm) signal(SIGINT, sigint) try: signal(SIGUSR1, sigusr1) except Exception: pass
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Start main loop
[ "Start", "main", "loop" ]
python
train
shi-cong/PYSTUDY
PYSTUDY/middleware/rabbitmqlib.py
https://github.com/shi-cong/PYSTUDY/blob/c8da7128ea18ecaa5849f2066d321e70d6f97f70/PYSTUDY/middleware/rabbitmqlib.py#L107-L114
def store_data(self, data): """ 存储数据到存储队列 :param data: 数据 :return: """ self.ch.basic_publish(exchange='', routing_key=self.store_queue, properties=pika.BasicProperties(delivery_mode=2), body=data)
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存储数据到存储队列 :param data: 数据 :return:
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python
train
honzamach/pydgets
pydgets/widgets.py
https://github.com/honzamach/pydgets/blob/5ca4ce19fc2d9b5f41441fb9163810f8ca502e79/pydgets/widgets.py#L1159-L1176
def fmt_row(self, columns, dimensions, row, **settings): """ Format single table row. """ cells = [] i = 0 for column in columns: cells.append(self.fmt_cell( row[i], dimensions[i], column, **settings[self.SETTING_TEXT_FORMATING] ) ) i += 1 return self.bchar('v', 'm', settings[self.SETTING_BORDER_STYLE], **settings[self.SETTING_BORDER_FORMATING]) + \ self.bchar('v', 'm', settings[self.SETTING_BORDER_STYLE], **settings[self.SETTING_BORDER_FORMATING]).join(cells) + \ self.bchar('v', 'm', settings[self.SETTING_BORDER_STYLE], **settings[self.SETTING_BORDER_FORMATING])
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Format single table row.
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python
train
odlgroup/odl
odl/contrib/datasets/images/cambridge.py
https://github.com/odlgroup/odl/blob/b8443f6aca90e191ba36c91d32253c5a36249a6c/odl/contrib/datasets/images/cambridge.py#L32-L59
def convert(image, shape, gray=False, dtype='float64', normalize='max'): """Convert image to standardized format. Several properties of the input image may be changed including the shape, data type and maximal value of the image. In addition, this function may convert the image into an ODL object and/or a gray scale image. """ image = image.astype(dtype) if gray: image[..., 0] *= 0.2126 image[..., 1] *= 0.7152 image[..., 2] *= 0.0722 image = np.sum(image, axis=2) if shape is not None: image = skimage.transform.resize(image, shape, mode='constant') image = image.astype(dtype) if normalize == 'max': image /= image.max() elif normalize == 'sum': image /= image.sum() else: assert False return image
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Convert image to standardized format. Several properties of the input image may be changed including the shape, data type and maximal value of the image. In addition, this function may convert the image into an ODL object and/or a gray scale image.
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python
train
theonion/django-bulbs
bulbs/content/serializers.py
https://github.com/theonion/django-bulbs/blob/0c0e6e3127a7dc487b96677fab95cacd2b3806da/bulbs/content/serializers.py#L24-L28
def to_internal_value(self, value): """Convert to integer id.""" natural_key = value.split("_") content_type = ContentType.objects.get_by_natural_key(*natural_key) return content_type.id
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Convert to integer id.
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python
train
agoragames/haigha
haigha/reader.py
https://github.com/agoragames/haigha/blob/7b004e1c0316ec14b94fec1c54554654c38b1a25/haigha/reader.py#L123-L145
def read_bits(self, num): ''' Read several bits packed into the same field. Will return as a list. The bit field itself is little-endian, though the order of the returned array looks big-endian for ease of decomposition. Reader('\x02').read_bits(2) -> [False,True] Reader('\x08').read_bits(2) -> [False,True,False,False,False,False,False,False] first_field, second_field = Reader('\x02').read_bits(2) Will raise BufferUnderflow if there's not enough bytes in the buffer. Will raise ValueError if num < 0 or num > 9 ''' # Perform a faster check on underflow if self._pos >= self._end_pos: raise self.BufferUnderflow() if num < 0 or num >= 9: raise ValueError("8 bits per field") field = ord(self._input[self._pos]) result = map(lambda x: field >> x & 1, xrange(num)) self._pos += 1 return result
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Read several bits packed into the same field. Will return as a list. The bit field itself is little-endian, though the order of the returned array looks big-endian for ease of decomposition. Reader('\x02').read_bits(2) -> [False,True] Reader('\x08').read_bits(2) -> [False,True,False,False,False,False,False,False] first_field, second_field = Reader('\x02').read_bits(2) Will raise BufferUnderflow if there's not enough bytes in the buffer. Will raise ValueError if num < 0 or num > 9
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python
train
TangoAlpha/liffylights
liffylights.py
https://github.com/TangoAlpha/liffylights/blob/7ae9ed947ecf039734014d98b6e18de0f26fa1d3/liffylights.py#L130-L153
def _gen_header(self, sequence, payloadtype): """ Create packet header. """ protocol = bytearray.fromhex("00 34") source = bytearray.fromhex("42 52 4b 52") target = bytearray.fromhex("00 00 00 00 00 00 00 00") reserved1 = bytearray.fromhex("00 00 00 00 00 00") sequence = pack("<B", sequence) ack = pack(">B", 3) reserved2 = bytearray.fromhex("00 00 00 00 00 00 00 00") packet_type = pack("<H", payloadtype) reserved3 = bytearray.fromhex("00 00") # assemble header header = bytearray(protocol) header.extend(source) header.extend(target) header.extend(reserved1) header.extend(ack) header.extend(sequence) header.extend(reserved2) header.extend(packet_type) header.extend(reserved3) return header
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Create packet header.
[ "Create", "packet", "header", "." ]
python
train
seung-lab/cloud-volume
cloudvolume/cacheservice.py
https://github.com/seung-lab/cloud-volume/blob/d2fd4500333f1bc3cd3e3919a8b649cec5d8e214/cloudvolume/cacheservice.py#L177-L233
def check_info_validity(self): """ ValueError if cache differs at all from source data layer with an excepton for volume_size which prints a warning. """ cache_info = self.get_json('info') if not cache_info: return fresh_info = self.vol._fetch_info() mismatch_error = ValueError(""" Data layer info file differs from cache. Please check whether this change invalidates your cache. If VALID do one of: 1) Manually delete the cache (see location below) 2) Refresh your on-disk cache as follows: vol = CloudVolume(..., cache=False) # refreshes from source vol.cache = True vol.commit_info() # writes to disk If INVALID do one of: 1) Delete the cache manually (see cache location below) 2) Instantiate as follows: vol = CloudVolume(..., cache=False) # refreshes info from source vol.flush_cache() # deletes cache vol.cache = True vol.commit_info() # writes info to disk CACHED: {cache} SOURCE: {source} CACHE LOCATION: {path} """.format( cache=cache_info, source=fresh_info, path=self.path )) try: fresh_sizes = [ scale['size'] for scale in fresh_info['scales'] ] cache_sizes = [ scale['size'] for scale in cache_info['scales'] ] except KeyError: raise mismatch_error for scale in fresh_info['scales']: del scale['size'] for scale in cache_info['scales']: del scale['size'] if fresh_info != cache_info: raise mismatch_error if fresh_sizes != cache_sizes: warn("WARNING: Data layer bounding box differs in cache.\nCACHED: {}\nSOURCE: {}\nCACHE LOCATION:{}".format( cache_sizes, fresh_sizes, self.path ))
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ValueError if cache differs at all from source data layer with an excepton for volume_size which prints a warning.
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python
train
mehcode/python-saml
saml/signature.py
https://github.com/mehcode/python-saml/blob/33ed62018efa9ec15b551f309429de510fa44321/saml/signature.py#L113-L166
def verify(xml, stream): """ Verify the signaure of an XML document with the given certificate. Returns `True` if the document is signed with a valid signature. Returns `False` if the document is not signed or if the signature is invalid. :param lxml.etree._Element xml: The document to sign :param file stream: The private key to sign the document with :rtype: Boolean """ # Import xmlsec here to delay initializing the C library in # case we don't need it. import xmlsec # Find the <Signature/> node. signature_node = xmlsec.tree.find_node(xml, xmlsec.Node.SIGNATURE) if signature_node is None: # No `signature` node found; we cannot verify return False # Create a digital signature context (no key manager is needed). ctx = xmlsec.SignatureContext() # Register <Response/> and <Assertion/> ctx.register_id(xml) for assertion in xml.xpath("//*[local-name()='Assertion']"): ctx.register_id(assertion) # Load the public key. key = None for fmt in [ xmlsec.KeyFormat.PEM, xmlsec.KeyFormat.CERT_PEM]: stream.seek(0) try: key = xmlsec.Key.from_memory(stream, fmt) break except ValueError: # xmlsec now throws when it can't load the key pass # Set the key on the context. ctx.key = key # Verify the signature. try: ctx.verify(signature_node) return True except Exception: return False
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Verify the signaure of an XML document with the given certificate. Returns `True` if the document is signed with a valid signature. Returns `False` if the document is not signed or if the signature is invalid. :param lxml.etree._Element xml: The document to sign :param file stream: The private key to sign the document with :rtype: Boolean
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python
valid
wandb/client
wandb/vendor/prompt_toolkit/shortcuts.py
https://github.com/wandb/client/blob/7d08954ed5674fee223cd85ed0d8518fe47266b2/wandb/vendor/prompt_toolkit/shortcuts.py#L664-L671
def confirm(message='Confirm (y or n) '): """ Display a confirmation prompt. """ assert isinstance(message, text_type) app = create_confirm_application(message) return run_application(app)
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Display a confirmation prompt.
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python
train
twilio/twilio-python
twilio/rest/api/v2010/account/__init__.py
https://github.com/twilio/twilio-python/blob/c867895f55dcc29f522e6e8b8868d0d18483132f/twilio/rest/api/v2010/account/__init__.py#L474-L483
def new_keys(self): """ Access the new_keys :returns: twilio.rest.api.v2010.account.new_key.NewKeyList :rtype: twilio.rest.api.v2010.account.new_key.NewKeyList """ if self._new_keys is None: self._new_keys = NewKeyList(self._version, account_sid=self._solution['sid'], ) return self._new_keys
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Access the new_keys :returns: twilio.rest.api.v2010.account.new_key.NewKeyList :rtype: twilio.rest.api.v2010.account.new_key.NewKeyList
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python
train
PyMLGame/pymlgame
game_example.py
https://github.com/PyMLGame/pymlgame/blob/450fe77d35f9a26c107586d6954f69c3895bf504/game_example.py#L134-L144
def gameloop(self): """ A game loop that circles through the methods. """ try: while True: self.handle_events() self.update() self.render() except KeyboardInterrupt: pass
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A game loop that circles through the methods.
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python
train
apache/incubator-heron
heron/tools/common/src/python/access/heron_api.py
https://github.com/apache/incubator-heron/blob/ad10325a0febe89ad337e561ebcbe37ec5d9a5ac/heron/tools/common/src/python/access/heron_api.py#L772-L799
def fetch_max(self, cluster, metric, topology, component, instance, timerange, environ=None): ''' :param cluster: :param metric: :param topology: :param component: :param instance: :param timerange: :param environ: :return: ''' components = [component] if component != "*" else (yield get_comps(cluster, environ, topology)) result = {} futures = [] for comp in components: query = self.get_query(metric, comp, instance) max_query = "MAX(%s)" % query future = get_metrics(cluster, environ, topology, timerange, max_query) futures.append(future) results = yield futures data = self.compute_max(results) result = self.get_metric_response(timerange, data, True) raise tornado.gen.Return(result)
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:param cluster: :param metric: :param topology: :param component: :param instance: :param timerange: :param environ: :return:
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python
valid
lpantano/seqcluster
seqcluster/libs/thinkbayes.py
https://github.com/lpantano/seqcluster/blob/774e23add8cd4fdc83d626cea3bd1f458e7d060d/seqcluster/libs/thinkbayes.py#L1633-L1649
def GaussianCdfInverse(p, mu=0, sigma=1): """Evaluates the inverse CDF of the gaussian distribution. See http://en.wikipedia.org/wiki/Normal_distribution#Quantile_function Args: p: float mu: mean parameter sigma: standard deviation parameter Returns: float """ x = ROOT2 * erfinv(2 * p - 1) return mu + x * sigma
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Evaluates the inverse CDF of the gaussian distribution. See http://en.wikipedia.org/wiki/Normal_distribution#Quantile_function Args: p: float mu: mean parameter sigma: standard deviation parameter Returns: float
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python
train
mikusjelly/apkutils
apkutils/elf/elfparser.py
https://github.com/mikusjelly/apkutils/blob/2db1ed0cdb610dfc55bfd77266e9a91e4764bba4/apkutils/elf/elfparser.py#L87-L100
def _section_from_spec(self, spec): ''' Retrieve a section given a "spec" (either number or name). Return None if no such section exists in the file. ''' try: num = int(spec) if num < self.elf_file.num_sections(): return self.elf_file.get_section(num) else: return None except ValueError: # Not a number. Must be a name then return self.elf_file.get_section_by_name(spec)
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Retrieve a section given a "spec" (either number or name). Return None if no such section exists in the file.
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python
train
mabuchilab/QNET
src/qnet/algebra/core/circuit_algebra.py
https://github.com/mabuchilab/QNET/blob/cc20d26dad78691d34c67173e5cd67dcac94208a/src/qnet/algebra/core/circuit_algebra.py#L130-L152
def get_blocks(self, block_structure=None): """For a reducible circuit, get a sequence of subblocks that when concatenated again yield the original circuit. The block structure given has to be compatible with the circuits actual block structure, i.e. it can only be more coarse-grained. Args: block_structure (tuple): The block structure according to which the subblocks are generated (default = ``None``, corresponds to the circuit's own block structure) Returns: A tuple of subblocks that the circuit consists of. Raises: .IncompatibleBlockStructures """ if block_structure is None: block_structure = self.block_structure try: return self._get_blocks(block_structure) except IncompatibleBlockStructures as e: raise e
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For a reducible circuit, get a sequence of subblocks that when concatenated again yield the original circuit. The block structure given has to be compatible with the circuits actual block structure, i.e. it can only be more coarse-grained. Args: block_structure (tuple): The block structure according to which the subblocks are generated (default = ``None``, corresponds to the circuit's own block structure) Returns: A tuple of subblocks that the circuit consists of. Raises: .IncompatibleBlockStructures
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python
train
cloudmesh/cloudmesh-common
cloudmesh/common/BaseConfigDict.py
https://github.com/cloudmesh/cloudmesh-common/blob/ae4fae09cd78205d179ea692dc58f0b0c8fea2b8/cloudmesh/common/BaseConfigDict.py#L393-L399
def yaml(self): """ returns the yaml output of the dict. """ return ordered_dump(OrderedDict(self), Dumper=yaml.SafeDumper, default_flow_style=False)
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returns the yaml output of the dict.
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python
train
gabstopper/smc-python
smc/core/engine.py
https://github.com/gabstopper/smc-python/blob/e027b8a5dcfaf884eada32d113d41c1e56b32457/smc/core/engine.py#L1007-L1024
def refresh(self, timeout=3, wait_for_finish=False, **kw): """ Refresh existing policy on specified device. This is an asynchronous call that will return a 'follower' link that can be queried to determine the status of the task. :: poller = engine.refresh() while not poller.done(): poller.wait(5) print('Percentage complete {}%'.format(poller.task.progress)) :param int timeout: timeout between queries :raises TaskRunFailed: refresh failed, possibly locked policy :rtype: TaskOperationPoller """ return Task.execute(self, 'refresh', timeout=timeout, wait_for_finish=wait_for_finish, **kw)
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Refresh existing policy on specified device. This is an asynchronous call that will return a 'follower' link that can be queried to determine the status of the task. :: poller = engine.refresh() while not poller.done(): poller.wait(5) print('Percentage complete {}%'.format(poller.task.progress)) :param int timeout: timeout between queries :raises TaskRunFailed: refresh failed, possibly locked policy :rtype: TaskOperationPoller
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python
train
bd808/python-iptools
iptools/__init__.py
https://github.com/bd808/python-iptools/blob/5d3fae0056297540355bb7c6c112703cfaa4b6ce/iptools/__init__.py#L58-L65
def _address2long(address): """ Convert an address string to a long. """ parsed = ipv4.ip2long(address) if parsed is None: parsed = ipv6.ip2long(address) return parsed
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Convert an address string to a long.
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python
train
Telefonica/toolium
toolium/pageelements/page_element.py
https://github.com/Telefonica/toolium/blob/56847c243b3a98876df74c184b75e43f8810e475/toolium/pageelements/page_element.py#L103-L111
def scroll_element_into_view(self): """Scroll element into view :returns: page element instance """ x = self.web_element.location['x'] y = self.web_element.location['y'] self.driver.execute_script('window.scrollTo({0}, {1})'.format(x, y)) return self
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Scroll element into view :returns: page element instance
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python
train
Contraz/demosys-py
demosys/loaders/scene/gltf.py
https://github.com/Contraz/demosys-py/blob/6466128a3029c4d09631420ccce73024025bd5b6/demosys/loaders/scene/gltf.py#L474-L476
def interleaves(self, info): """Does the buffer interleave with this one?""" return info.byte_offset == self.component_type.size * self.components
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Does the buffer interleave with this one?
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python
valid
ctuning/ck
ck/kernel.py
https://github.com/ctuning/ck/blob/7e009814e975f8742790d3106340088a46223714/ck/kernel.py#L3118-L3261
def perform_remote_action(i): """ Input: { See 'perform_action' function } Output: { See 'perform_action' function } """ # Import modules compatible with Python 2.x and 3.x import urllib try: import urllib.request as urllib2 except: import urllib2 # pragma: no cover try: from urllib.parse import urlencode except: from urllib import urlencode # pragma: no cover rr={'return':0} # Get action act=i.get('action','') # Check output o=i.get('out','') if o=='con': # out('Initiating remote access ...') # out('') i['out']='con' i['quiet']='yes' if act=='pull': i['out']='json' else: i['out']='json' # # Clean up input # if o!='json_file': # rr['out']='json' # Decided to return json to show that it's remote ... if 'cid' in i: del(i['cid']) # already processed # Get URL url=i.get('remote_server_url','') # Process i if 'remote_server_url' in i: del(i['remote_server_url']) # Pre process if push file ... if act=='push': # Check file fn=i.get('filename','') if fn=='': x=i.get('cids',[]) if len(x)>0: fn=x[0] if fn=='': return {'return':1, 'error':'filename is empty'} if not os.path.isfile(fn): return {'return':1, 'error':'file '+fn+' not found'} rx=convert_file_to_upload_string({'filename':fn}) if rx['return']>0: return rx i['file_content_base64']=rx['file_content_base64'] # Leave only filename without path i['filename']=os.path.basename(fn) # Prepare post variables r=dumps_json({'dict':i, 'skip_indent':'yes'}) if r['return']>0: return r s=r['string'].encode('utf8') post=urlencode({'ck_json':s}) if sys.version_info[0]>2: post=post.encode('utf8') # If auth au=i.get('remote_server_user','') if au!='': del(i['remote_server_user']) ap=i.get('remote_server_pass','') if ap!='': del(i['remote_server_pass']) auth = urllib2.HTTPPasswordMgrWithDefaultRealm() auth.add_password(None, url, au, ap) urllib2.install_opener(urllib2.build_opener(urllib2.HTTPBasicAuthHandler(auth))) # Prepare request request = urllib2.Request(url, post) # Connect try: f=urllib2.urlopen(request) except Exception as e: return {'return':1, 'error':'Access to remote CK repository failed ('+format(e)+')'} # Read from Internet try: s=f.read() f.close() except Exception as e: return {'return':1, 'error':'Failed reading stream from remote CK web service ('+format(e)+')'} # Check output try: s=s.decode('utf8') except Exception as e: pass if o=='con' and act!='pull': out(s.rstrip()) else: # Try to convert output to dictionary r=convert_json_str_to_dict({'str':s, 'skip_quote_replacement':'yes'}) if r['return']>0: return {'return':1, 'error':'can\'t parse output from remote CK server ('+r['error']+'):\n'+s[:256]+'\n\n...)'} d=r['dict'] if 'return' in d: d['return']=int(d['return']) # Fix for some strange behavior when 'return' is not integer - should check why ... if d.get('return',0)>0: return d # Post process if pull file ... if act=='pull': if o!='json' and o!='json_file': # Convert encoded file to real file ... x=d.get('file_content_base64','') fn=d.get('filename','') if fn=='': fn=cfg['default_archive_name'] r=convert_upload_string_to_file({'file_content_base64':x, 'filename':fn}) if r['return']>0: return r if 'file_content_base64' in d: del(d['file_content_base64']) rr.update(d) # Restore original output i['out']=o return rr
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python
train
tensorflow/tensor2tensor
tensor2tensor/utils/learning_rate.py
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/utils/learning_rate.py#L105-L114
def _global_step(hparams): """Adjust global step if a multi-step optimizer is used.""" step = tf.to_float(tf.train.get_or_create_global_step()) multiplier = hparams.optimizer_multistep_accumulate_steps if not multiplier: return step tf.logging.info("Dividing global step by %d for multi-step optimizer." % multiplier) return step / tf.to_float(multiplier)
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Adjust global step if a multi-step optimizer is used.
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python
train
scanny/python-pptx
pptx/api.py
https://github.com/scanny/python-pptx/blob/d6ab8234f8b03953d2f831ff9394b1852db34130/pptx/api.py#L20-L36
def Presentation(pptx=None): """ Return a |Presentation| object loaded from *pptx*, where *pptx* can be either a path to a ``.pptx`` file (a string) or a file-like object. If *pptx* is missing or ``None``, the built-in default presentation "template" is loaded. """ if pptx is None: pptx = _default_pptx_path() presentation_part = Package.open(pptx).main_document_part if not _is_pptx_package(presentation_part): tmpl = "file '%s' is not a PowerPoint file, content type is '%s'" raise ValueError(tmpl % (pptx, presentation_part.content_type)) return presentation_part.presentation
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Return a |Presentation| object loaded from *pptx*, where *pptx* can be either a path to a ``.pptx`` file (a string) or a file-like object. If *pptx* is missing or ``None``, the built-in default presentation "template" is loaded.
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python
train
jupyterhub/kubespawner
kubespawner/spawner.py
https://github.com/jupyterhub/kubespawner/blob/46a4b109c5e657a4c3d5bfa8ea4731ec6564ea13/kubespawner/spawner.py#L1839-L1873
def options_from_form(self, formdata): """get the option selected by the user on the form This only constructs the user_options dict, it should not actually load any options. That is done later in `.load_user_options()` Args: formdata: user selection returned by the form To access to the value, you can use the `get` accessor and the name of the html element, for example:: formdata.get('profile',[0]) to get the value of the form named "profile", as defined in `form_template`:: <select class="form-control" name="profile"...> </select> Returns: user_options (dict): the selected profile in the user_options form, e.g. ``{"profile": "8 CPUs"}`` """ if not self.profile_list or self._profile_list is None: return formdata # Default to first profile if somehow none is provided try: selected_profile = int(formdata.get('profile', [0])[0]) options = self._profile_list[selected_profile] except (TypeError, IndexError, ValueError): raise web.HTTPError(400, "No such profile: %i", formdata.get('profile', None)) return { 'profile': options['display_name'] }
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get the option selected by the user on the form This only constructs the user_options dict, it should not actually load any options. That is done later in `.load_user_options()` Args: formdata: user selection returned by the form To access to the value, you can use the `get` accessor and the name of the html element, for example:: formdata.get('profile',[0]) to get the value of the form named "profile", as defined in `form_template`:: <select class="form-control" name="profile"...> </select> Returns: user_options (dict): the selected profile in the user_options form, e.g. ``{"profile": "8 CPUs"}``
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python
train
Alignak-monitoring/alignak
alignak/external_command.py
https://github.com/Alignak-monitoring/alignak/blob/f3c145207e83159b799d3714e4241399c7740a64/alignak/external_command.py#L2195-L2208
def disable_host_notifications(self, host): """Disable notifications for a host Format of the line that triggers function call:: DISABLE_HOST_NOTIFICATIONS;<host_name> :param host: host to edit :type host: alignak.objects.host.Host :return: None """ if host.notifications_enabled: host.modified_attributes |= DICT_MODATTR["MODATTR_NOTIFICATIONS_ENABLED"].value host.notifications_enabled = False self.send_an_element(host.get_update_status_brok())
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Disable notifications for a host Format of the line that triggers function call:: DISABLE_HOST_NOTIFICATIONS;<host_name> :param host: host to edit :type host: alignak.objects.host.Host :return: None
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python
train
polyaxon/polyaxon-cli
polyaxon_cli/cli/job.py
https://github.com/polyaxon/polyaxon-cli/blob/a7f5eed74d4d909cad79059f3c21c58606881449/polyaxon_cli/cli/job.py#L131-L169
def update(ctx, name, description, tags): """Update job. Uses [Caching](/references/polyaxon-cli/#caching) Example: \b ```bash $ polyaxon job -j 2 update --description="new description for my job" ``` """ user, project_name, _job = get_job_or_local(ctx.obj.get('project'), ctx.obj.get('job')) update_dict = {} if name: update_dict['name'] = name if description: update_dict['description'] = description tags = validate_tags(tags) if tags: update_dict['tags'] = tags if not update_dict: Printer.print_warning('No argument was provided to update the job.') sys.exit(0) try: response = PolyaxonClient().job.update_job( user, project_name, _job, update_dict) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not update job `{}`.'.format(_job)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1) Printer.print_success("Job updated.") get_job_details(response)
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Update job. Uses [Caching](/references/polyaxon-cli/#caching) Example: \b ```bash $ polyaxon job -j 2 update --description="new description for my job" ```
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python
valid
Sheeprider/BitBucket-api
bitbucket/bitbucket.py
https://github.com/Sheeprider/BitBucket-api/blob/be45515d506d87f14807a676f3c2f20d79674b75/bitbucket/bitbucket.py#L216-L251
def dispatch(self, method, url, auth=None, params=None, **kwargs): """ Send HTTP request, with given method, credentials and data to the given URL, and return the success and the result on success. """ r = Request( method=method, url=url, auth=auth, params=params, data=kwargs) s = Session() resp = s.send(r.prepare()) status = resp.status_code text = resp.text error = resp.reason if status >= 200 and status < 300: if text: try: return (True, json.loads(text)) except TypeError: pass except ValueError: pass return (True, text) elif status >= 300 and status < 400: return ( False, 'Unauthorized access, ' 'please check your credentials.') elif status >= 400 and status < 500: return (False, 'Service not found.') elif status >= 500 and status < 600: return (False, 'Server error.') else: return (False, error)
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Send HTTP request, with given method, credentials and data to the given URL, and return the success and the result on success.
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python
train
Robpol86/sphinxcontrib-versioning
sphinxcontrib/versioning/__main__.py
https://github.com/Robpol86/sphinxcontrib-versioning/blob/920edec0ac764081b583a2ecf4e6952762b9dbf2/sphinxcontrib/versioning/__main__.py#L80-L89
def invoke(self, ctx): """Inject overflow arguments into context state. :param click.core.Context ctx: Click context. :return: super() return value. """ if self.overflow: ctx.ensure_object(Config).update(dict(overflow=self.overflow)) return super(ClickGroup, self).invoke(ctx)
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Inject overflow arguments into context state. :param click.core.Context ctx: Click context. :return: super() return value.
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python
train
lreis2415/PyGeoC
pygeoc/vector.py
https://github.com/lreis2415/PyGeoC/blob/9a92d1a229bb74298e3c57f27c97079980b5f729/pygeoc/vector.py#L94-L117
def write_line_shp(line_list, out_shp): """Export ESRI Shapefile -- Line feature""" print('Write line shapefile: %s' % out_shp) driver = ogr_GetDriverByName(str('ESRI Shapefile')) if driver is None: print('ESRI Shapefile driver not available.') sys.exit(1) if os.path.exists(out_shp): driver.DeleteDataSource(out_shp) ds = driver.CreateDataSource(out_shp.rpartition(os.sep)[0]) if ds is None: print('ERROR Output: Creation of output file failed.') sys.exit(1) lyr = ds.CreateLayer(str(out_shp.rpartition(os.sep)[2].split('.')[0]), None, wkbLineString) for l in line_list: line = ogr_Geometry(wkbLineString) for i in l: line.AddPoint(i[0], i[1]) templine = ogr_CreateGeometryFromJson(line.ExportToJson()) feature = ogr_Feature(lyr.GetLayerDefn()) feature.SetGeometry(templine) lyr.CreateFeature(feature) feature.Destroy() ds.Destroy()
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Export ESRI Shapefile -- Line feature
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python
train
spdx/tools-python
spdx/parsers/tagvalue.py
https://github.com/spdx/tools-python/blob/301d72f6ae57c832c1da7f6402fa49b192de6810/spdx/parsers/tagvalue.py#L400-L409
def p_file_contrib_1(self, p): """file_contrib : FILE_CONTRIB LINE""" try: if six.PY2: value = p[2].decode(encoding='utf-8') else: value = p[2] self.builder.add_file_contribution(self.document, value) except OrderError: self.order_error('FileContributor', 'FileName', p.lineno(1))
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file_contrib : FILE_CONTRIB LINE
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python
valid
quantopian/alphalens
alphalens/utils.py
https://github.com/quantopian/alphalens/blob/d43eac871bb061e956df936794d3dd514da99e44/alphalens/utils.py#L830-L853
def std_conversion(period_std, base_period): """ one_period_len standard deviation (or standard error) approximation Parameters ---------- period_std: pd.DataFrame DataFrame containing standard deviation or standard error values with column headings representing the return period. base_period: string The base period length used in the conversion It must follow pandas.Timedelta constructor format (e.g. '1 days', '1D', '30m', '3h', '1D1h', etc) Returns ------- pd.DataFrame DataFrame in same format as input but with one-period standard deviation/error values. """ period_len = period_std.name conversion_factor = (pd.Timedelta(period_len) / pd.Timedelta(base_period)) return period_std / np.sqrt(conversion_factor)
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one_period_len standard deviation (or standard error) approximation Parameters ---------- period_std: pd.DataFrame DataFrame containing standard deviation or standard error values with column headings representing the return period. base_period: string The base period length used in the conversion It must follow pandas.Timedelta constructor format (e.g. '1 days', '1D', '30m', '3h', '1D1h', etc) Returns ------- pd.DataFrame DataFrame in same format as input but with one-period standard deviation/error values.
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python
train
breuleux/hrepr
hrepr/__init__.py
https://github.com/breuleux/hrepr/blob/a411395d31ac7c8c071d174e63a093751aa5997b/hrepr/__init__.py#L236-L256
def stdrepr_short(self, obj, *, cls=None, tag='span'): """ Standard short representation for objects, used for objects at a depth that exceeds ``hrepr_object.config.max_depth``. That representation is just the object's type between ``<>``s, e.g. ``<MyClass>``. This behavior can be overriden with a ``__hrepr_short__`` method on the object, or an entry in ``hrepr_object.type_handlers_short``. Args: obj: The object to represent. cls (optional): The class name for the representation. If None, stdrepr will use ``'hrepr-' + obj.__class__.___name__`` tag (optional): The tag for the representation, defaults to 'span'. """ cls_name = obj.__class__.__name__ if cls is None: cls = f'hrepr-short-{cls_name}' return getattr(self.H, tag)[cls](f'<{cls_name}>')
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Standard short representation for objects, used for objects at a depth that exceeds ``hrepr_object.config.max_depth``. That representation is just the object's type between ``<>``s, e.g. ``<MyClass>``. This behavior can be overriden with a ``__hrepr_short__`` method on the object, or an entry in ``hrepr_object.type_handlers_short``. Args: obj: The object to represent. cls (optional): The class name for the representation. If None, stdrepr will use ``'hrepr-' + obj.__class__.___name__`` tag (optional): The tag for the representation, defaults to 'span'.
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python
train
angr/angr
angr/calling_conventions.py
https://github.com/angr/angr/blob/4e2f97d56af5419ee73bdb30482c8dd8ff5f3e40/angr/calling_conventions.py#L667-L687
def get_return_val(self, state, is_fp=None, size=None, stack_base=None): """ Get the return value out of the given state """ ty = self.func_ty.returnty if self.func_ty is not None else None if self.ret_val is not None: loc = self.ret_val elif is_fp is not None: loc = self.FP_RETURN_VAL if is_fp else self.RETURN_VAL elif ty is not None: loc = self.FP_RETURN_VAL if isinstance(ty, SimTypeFloat) else self.RETURN_VAL else: loc = self.RETURN_VAL if loc is None: raise NotImplementedError("This SimCC doesn't know how to get this value - should be implemented") val = loc.get_value(state, stack_base=stack_base, size=None if ty is None else ty.size//state.arch.byte_width) if self.is_fp_arg(loc) or self.is_fp_value(val) or isinstance(ty, SimTypeFloat): val = val.raw_to_fp() return val
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Get the return value out of the given state
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python
train
hyperledger/indy-plenum
plenum/server/catchup/catchup_rep_service.py
https://github.com/hyperledger/indy-plenum/blob/dcd144e238af7f17a869ffc9412f13dc488b7020/plenum/server/catchup/catchup_rep_service.py#L374-L425
def _has_valid_catchup_replies(self, seq_no: int, txns_to_process: List[Tuple[int, Any]]) -> Tuple[bool, str, int]: """ Transforms transactions for ledger! Returns: Whether catchup reply corresponding to seq_no Name of node from which txns came Number of transactions ready to be processed """ # TODO: Remove after stop passing seqNo here assert seq_no == txns_to_process[0][0] # Here seqNo has to be the seqNo of first transaction of # `catchupReplies` # Get the transactions in the catchup reply which has sequence # number `seqNo` node_name, catchup_rep = self._find_catchup_reply_for_seq_no(seq_no) txns = catchup_rep.txns # Add only those transaction in the temporary tree from the above # batch which are not present in the ledger # Integer keys being converted to strings when marshaled to JSON txns = [self._provider.transform_txn_for_ledger(txn) for s, txn in txns_to_process[:len(txns)] if str(s) in txns] # Creating a temporary tree which will be used to verify consistency # proof, by inserting transactions. Duplicating a merkle tree is not # expensive since we are using a compact merkle tree. temp_tree = self._ledger.treeWithAppliedTxns(txns) proof = catchup_rep.consProof final_size = self._catchup_till.final_size final_hash = self._catchup_till.final_hash try: logger.info("{} verifying proof for {}, {}, {}, {}, {}". format(self, temp_tree.tree_size, final_size, temp_tree.root_hash, final_hash, proof)) verified = self._provider.verifier(self._ledger_id).verify_tree_consistency( temp_tree.tree_size, final_size, temp_tree.root_hash, Ledger.strToHash(final_hash), [Ledger.strToHash(p) for p in proof] ) except Exception as ex: logger.info("{} could not verify catchup reply {} since {}".format(self, catchup_rep, ex)) verified = False return bool(verified), node_name, len(txns)
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Transforms transactions for ledger! Returns: Whether catchup reply corresponding to seq_no Name of node from which txns came Number of transactions ready to be processed
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python
train
rande/python-simple-ioc
ioc/extra/tornado/router.py
https://github.com/rande/python-simple-ioc/blob/36ddf667c1213a07a53cd4cdd708d02494e5190b/ioc/extra/tornado/router.py#L32-L42
def generate_static(self, path): """ This method generates a valid path to the public folder of the running project """ if not path: return "" if path[0] == '/': return "%s?v=%s" % (path, self.version) return "%s/%s?v=%s" % (self.static, path, self.version)
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This method generates a valid path to the public folder of the running project
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python
train
saltstack/salt
salt/modules/netbox.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/netbox.py#L644-L697
def openconfig_lacp(device_name=None): ''' .. versionadded:: 2019.2.0 Return a dictionary structured as standardised in the `openconfig-lacp <http://ops.openconfig.net/branches/master/openconfig-lacp.html>`_ YANG model, with configuration data for Link Aggregation Control Protocol (LACP) for aggregate interfaces. .. note:: The ``interval`` and ``lacp_mode`` keys have the values set as ``SLOW`` and ``ACTIVE`` respectively, as this data is not currently available in Netbox, therefore defaulting to the values defined in the standard. See `interval <http://ops.openconfig.net/branches/master/docs/openconfig-lacp.html#lacp-interfaces-interface-config-interval>`_ and `lacp-mode <http://ops.openconfig.net/branches/master/docs/openconfig-lacp.html#lacp-interfaces-interface-config-lacp-mode>`_ for further details. device_name: ``None`` The name of the device to query the LACP information for. If not provided, will use the Minion ID. CLI Example: .. code-block:: bash salt '*' netbox.openconfig_lacp salt '*' netbox.openconfig_lacp device_name=cr1.thn.lon ''' oc_lacp = {} interfaces = get_interfaces(device_name=device_name) for interface in interfaces: if not interface['lag']: continue if_name, if_unit = _if_name_unit(interface['name']) parent_if = interface['lag']['name'] if parent_if not in oc_lacp: oc_lacp[parent_if] = { 'config': { 'name': parent_if, 'interval': 'SLOW', 'lacp_mode': 'ACTIVE' }, 'members': { 'member': {} } } oc_lacp[parent_if]['members']['member'][if_name] = {} return { 'lacp': { 'interfaces': { 'interface': oc_lacp } } }
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.. versionadded:: 2019.2.0 Return a dictionary structured as standardised in the `openconfig-lacp <http://ops.openconfig.net/branches/master/openconfig-lacp.html>`_ YANG model, with configuration data for Link Aggregation Control Protocol (LACP) for aggregate interfaces. .. note:: The ``interval`` and ``lacp_mode`` keys have the values set as ``SLOW`` and ``ACTIVE`` respectively, as this data is not currently available in Netbox, therefore defaulting to the values defined in the standard. See `interval <http://ops.openconfig.net/branches/master/docs/openconfig-lacp.html#lacp-interfaces-interface-config-interval>`_ and `lacp-mode <http://ops.openconfig.net/branches/master/docs/openconfig-lacp.html#lacp-interfaces-interface-config-lacp-mode>`_ for further details. device_name: ``None`` The name of the device to query the LACP information for. If not provided, will use the Minion ID. CLI Example: .. code-block:: bash salt '*' netbox.openconfig_lacp salt '*' netbox.openconfig_lacp device_name=cr1.thn.lon
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python
train
Devoxin/Lavalink.py
lavalink/PlayerManager.py
https://github.com/Devoxin/Lavalink.py/blob/63f55c3d726d24c4cfd3674d3cd6aab6f5be110d/lavalink/PlayerManager.py#L55-L60
def connected_channel(self): """ Returns the voice channel the player is connected to. """ if not self.channel_id: return None return self._lavalink.bot.get_channel(int(self.channel_id))
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Returns the voice channel the player is connected to.
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python
valid
rochacbruno/manage
manage/commands_collector.py
https://github.com/rochacbruno/manage/blob/e904c451862f036f4be8723df5704a9844103c74/manage/commands_collector.py#L10-L27
def add_click_commands(module, cli, command_dict, namespaced): """Loads all click commands""" module_commands = [ item for item in getmembers(module) if isinstance(item[1], BaseCommand) ] options = command_dict.get('config', {}) namespace = command_dict.get('namespace') for name, function in module_commands: f_options = options.get(name, {}) command_name = f_options.get('name', getattr(function, 'name', name)) if namespace: command_name = '{}_{}'.format(namespace, command_name) elif namespaced: module_namespace = module.__name__.split('.')[-1] command_name = '{}_{}'.format(module_namespace, command_name) function.short_help = f_options.get('help_text', function.short_help) cli.add_command(function, name=command_name)
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Loads all click commands
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python
train
saltstack/salt
salt/utils/profile.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/profile.py#L30-L47
def profile_func(filename=None): ''' Decorator for adding profiling to a nested function in Salt ''' def proffunc(fun): def profiled_func(*args, **kwargs): logging.info('Profiling function %s', fun.__name__) try: profiler = cProfile.Profile() retval = profiler.runcall(fun, *args, **kwargs) profiler.dump_stats((filename or '{0}_func.profile' .format(fun.__name__))) except IOError: logging.exception('Could not open profile file %s', filename) return retval return profiled_func return proffunc
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Decorator for adding profiling to a nested function in Salt
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python
train
CartoDB/cartoframes
cartoframes/utils.py
https://github.com/CartoDB/cartoframes/blob/c94238a545f3dec45963dac3892540942b6f0df8/cartoframes/utils.py#L60-L67
def safe_quotes(text, escape_single_quotes=False): """htmlify string""" if isinstance(text, str): safe_text = text.replace('"', "&quot;") if escape_single_quotes: safe_text = safe_text.replace("'", "&#92;'") return safe_text.replace('True', 'true') return text
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htmlify string
[ "htmlify", "string" ]
python
train
tensorflow/cleverhans
examples/multigpu_advtrain/evaluator.py
https://github.com/tensorflow/cleverhans/blob/97488e215760547b81afc53f5e5de8ba7da5bd98/examples/multigpu_advtrain/evaluator.py#L138-L159
def eval_advs(self, x, y, preds_adv, X_test, Y_test, att_type): """ Evaluate the accuracy of the model on adversarial examples :param x: symbolic input to model. :param y: symbolic variable for the label. :param preds_adv: symbolic variable for the prediction on an adversarial example. :param X_test: NumPy array of test set inputs. :param Y_test: NumPy array of test set labels. :param att_type: name of the attack. """ end = (len(X_test) // self.batch_size) * self.batch_size if self.hparams.fast_tests: end = 10*self.batch_size acc = model_eval(self.sess, x, y, preds_adv, X_test[:end], Y_test[:end], args=self.eval_params) self.log_value('test_accuracy_%s' % att_type, acc, 'Test accuracy on adversarial examples') return acc
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Evaluate the accuracy of the model on adversarial examples :param x: symbolic input to model. :param y: symbolic variable for the label. :param preds_adv: symbolic variable for the prediction on an adversarial example. :param X_test: NumPy array of test set inputs. :param Y_test: NumPy array of test set labels. :param att_type: name of the attack.
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python
train
what-studio/profiling
profiling/tracing/__init__.py
https://github.com/what-studio/profiling/blob/49666ba3ea295eb73782ae6c18a4ec7929d7d8b7/profiling/tracing/__init__.py#L116-L124
def record_leaving(self, time, code, frame_key, parent_stats): """Left from a function call.""" try: stats = parent_stats.get_child(code) time_entered = self._times_entered.pop((code, frame_key)) except KeyError: return time_elapsed = time - time_entered stats.deep_time += max(0, time_elapsed)
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Left from a function call.
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python
train
wavycloud/pyboto3
pyboto3/mturk.py
https://github.com/wavycloud/pyboto3/blob/924957ccf994303713a4eed90b775ff2ab95b2e5/pyboto3/mturk.py#L195-L442
def create_hit(MaxAssignments=None, AutoApprovalDelayInSeconds=None, LifetimeInSeconds=None, AssignmentDurationInSeconds=None, Reward=None, Title=None, Keywords=None, Description=None, Question=None, RequesterAnnotation=None, QualificationRequirements=None, UniqueRequestToken=None, AssignmentReviewPolicy=None, HITReviewPolicy=None, HITLayoutId=None, HITLayoutParameters=None): """ The CreateHIT operation creates a new Human Intelligence Task (HIT). The new HIT is made available for Workers to find and accept on the Amazon Mechanical Turk website. This operation allows you to specify a new HIT by passing in values for the properties of the HIT, such as its title, reward amount and number of assignments. When you pass these values to CreateHIT , a new HIT is created for you, with a new HITTypeID . The HITTypeID can be used to create additional HITs in the future without needing to specify common parameters such as the title, description and reward amount each time. An alternative way to create HITs is to first generate a HITTypeID using the CreateHITType operation and then call the CreateHITWithHITType operation. This is the recommended best practice for Requesters who are creating large numbers of HITs. CreateHIT also supports several ways to provide question data: by providing a value for the Question parameter that fully specifies the contents of the HIT, or by providing a HitLayoutId and associated HitLayoutParameters . See also: AWS API Documentation :example: response = client.create_hit( MaxAssignments=123, AutoApprovalDelayInSeconds=123, LifetimeInSeconds=123, AssignmentDurationInSeconds=123, Reward='string', Title='string', Keywords='string', Description='string', Question='string', RequesterAnnotation='string', QualificationRequirements=[ { 'QualificationTypeId': 'string', 'Comparator': 'LessThan'|'LessThanOrEqualTo'|'GreaterThan'|'GreaterThanOrEqualTo'|'EqualTo'|'NotEqualTo'|'Exists'|'DoesNotExist'|'In'|'NotIn', 'IntegerValues': [ 123, ], 'LocaleValues': [ { 'Country': 'string', 'Subdivision': 'string' }, ], 'RequiredToPreview': True|False }, ], UniqueRequestToken='string', AssignmentReviewPolicy={ 'PolicyName': 'string', 'Parameters': [ { 'Key': 'string', 'Values': [ 'string', ], 'MapEntries': [ { 'Key': 'string', 'Values': [ 'string', ] }, ] }, ] }, HITReviewPolicy={ 'PolicyName': 'string', 'Parameters': [ { 'Key': 'string', 'Values': [ 'string', ], 'MapEntries': [ { 'Key': 'string', 'Values': [ 'string', ] }, ] }, ] }, HITLayoutId='string', HITLayoutParameters=[ { 'Name': 'string', 'Value': 'string' }, ] ) :type MaxAssignments: integer :param MaxAssignments: The number of times the HIT can be accepted and completed before the HIT becomes unavailable. :type AutoApprovalDelayInSeconds: integer :param AutoApprovalDelayInSeconds: The number of seconds after an assignment for the HIT has been submitted, after which the assignment is considered Approved automatically unless the Requester explicitly rejects it. :type LifetimeInSeconds: integer :param LifetimeInSeconds: [REQUIRED] An amount of time, in seconds, after which the HIT is no longer available for users to accept. After the lifetime of the HIT elapses, the HIT no longer appears in HIT searches, even if not all of the assignments for the HIT have been accepted. :type AssignmentDurationInSeconds: integer :param AssignmentDurationInSeconds: [REQUIRED] The amount of time, in seconds, that a Worker has to complete the HIT after accepting it. If a Worker does not complete the assignment within the specified duration, the assignment is considered abandoned. If the HIT is still active (that is, its lifetime has not elapsed), the assignment becomes available for other users to find and accept. :type Reward: string :param Reward: [REQUIRED] The amount of money the Requester will pay a Worker for successfully completing the HIT. :type Title: string :param Title: [REQUIRED] The title of the HIT. A title should be short and descriptive about the kind of task the HIT contains. On the Amazon Mechanical Turk web site, the HIT title appears in search results, and everywhere the HIT is mentioned. :type Keywords: string :param Keywords: One or more words or phrases that describe the HIT, separated by commas. These words are used in searches to find HITs. :type Description: string :param Description: [REQUIRED] A general description of the HIT. A description includes detailed information about the kind of task the HIT contains. On the Amazon Mechanical Turk web site, the HIT description appears in the expanded view of search results, and in the HIT and assignment screens. A good description gives the user enough information to evaluate the HIT before accepting it. :type Question: string :param Question: The data the person completing the HIT uses to produce the results. Constraints: Must be a QuestionForm data structure, an ExternalQuestion data structure, or an HTMLQuestion data structure. The XML question data must not be larger than 64 kilobytes (65,535 bytes) in size, including whitespace. Either a Question parameter or a HITLayoutId parameter must be provided. :type RequesterAnnotation: string :param RequesterAnnotation: An arbitrary data field. The RequesterAnnotation parameter lets your application attach arbitrary data to the HIT for tracking purposes. For example, this parameter could be an identifier internal to the Requester's application that corresponds with the HIT. The RequesterAnnotation parameter for a HIT is only visible to the Requester who created the HIT. It is not shown to the Worker, or any other Requester. The RequesterAnnotation parameter may be different for each HIT you submit. It does not affect how your HITs are grouped. :type QualificationRequirements: list :param QualificationRequirements: A condition that a Worker's Qualifications must meet before the Worker is allowed to accept and complete the HIT. (dict) --The QualificationRequirement data structure describes a Qualification that a Worker must have before the Worker is allowed to accept a HIT. A requirement may optionally state that a Worker must have the Qualification in order to preview the HIT. QualificationTypeId (string) -- [REQUIRED]The ID of the Qualification type for the requirement. Comparator (string) -- [REQUIRED]The kind of comparison to make against a Qualification's value. You can compare a Qualification's value to an IntegerValue to see if it is LessThan, LessThanOrEqualTo, GreaterThan, GreaterThanOrEqualTo, EqualTo, or NotEqualTo the IntegerValue. You can compare it to a LocaleValue to see if it is EqualTo, or NotEqualTo the LocaleValue. You can check to see if the value is In or NotIn a set of IntegerValue or LocaleValue values. Lastly, a Qualification requirement can also test if a Qualification Exists or DoesNotExist in the user's profile, regardless of its value. IntegerValues (list) --The integer value to compare against the Qualification's value. IntegerValue must not be present if Comparator is Exists or DoesNotExist. IntegerValue can only be used if the Qualification type has an integer value; it cannot be used with the Worker_Locale QualificationType ID. When performing a set comparison by using the In or the NotIn comparator, you can use up to 15 IntegerValue elements in a QualificationRequirement data structure. (integer) -- LocaleValues (list) --The locale value to compare against the Qualification's value. The local value must be a valid ISO 3166 country code or supports ISO 3166-2 subdivisions. LocaleValue can only be used with a Worker_Locale QualificationType ID. LocaleValue can only be used with the EqualTo, NotEqualTo, In, and NotIn comparators. You must only use a single LocaleValue element when using the EqualTo or NotEqualTo comparators. When performing a set comparison by using the In or the NotIn comparator, you can use up to 30 LocaleValue elements in a QualificationRequirement data structure. (dict) --The Locale data structure represents a geographical region or location. Country (string) -- [REQUIRED]The country of the locale. Must be a valid ISO 3166 country code. For example, the code US refers to the United States of America. Subdivision (string) --The state or subdivision of the locale. A valid ISO 3166-2 subdivision code. For example, the code WA refers to the state of Washington. RequiredToPreview (boolean) --If true, the question data for the HIT will not be shown when a Worker whose Qualifications do not meet this requirement tries to preview the HIT. That is, a Worker's Qualifications must meet all of the requirements for which RequiredToPreview is true in order to preview the HIT. If a Worker meets all of the requirements where RequiredToPreview is true (or if there are no such requirements), but does not meet all of the requirements for the HIT, the Worker will be allowed to preview the HIT's question data, but will not be allowed to accept and complete the HIT. The default is false. :type UniqueRequestToken: string :param UniqueRequestToken: A unique identifier for this request which allows you to retry the call on error without creating duplicate HITs. This is useful in cases such as network timeouts where it is unclear whether or not the call succeeded on the server. If the HIT already exists in the system from a previous call using the same UniqueRequestToken, subsequent calls will return a AWS.MechanicalTurk.HitAlreadyExists error with a message containing the HITId. Note Note: It is your responsibility to ensure uniqueness of the token. The unique token expires after 24 hours. Subsequent calls using the same UniqueRequestToken made after the 24 hour limit could create duplicate HITs. :type AssignmentReviewPolicy: dict :param AssignmentReviewPolicy: The Assignment-level Review Policy applies to the assignments under the HIT. You can specify for Mechanical Turk to take various actions based on the policy. PolicyName (string) --Name of a Review Policy: SimplePlurality/2011-09-01 or ScoreMyKnownAnswers/2011-09-01 Parameters (list) --Name of the parameter from the Review policy. (dict) --Name of the parameter from the Review policy. Key (string) --Name of the parameter from the list of Review Polices. Values (list) --The list of values of the Parameter (string) -- MapEntries (list) --List of ParameterMapEntry objects. (dict) --This data structure is the data type for the AnswerKey parameter of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Key (string) --The QuestionID from the HIT that is used to identify which question requires Mechanical Turk to score as part of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Values (list) --The list of answers to the question specified in the MapEntry Key element. The Worker must match all values in order for the answer to be scored correctly. (string) -- :type HITReviewPolicy: dict :param HITReviewPolicy: The HIT-level Review Policy applies to the HIT. You can specify for Mechanical Turk to take various actions based on the policy. PolicyName (string) --Name of a Review Policy: SimplePlurality/2011-09-01 or ScoreMyKnownAnswers/2011-09-01 Parameters (list) --Name of the parameter from the Review policy. (dict) --Name of the parameter from the Review policy. Key (string) --Name of the parameter from the list of Review Polices. Values (list) --The list of values of the Parameter (string) -- MapEntries (list) --List of ParameterMapEntry objects. (dict) --This data structure is the data type for the AnswerKey parameter of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Key (string) --The QuestionID from the HIT that is used to identify which question requires Mechanical Turk to score as part of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Values (list) --The list of answers to the question specified in the MapEntry Key element. The Worker must match all values in order for the answer to be scored correctly. (string) -- :type HITLayoutId: string :param HITLayoutId: The HITLayoutId allows you to use a pre-existing HIT design with placeholder values and create an additional HIT by providing those values as HITLayoutParameters. Constraints: Either a Question parameter or a HITLayoutId parameter must be provided. :type HITLayoutParameters: list :param HITLayoutParameters: If the HITLayoutId is provided, any placeholder values must be filled in with values using the HITLayoutParameter structure. For more information, see HITLayout. (dict) --The HITLayoutParameter data structure defines parameter values used with a HITLayout. A HITLayout is a reusable Amazon Mechanical Turk project template used to provide Human Intelligence Task (HIT) question data for CreateHIT. Name (string) --The name of the parameter in the HITLayout. Value (string) --The value substituted for the parameter referenced in the HITLayout. :rtype: dict :return: { 'HIT': { 'HITId': 'string', 'HITTypeId': 'string', 'HITGroupId': 'string', 'HITLayoutId': 'string', 'CreationTime': datetime(2015, 1, 1), 'Title': 'string', 'Description': 'string', 'Question': 'string', 'Keywords': 'string', 'HITStatus': 'Assignable'|'Unassignable'|'Reviewable'|'Reviewing'|'Disposed', 'MaxAssignments': 123, 'Reward': 'string', 'AutoApprovalDelayInSeconds': 123, 'Expiration': datetime(2015, 1, 1), 'AssignmentDurationInSeconds': 123, 'RequesterAnnotation': 'string', 'QualificationRequirements': [ { 'QualificationTypeId': 'string', 'Comparator': 'LessThan'|'LessThanOrEqualTo'|'GreaterThan'|'GreaterThanOrEqualTo'|'EqualTo'|'NotEqualTo'|'Exists'|'DoesNotExist'|'In'|'NotIn', 'IntegerValues': [ 123, ], 'LocaleValues': [ { 'Country': 'string', 'Subdivision': 'string' }, ], 'RequiredToPreview': True|False }, ], 'HITReviewStatus': 'NotReviewed'|'MarkedForReview'|'ReviewedAppropriate'|'ReviewedInappropriate', 'NumberOfAssignmentsPending': 123, 'NumberOfAssignmentsAvailable': 123, 'NumberOfAssignmentsCompleted': 123 } } :returns: (integer) -- """ pass
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The CreateHIT operation creates a new Human Intelligence Task (HIT). The new HIT is made available for Workers to find and accept on the Amazon Mechanical Turk website. This operation allows you to specify a new HIT by passing in values for the properties of the HIT, such as its title, reward amount and number of assignments. When you pass these values to CreateHIT , a new HIT is created for you, with a new HITTypeID . The HITTypeID can be used to create additional HITs in the future without needing to specify common parameters such as the title, description and reward amount each time. An alternative way to create HITs is to first generate a HITTypeID using the CreateHITType operation and then call the CreateHITWithHITType operation. This is the recommended best practice for Requesters who are creating large numbers of HITs. CreateHIT also supports several ways to provide question data: by providing a value for the Question parameter that fully specifies the contents of the HIT, or by providing a HitLayoutId and associated HitLayoutParameters . See also: AWS API Documentation :example: response = client.create_hit( MaxAssignments=123, AutoApprovalDelayInSeconds=123, LifetimeInSeconds=123, AssignmentDurationInSeconds=123, Reward='string', Title='string', Keywords='string', Description='string', Question='string', RequesterAnnotation='string', QualificationRequirements=[ { 'QualificationTypeId': 'string', 'Comparator': 'LessThan'|'LessThanOrEqualTo'|'GreaterThan'|'GreaterThanOrEqualTo'|'EqualTo'|'NotEqualTo'|'Exists'|'DoesNotExist'|'In'|'NotIn', 'IntegerValues': [ 123, ], 'LocaleValues': [ { 'Country': 'string', 'Subdivision': 'string' }, ], 'RequiredToPreview': True|False }, ], UniqueRequestToken='string', AssignmentReviewPolicy={ 'PolicyName': 'string', 'Parameters': [ { 'Key': 'string', 'Values': [ 'string', ], 'MapEntries': [ { 'Key': 'string', 'Values': [ 'string', ] }, ] }, ] }, HITReviewPolicy={ 'PolicyName': 'string', 'Parameters': [ { 'Key': 'string', 'Values': [ 'string', ], 'MapEntries': [ { 'Key': 'string', 'Values': [ 'string', ] }, ] }, ] }, HITLayoutId='string', HITLayoutParameters=[ { 'Name': 'string', 'Value': 'string' }, ] ) :type MaxAssignments: integer :param MaxAssignments: The number of times the HIT can be accepted and completed before the HIT becomes unavailable. :type AutoApprovalDelayInSeconds: integer :param AutoApprovalDelayInSeconds: The number of seconds after an assignment for the HIT has been submitted, after which the assignment is considered Approved automatically unless the Requester explicitly rejects it. :type LifetimeInSeconds: integer :param LifetimeInSeconds: [REQUIRED] An amount of time, in seconds, after which the HIT is no longer available for users to accept. After the lifetime of the HIT elapses, the HIT no longer appears in HIT searches, even if not all of the assignments for the HIT have been accepted. :type AssignmentDurationInSeconds: integer :param AssignmentDurationInSeconds: [REQUIRED] The amount of time, in seconds, that a Worker has to complete the HIT after accepting it. If a Worker does not complete the assignment within the specified duration, the assignment is considered abandoned. If the HIT is still active (that is, its lifetime has not elapsed), the assignment becomes available for other users to find and accept. :type Reward: string :param Reward: [REQUIRED] The amount of money the Requester will pay a Worker for successfully completing the HIT. :type Title: string :param Title: [REQUIRED] The title of the HIT. A title should be short and descriptive about the kind of task the HIT contains. On the Amazon Mechanical Turk web site, the HIT title appears in search results, and everywhere the HIT is mentioned. :type Keywords: string :param Keywords: One or more words or phrases that describe the HIT, separated by commas. These words are used in searches to find HITs. :type Description: string :param Description: [REQUIRED] A general description of the HIT. A description includes detailed information about the kind of task the HIT contains. On the Amazon Mechanical Turk web site, the HIT description appears in the expanded view of search results, and in the HIT and assignment screens. A good description gives the user enough information to evaluate the HIT before accepting it. :type Question: string :param Question: The data the person completing the HIT uses to produce the results. Constraints: Must be a QuestionForm data structure, an ExternalQuestion data structure, or an HTMLQuestion data structure. The XML question data must not be larger than 64 kilobytes (65,535 bytes) in size, including whitespace. Either a Question parameter or a HITLayoutId parameter must be provided. :type RequesterAnnotation: string :param RequesterAnnotation: An arbitrary data field. The RequesterAnnotation parameter lets your application attach arbitrary data to the HIT for tracking purposes. For example, this parameter could be an identifier internal to the Requester's application that corresponds with the HIT. The RequesterAnnotation parameter for a HIT is only visible to the Requester who created the HIT. It is not shown to the Worker, or any other Requester. The RequesterAnnotation parameter may be different for each HIT you submit. It does not affect how your HITs are grouped. :type QualificationRequirements: list :param QualificationRequirements: A condition that a Worker's Qualifications must meet before the Worker is allowed to accept and complete the HIT. (dict) --The QualificationRequirement data structure describes a Qualification that a Worker must have before the Worker is allowed to accept a HIT. A requirement may optionally state that a Worker must have the Qualification in order to preview the HIT. QualificationTypeId (string) -- [REQUIRED]The ID of the Qualification type for the requirement. Comparator (string) -- [REQUIRED]The kind of comparison to make against a Qualification's value. You can compare a Qualification's value to an IntegerValue to see if it is LessThan, LessThanOrEqualTo, GreaterThan, GreaterThanOrEqualTo, EqualTo, or NotEqualTo the IntegerValue. You can compare it to a LocaleValue to see if it is EqualTo, or NotEqualTo the LocaleValue. You can check to see if the value is In or NotIn a set of IntegerValue or LocaleValue values. Lastly, a Qualification requirement can also test if a Qualification Exists or DoesNotExist in the user's profile, regardless of its value. IntegerValues (list) --The integer value to compare against the Qualification's value. IntegerValue must not be present if Comparator is Exists or DoesNotExist. IntegerValue can only be used if the Qualification type has an integer value; it cannot be used with the Worker_Locale QualificationType ID. When performing a set comparison by using the In or the NotIn comparator, you can use up to 15 IntegerValue elements in a QualificationRequirement data structure. (integer) -- LocaleValues (list) --The locale value to compare against the Qualification's value. The local value must be a valid ISO 3166 country code or supports ISO 3166-2 subdivisions. LocaleValue can only be used with a Worker_Locale QualificationType ID. LocaleValue can only be used with the EqualTo, NotEqualTo, In, and NotIn comparators. You must only use a single LocaleValue element when using the EqualTo or NotEqualTo comparators. When performing a set comparison by using the In or the NotIn comparator, you can use up to 30 LocaleValue elements in a QualificationRequirement data structure. (dict) --The Locale data structure represents a geographical region or location. Country (string) -- [REQUIRED]The country of the locale. Must be a valid ISO 3166 country code. For example, the code US refers to the United States of America. Subdivision (string) --The state or subdivision of the locale. A valid ISO 3166-2 subdivision code. For example, the code WA refers to the state of Washington. RequiredToPreview (boolean) --If true, the question data for the HIT will not be shown when a Worker whose Qualifications do not meet this requirement tries to preview the HIT. That is, a Worker's Qualifications must meet all of the requirements for which RequiredToPreview is true in order to preview the HIT. If a Worker meets all of the requirements where RequiredToPreview is true (or if there are no such requirements), but does not meet all of the requirements for the HIT, the Worker will be allowed to preview the HIT's question data, but will not be allowed to accept and complete the HIT. The default is false. :type UniqueRequestToken: string :param UniqueRequestToken: A unique identifier for this request which allows you to retry the call on error without creating duplicate HITs. This is useful in cases such as network timeouts where it is unclear whether or not the call succeeded on the server. If the HIT already exists in the system from a previous call using the same UniqueRequestToken, subsequent calls will return a AWS.MechanicalTurk.HitAlreadyExists error with a message containing the HITId. Note Note: It is your responsibility to ensure uniqueness of the token. The unique token expires after 24 hours. Subsequent calls using the same UniqueRequestToken made after the 24 hour limit could create duplicate HITs. :type AssignmentReviewPolicy: dict :param AssignmentReviewPolicy: The Assignment-level Review Policy applies to the assignments under the HIT. You can specify for Mechanical Turk to take various actions based on the policy. PolicyName (string) --Name of a Review Policy: SimplePlurality/2011-09-01 or ScoreMyKnownAnswers/2011-09-01 Parameters (list) --Name of the parameter from the Review policy. (dict) --Name of the parameter from the Review policy. Key (string) --Name of the parameter from the list of Review Polices. Values (list) --The list of values of the Parameter (string) -- MapEntries (list) --List of ParameterMapEntry objects. (dict) --This data structure is the data type for the AnswerKey parameter of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Key (string) --The QuestionID from the HIT that is used to identify which question requires Mechanical Turk to score as part of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Values (list) --The list of answers to the question specified in the MapEntry Key element. The Worker must match all values in order for the answer to be scored correctly. (string) -- :type HITReviewPolicy: dict :param HITReviewPolicy: The HIT-level Review Policy applies to the HIT. You can specify for Mechanical Turk to take various actions based on the policy. PolicyName (string) --Name of a Review Policy: SimplePlurality/2011-09-01 or ScoreMyKnownAnswers/2011-09-01 Parameters (list) --Name of the parameter from the Review policy. (dict) --Name of the parameter from the Review policy. Key (string) --Name of the parameter from the list of Review Polices. Values (list) --The list of values of the Parameter (string) -- MapEntries (list) --List of ParameterMapEntry objects. (dict) --This data structure is the data type for the AnswerKey parameter of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Key (string) --The QuestionID from the HIT that is used to identify which question requires Mechanical Turk to score as part of the ScoreMyKnownAnswers/2011-09-01 Review Policy. Values (list) --The list of answers to the question specified in the MapEntry Key element. The Worker must match all values in order for the answer to be scored correctly. (string) -- :type HITLayoutId: string :param HITLayoutId: The HITLayoutId allows you to use a pre-existing HIT design with placeholder values and create an additional HIT by providing those values as HITLayoutParameters. Constraints: Either a Question parameter or a HITLayoutId parameter must be provided. :type HITLayoutParameters: list :param HITLayoutParameters: If the HITLayoutId is provided, any placeholder values must be filled in with values using the HITLayoutParameter structure. For more information, see HITLayout. (dict) --The HITLayoutParameter data structure defines parameter values used with a HITLayout. A HITLayout is a reusable Amazon Mechanical Turk project template used to provide Human Intelligence Task (HIT) question data for CreateHIT. Name (string) --The name of the parameter in the HITLayout. Value (string) --The value substituted for the parameter referenced in the HITLayout. :rtype: dict :return: { 'HIT': { 'HITId': 'string', 'HITTypeId': 'string', 'HITGroupId': 'string', 'HITLayoutId': 'string', 'CreationTime': datetime(2015, 1, 1), 'Title': 'string', 'Description': 'string', 'Question': 'string', 'Keywords': 'string', 'HITStatus': 'Assignable'|'Unassignable'|'Reviewable'|'Reviewing'|'Disposed', 'MaxAssignments': 123, 'Reward': 'string', 'AutoApprovalDelayInSeconds': 123, 'Expiration': datetime(2015, 1, 1), 'AssignmentDurationInSeconds': 123, 'RequesterAnnotation': 'string', 'QualificationRequirements': [ { 'QualificationTypeId': 'string', 'Comparator': 'LessThan'|'LessThanOrEqualTo'|'GreaterThan'|'GreaterThanOrEqualTo'|'EqualTo'|'NotEqualTo'|'Exists'|'DoesNotExist'|'In'|'NotIn', 'IntegerValues': [ 123, ], 'LocaleValues': [ { 'Country': 'string', 'Subdivision': 'string' }, ], 'RequiredToPreview': True|False }, ], 'HITReviewStatus': 'NotReviewed'|'MarkedForReview'|'ReviewedAppropriate'|'ReviewedInappropriate', 'NumberOfAssignmentsPending': 123, 'NumberOfAssignmentsAvailable': 123, 'NumberOfAssignmentsCompleted': 123 } } :returns: (integer) --
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python
train