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ownport/scrapy-dblite
dblite/__init__.py
https://github.com/ownport/scrapy-dblite/blob/6de5021caa31d439478d9808738b046d1db699c9/dblite/__init__.py#L318-L330
def delete(self, criteria=None, _all=False): ''' delete dictionary(ies) in sqlite database _all = True - delete all items ''' if isinstance(criteria, self._item_class): criteria = {'_id': criteria['_id']} if criteria is None and not _all: raise RuntimeError('Criteria is not defined') SQL = SQLBuilder(self._table, criteria).delete() self._cursor.execute(SQL)
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delete dictionary(ies) in sqlite database _all = True - delete all items
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python
train
pygeobuf/pygeobuf
geobuf/scripts/cli.py
https://github.com/pygeobuf/pygeobuf/blob/c9e055ab47532781626cfe2c931a8444820acf05/geobuf/scripts/cli.py#L46-L61
def encode(precision, with_z): """Given GeoJSON on stdin, writes a geobuf file to stdout.""" logger = logging.getLogger('geobuf') stdin = click.get_text_stream('stdin') sink = click.get_binary_stream('stdout') try: data = json.load(stdin) pbf = geobuf.encode( data, precision if precision >= 0 else 6, 3 if with_z else 2) sink.write(pbf) sys.exit(0) except Exception: logger.exception("Failed. Exception caught") sys.exit(1)
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Given GeoJSON on stdin, writes a geobuf file to stdout.
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python
train
saltstack/salt
salt/cloud/clouds/linode.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/cloud/clouds/linode.py#L1318-L1360
def show_pricing(kwargs=None, call=None): ''' Show pricing for a particular profile. This is only an estimate, based on unofficial pricing sources. .. versionadded:: 2015.8.0 CLI Example: .. code-block:: bash salt-cloud -f show_pricing my-linode-config profile=my-linode-profile ''' if call != 'function': raise SaltCloudException( 'The show_instance action must be called with -f or --function.' ) profile = __opts__['profiles'].get(kwargs['profile'], {}) if not profile: raise SaltCloudNotFound( 'The requested profile was not found.' ) # Make sure the profile belongs to Linode provider = profile.get('provider', '0:0') comps = provider.split(':') if len(comps) < 2 or comps[1] != 'linode': raise SaltCloudException( 'The requested profile does not belong to Linode.' ) plan_id = get_plan_id(kwargs={'label': profile['size']}) response = _query('avail', 'linodeplans', args={'PlanID': plan_id})['DATA'][0] ret = {} ret['per_hour'] = response['HOURLY'] ret['per_day'] = ret['per_hour'] * 24 ret['per_week'] = ret['per_day'] * 7 ret['per_month'] = response['PRICE'] ret['per_year'] = ret['per_month'] * 12 return {profile['profile']: ret}
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Show pricing for a particular profile. This is only an estimate, based on unofficial pricing sources. .. versionadded:: 2015.8.0 CLI Example: .. code-block:: bash salt-cloud -f show_pricing my-linode-config profile=my-linode-profile
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python
train
eleme/meepo
meepo/utils.py
https://github.com/eleme/meepo/blob/8212f0fe9b1d44be0c5de72d221a31c1d24bfe7a/meepo/utils.py#L57-L64
def cast_str(s, encoding='utf8', errors='strict'): """cast bytes or str to str""" if isinstance(s, bytes): return s.decode(encoding, errors) elif isinstance(s, str): return s else: raise TypeError("Expected unicode or bytes, got %r" % s)
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cast bytes or str to str
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python
train
bukun/TorCMS
torcms/core/tools.py
https://github.com/bukun/TorCMS/blob/6567c7fe2604a1d646d4570c017840958630ed2b/torcms/core/tools.py#L251-L288
def gen_pager_purecss(cat_slug, page_num, current): ''' Generate pager of purecss. ''' if page_num == 1: return '' pager_shouye = '''<li class="pure-menu-item {0}"> <a class="pure-menu-link" href="{1}">&lt;&lt; 首页</a></li>'''.format( 'hidden' if current <= 1 else '', cat_slug ) pager_pre = '''<li class="pure-menu-item {0}"> <a class="pure-menu-link" href="{1}/{2}">&lt; 前页</a> </li>'''.format('hidden' if current <= 1 else '', cat_slug, current - 1) pager_mid = '' for ind in range(0, page_num): tmp_mid = '''<li class="pure-menu-item {0}"> <a class="pure-menu-link" href="{1}/{2}">{2}</a></li> '''.format('selected' if ind + 1 == current else '', cat_slug, ind + 1) pager_mid += tmp_mid pager_next = '''<li class="pure-menu-item {0}"> <a class="pure-menu-link" href="{1}/{2}">后页 &gt;</a> </li> '''.format('hidden' if current >= page_num else '', cat_slug, current + 1) pager_last = '''<li class="pure-menu-item {0}"> <a hclass="pure-menu-link" ref="{1}/{2}">末页 &gt;&gt;</a> </li> '''.format('hidden' if current >= page_num else '', cat_slug, page_num) pager = pager_shouye + pager_pre + pager_mid + pager_next + pager_last return pager
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Generate pager of purecss.
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python
train
DataDog/integrations-core
kubernetes_state/datadog_checks/kubernetes_state/kubernetes_state.py
https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/kubernetes_state/datadog_checks/kubernetes_state/kubernetes_state.py#L666-L679
def count_objects_by_tags(self, metric, scraper_config): """ Count objects by whitelisted tags and submit counts as gauges. """ config = self.object_count_params[metric.name] metric_name = "{}.{}".format(scraper_config['namespace'], config['metric_name']) object_counter = Counter() for sample in metric.samples: tags = [ self._label_to_tag(l, sample[self.SAMPLE_LABELS], scraper_config) for l in config['allowed_labels'] ] + scraper_config['custom_tags'] object_counter[tuple(sorted(tags))] += sample[self.SAMPLE_VALUE] for tags, count in iteritems(object_counter): self.gauge(metric_name, count, tags=list(tags))
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Count objects by whitelisted tags and submit counts as gauges.
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python
train
pearu/pyvtk
pyvtk/common.py
https://github.com/pearu/pyvtk/blob/b004ec3c03299a2d75338a4be93dd29f076b70ab/pyvtk/common.py#L208-L233
def get_3_3_tuple(self,obj,default=None): """Return tuple of 3-tuples """ if is_sequence2(obj): ret = [] for i in range(3): if i<len(obj): ret.append(self.get_3_tuple(obj[i],default)) else: ret.append(self.get_3_tuple(default,default)) return tuple(ret) if is_sequence(obj): if len(obj)>9: log.warning('ignoring elements obj[i], i>=9') r = obj[:9] r = [self.get_3_tuple(r[j:j+3],default) for j in range(0,len(r),3)] if len(r)<3: log.warning('filling with default value (%s) to obtain size=3'%(default[0])) while len(r)<3: r.append(self.get_3_tuple(default,default)) return tuple(r) log.warning('filling with default value (%s) to obtain size=3'%(default[0])) r1 = self.get_3_tuple(obj,default) r2 = self.get_3_tuple(default,default) r3 = self.get_3_tuple(default,default) return (r1,r2,r3)
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Return tuple of 3-tuples
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python
train
has2k1/mizani
mizani/bounds.py
https://github.com/has2k1/mizani/blob/312d0550ee0136fd1b0384829b33f3b2065f47c8/mizani/bounds.py#L39-L70
def rescale(x, to=(0, 1), _from=None): """ Rescale numeric vector to have specified minimum and maximum. Parameters ---------- x : array_like | numeric 1D vector of values to manipulate. to : tuple output range (numeric vector of length two) _from : tuple input range (numeric vector of length two). If not given, is calculated from the range of x Returns ------- out : array_like Rescaled values Examples -------- >>> x = [0, 2, 4, 6, 8, 10] >>> rescale(x) array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]) >>> rescale(x, to=(0, 2)) array([0. , 0.4, 0.8, 1.2, 1.6, 2. ]) >>> rescale(x, to=(0, 2), _from=(0, 20)) array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]) """ if _from is None: _from = np.min(x), np.max(x) return np.interp(x, _from, to)
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Rescale numeric vector to have specified minimum and maximum. Parameters ---------- x : array_like | numeric 1D vector of values to manipulate. to : tuple output range (numeric vector of length two) _from : tuple input range (numeric vector of length two). If not given, is calculated from the range of x Returns ------- out : array_like Rescaled values Examples -------- >>> x = [0, 2, 4, 6, 8, 10] >>> rescale(x) array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]) >>> rescale(x, to=(0, 2)) array([0. , 0.4, 0.8, 1.2, 1.6, 2. ]) >>> rescale(x, to=(0, 2), _from=(0, 20)) array([0. , 0.2, 0.4, 0.6, 0.8, 1. ])
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python
valid
bcbio/bcbio-nextgen
bcbio/pipeline/qcsummary.py
https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/pipeline/qcsummary.py#L38-L58
def generate_parallel(samples, run_parallel): """Provide parallel preparation of summary information for alignment and variant calling. """ to_analyze, extras = _split_samples_by_qc(samples) qced = run_parallel("pipeline_summary", to_analyze) samples = _combine_qc_samples(qced) + extras qsign_info = run_parallel("qsignature_summary", [samples]) metadata_file = _merge_metadata([samples]) summary_file = write_project_summary(samples, qsign_info) out = [] for data in samples: if "summary" not in data[0]: data[0]["summary"] = {} data[0]["summary"]["project"] = summary_file data[0]["summary"]["metadata"] = metadata_file if qsign_info: data[0]["summary"]["mixup_check"] = qsign_info[0]["out_dir"] out.append(data) out = _add_researcher_summary(out, summary_file) # MultiQC must be run after all file outputs are set: return [[utils.to_single_data(d)] for d in run_parallel("multiqc_summary", [out])]
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Provide parallel preparation of summary information for alignment and variant calling.
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python
train
bronto/javasphinx
javasphinx/compiler.py
https://github.com/bronto/javasphinx/blob/cd1df27f1d70efaae079b74573efdd8e069ff02d/javasphinx/compiler.py#L95-L106
def __output_see(self, see): """ Convert the argument to a @see tag to rest """ if see.startswith('<a href'): # HTML link -- <a href="...">...</a> return self.__html_to_rst(see) elif '"' in see: # Plain text return see else: # Type reference (default) return ':java:ref:`%s`' % (see.replace('#', '.').replace(' ', ''),)
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Convert the argument to a @see tag to rest
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python
train
robehickman/simple-http-file-sync
shttpfs/crypto.py
https://github.com/robehickman/simple-http-file-sync/blob/fa29b3ee58e9504e1d3ddfc0c14047284bf9921d/shttpfs/crypto.py#L4-L10
def prompt_for_new_password(): """ Prompt the user to enter a new password, with confirmation """ while True: passw = getpass.getpass() passw2 = getpass.getpass() if passw == passw2: return passw print 'Passwords do not match'
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Prompt the user to enter a new password, with confirmation
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python
train
RudolfCardinal/pythonlib
cardinal_pythonlib/interval.py
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/interval.py#L925-L974
def subset(self, interval: Interval, flexibility: int = 2) -> "IntervalList": """ Returns an IntervalList that's a subset of this one, only containing intervals that meet the "interval" parameter criterion. What "meet" means is defined by the ``flexibility`` parameter. ``flexibility == 0``: permits only wholly contained intervals: .. code-block:: none interval: I----------------I intervals in self that will/won't be returned: N---N N---N Y---Y N---N N---N N---N N---N ``flexibility == 1``: permits overlapping intervals as well: .. code-block:: none I----------------I N---N Y---Y Y---Y Y---Y N---N N---N N---N ``flexibility == 2``: permits adjoining intervals as well: .. code-block:: none I----------------I N---N Y---Y Y---Y Y---Y N---N Y---Y Y---Y """ if flexibility not in [0, 1, 2]: raise ValueError("subset: bad flexibility value") permitted = [] for i in self.intervals: if flexibility == 0: ok = i.start > interval.start and i.end < interval.end elif flexibility == 1: ok = i.end > interval.start and i.start < interval.end else: ok = i.end >= interval.start and i.start <= interval.end if ok: permitted.append(i) return IntervalList(permitted)
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Returns an IntervalList that's a subset of this one, only containing intervals that meet the "interval" parameter criterion. What "meet" means is defined by the ``flexibility`` parameter. ``flexibility == 0``: permits only wholly contained intervals: .. code-block:: none interval: I----------------I intervals in self that will/won't be returned: N---N N---N Y---Y N---N N---N N---N N---N ``flexibility == 1``: permits overlapping intervals as well: .. code-block:: none I----------------I N---N Y---Y Y---Y Y---Y N---N N---N N---N ``flexibility == 2``: permits adjoining intervals as well: .. code-block:: none I----------------I N---N Y---Y Y---Y Y---Y N---N Y---Y Y---Y
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python
train
rodluger/everest
everest/missions/k2/k2.py
https://github.com/rodluger/everest/blob/6779591f9f8b3556847e2fbf761bdfac7520eaea/everest/missions/k2/k2.py#L1847-L1867
def GetTargetCBVs(model): ''' Returns the design matrix of CBVs for the given target. :param model: An instance of the :py:obj:`everest` model for the target ''' # Get the info season = model.season name = model.name # We use the LC light curves as CBVs; there aren't # enough SC light curves to get a good set if name.endswith('.sc'): name = name[:-3] model.XCBV = sysrem.GetCBVs(season, model=name, niter=model.cbv_niter, sv_win=model.cbv_win, sv_order=model.cbv_order)
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Returns the design matrix of CBVs for the given target. :param model: An instance of the :py:obj:`everest` model for the target
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python
train
saltstack/salt
salt/modules/file.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/file.py#L3650-L3672
def readdir(path): ''' .. versionadded:: 2014.1.0 Return a list containing the contents of a directory CLI Example: .. code-block:: bash salt '*' file.readdir /path/to/dir/ ''' path = os.path.expanduser(path) if not os.path.isabs(path): raise SaltInvocationError('Dir path must be absolute.') if not os.path.isdir(path): raise SaltInvocationError('A valid directory was not specified.') dirents = ['.', '..'] dirents.extend(os.listdir(path)) return dirents
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.. versionadded:: 2014.1.0 Return a list containing the contents of a directory CLI Example: .. code-block:: bash salt '*' file.readdir /path/to/dir/
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python
train
cwacek/python-jsonschema-objects
python_jsonschema_objects/classbuilder.py
https://github.com/cwacek/python-jsonschema-objects/blob/54c82bfaec9c099c472663742abfc7de373a5e49/python_jsonschema_objects/classbuilder.py#L557-L736
def _build_object(self, nm, clsdata, parents,**kw): logger.debug(util.lazy_format("Building object {0}", nm)) # To support circular references, we tag objects that we're # currently building as "under construction" self.under_construction.add(nm) props = {} defaults = set() properties = {} for p in parents: properties = util.propmerge(properties, p.__propinfo__) if 'properties' in clsdata: properties = util.propmerge(properties, clsdata['properties']) name_translation = {} for prop, detail in properties.items(): logger.debug(util.lazy_format("Handling property {0}.{1}",nm, prop)) properties[prop]['raw_name'] = prop name_translation[prop] = prop.replace('@', '') prop = name_translation[prop] if detail.get('default', None) is not None: defaults.add(prop) if detail.get('type', None) == 'object': uri = "{0}/{1}_{2}".format(nm, prop, "<anonymous>") self.resolved[uri] = self.construct( uri, detail, (ProtocolBase,)) props[prop] = make_property(prop, {'type': self.resolved[uri]}, self.resolved[uri].__doc__) properties[prop]['type'] = self.resolved[uri] elif 'type' not in detail and '$ref' in detail: ref = detail['$ref'] uri = util.resolve_ref_uri(self.resolver.resolution_scope, ref) logger.debug(util.lazy_format( "Resolving reference {0} for {1}.{2}", ref, nm, prop )) if uri in self.resolved: typ = self.resolved[uri] else: typ = self.construct(uri, detail, (ProtocolBase,)) props[prop] = make_property(prop, {'type': typ}, typ.__doc__) properties[prop]['$ref'] = uri properties[prop]['type'] = typ elif 'oneOf' in detail: potential = self.resolve_classes(detail['oneOf']) logger.debug(util.lazy_format("Designating {0} as oneOf {1}", prop, potential)) desc = detail[ 'description'] if 'description' in detail else "" props[prop] = make_property(prop, {'type': potential}, desc ) elif 'type' in detail and detail['type'] == 'array': if 'items' in detail and isinstance(detail['items'], dict): if '$ref' in detail['items']: uri = util.resolve_ref_uri( self.resolver.resolution_scope, detail['items']['$ref']) typ = self.construct(uri, detail['items']) constraints = copy.copy(detail) constraints['strict'] = kw.get('strict') propdata = { 'type': 'array', 'validator': python_jsonschema_objects.wrapper_types.ArrayWrapper.create( uri, item_constraint=typ, **constraints)} else: uri = "{0}/{1}_{2}".format(nm, prop, "<anonymous_field>") try: if 'oneOf' in detail['items']: typ = TypeProxy([ self.construct(uri + "_%s" % i, item_detail) if '$ref' not in item_detail else self.construct(util.resolve_ref_uri( self.resolver.resolution_scope, item_detail['$ref']), item_detail) for i, item_detail in enumerate(detail['items']['oneOf'])] ) else: typ = self.construct(uri, detail['items']) constraints = copy.copy(detail) constraints['strict'] = kw.get('strict') propdata = {'type': 'array', 'validator': python_jsonschema_objects.wrapper_types.ArrayWrapper.create( uri, item_constraint=typ, **constraints)} except NotImplementedError: typ = detail['items'] constraints = copy.copy(detail) constraints['strict'] = kw.get('strict') propdata = {'type': 'array', 'validator': python_jsonschema_objects.wrapper_types.ArrayWrapper.create( uri, item_constraint=typ, **constraints)} props[prop] = make_property(prop, propdata, typ.__doc__) elif 'items' in detail: typs = [] for i, elem in enumerate(detail['items']): uri = "{0}/{1}/<anonymous_{2}>".format(nm, prop, i) typ = self.construct(uri, elem) typs.append(typ) props[prop] = make_property(prop, {'type': typs}, ) else: desc = detail[ 'description'] if 'description' in detail else "" uri = "{0}/{1}".format(nm, prop) typ = self.construct(uri, detail) props[prop] = make_property(prop, {'type': typ}, desc) """ If this object itself has a 'oneOf' designation, then make the validation 'type' the list of potential objects. """ if 'oneOf' in clsdata: klasses = self.resolve_classes(clsdata['oneOf']) # Need a validation to check that it meets one of them props['__validation__'] = {'type': klasses} props['__extensible__'] = pattern_properties.ExtensibleValidator( nm, clsdata, self) props['__prop_names__'] = name_translation props['__propinfo__'] = properties required = set.union(*[p.__required__ for p in parents]) if 'required' in clsdata: for prop in clsdata['required']: required.add(prop) invalid_requires = [req for req in required if req not in props['__propinfo__']] if len(invalid_requires) > 0: raise validators.ValidationError("Schema Definition Error: {0} schema requires " "'{1}', but properties are not defined" .format(nm, invalid_requires)) props['__required__'] = required props['__has_default__'] = defaults if required and kw.get("strict"): props['__strict__'] = True props['__title__'] = clsdata.get('title') cls = type(str(nm.split('/')[-1]), tuple(parents), props) self.under_construction.remove(nm) return cls
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If this object itself has a 'oneOf' designation, then make the validation 'type' the list of potential objects.
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python
train
BernardFW/bernard
src/bernard/utils.py
https://github.com/BernardFW/bernard/blob/9c55703e5ffe5717c9fa39793df59dbfa5b4c5ab/src/bernard/utils.py#L234-L259
def dict_is_subset(subset: Any, full_set: Any) -> bool: """ Checks that all keys present in `subset` are present and have the same value in `full_set`. If a key is in `full_set` but not in `subset` then True will be returned anyways. """ if not isinstance(subset, full_set.__class__): return False elif isinstance(subset, dict): for k, v in subset.items(): if k not in full_set or not dict_is_subset(v, full_set[k]): return False return True elif isinstance(subset, list): if len(subset) != len(full_set): return False for a, b in zip(subset, full_set): if not dict_is_subset(a, b): return False return True else: return subset == full_set
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Checks that all keys present in `subset` are present and have the same value in `full_set`. If a key is in `full_set` but not in `subset` then True will be returned anyways.
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python
train
bslatkin/dpxdt
dpxdt/client/pdiff_worker.py
https://github.com/bslatkin/dpxdt/blob/9f860de1731021d99253670429e5f2157e1f6297/dpxdt/client/pdiff_worker.py#L226-L240
def register(coordinator): """Registers this module as a worker with the given coordinator.""" utils.verify_binary('pdiff_compare_binary', ['-version']) utils.verify_binary('pdiff_composite_binary', ['-version']) assert FLAGS.pdiff_threads > 0 assert FLAGS.queue_server_prefix item = queue_worker.RemoteQueueWorkflow( constants.PDIFF_QUEUE_NAME, DoPdiffQueueWorkflow, max_tasks=FLAGS.pdiff_threads, wait_seconds=FLAGS.pdiff_wait_seconds) item.root = True coordinator.input_queue.put(item)
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Registers this module as a worker with the given coordinator.
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python
train
awslabs/sockeye
sockeye/evaluate.py
https://github.com/awslabs/sockeye/blob/5d64a1ee1ef3cbba17c6d1d94bc061020c43f6ab/sockeye/evaluate.py#L94-L103
def raw_corpus_length_ratio(hypotheses: Iterable[str], references: Iterable[str]) -> float: """ Simple wrapper around length ratio implementation. :param hypotheses: Hypotheses stream. :param references: Reference stream. :return: Length ratio score as float. """ ratios = [len(h.split())/len(r.split()) for h, r in zip(hypotheses, references)] return sum(ratios)/len(ratios) if len(ratios) else 0.0
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Simple wrapper around length ratio implementation. :param hypotheses: Hypotheses stream. :param references: Reference stream. :return: Length ratio score as float.
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python
train
modin-project/modin
modin/pandas/general.py
https://github.com/modin-project/modin/blob/5b77d242596560c646b8405340c9ce64acb183cb/modin/pandas/general.py#L13-L25
def isna(obj): """ Detect missing values for an array-like object. Args: obj: Object to check for null or missing values. Returns: bool or array-like of bool """ if isinstance(obj, BasePandasDataset): return obj.isna() else: return pandas.isna(obj)
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Detect missing values for an array-like object. Args: obj: Object to check for null or missing values. Returns: bool or array-like of bool
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python
train
postlund/pyatv
pyatv/mrp/srp.py
https://github.com/postlund/pyatv/blob/655dfcda4e2f9d1c501540e18da4f480d8bf0e70/pyatv/mrp/srp.py#L145-L153
def step1(self, pin): """First pairing step.""" context = SRPContext( 'Pair-Setup', str(pin), prime=constants.PRIME_3072, generator=constants.PRIME_3072_GEN, hash_func=hashlib.sha512) self._session = SRPClientSession( context, binascii.hexlify(self._auth_private).decode())
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First pairing step.
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python
train
shexSpec/grammar
parsers/python/pyshexc/parser_impl/shex_node_expression_parser.py
https://github.com/shexSpec/grammar/blob/4497cd1f73fa6703bca6e2cb53ba9c120f22e48c/parsers/python/pyshexc/parser_impl/shex_node_expression_parser.py#L64-L67
def visitNodeConstraintValueSet(self, ctx: ShExDocParser.NodeConstraintValueSetContext): """ nodeConstraint: valueSet xsFacet* #nodeConstraintValueSet """ self.nodeconstraint.values = [] self.visitChildren(ctx)
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nodeConstraint: valueSet xsFacet* #nodeConstraintValueSet
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python
train
qualisys/qualisys_python_sdk
qtm/packet.py
https://github.com/qualisys/qualisys_python_sdk/blob/127d7eeebc2b38b5cafdfa5d1d0198437fedd274/qtm/packet.py#L484-L490
def get_3d_markers_residual( self, component_info=None, data=None, component_position=None ): """Get 3D markers with residual.""" return self._get_3d_markers( RT3DMarkerPositionResidual, component_info, data, component_position )
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Get 3D markers with residual.
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python
valid
NeuroanatomyAndConnectivity/surfdist
surfdist/utils.py
https://github.com/NeuroanatomyAndConnectivity/surfdist/blob/849fdfbb2822ff1aa530a3b0bc955a4312e3edf1/surfdist/utils.py#L31-L46
def triangles_keep_cortex(triangles, cortex): """ Remove triangles with nodes not contained in the cortex label array """ # for or each face/triangle keep only those that only contain nodes within the list of cortex nodes input_shape = triangles.shape triangle_is_in_cortex = np.all(np.reshape(np.in1d(triangles.ravel(), cortex), input_shape), axis=1) cortex_triangles_old = np.array(triangles[triangle_is_in_cortex], dtype=np.int32) # reassign node index before outputting triangles new_index = np.digitize(cortex_triangles_old.ravel(), cortex, right=True) cortex_triangles = np.array(np.arange(len(cortex))[new_index].reshape(cortex_triangles_old.shape), dtype=np.int32) return cortex_triangles
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Remove triangles with nodes not contained in the cortex label array
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python
train
NuGrid/NuGridPy
nugridpy/h5T.py
https://github.com/NuGrid/NuGridPy/blob/eee8047446e398be77362d82c1d8b3310054fab0/nugridpy/h5T.py#L543-L980
def get(self, cycle_list, dataitem=None, isotope=None, sparse=1): ''' Get Data from HDF5 files. There are three ways to call this function 1. get(dataitem) Fetches the datatiem for all cycles. If dataitem is a header attribute or list of attributes then the data is retured. If detaitem an individulal or list of column attributes, data columns or isotopes/elements the data is returned for all cycles. 2. get(cycle_list, dataitem) Fetches the dataitem or list of dataitems for the cycle or list of cycles. The variable dataitems can contain column attributes, data columns, and isotopes/elemnts. 3. get(cycle_list, dataitem, isotope) Fetches the dataitems like the seccond method except that one of the dataitems must be either "iso_massf" or "yps", and in the data returned "iso_massf" and "yps" are replaced with the data from the isotopes. The isotopes must be in the form given by se.isotopes or se.elements. Parameters ---------- cycle_list : list, integer or string If cycle_list is a list or string and all of the entries are header attributes then the attributes are returned. If cycle_list is a list or string of dataitems then the dataitems are fetched for all cycles. If cycle_list is a list, integer or string of cycle numbers then data is returned for those cycles. dataitem: list or string, optional If dataitem is not None then the data for each item is returned for the cycle or list of cycles. dataitem may be an individual or a mixed list of column attributes, column data or isotopes/elements. If dataitem is None then cycle_list must be a string. The default is None. isotope: list or string, optional If one of the dataitems is "iso_massf" or "yps" then it is replaced with the data from the individual isotopes/elements listed in isotope. The default is None. sparse : int Implements a sparsity factor on the fetched data i.e. only the i th cycle in cycle_list data is returned, where i = sparse. ''' # Check out the inputs t1=time.time() isotopes_of_interest = [] nested_list = False # if one of cycle_list, dataitem or isotope is given as a string convert it to a list if isinstance(cycle_list, basestring): cycle_list = [cycle_list] else: try: if len(cycle_list) == 1: nested_list = True except TypeError: pass #leave nested_list as false if isinstance(dataitem, basestring): dataitem = [dataitem] if isinstance(isotope, basestring): isotope = [isotope] if dataitem==None and isotope==None: option_ind = 1 dataitem = cycle_list if not any([item in self.hattrs for item in dataitem]): cycle_list = self.cycles else: first_file = mrT.File(self.h5s[0].filename,'r') dat = [] # get all dataitems from header attributes for item in dataitem: tmp = first_file.attrs.get(item, None) try: if len(tmp) == 1: tmp = tmp[0] except TypeError: #if a scaler is returned do nothing pass dat.append(tmp) # if only one header attribute is required dont return as a list if (len(dat) == 1) and (not nested_list): dat = dat[0] first_file.close() return dat if any([item.split('-')[0] in self.isos for item in dataitem]): return self.get(cycle_list,dataitem,sparse=sparse) elif isotope==None: option_ind = 2 cycle_list = cycle_list dataitem = dataitem # if one dataitem is given as a string convert it to a list if isinstance(dataitem, basestring): dataitem = [dataitem] new_dataitem = [] new_isotopes = [] for item in dataitem: if item.split('-')[0] in self.isos: new_isotopes.append(item) else: new_dataitem.append(item) if len(new_isotopes) != 0: tmp = [] try: tmp = self.get(cycle_list,new_dataitem + ['iso_massf'],new_isotopes,sparse=sparse) except: # in some old se files there maybe still yps as the name for the abundance arrays tmp = self.get(cycle_list,new_dataitem + ['yps'],new_isotopes,sparse=sparse) # modify the dat list so dat is structured like dataitems dat = [] #make sure tmp containes the data as a list of cycles if isinstance(cycle_list, basestring): tmp = [tmp] else: try: if len(cycle_list) == 1: tmp = [tmp] except TypeError: tmp = [tmp] for cyc in tmp: temp_dataitem = [] for item in dataitem: if item in new_dataitem: temp_dataitem.append(cyc[new_dataitem.index(item)]) else: if len(new_dataitem) == 0: temp_dataitem = cyc else: if len(new_isotopes) == 1: temp_dataitem.append(cyc[-1]) else: temp_dataitem.append(cyc[-1][new_isotopes.index(item)]) dat.append(temp_dataitem) if (len(dat) == 1) and (not nested_list): dat = dat[0] return dat else: # there is an implicite rule here that if you want 2D arrays you have # to give 3 args, or, in other words you have to give a cycle or cycle # array; there is no good reason for that, except the programmers # laziness option_ind = 3 cycle_list = cycle_list dataitem = dataitem isotopes_of_interest = isotope # we need to find out the shellnb to know if any yps array may just be # a one row array, as - for example- in the surf.h5 files # SJONES: I think here we only need to look at the first shellnb(!) #shellnb=self.get(cycle_list,'shellnb') try: #check if cycle_list is not a list cycle_list[0] except (TypeError,IndexError): cycle_list = [cycle_list] shellnb=self.get(cycle_list[0],'shellnb') if sparse <1: sparse=1 # Just in case the user inputs integers try: for x in range(len(cycle_list)): cycle_list[x] = str(cycle_list[x]) except TypeError: cycle_list = [str(cycle_list)] if option_ind != 1: try: #if it is a single cycle make sure its formatted correctly if cycle_list.isdigit(): cycle_list = [cycle_list] for cycle in cycle_list: if len(cycle) != len(self.cycles[0]): #print "a" diff = len(self.cycles[0])-len(cycle) OO = '' while diff >=1: OO+='0' cycle = OO+cycle except AttributeError: ##if it is a list of cycles make sure its formatted correctly if cycle_list[0].isdigit(): for x in range(len(cycle_list)): if len(str(cycle_list[x])) != len(str(self.cycles[0])): #print "b" diff = len(str(self.cycles[0]))-len(str(cycle_list[x])) OO = '' while diff >=1: OO+='0' diff-=1 try: cycle_list[x] = OO+cycle_list[x] except TypeError: cycle_list[0] = OO+cycle_list[0] dat = [] cycle_list.sort() cyclelist=np.array(list(map(int, cycle_list))) # cycles_requested is a list of indices from cyclelist # The index of the larges and smallest indices should be stored # in sorted order. As new requests are made if the requests # border or over lap then only keep the index of the larges and # smallest indices. cycles_requested = [] # Sometimes bad data or last restart.h5 files contain no cycles, # causing the code to crash. Do a simple try/except here: file_min=[] file_max=[] try: for h5 in self.h5s: file_min.append(int(h5.cycle[0])) file_max.append(int(h5.cycle[-1])) except IndexError: print('File '+h5.filename+' contains no data, please remove or rename it') print('Once the file has been removed or renamed, the preprocessor file must be re-written. Do this by either removing the file h5Preproc.txt from the data directory or by invoking the se instance with rewrite=True') print('At present, h5T cannot check for empty files since the overhead using the mounted VOSpace would be too great.') raise IOError('Cycle-less file encountered') file_min.sort() file_max.sort() for h5 in self.h5s: #initalize file metadata min_file = int(h5.cycle[0]) max_file = int(h5.cycle[-1]) min_list = int(cyclelist[0]) max_list = int(cyclelist[-1]) index_min = None #if None start at begining index_max = None #if None finish at end # SJONES Now we need to add the case that the set only contains one file: if len(file_min) == 1: min_file = min_list - 1 max_file = max_list + 1 else: file_index = file_min.index(min_file) if file_index == 0: if min_list - 1 < min_file: min_file = min_list - 1 max_file = (file_min[file_index + 1] + max_file)//2 elif file_index == len(file_min) - 1: min_file = (file_max[file_index - 1] + min_file)//2 + 1 if max_list + 1 > max_file: max_file = max_list + 1 else: min_file = (file_max[file_index - 1] + min_file)//2 + 1 max_file = (file_min[file_index + 1] + max_file)//2 # calculate the left and right limits of the intersection # of the lists h5.cycle and cyclelist if (max_list < min_file) or (max_file < min_list): # the lists do not intersect continue elif (min_list <= min_file) and (max_file <= max_list): # all of h5.cycle is within cyclelist index_min = bisect.bisect_left(cyclelist, min_file) index_max = bisect.bisect_right(cyclelist, max_file) elif (min_file <= min_list) and (max_list <= max_file): # all of cyclelist is within h5.cycle index_min = None index_max = None else: if min_list > min_file: # cyclelist overlaps the right edge of h5.cycle index_min = None index_max = bisect.bisect_right(cyclelist, max_file) else: # cyclelist overlaps the left edge of h5.cylce index_min = bisect.bisect_left(cyclelist, min_file) index_max = None # maintin list of all requested cycles by keeping trak of # the maximum and minimum indices imin = index_min if index_min == None: imin = 0 imax = index_max if index_max == None: imax = len(cyclelist) request_min = bisect.bisect_left(cycles_requested, imin) request_max = bisect.bisect_right(cycles_requested, imax) # if the new request overlabs older request remove them del cycles_requested[request_min:request_max] if ((request_max-request_min) % 2) ==1: # new and old request overlaped on one edge only if request_min % 2 == 0: # add new starting index cycles_requested.insert(request_min, imin) else: # add new ending index cycles_requested.insert(request_min, imax) else: # new and old requests overlaped on two edges if request_min % 2 == 0: # old request was contained with in new request cycles_requested.insert(request_min, imin) cycles_requested.insert(request_min + 1, imax) else: # new request wat contained within old request pass if not self.h5sStarted[self.h5s.index(h5)]: h5.start() h5.join() temp = h5.fetch_data_sam(dataitem,cycle_list[index_min:index_max],len(cycle_list),len(dat)) self.h5sStarted[self.h5s.index(h5)]=True else: temp = h5.fetch_data_sam(dataitem,cycle_list[index_min:index_max],len(cycle_list),len(dat)) temp_dat = [] for temp_num, temp_cycle in enumerate(temp): temp_dataforcycle = [] for dataitem_num, temp_dataitem in enumerate(temp_cycle): # identify what cycle the temp data was collected from temp_dataitem=self.red_dim(temp_dataitem) # if option_ind == 3 and isotopes_of_interest != []: if (dataitem[dataitem_num] == 'iso_massf' or dataitem[dataitem_num] == 'yps') and isotopes_of_interest != []: # Figure out the index index = [] iso_tmp = [] if 'iso' in dataitem[dataitem_num]: #if we are looking at an isotope iso_tmp = self.isotopes else: iso_tmp = self.elements for iso in isotopes_of_interest: #finds the location of the isotope x = iso_tmp.index(iso) index.append(x) if index == []: # if none of the isotopes of interest are found # then the index defaults to [0], so that the loop # will still try to acess the data in t. index = [0] islist=True if len(cycle_list)==1: islist=False # shellnb_index = 0 # if index_min == None: # shellnb_index = temp_num # else: # shellnb_index = index_min + temp_num temp_multicyc = [] for i in index: # if islist: # if shellnb[shellnb_index] == 1: # again take care of 1-row 2D arrays if shellnb == 1: # again take care of 1-row 2D arrays temp_multicyc.append(temp_dataitem[i]) else: temp_multicyc.append(temp_dataitem[:,i]) # else: # if shellnb == 1: # again take care of 1-row 2D arrays # temp_multicyc.append(temp_dataitem[i]) # else: # temp_multicyc.append(temp_dataitem[:,i]) if len(temp_multicyc) == 1: # agian take care of 1-row arrays temp_multicyc = temp_multicyc[0] temp_dataitem = temp_multicyc temp_dataforcycle.append(temp_dataitem) if len(temp_dataforcycle) == 1: # agian take care of 1-row arrays temp_dataforcycle = temp_dataforcycle[0] # Now add the information to the list we pass back temp_dat.append(temp_dataforcycle) # calculate the proper insertion point for the data colected from # the file h5 in self.h5s insert_pnt = 0 if index_min is not None: #alex: in py2: x < None == False for i in range(len(cycles_requested)): if i % 2 == 1: if cycles_requested[i] < index_min: insert_pnt += cycles_requested[i] - cycles_requested[i-1] elif cycles_requested[i - 1] < index_min: insert_pnt += index_min - cycles_requested[i - 1] # insert the cycle data from the current file into the apropiat place # in the output data. dat[insert_pnt:insert_pnt] = temp_dat #check if cycles were not requested from the file # SJONES comment # missing_cycles = np.array([]) # if len(cycles_requested) != 2: # if len(cycles_requested) == 0: # missing_cycles = np.array([cycle_list]) # else: # cycles_requested = [None] + cycles_requested + [None] # for i in xrange(0, len(cycles_requested), 2): # min = cycles_requested[i] # max = cycles_requested[i + 1] # missing_cycles = np.append(missing_cycles, cycle_list[min:max]) # print "The requested cycles: " + str(missing_cycles) + " are not available in this data set" # elif (cycles_requested[0] != 0) or (cycles_requested[1] != len(cyclelist)): # min = cycles_requested[0] # max = cycles_requested[1] # missing_cycles = np.append(missing_cycles, cycle_list[0:min]) # missing_cycles = np.append(missing_cycles, cycle_list[max:]) # print "The requested cycles: " + str(missing_cycles) + " are not available in this data set" if len(dat) < 2 and option_ind != 3 and (not nested_list): try: dat = dat[0] except IndexError: None except TypeError: None try: if len(dat) < 2 and isotopes_of_interest != []: dat = dat[0] except TypeError: None except IndexError: None t2=time.time() return dat
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Get Data from HDF5 files. There are three ways to call this function 1. get(dataitem) Fetches the datatiem for all cycles. If dataitem is a header attribute or list of attributes then the data is retured. If detaitem an individulal or list of column attributes, data columns or isotopes/elements the data is returned for all cycles. 2. get(cycle_list, dataitem) Fetches the dataitem or list of dataitems for the cycle or list of cycles. The variable dataitems can contain column attributes, data columns, and isotopes/elemnts. 3. get(cycle_list, dataitem, isotope) Fetches the dataitems like the seccond method except that one of the dataitems must be either "iso_massf" or "yps", and in the data returned "iso_massf" and "yps" are replaced with the data from the isotopes. The isotopes must be in the form given by se.isotopes or se.elements. Parameters ---------- cycle_list : list, integer or string If cycle_list is a list or string and all of the entries are header attributes then the attributes are returned. If cycle_list is a list or string of dataitems then the dataitems are fetched for all cycles. If cycle_list is a list, integer or string of cycle numbers then data is returned for those cycles. dataitem: list or string, optional If dataitem is not None then the data for each item is returned for the cycle or list of cycles. dataitem may be an individual or a mixed list of column attributes, column data or isotopes/elements. If dataitem is None then cycle_list must be a string. The default is None. isotope: list or string, optional If one of the dataitems is "iso_massf" or "yps" then it is replaced with the data from the individual isotopes/elements listed in isotope. The default is None. sparse : int Implements a sparsity factor on the fetched data i.e. only the i th cycle in cycle_list data is returned, where i = sparse.
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python
train
fr33jc/bang
bang/providers/aws.py
https://github.com/fr33jc/bang/blob/8f000713f88d2a9a8c1193b63ca10a6578560c16/bang/providers/aws.py#L30-L42
def server_to_dict(server): """ Returns the :class:`dict` representation of a server object. The returned :class:`dict` is meant to be consumed by :class:`~bang.deployers.cloud.ServerDeployer` objects. """ return { A.server.ID: server.id, A.server.PUBLIC_IPS: [server.public_dns_name], A.server.PRIVATE_IPS: [server.private_dns_name], }
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Returns the :class:`dict` representation of a server object. The returned :class:`dict` is meant to be consumed by :class:`~bang.deployers.cloud.ServerDeployer` objects.
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python
train
dtmilano/AndroidViewClient
src/com/dtmilano/android/viewclient.py
https://github.com/dtmilano/AndroidViewClient/blob/7e6e83fde63af99e5e4ab959712ecf94f9881aa2/src/com/dtmilano/android/viewclient.py#L3188-L3212
def traverse(self, root="ROOT", indent="", transform=None, stream=sys.stdout): ''' Traverses the C{View} tree and prints its nodes. The nodes are printed converting them to string but other transformations can be specified by providing a method name as the C{transform} parameter. @type root: L{View} @param root: the root node from where the traverse starts @type indent: str @param indent: the indentation string to use to print the nodes @type transform: method @param transform: a method to use to transform the node before is printed ''' if transform is None: # this cannot be a default value, otherwise # TypeError: 'staticmethod' object is not callable # is raised transform = ViewClient.TRAVERSE_CIT if type(root) == types.StringType and root == "ROOT": root = self.root return ViewClient.__traverse(root, indent, transform, stream)
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Traverses the C{View} tree and prints its nodes. The nodes are printed converting them to string but other transformations can be specified by providing a method name as the C{transform} parameter. @type root: L{View} @param root: the root node from where the traverse starts @type indent: str @param indent: the indentation string to use to print the nodes @type transform: method @param transform: a method to use to transform the node before is printed
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python
train
MKLab-ITI/reveal-graph-embedding
reveal_graph_embedding/embedding/common.py
https://github.com/MKLab-ITI/reveal-graph-embedding/blob/eda862687aa5a64b79c6b12de1b4dca6ce986dc8/reveal_graph_embedding/embedding/common.py#L49-L67
def normalize_columns(features): """ This performs column normalization of community embedding features. Input: - X in R^(nxC_n): The community indicator matrix. Output: - X_norm in R^(nxC_n): The tf-idf + row normalized community indicator matrix. """ # Calculate inverse document frequency. features = features.tocsc() for j in range(features.shape[1]): document_frequency = features.getcol(j).data.size if document_frequency > 1: features.data[features.indptr[j]: features.indptr[j + 1]] =\ features.data[features.indptr[j]: features.indptr[j + 1]]/np.sqrt(np.log(document_frequency)) features = features.tocsr() return features
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This performs column normalization of community embedding features. Input: - X in R^(nxC_n): The community indicator matrix. Output: - X_norm in R^(nxC_n): The tf-idf + row normalized community indicator matrix.
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python
train
apple/turicreate
src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/message_factory.py
https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/message_factory.py#L57-L87
def GetPrototype(self, descriptor): """Builds a proto2 message class based on the passed in descriptor. Passing a descriptor with a fully qualified name matching a previous invocation will cause the same class to be returned. Args: descriptor: The descriptor to build from. Returns: A class describing the passed in descriptor. """ if descriptor.full_name not in self._classes: descriptor_name = descriptor.name if str is bytes: # PY2 descriptor_name = descriptor.name.encode('ascii', 'ignore') result_class = reflection.GeneratedProtocolMessageType( descriptor_name, (message.Message,), {'DESCRIPTOR': descriptor, '__module__': None}) # If module not set, it wrongly points to the reflection.py module. self._classes[descriptor.full_name] = result_class for field in descriptor.fields: if field.message_type: self.GetPrototype(field.message_type) for extension in result_class.DESCRIPTOR.extensions: if extension.containing_type.full_name not in self._classes: self.GetPrototype(extension.containing_type) extended_class = self._classes[extension.containing_type.full_name] extended_class.RegisterExtension(extension) return self._classes[descriptor.full_name]
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Builds a proto2 message class based on the passed in descriptor. Passing a descriptor with a fully qualified name matching a previous invocation will cause the same class to be returned. Args: descriptor: The descriptor to build from. Returns: A class describing the passed in descriptor.
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python
train
ensime/ensime-vim
ensime_shared/editor.py
https://github.com/ensime/ensime-vim/blob/caa734e84f002b25446c615706283a74edd4ecfe/ensime_shared/editor.py#L298-L303
def get_error_at(self, cursor): """Return error at position `cursor`.""" for error in self._errors: if error.includes(self._vim.eval("expand('%:p')"), cursor): return error return None
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Return error at position `cursor`.
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python
train
hfaran/slack-export-viewer
slackviewer/reader.py
https://github.com/hfaran/slack-export-viewer/blob/bbe97f5cd9f72a0cc41c7395cef23860b44918f8/slackviewer/reader.py#L89-L111
def compile_mpim_users(self): """ Gets the info for the members within the multiple person instant message Returns a list of all dms with the members that have ever existed :rtype: [object] { name: <name> users: [<user_id>] } """ mpim_data = self._read_from_json("mpims.json") mpims = [c for c in mpim_data.values()] all_mpim_users = [] for mpim in mpims: mpim_members = {"name": mpim["name"], "users": [self.__USER_DATA[m] for m in mpim["members"]]} all_mpim_users.append(mpim_members) return all_mpim_users
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Gets the info for the members within the multiple person instant message Returns a list of all dms with the members that have ever existed :rtype: [object] { name: <name> users: [<user_id>] }
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python
train
jazzband/sorl-thumbnail
sorl/thumbnail/engines/base.py
https://github.com/jazzband/sorl-thumbnail/blob/22ccd9781462a820f963f57018ad3dcef85053ed/sorl/thumbnail/engines/base.py#L15-L28
def create(self, image, geometry, options): """ Processing conductor, returns the thumbnail as an image engine instance """ image = self.cropbox(image, geometry, options) image = self.orientation(image, geometry, options) image = self.colorspace(image, geometry, options) image = self.remove_border(image, options) image = self.scale(image, geometry, options) image = self.crop(image, geometry, options) image = self.rounded(image, geometry, options) image = self.blur(image, geometry, options) image = self.padding(image, geometry, options) return image
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Processing conductor, returns the thumbnail as an image engine instance
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python
train
materialsproject/pymatgen
pymatgen/io/vasp/outputs.py
https://github.com/materialsproject/pymatgen/blob/4ca558cf72f8d5f8a1f21dfdfc0181a971c186da/pymatgen/io/vasp/outputs.py#L859-L877
def eigenvalue_band_properties(self): """ Band properties from the eigenvalues as a tuple, (band gap, cbm, vbm, is_band_gap_direct). """ vbm = -float("inf") vbm_kpoint = None cbm = float("inf") cbm_kpoint = None for spin, d in self.eigenvalues.items(): for k, val in enumerate(d): for (eigenval, occu) in val: if occu > self.occu_tol and eigenval > vbm: vbm = eigenval vbm_kpoint = k elif occu <= self.occu_tol and eigenval < cbm: cbm = eigenval cbm_kpoint = k return max(cbm - vbm, 0), cbm, vbm, vbm_kpoint == cbm_kpoint
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Band properties from the eigenvalues as a tuple, (band gap, cbm, vbm, is_band_gap_direct).
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python
train
drslump/pyshould
pyshould/expectation.py
https://github.com/drslump/pyshould/blob/7210859d4c84cfbaa64f91b30c2a541aea788ddf/pyshould/expectation.py#L51-L57
def clone(self): """ Clone this expression """ from copy import copy clone = copy(self) clone.expr = copy(self.expr) clone.factory = False return clone
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Clone this expression
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python
train
lemieuxl/pyGenClean
pyGenClean/Misc/compare_gold_standard.py
https://github.com/lemieuxl/pyGenClean/blob/6173a48ccc0cf3a3bd711b1f2a1fa16248b8bf55/pyGenClean/Misc/compare_gold_standard.py#L436-L474
def read_same_samples_file(filename, out_prefix): """Reads a file containing same samples.""" # The same samples same_samples = [] # Creating the extraction files gold_file = None try: gold_file = open(out_prefix + ".gold_samples2keep", 'w') except IOError: msg = "{}: can't create file".format(out_prefix + ".gold_samples2keep") raise ProgramError(msg) source_file = None try: source_file = open(out_prefix + ".source_panel_samples2keep", 'w') except IOError: msg = ("{}: can't create " "file".format(out_prefix + ".source_panel_samples2keep")) raise ProgramError(msg) with open(filename, 'r') as input_file: for line in input_file: row = line.rstrip("\r\n").split("\t") # Getting the samples gold_sample = tuple(row[:2]) source_sample = tuple(row[2:]) same_samples.append((gold_sample, source_sample)) # Printing files print >>gold_file, "\t".join(gold_sample) print >>source_file, "\t".join(source_sample) # Closing the files gold_file.close() source_file.close() return same_samples
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Reads a file containing same samples.
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python
train
coursera-dl/coursera-dl
coursera/cookies.py
https://github.com/coursera-dl/coursera-dl/blob/9b434bcf3c4011bf3181429fe674633ae5fb7d4d/coursera/cookies.py#L209-L217
def do_we_have_enough_cookies(cj, class_name): """ Check whether we have all the required cookies to authenticate on class.coursera.org. """ domain = 'class.coursera.org' path = "/" + class_name return cj.get('csrf_token', domain=domain, path=path) is not None
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Check whether we have all the required cookies to authenticate on class.coursera.org.
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python
train
radjkarl/imgProcessor
imgProcessor/camera/NoiseLevelFunction.py
https://github.com/radjkarl/imgProcessor/blob/7c5a28718f81c01a430152c60a686ac50afbfd7c/imgProcessor/camera/NoiseLevelFunction.py#L131-L150
def smooth(x, y, weights): ''' in case the NLF cannot be described by a square root function commit bounded polynomial interpolation ''' # Spline hard to smooth properly, therefore solfed with # bounded polynomal interpolation # ext=3: no extrapolation, but boundary value # return UnivariateSpline(x, y, w=weights, # s=len(y)*weights.max()*100, ext=3) # return np.poly1d(np.polyfit(x,y,w=weights,deg=2)) p = np.polyfit(x, y, w=weights, deg=2) if np.any(np.isnan(p)): # couldn't even do polynomial fit # as last option: assume constant noise my = np.average(y, weights=weights) return lambda x: my return lambda xint: np.poly1d(p)(np.clip(xint, x[0], x[-1]))
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in case the NLF cannot be described by a square root function commit bounded polynomial interpolation
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python
train
Telefonica/toolium
toolium/utils.py
https://github.com/Telefonica/toolium/blob/56847c243b3a98876df74c184b75e43f8810e475/toolium/utils.py#L524-L538
def _download_video(self, video_url, video_name): """Download a video from the remote node :param video_url: video url :param video_name: video name """ filename = '{0:0=2d}_{1}'.format(DriverWrappersPool.videos_number, video_name) filename = '{}.mp4'.format(get_valid_filename(filename)) filepath = os.path.join(DriverWrappersPool.videos_directory, filename) if not os.path.exists(DriverWrappersPool.videos_directory): os.makedirs(DriverWrappersPool.videos_directory) response = requests.get(video_url) open(filepath, 'wb').write(response.content) self.logger.info("Video saved in '%s'", filepath) DriverWrappersPool.videos_number += 1
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Download a video from the remote node :param video_url: video url :param video_name: video name
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python
train
pypa/pipenv
pipenv/patched/notpip/_internal/configuration.py
https://github.com/pypa/pipenv/blob/cae8d76c210b9777e90aab76e9c4b0e53bb19cde/pipenv/patched/notpip/_internal/configuration.py#L139-L146
def get_value(self, key): # type: (str) -> Any """Get a value from the configuration. """ try: return self._dictionary[key] except KeyError: raise ConfigurationError("No such key - {}".format(key))
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Get a value from the configuration.
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python
train
cdgriffith/puremagic
puremagic/main.py
https://github.com/cdgriffith/puremagic/blob/ae2c4c400930b8a19519e787f61dd779db7e415b/puremagic/main.py#L116-L126
def _file_details(filename): """ Grab the start and end of the file""" max_head, max_foot = _max_lengths() with open(filename, "rb") as fin: head = fin.read(max_head) try: fin.seek(-max_foot, os.SEEK_END) except IOError: fin.seek(0) foot = fin.read() return head, foot
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Grab the start and end of the file
[ "Grab", "the", "start", "and", "end", "of", "the", "file" ]
python
train
aichaos/rivescript-python
rivescript/rivescript.py
https://github.com/aichaos/rivescript-python/blob/b55c820cf02a194605fd66af1f070e239f84ed31/rivescript/rivescript.py#L640-L653
def set_variable(self, name, value): """Set a bot variable. Equivalent to ``! var`` in RiveScript code. :param str name: The name of the variable to set. :param str value: The value of the variable. Set this to ``None`` to delete the variable. """ if value is None: # Unset the variable. if name in self._var: del self._var[name] self._var[name] = value
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Set a bot variable. Equivalent to ``! var`` in RiveScript code. :param str name: The name of the variable to set. :param str value: The value of the variable. Set this to ``None`` to delete the variable.
[ "Set", "a", "bot", "variable", "." ]
python
train
pantsbuild/pants
src/python/pants/pantsd/service/fs_event_service.py
https://github.com/pantsbuild/pants/blob/b72e650da0df685824ffdcc71988b8c282d0962d/src/python/pants/pantsd/service/fs_event_service.py#L105-L124
def run(self): """Main service entrypoint. Called via Thread.start() via PantsDaemon.run().""" if not (self._watchman and self._watchman.is_alive()): raise PantsService.ServiceError('watchman is not running, bailing!') # Enable watchman for the build root. self._watchman.watch_project(self._build_root) subscriptions = list(self._handlers.values()) # Setup subscriptions and begin the main event firing loop. for handler_name, event_data in self._watchman.subscribed(self._build_root, subscriptions): self._state.maybe_pause() if self._state.is_terminating: break if event_data: # As we receive events from watchman, trigger the relevant handlers. self.fire_callback(handler_name, event_data)
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Main service entrypoint. Called via Thread.start() via PantsDaemon.run().
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python
train
inasafe/inasafe
extras/data_audit.py
https://github.com/inasafe/inasafe/blob/831d60abba919f6d481dc94a8d988cc205130724/extras/data_audit.py#L237-L405
def license_file_is_valid(license_filename, data_filename, dirpath='.', verbose=False): """Check that XML license file for given filename_to_verify is valid. Input: license_filename: XML license file (must be an absolute path name) data_filename: The data filename that is being audited dir_path: Where the files live verbose: Optional verbosity Check for each datafile listed that * Datafile tags are there and match the one specified * Fields are non empty (except IP_info which can be left blank) * Datafile exists * Checksum is correct * Datafile is flagged as publishable If anything is violated an appropriate exception is raised. If everything is honky dory the function will return True. """ if verbose: print 'Parsing', license_filename doc = xml2object(license_filename) # Check that file is valid (e.g. all elements there) if not doc.has_key('ga_license_file'): msg = 'License file %s must have two elements' %license_filename msg += ' at the root level. They are\n' msg += ' <?xml version="1.0" encoding="iso-8859-1"?>\n' msg += ' <ga_license_file>\n' msg += 'The second element was found to be %s' %doc.keys() raise WrongTags, msg # Validate elements: metadata, datafile, datafile, ... # FIXME (Ole): I'd like this to verified by the parser # using a proper DTD template one day.... # For not, let's check the main ones. elements = doc['ga_license_file'] if not elements.has_key('metadata'): msg = 'Tag %s must have the element "metadata"'\ %doc.keys()[0] msg += 'The element found was %s' %elements[0].nodeName raise WrongTags, msg if not elements.has_key('datafile'): msg = 'Tag %s must have the element "datafile"'\ %doc.keys()[0] msg += 'The element found was %s' %elements[0].nodeName raise WrongTags, msg for key in elements.keys(): msg = 'Invalid tag: %s' %key if not key in ['metadata', 'datafile']: raise WrongTags, msg # Extract information for metadata section if verbose: print metadata = elements['metadata'] author = metadata['author'] if verbose: print 'Author: ', author if author == '': msg = 'Missing author' raise Exception, msg #svn_keywords = metadata['svn_keywords'] #if verbose: print 'SVN keywords: ', svn_keywords # Extract information for datafile sections datafile = elements['datafile'] if isinstance(datafile, XML_element): datafile = [datafile] # Check that filename to verify is listed in license file found = False for data in datafile: if data['filename'] == data_filename: found = True break if not found: msg = 'Specified filename to verify %s ' %data_filename msg += 'did not appear in license file %s' %license_filename raise FilenameMismatch, msg # Check contents for selected data_filename #for data in datafile: # if verbose: print # Filename if data['filename'] == '': msg = 'Missing filename' raise FilenameMismatch, msg else: filename = join(dirpath, data['filename']) if verbose: print 'Filename: "%s"' %filename try: fid = open(filename, 'r') except: msg = 'Specified filename %s could not be opened'\ %filename raise FilenameMismatch, msg # CRC reported_crc = data['checksum'] if verbose: print 'Checksum: "%s"' %reported_crc file_crc = str(compute_checksum(filename)) if reported_crc != file_crc: msg = 'Bad checksum (CRC).\n' msg += ' The CRC reported in license file "%s" is "%s"\n'\ %(license_filename, reported_crc) msg += ' The CRC computed from file "%s" is "%s"'\ %(filename, file_crc) raise CRCMismatch, msg # Accountable accountable = data['accountable'] if verbose: print 'Accountable: "%s"' %accountable if accountable == '': msg = 'No accountable person specified' raise Empty, msg # Source source = data['source'] if verbose: print 'Source: "%s"' %source if source == '': msg = 'No source specified' raise Empty, msg # IP owner ip_owner = data['IP_owner'] if verbose: print 'IP owner: "%s"' %ip_owner if ip_owner == '': msg = 'No IP owner specified' raise Empty, msg # IP info ip_info = data['IP_info'] if verbose: print 'IP info: "%s"' %ip_info #if ip_info == '': # msg = 'No IP info specified' # raise Empty, msg # Publishable publishable = data['publishable'] if verbose: print 'Publishable: "%s"' %publishable if publishable == '': msg = 'No publishable value specified' raise NotPublishable, msg if publishable.upper() != 'YES': msg = 'Data file %s is not flagged as publishable'\ %fid.name raise NotPublishable, msg # If we get this far, the license file is OK return True
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Check that XML license file for given filename_to_verify is valid. Input: license_filename: XML license file (must be an absolute path name) data_filename: The data filename that is being audited dir_path: Where the files live verbose: Optional verbosity Check for each datafile listed that * Datafile tags are there and match the one specified * Fields are non empty (except IP_info which can be left blank) * Datafile exists * Checksum is correct * Datafile is flagged as publishable If anything is violated an appropriate exception is raised. If everything is honky dory the function will return True.
[ "Check", "that", "XML", "license", "file", "for", "given", "filename_to_verify", "is", "valid", "." ]
python
train
Gandi/gandi.cli
gandi/cli/modules/domain.py
https://github.com/Gandi/gandi.cli/blob/6ee5b8fc8ec44b0a6c232043ca610606ad8f693d/gandi/cli/modules/domain.py#L30-L77
def create(cls, fqdn, duration, owner, admin, tech, bill, nameserver, extra_parameter, background): """Create a domain.""" fqdn = fqdn.lower() if not background and not cls.intty(): background = True result = cls.call('domain.available', [fqdn]) while result[fqdn] == 'pending': time.sleep(1) result = cls.call('domain.available', [fqdn]) if result[fqdn] == 'unavailable': raise DomainNotAvailable('%s is not available' % fqdn) # retrieve handle of user and save it to configuration user_handle = cls.call('contact.info')['handle'] cls.configure(True, 'api.handle', user_handle) owner_ = owner or user_handle admin_ = admin or user_handle tech_ = tech or user_handle bill_ = bill or user_handle domain_params = { 'duration': duration, 'owner': owner_, 'admin': admin_, 'tech': tech_, 'bill': bill_, } if nameserver: domain_params['nameservers'] = nameserver if extra_parameter: domain_params['extra'] = {} for extra in extra_parameter: domain_params['extra'][extra[0]] = extra[1] result = cls.call('domain.create', fqdn, domain_params) if background: return result # interactive mode, run a progress bar cls.echo('Creating your domain.') cls.display_progress(result) cls.echo('Your domain %s has been created.' % fqdn)
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Create a domain.
[ "Create", "a", "domain", "." ]
python
train
pywbem/pywbem
pywbem/cim_obj.py
https://github.com/pywbem/pywbem/blob/e54ecb82c2211e289a268567443d60fdd489f1e4/pywbem/cim_obj.py#L466-L577
def _mof_escaped(strvalue): # Note: This is a raw docstring because it shows many backslashes, and # that avoids having to double them. r""" Return a MOF-escaped string from the input string. Parameters: strvalue (:term:`unicode string`): The string value. Must not be `None`. Special characters must not be backslash-escaped. Details on backslash-escaping: `DSP0004` defines that the character repertoire for MOF string constants is the entire repertoire for the CIM string datatype. That is, the entire Unicode character repertoire except for U+0000. The only character for which `DSP0004` requires the use of a MOF escape sequence in a MOF string constant, is the double quote (because a MOF string constant is enclosed in double quotes). `DSP0004` defines MOF escape sequences for several more characters, but it does not require their use in MOF. For example, it is valid for a MOF string constant to contain the (unescaped) characters U+000D (newline) or U+0009 (horizontal tab), and others. Processing the MOF escape sequences as unescaped characters may not be supported by MOF-related tools, and therefore this function plays it safe and uses the MOF escape sequences defined in `DSP0004` as much as possible. The following table shows the MOF escape sequences defined in `DSP0004` and whether they are used (i.e. generated) by this function: ========== ==== =========================================================== MOF escape Used Character sequence ========== ==== =========================================================== \b yes U+0008: Backspace \t yes U+0009: Horizontal tab \n yes U+000A: Line feed \f yes U+000C: Form feed \r yes U+000D: Carriage return \" yes U+0022: Double quote (") (required to be used) \' yes U+0027: Single quote (') \\ yes U+005C: Backslash (\) \x<hex> (1) U+<hex>: Any UCS-2 character, where <hex> is one to four hex digits, representing its UCS code position (this form is limited to the UCS-2 character repertoire) \X<hex> no U+<hex>: Any UCS-2 character, where <hex> is one to four hex digits, representing its UCS code position (this form is limited to the UCS-2 character repertoire) ========== ==== =========================================================== (1) Yes, for all other characters in the so called "control range" U+0001..U+001F. """ escaped_str = strvalue # Escape backslash (\) escaped_str = escaped_str.replace('\\', '\\\\') # Escape \b, \t, \n, \f, \r # Note, the Python escape sequences happen to be the same as in MOF escaped_str = escaped_str.\ replace('\b', '\\b').\ replace('\t', '\\t').\ replace('\n', '\\n').\ replace('\f', '\\f').\ replace('\r', '\\r') # Escape remaining control characters (U+0001...U+001F), skipping # U+0008, U+0009, U+000A, U+000C, U+000D that are already handled. # We hard code it to be faster, plus we can easily skip already handled # chars. # The generic code would be (not skipping already handled chars): # for cp in range(1, 32): # c = six.unichr(cp) # esc = '\\x{0:04X}'.format(cp) # escaped_str = escaped_str.replace(c, esc) escaped_str = escaped_str.\ replace(u'\u0001', '\\x0001').\ replace(u'\u0002', '\\x0002').\ replace(u'\u0003', '\\x0003').\ replace(u'\u0004', '\\x0004').\ replace(u'\u0005', '\\x0005').\ replace(u'\u0006', '\\x0006').\ replace(u'\u0007', '\\x0007').\ replace(u'\u000B', '\\x000B').\ replace(u'\u000E', '\\x000E').\ replace(u'\u000F', '\\x000F').\ replace(u'\u0010', '\\x0010').\ replace(u'\u0011', '\\x0011').\ replace(u'\u0012', '\\x0012').\ replace(u'\u0013', '\\x0013').\ replace(u'\u0014', '\\x0014').\ replace(u'\u0015', '\\x0015').\ replace(u'\u0016', '\\x0016').\ replace(u'\u0017', '\\x0017').\ replace(u'\u0018', '\\x0018').\ replace(u'\u0019', '\\x0019').\ replace(u'\u001A', '\\x001A').\ replace(u'\u001B', '\\x001B').\ replace(u'\u001C', '\\x001C').\ replace(u'\u001D', '\\x001D').\ replace(u'\u001E', '\\x001E').\ replace(u'\u001F', '\\x001F') # Escape single and double quote escaped_str = escaped_str.replace('"', '\\"') escaped_str = escaped_str.replace("'", "\\'") return escaped_str
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r""" Return a MOF-escaped string from the input string. Parameters: strvalue (:term:`unicode string`): The string value. Must not be `None`. Special characters must not be backslash-escaped. Details on backslash-escaping: `DSP0004` defines that the character repertoire for MOF string constants is the entire repertoire for the CIM string datatype. That is, the entire Unicode character repertoire except for U+0000. The only character for which `DSP0004` requires the use of a MOF escape sequence in a MOF string constant, is the double quote (because a MOF string constant is enclosed in double quotes). `DSP0004` defines MOF escape sequences for several more characters, but it does not require their use in MOF. For example, it is valid for a MOF string constant to contain the (unescaped) characters U+000D (newline) or U+0009 (horizontal tab), and others. Processing the MOF escape sequences as unescaped characters may not be supported by MOF-related tools, and therefore this function plays it safe and uses the MOF escape sequences defined in `DSP0004` as much as possible. The following table shows the MOF escape sequences defined in `DSP0004` and whether they are used (i.e. generated) by this function: ========== ==== =========================================================== MOF escape Used Character sequence ========== ==== =========================================================== \b yes U+0008: Backspace \t yes U+0009: Horizontal tab \n yes U+000A: Line feed \f yes U+000C: Form feed \r yes U+000D: Carriage return \" yes U+0022: Double quote (") (required to be used) \' yes U+0027: Single quote (') \\ yes U+005C: Backslash (\) \x<hex> (1) U+<hex>: Any UCS-2 character, where <hex> is one to four hex digits, representing its UCS code position (this form is limited to the UCS-2 character repertoire) \X<hex> no U+<hex>: Any UCS-2 character, where <hex> is one to four hex digits, representing its UCS code position (this form is limited to the UCS-2 character repertoire) ========== ==== =========================================================== (1) Yes, for all other characters in the so called "control range" U+0001..U+001F.
[ "r", "Return", "a", "MOF", "-", "escaped", "string", "from", "the", "input", "string", "." ]
python
train
jenanwise/codequality
codequality/main.py
https://github.com/jenanwise/codequality/blob/8a2bd767fd73091c49a5318fdbfb2b4fff77533d/codequality/main.py#L152-L174
def _resolve_paths(self, *paths): """ Resolve paths into a set of filenames (no directories) to check. External tools will handle directories as arguments differently, so for consistency we just want to pass them filenames. This method will recursively walk all directories and filter out any paths that match self.options.ignores. """ result = set() for path in paths: if os.path.isdir(path): for dirpath, _, filenames in os.walk(path): for filename in filenames: path = os.path.join(dirpath, filename) if path.startswith('.'): path = path[1:].lstrip('/') if not self._should_ignore(path): result.add(path) else: result.add(path) return result
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Resolve paths into a set of filenames (no directories) to check. External tools will handle directories as arguments differently, so for consistency we just want to pass them filenames. This method will recursively walk all directories and filter out any paths that match self.options.ignores.
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python
train
hotdoc/hotdoc
hotdoc/utils/setup_utils.py
https://github.com/hotdoc/hotdoc/blob/1067cdc8482b585b364a38fb52ca5d904e486280/hotdoc/utils/setup_utils.py#L116-L133
def symlink(source, link_name): """ Method to allow creating symlinks on Windows """ if os.path.islink(link_name) and os.readlink(link_name) == source: return os_symlink = getattr(os, "symlink", None) if callable(os_symlink): os_symlink(source, link_name) else: import ctypes csl = ctypes.windll.kernel32.CreateSymbolicLinkW csl.argtypes = (ctypes.c_wchar_p, ctypes.c_wchar_p, ctypes.c_uint32) csl.restype = ctypes.c_ubyte flags = 1 if os.path.isdir(source) else 0 if csl(link_name, source, flags) == 0: raise ctypes.WinError()
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Method to allow creating symlinks on Windows
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python
train
rfverbruggen/rachiopy
rachiopy/schedulerule.py
https://github.com/rfverbruggen/rachiopy/blob/c91abc9984f0f453e60fa905285c1b640c3390ae/rachiopy/schedulerule.py#L33-L36
def get(self, sched_rule_id): """Retrieve the information for a scheduleRule entity.""" path = '/'.join(['schedulerule', sched_rule_id]) return self.rachio.get(path)
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Retrieve the information for a scheduleRule entity.
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python
train
Spinmob/spinmob
_plotting_mess.py
https://github.com/Spinmob/spinmob/blob/f037f5df07f194bcd4a01f4d9916e57b9e8fb45a/_plotting_mess.py#L441-L524
def realimag_data(xdata, ydata, eydata=None, exdata=None, xscale='linear', rscale='linear', iscale='linear', rlabel='Real', ilabel='Imaginary', figure='gcf', clear=1, draw=True, **kwargs): """ Plots the real and imaginary parts of complex ydata vs xdata. Parameters ---------- xdata Real-valued x-axis data ydata Complex-valued y-axis data eydata=None Complex-valued y-error exdata=None Real-valued x-error xscale='linear' 'log' or 'linear' scale of the x axis rscale='linear' 'log' or 'linear' scale of the real axis iscale='linear' 'log' or 'linear' scale of the imaginary axis rlabel='Magnitude' y-axis label for real value plot ilabel='Phase' y-axis label for imaginary value plot figure='gcf' Plot on the specified figure instance or 'gcf' for current figure. clear=1 Clear the figure? draw=True Draw the figure when completed? See spinmob.plot.xy.data() for additional optional keyword arguments. """ _pylab.ioff() # Make sure the dimensionality of the data sets matches xdata, ydata = _match_data_sets(xdata, ydata) exdata = _match_error_to_data_set(xdata, exdata) eydata = _match_error_to_data_set(ydata, eydata) # convert to real imag, and get error bars rdata = [] idata = [] erdata = [] eidata = [] for l in range(len(ydata)): rdata.append(_n.real(ydata[l])) idata.append(_n.imag(ydata[l])) if eydata[l] is None: erdata.append(None) eidata.append(None) else: erdata.append(_n.real(eydata[l])) eidata.append(_n.imag(eydata[l])) # set up the figure and axes if figure == 'gcf': f = _pylab.gcf() if clear: f.clear() axes1 = _pylab.subplot(211) axes2 = _pylab.subplot(212,sharex=axes1) if 'xlabel' in kwargs : xlabel=kwargs.pop('xlabel') else: xlabel='' if 'ylabel' in kwargs : kwargs.pop('ylabel') if 'tall' not in kwargs: kwargs['tall'] = False if 'autoformat' not in kwargs: kwargs['autoformat'] = True autoformat = kwargs['autoformat'] kwargs['autoformat'] = False kwargs['xlabel'] = '' xy_data(xdata, rdata, eydata=erdata, exdata=exdata, ylabel=rlabel, axes=axes1, clear=0, xscale=xscale, yscale=rscale, draw=False, **kwargs) kwargs['autoformat'] = autoformat kwargs['xlabel'] = xlabel xy_data(xdata, idata, eydata=eidata, exdata=exdata, ylabel=ilabel, axes=axes2, clear=0, xscale=xscale, yscale=iscale, draw=False, **kwargs) axes2.set_title('') if draw: _pylab.ion() _pylab.draw() _pylab.show()
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Plots the real and imaginary parts of complex ydata vs xdata. Parameters ---------- xdata Real-valued x-axis data ydata Complex-valued y-axis data eydata=None Complex-valued y-error exdata=None Real-valued x-error xscale='linear' 'log' or 'linear' scale of the x axis rscale='linear' 'log' or 'linear' scale of the real axis iscale='linear' 'log' or 'linear' scale of the imaginary axis rlabel='Magnitude' y-axis label for real value plot ilabel='Phase' y-axis label for imaginary value plot figure='gcf' Plot on the specified figure instance or 'gcf' for current figure. clear=1 Clear the figure? draw=True Draw the figure when completed? See spinmob.plot.xy.data() for additional optional keyword arguments.
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python
train
kolypto/py-smsframework
smsframework/providers/loopback.py
https://github.com/kolypto/py-smsframework/blob/4f3d812711f5e2e037dc80c4014c815fe2d68a0b/smsframework/providers/loopback.py#L46-L66
def received(self, src, body): """ Simulate an incoming message :type src: str :param src: Message source :type boby: str | unicode :param body: Message body :rtype: IncomingMessage """ # Create the message self._msgid += 1 message = IncomingMessage(src, body, self._msgid) # Log traffic self._traffic.append(message) # Handle it self._receive_message(message) # Finish return message
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Simulate an incoming message :type src: str :param src: Message source :type boby: str | unicode :param body: Message body :rtype: IncomingMessage
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python
test
CxAalto/gtfspy
gtfspy/stats.py
https://github.com/CxAalto/gtfspy/blob/bddba4b74faae6c1b91202f19184811e326547e5/gtfspy/stats.py#L48-L64
def get_median_lat_lon_of_stops(gtfs): """ Get median latitude AND longitude of stops Parameters ---------- gtfs: GTFS Returns ------- median_lat : float median_lon : float """ stops = gtfs.get_table("stops") median_lat = numpy.percentile(stops['lat'].values, 50) median_lon = numpy.percentile(stops['lon'].values, 50) return median_lat, median_lon
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Get median latitude AND longitude of stops Parameters ---------- gtfs: GTFS Returns ------- median_lat : float median_lon : float
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python
valid
RusticiSoftware/TinCanPython
tincan/remote_lrs.py
https://github.com/RusticiSoftware/TinCanPython/blob/424eedaa6d19221efb1108edb915fc332abbb317/tincan/remote_lrs.py#L738-L779
def retrieve_agent_profile(self, agent, profile_id): """Retrieve agent profile with the specified parameters :param agent: Agent object of the desired agent profile :type agent: :class:`tincan.agent.Agent` :param profile_id: UUID of the desired agent profile :type profile_id: str | unicode :return: LRS Response object with an agent profile doc as content :rtype: :class:`tincan.lrs_response.LRSResponse` """ if not isinstance(agent, Agent): agent = Agent(agent) request = HTTPRequest( method="GET", resource="agents/profile", ignore404=True ) request.query_params = { "profileId": profile_id, "agent": agent.to_json(self.version) } lrs_response = self._send_request(request) if lrs_response.success: doc = AgentProfileDocument( id=profile_id, content=lrs_response.data, agent=agent ) headers = lrs_response.response.getheaders() if "lastModified" in headers and headers["lastModified"] is not None: doc.timestamp = headers["lastModified"] if "contentType" in headers and headers["contentType"] is not None: doc.content_type = headers["contentType"] if "etag" in headers and headers["etag"] is not None: doc.etag = headers["etag"] lrs_response.content = doc return lrs_response
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Retrieve agent profile with the specified parameters :param agent: Agent object of the desired agent profile :type agent: :class:`tincan.agent.Agent` :param profile_id: UUID of the desired agent profile :type profile_id: str | unicode :return: LRS Response object with an agent profile doc as content :rtype: :class:`tincan.lrs_response.LRSResponse`
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python
train
saltstack/salt
salt/state.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/state.py#L586-L618
def order_chunks(self, chunks): ''' Sort the chunk list verifying that the chunks follow the order specified in the order options. ''' cap = 1 for chunk in chunks: if 'order' in chunk: if not isinstance(chunk['order'], int): continue chunk_order = chunk['order'] if chunk_order > cap - 1 and chunk_order > 0: cap = chunk_order + 100 for chunk in chunks: if 'order' not in chunk: chunk['order'] = cap continue if not isinstance(chunk['order'], (int, float)): if chunk['order'] == 'last': chunk['order'] = cap + 1000000 elif chunk['order'] == 'first': chunk['order'] = 0 else: chunk['order'] = cap if 'name_order' in chunk: chunk['order'] = chunk['order'] + chunk.pop('name_order') / 10000.0 if chunk['order'] < 0: chunk['order'] = cap + 1000000 + chunk['order'] chunk['name'] = salt.utils.data.decode(chunk['name']) chunks.sort(key=lambda chunk: (chunk['order'], '{0[state]}{0[name]}{0[fun]}'.format(chunk))) return chunks
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Sort the chunk list verifying that the chunks follow the order specified in the order options.
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python
train
wtolson/pysis
pysis/util/file_manipulation.py
https://github.com/wtolson/pysis/blob/7b907c8104bddfbb14c603de4d666c2101e1f999/pysis/util/file_manipulation.py#L11-L26
def write_file_list(filename, file_list=[], glob=None): """Write a list of files to a file. :param filename: the name of the file to write the list to :param file_list: a list of filenames to write to a file :param glob: if glob is specified, it will ignore file_list and instead create a list of files based on the pattern provide by glob (ex. *.cub) """ if glob: file_list = iglob(glob) with open(filename, 'w') as f: for line in file_list: f.write(line + '\n')
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Write a list of files to a file. :param filename: the name of the file to write the list to :param file_list: a list of filenames to write to a file :param glob: if glob is specified, it will ignore file_list and instead create a list of files based on the pattern provide by glob (ex. *.cub)
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python
train
trentm/cmdln
examples/svn.py
https://github.com/trentm/cmdln/blob/55e980cf52c9b03e62d2349a7e62c9101d08ae10/examples/svn.py#L1067-L1086
def do_switch(self, subcmd, opts, *args): """Update the working copy to a different URL. usage: 1. switch URL [PATH] 2. switch --relocate FROM TO [PATH...] 1. Update the working copy to mirror a new URL within the repository. This behaviour is similar to 'svn update', and is the way to move a working copy to a branch or tag within the same repository. 2. Rewrite working copy URL metadata to reflect a syntactic change only. This is used when repository's root URL changes (such as a schema or hostname change) but your working copy still reflects the same directory within the same repository. ${cmd_option_list} """ print "'svn %s' opts: %s" % (subcmd, opts) print "'svn %s' args: %s" % (subcmd, args)
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Update the working copy to a different URL. usage: 1. switch URL [PATH] 2. switch --relocate FROM TO [PATH...] 1. Update the working copy to mirror a new URL within the repository. This behaviour is similar to 'svn update', and is the way to move a working copy to a branch or tag within the same repository. 2. Rewrite working copy URL metadata to reflect a syntactic change only. This is used when repository's root URL changes (such as a schema or hostname change) but your working copy still reflects the same directory within the same repository. ${cmd_option_list}
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python
train
brocade/pynos
pynos/versions/ver_6/ver_6_0_1/yang/brocade_system_monitor.py
https://github.com/brocade/pynos/blob/bd8a34e98f322de3fc06750827d8bbc3a0c00380/pynos/versions/ver_6/ver_6_0_1/yang/brocade_system_monitor.py#L25-L36
def system_monitor_fan_threshold_down_threshold(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") system_monitor = ET.SubElement(config, "system-monitor", xmlns="urn:brocade.com:mgmt:brocade-system-monitor") fan = ET.SubElement(system_monitor, "fan") threshold = ET.SubElement(fan, "threshold") down_threshold = ET.SubElement(threshold, "down-threshold") down_threshold.text = kwargs.pop('down_threshold') callback = kwargs.pop('callback', self._callback) return callback(config)
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Auto Generated Code
[ "Auto", "Generated", "Code" ]
python
train
hyperledger/indy-plenum
plenum/server/node.py
https://github.com/hyperledger/indy-plenum/blob/dcd144e238af7f17a869ffc9412f13dc488b7020/plenum/server/node.py#L637-L648
def execute_pool_txns(self, three_pc_batch) -> List: """ Execute a transaction that involves consensus pool management, like adding a node, client or a steward. :param ppTime: PrePrepare request time :param reqs_keys: requests keys to be committed """ committed_txns = self.default_executer(three_pc_batch) for txn in committed_txns: self.poolManager.onPoolMembershipChange(txn) return committed_txns
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Execute a transaction that involves consensus pool management, like adding a node, client or a steward. :param ppTime: PrePrepare request time :param reqs_keys: requests keys to be committed
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python
train
apple/turicreate
src/unity/python/turicreate/toolkits/recommender/util.py
https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/toolkits/recommender/util.py#L927-L988
def get_similar_items(self, items=None, k=10, verbose=False): """ Get the k most similar items for each item in items. Each type of recommender has its own model for the similarity between items. For example, the item_similarity_recommender will return the most similar items according to the user-chosen similarity; the factorization_recommender will return the nearest items based on the cosine similarity between latent item factors. Parameters ---------- items : SArray or list; optional An :class:`~turicreate.SArray` or list of item ids for which to get similar items. If 'None', then return the `k` most similar items for all items in the training set. k : int, optional The number of similar items for each item. verbose : bool, optional Progress printing is shown. Returns ------- out : SFrame A SFrame with the top ranked similar items for each item. The columns `item`, 'similar', 'score' and 'rank', where `item` matches the item column name specified at training time. The 'rank' is between 1 and `k` and 'score' gives the similarity score of that item. The value of the score depends on the method used for computing item similarities. Examples -------- >>> sf = turicreate.SFrame({'user_id': ["0", "0", "0", "1", "1", "2", "2", "2"], 'item_id': ["a", "b", "c", "a", "b", "b", "c", "d"]}) >>> m = turicreate.item_similarity_recommender.create(sf) >>> nn = m.get_similar_items() """ if items is None: get_all_items = True items = _SArray() else: get_all_items = False if isinstance(items, list): items = _SArray(items) def check_type(arg, arg_name, required_type, allowed_types): if not isinstance(arg, required_type): raise TypeError("Parameter " + arg_name + " must be of type(s) " + (", ".join(allowed_types) ) + "; Type '" + str(type(arg)) + "' not recognized.") check_type(items, "items", _SArray, ["SArray", "list"]) check_type(k, "k", int, ["int"]) return self.__proxy__.get_similar_items(items, k, verbose, get_all_items)
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Get the k most similar items for each item in items. Each type of recommender has its own model for the similarity between items. For example, the item_similarity_recommender will return the most similar items according to the user-chosen similarity; the factorization_recommender will return the nearest items based on the cosine similarity between latent item factors. Parameters ---------- items : SArray or list; optional An :class:`~turicreate.SArray` or list of item ids for which to get similar items. If 'None', then return the `k` most similar items for all items in the training set. k : int, optional The number of similar items for each item. verbose : bool, optional Progress printing is shown. Returns ------- out : SFrame A SFrame with the top ranked similar items for each item. The columns `item`, 'similar', 'score' and 'rank', where `item` matches the item column name specified at training time. The 'rank' is between 1 and `k` and 'score' gives the similarity score of that item. The value of the score depends on the method used for computing item similarities. Examples -------- >>> sf = turicreate.SFrame({'user_id': ["0", "0", "0", "1", "1", "2", "2", "2"], 'item_id': ["a", "b", "c", "a", "b", "b", "c", "d"]}) >>> m = turicreate.item_similarity_recommender.create(sf) >>> nn = m.get_similar_items()
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python
train
jim-easterbrook/pyctools
src/pyctools/core/frame.py
https://github.com/jim-easterbrook/pyctools/blob/2a958665326892f45f249bebe62c2c23f306732b/src/pyctools/core/frame.py#L324-L342
def get(self, tag, default=None): """Get a metadata value. Each metadata value is referenced by a ``tag`` -- a short string such as ``'xlen'`` or ``'audit'``. In the sidecar file these tag names are prepended with ``'Xmp.pyctools.'``, which corresponds to a custom namespace in the XML file. :param str tag: The tag name. :returns: The metadata value associated with ``tag``. :rtype: :py:class:`str` """ full_tag = 'Xmp.pyctools.' + tag if full_tag in self.data: return self.data[full_tag] return default
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Get a metadata value. Each metadata value is referenced by a ``tag`` -- a short string such as ``'xlen'`` or ``'audit'``. In the sidecar file these tag names are prepended with ``'Xmp.pyctools.'``, which corresponds to a custom namespace in the XML file. :param str tag: The tag name. :returns: The metadata value associated with ``tag``. :rtype: :py:class:`str`
[ "Get", "a", "metadata", "value", "." ]
python
train
ska-sa/spead2
spead2/__init__.py
https://github.com/ska-sa/spead2/blob/cac95fd01d8debaa302d2691bd26da64b7828bc6/spead2/__init__.py#L81-L97
def parse_range_list(ranges): """Split a string like 2,3-5,8,9-11 into a list of integers. This is intended to ease adding command-line options for dealing with affinity. """ if not ranges: return [] parts = ranges.split(',') out = [] for part in parts: fields = part.split('-', 1) if len(fields) == 2: start = int(fields[0]) end = int(fields[1]) out.extend(range(start, end + 1)) else: out.append(int(fields[0])) return out
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Split a string like 2,3-5,8,9-11 into a list of integers. This is intended to ease adding command-line options for dealing with affinity.
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python
train
softlayer/softlayer-python
SoftLayer/managers/block.py
https://github.com/softlayer/softlayer-python/blob/9f181be08cc3668353b05a6de0cb324f52cff6fa/SoftLayer/managers/block.py#L306-L333
def order_modified_volume(self, volume_id, new_size=None, new_iops=None, new_tier_level=None): """Places an order for modifying an existing block volume. :param volume_id: The ID of the volume to be modified :param new_size: The new size/capacity for the volume :param new_iops: The new IOPS for the volume :param new_tier_level: The new tier level for the volume :return: Returns a SoftLayer_Container_Product_Order_Receipt """ mask_items = [ 'id', 'billingItem', 'storageType[keyName]', 'capacityGb', 'provisionedIops', 'storageTierLevel', 'staasVersion', 'hasEncryptionAtRest', ] block_mask = ','.join(mask_items) volume = self.get_block_volume_details(volume_id, mask=block_mask) order = storage_utils.prepare_modify_order_object( self, volume, new_iops, new_tier_level, new_size ) return self.client.call('Product_Order', 'placeOrder', order)
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Places an order for modifying an existing block volume. :param volume_id: The ID of the volume to be modified :param new_size: The new size/capacity for the volume :param new_iops: The new IOPS for the volume :param new_tier_level: The new tier level for the volume :return: Returns a SoftLayer_Container_Product_Order_Receipt
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python
train
krukas/Trionyx
trionyx/quickstart/__init__.py
https://github.com/krukas/Trionyx/blob/edac132cc0797190153f2e60bc7e88cb50e80da6/trionyx/quickstart/__init__.py#L47-L66
def create_app(self, apps_path, name): """ Create Trionyx app in given path :param str path: path to create app in. :param str name: name of app :raises FileExistsError: """ app_path = os.path.join(apps_path, name.lower()) shutil.copytree(self.app_path, app_path) self.update_file(app_path, '__init__.py', { 'name': name.lower() }) self.update_file(app_path, 'apps.py', { 'name': name.lower(), 'verbose_name': name.capitalize() })
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Create Trionyx app in given path :param str path: path to create app in. :param str name: name of app :raises FileExistsError:
[ "Create", "Trionyx", "app", "in", "given", "path" ]
python
train
peopledoc/workalendar
workalendar/core.py
https://github.com/peopledoc/workalendar/blob/d044d5dfc1709ec388db34dab583dd554cc66c4e/workalendar/core.py#L304-L318
def get_first_weekday_after(day, weekday): """Get the first weekday after a given day. If the day is the same weekday, the same day will be returned. >>> # the first monday after Apr 1 2015 >>> Calendar.get_first_weekday_after(date(2015, 4, 1), MON) datetime.date(2015, 4, 6) >>> # the first tuesday after Apr 14 2015 >>> Calendar.get_first_weekday_after(date(2015, 4, 14), TUE) datetime.date(2015, 4, 14) """ day_delta = (weekday - day.weekday()) % 7 day = day + timedelta(days=day_delta) return day
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Get the first weekday after a given day. If the day is the same weekday, the same day will be returned. >>> # the first monday after Apr 1 2015 >>> Calendar.get_first_weekday_after(date(2015, 4, 1), MON) datetime.date(2015, 4, 6) >>> # the first tuesday after Apr 14 2015 >>> Calendar.get_first_weekday_after(date(2015, 4, 14), TUE) datetime.date(2015, 4, 14)
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python
train
Duke-GCB/DukeDSClient
ddsc/core/ignorefile.py
https://github.com/Duke-GCB/DukeDSClient/blob/117f68fb9bae82e4c81ea487ad5d61ac350f3726/ddsc/core/ignorefile.py#L47-L55
def add_filename_pattern(self, dir_name, pattern): """ Adds a Unix shell-style wildcard pattern underneath the specified directory :param dir_name: str: directory that contains the pattern :param pattern: str: Unix shell-style wildcard pattern """ full_pattern = '{}{}{}'.format(dir_name, os.sep, pattern) filename_regex = fnmatch.translate(full_pattern) self.regex_list.append(re.compile(filename_regex))
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Adds a Unix shell-style wildcard pattern underneath the specified directory :param dir_name: str: directory that contains the pattern :param pattern: str: Unix shell-style wildcard pattern
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python
train
tdryer/hangups
hangups/client.py
https://github.com/tdryer/hangups/blob/85c0bf0a57698d077461283895707260f9dbf931/hangups/client.py#L547-L552
async def get_suggested_entities(self, get_suggested_entities_request): """Return suggested contacts.""" response = hangouts_pb2.GetSuggestedEntitiesResponse() await self._pb_request('contacts/getsuggestedentities', get_suggested_entities_request, response) return response
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Return suggested contacts.
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python
valid
blue-yonder/tsfresh
tsfresh/utilities/string_manipulation.py
https://github.com/blue-yonder/tsfresh/blob/c72c9c574371cf7dd7d54e00a466792792e5d202/tsfresh/utilities/string_manipulation.py#L47-L71
def convert_to_output_format(param): """ Helper function to convert parameters to a valid string, that can be used in a column name. Does the opposite which is used in the from_columns function. The parameters are sorted by their name and written out in the form <param name>_<param value>__<param name>_<param value>__ ... If a <param_value> is a string, this method will wrap it with parenthesis ", so "<param_value>" :param param: The dictionary of parameters to write out :type param: dict :return: The string of parsed parameters :rtype: str """ def add_parenthesis_if_string_value(x): if isinstance(x, string_types): return '"' + str(x) + '"' else: return str(x) return "__".join(str(key) + "_" + add_parenthesis_if_string_value(param[key]) for key in sorted(param.keys()))
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Helper function to convert parameters to a valid string, that can be used in a column name. Does the opposite which is used in the from_columns function. The parameters are sorted by their name and written out in the form <param name>_<param value>__<param name>_<param value>__ ... If a <param_value> is a string, this method will wrap it with parenthesis ", so "<param_value>" :param param: The dictionary of parameters to write out :type param: dict :return: The string of parsed parameters :rtype: str
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python
train
nadirizr/json-logic-py
json_logic/__init__.py
https://github.com/nadirizr/json-logic-py/blob/5fda9125eab4178f8f81c7779291940e31e87bab/json_logic/__init__.py#L59-L63
def less_or_equal(a, b, *args): """Implements the '<=' operator with JS-style type coertion.""" return ( less(a, b) or soft_equals(a, b) ) and (not args or less_or_equal(b, *args))
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Implements the '<=' operator with JS-style type coertion.
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python
valid
ARMmbed/mbed-cloud-sdk-python
src/mbed_cloud/_backends/billing/apis/default_api.py
https://github.com/ARMmbed/mbed-cloud-sdk-python/blob/c0af86fb2cdd4dc7ed26f236139241067d293509/src/mbed_cloud/_backends/billing/apis/default_api.py#L414-L435
def get_service_package_quota_history(self, **kwargs): # noqa: E501 """Service package quota history. # noqa: E501 Get your quota usage history. This API is available for commercial accounts. Aggregator accounts can see own and subtenant quota usage data. History data is ordered in ascending order based on the added timestamp. **Example usage:** curl -X GET https://api.us-east-1.mbedcloud.com/v3/service-packages-quota-history -H 'authorization: Bearer {api-key}' # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass asynchronous=True >>> thread = api.get_service_package_quota_history(asynchronous=True) >>> result = thread.get() :param asynchronous bool :param int limit: Maximum amount of quota history entries contained in one paged response. :param str after: To fetch after which quota history ID. The results will contain entries after specified entry. :return: ServicePackageQuotaHistoryResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('asynchronous'): return self.get_service_package_quota_history_with_http_info(**kwargs) # noqa: E501 else: (data) = self.get_service_package_quota_history_with_http_info(**kwargs) # noqa: E501 return data
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Service package quota history. # noqa: E501 Get your quota usage history. This API is available for commercial accounts. Aggregator accounts can see own and subtenant quota usage data. History data is ordered in ascending order based on the added timestamp. **Example usage:** curl -X GET https://api.us-east-1.mbedcloud.com/v3/service-packages-quota-history -H 'authorization: Bearer {api-key}' # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass asynchronous=True >>> thread = api.get_service_package_quota_history(asynchronous=True) >>> result = thread.get() :param asynchronous bool :param int limit: Maximum amount of quota history entries contained in one paged response. :param str after: To fetch after which quota history ID. The results will contain entries after specified entry. :return: ServicePackageQuotaHistoryResponse If the method is called asynchronously, returns the request thread.
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python
train
mlavin/django-all-access
allaccess/clients.py
https://github.com/mlavin/django-all-access/blob/4b15b6c9dedf8080a7c477e0af1142c609ec5598/allaccess/clients.py#L99-L109
def get_redirect_args(self, request, callback): "Get request parameters for redirect url." callback = force_text(request.build_absolute_uri(callback)) raw_token = self.get_request_token(request, callback) token, secret = self.parse_raw_token(raw_token) if token is not None and secret is not None: request.session[self.session_key] = raw_token return { 'oauth_token': token, 'oauth_callback': callback, }
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Get request parameters for redirect url.
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python
train
vtkiorg/vtki
vtki/qt_plotting.py
https://github.com/vtkiorg/vtki/blob/5ccad7ae6d64a03e9594c9c7474c8aab3eb22dd1/vtki/qt_plotting.py#L472-L501
def update_app_icon(self): """ Update the app icon if the user is not trying to resize the window. """ if os.name == 'nt' or not hasattr(self, '_last_window_size'): # pragma: no cover # DO NOT EVEN ATTEMPT TO UPDATE ICON ON WINDOWS return cur_time = time.time() if self._last_window_size != self.window_size: # pragma: no cover # Window size hasn't remained constant since last render. # This means the user is resizing it so ignore update. pass elif ((cur_time - self._last_update_time > BackgroundPlotter.ICON_TIME_STEP) and self._last_camera_pos != self.camera_position): # its been a while since last update OR # the camera position has changed and its been at leat one second # Update app icon as preview of the window img = pad_image(self.image) qimage = QtGui.QImage(img.copy(), img.shape[1], img.shape[0], QtGui.QImage.Format_RGB888) icon = QtGui.QIcon(QtGui.QPixmap.fromImage(qimage)) self.app.setWindowIcon(icon) # Update trackers self._last_update_time = cur_time self._last_camera_pos = self.camera_position # Update trackers self._last_window_size = self.window_size
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Update the app icon if the user is not trying to resize the window.
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python
train
facelessuser/soupsieve
soupsieve/__meta__.py
https://github.com/facelessuser/soupsieve/blob/24859cc3e756ebf46b75547d49c6b4a7bf35ee82/soupsieve/__meta__.py#L157-L186
def parse_version(ver, pre=False): """Parse version into a comparable Version tuple.""" m = RE_VER.match(ver) # Handle major, minor, micro major = int(m.group('major')) minor = int(m.group('minor')) if m.group('minor') else 0 micro = int(m.group('micro')) if m.group('micro') else 0 # Handle pre releases if m.group('type'): release = PRE_REL_MAP[m.group('type')] pre = int(m.group('pre')) else: release = "final" pre = 0 # Handle development releases dev = m.group('dev') if m.group('dev') else 0 if m.group('dev'): dev = int(m.group('dev')) release = '.dev-' + release if pre else '.dev' else: dev = 0 # Handle post post = int(m.group('post')) if m.group('post') else 0 return Version(major, minor, micro, release, pre, post, dev)
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Parse version into a comparable Version tuple.
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python
train
mbj4668/pyang
pyang/translators/dsdl.py
https://github.com/mbj4668/pyang/blob/f2a5cc3142162e5b9ee4e18d154568d939ff63dd/pyang/translators/dsdl.py#L666-L680
def install_def(self, name, dstmt, def_map, interleave=False): """Install definition `name` into the appropriate dictionary. `dstmt` is the definition statement ('typedef' or 'grouping') that is to be mapped to a RELAX NG named pattern '<define name="`name`">'. `def_map` must be either `self.local_defs` or `self.global_defs`. `interleave` determines the interleave status inside the definition. """ delem = SchemaNode.define(name, interleave=interleave) delem.attr["name"] = name def_map[name] = delem if def_map is self.global_defs: self.gg_level += 1 self.handle_substmts(dstmt, delem) if def_map is self.global_defs: self.gg_level -= 1
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Install definition `name` into the appropriate dictionary. `dstmt` is the definition statement ('typedef' or 'grouping') that is to be mapped to a RELAX NG named pattern '<define name="`name`">'. `def_map` must be either `self.local_defs` or `self.global_defs`. `interleave` determines the interleave status inside the definition.
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python
train
studionow/pybrightcove
pybrightcove/config.py
https://github.com/studionow/pybrightcove/blob/19c946b689a80156e070fe9bc35589c4b768e614/pybrightcove/config.py#L40-L46
def has_option(section, name): """ Wrapper around ConfigParser's ``has_option`` method. """ cfg = ConfigParser.SafeConfigParser({"working_dir": "/tmp", "debug": "0"}) cfg.read(CONFIG_LOCATIONS) return cfg.has_option(section, name)
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Wrapper around ConfigParser's ``has_option`` method.
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python
train
klen/zeta-library
zetalibrary/main.py
https://github.com/klen/zeta-library/blob/b76f89000f467e10ddcc94aded3f6c6bf4a0e5bd/zetalibrary/main.py#L42-L58
def watch(args): " Watch directory for changes and auto pack sources " assert op.isdir(args.source), "Watch mode allowed only for directories." print 'Zeta-library v. %s watch mode' % VERSION print '================================' print 'Ctrl+C for exit\n' observer = Observer() handler = ZetaTrick(args=args) observer.schedule(handler, args.source, recursive=True) observer.start() try: while True: time.sleep(1) except KeyboardInterrupt: observer.stop() print "\nWatch mode stoped." observer.join()
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Watch directory for changes and auto pack sources
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python
train
cloudera/cm_api
python/src/cm_api/endpoints/role_config_groups.py
https://github.com/cloudera/cm_api/blob/5d2512375bd94684b4da36df9e0d9177865ffcbb/python/src/cm_api/endpoints/role_config_groups.py#L210-L219
def update_config(self, config): """ Update the group's configuration. @param config: Dictionary with configuration to update. @return: Dictionary with updated configuration. """ path = self._path() + '/config' resp = self._get_resource_root().put(path, data = config_to_json(config)) return json_to_config(resp)
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Update the group's configuration. @param config: Dictionary with configuration to update. @return: Dictionary with updated configuration.
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python
train
materialsproject/pymatgen
pymatgen/io/abinit/nodes.py
https://github.com/materialsproject/pymatgen/blob/4ca558cf72f8d5f8a1f21dfdfc0181a971c186da/pymatgen/io/abinit/nodes.py#L826-L836
def get_graphviz_dirtree(self, engine="automatic", **kwargs): """ Generate directory graph in the DOT language. The graph show the files and directories in the node workdir. Returns: graphviz.Digraph <https://graphviz.readthedocs.io/en/stable/api.html#digraph> """ if engine == "automatic": engine = "fdp" return Dirviz(self.workdir).get_cluster_graph(engine=engine, **kwargs)
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Generate directory graph in the DOT language. The graph show the files and directories in the node workdir. Returns: graphviz.Digraph <https://graphviz.readthedocs.io/en/stable/api.html#digraph>
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python
train
openeventdata/mordecai
mordecai/utilities.py
https://github.com/openeventdata/mordecai/blob/bd82b8bcc27621345c57cbe9ec7f8c8552620ffc/mordecai/utilities.py#L218-L231
def structure_results(res): """Format Elasticsearch result as Python dictionary""" out = {'hits': {'hits': []}} keys = [u'admin1_code', u'admin2_code', u'admin3_code', u'admin4_code', u'alternativenames', u'asciiname', u'cc2', u'coordinates', u'country_code2', u'country_code3', u'dem', u'elevation', u'feature_class', u'feature_code', u'geonameid', u'modification_date', u'name', u'population', u'timezone'] for i in res: i_out = {} for k in keys: i_out[k] = i[k] out['hits']['hits'].append(i_out) return out
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Format Elasticsearch result as Python dictionary
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python
train
googleapis/google-cloud-python
bigquery/google/cloud/bigquery/dbapi/_helpers.py
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/dbapi/_helpers.py#L102-L117
def to_query_parameters(parameters): """Converts DB-API parameter values into query parameters. :type parameters: Mapping[str, Any] or Sequence[Any] :param parameters: A dictionary or sequence of query parameter values. :rtype: List[google.cloud.bigquery.query._AbstractQueryParameter] :returns: A list of query parameters. """ if parameters is None: return [] if isinstance(parameters, collections_abc.Mapping): return to_query_parameters_dict(parameters) return to_query_parameters_list(parameters)
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Converts DB-API parameter values into query parameters. :type parameters: Mapping[str, Any] or Sequence[Any] :param parameters: A dictionary or sequence of query parameter values. :rtype: List[google.cloud.bigquery.query._AbstractQueryParameter] :returns: A list of query parameters.
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python
train
zeaphoo/reston
reston/core/apk.py
https://github.com/zeaphoo/reston/blob/96502487b2259572df55237c9526f92627465088/reston/core/apk.py#L290-L313
def get_app_name(self): """ Return the appname of the APK :rtype: string """ main_activity_name = self.get_main_activity() app_name = self.get_element('activity', 'label', name=main_activity_name) if not app_name: app_name = self.get_element('application', 'label') if app_name.startswith("@"): res_id = int(app_name[1:], 16) res_parser = self.get_android_resources() try: app_name = res_parser.get_resolved_res_configs( res_id, ARSCResTableConfig.default_config())[0][1] except Exception as e: anconf.warning("Exception selecting app name: %s" % e) app_name = "" return app_name
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Return the appname of the APK :rtype: string
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python
train
torfsen/service
src/service/__init__.py
https://github.com/torfsen/service/blob/d0dd824fce9237825c1943b30cd14f7b0f5957a6/src/service/__init__.py#L279-L291
def send_signal(self, s): """ Send a signal to the daemon process. The signal must have been enabled using the ``signals`` parameter of :py:meth:`Service.__init__`. Otherwise, a ``ValueError`` is raised. """ self._get_signal_event(s) # Check if signal has been enabled pid = self.get_pid() if not pid: raise ValueError('Daemon is not running.') os.kill(pid, s)
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Send a signal to the daemon process. The signal must have been enabled using the ``signals`` parameter of :py:meth:`Service.__init__`. Otherwise, a ``ValueError`` is raised.
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python
train
lextoumbourou/txstripe
txstripe/resource.py
https://github.com/lextoumbourou/txstripe/blob/a69e67f524258026fd1840655a0578311bba3b89/txstripe/resource.py#L374-L377
def invoice_items(self, **params): """Return a deferred.""" params['customer'] = self.id return InvoiceItem.all(self.api_key, **params)
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Return a deferred.
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python
train
slimkrazy/python-google-places
googleplaces/__init__.py
https://github.com/slimkrazy/python-google-places/blob/d4b7363e1655cdc091a6253379f6d2a95b827881/googleplaces/__init__.py#L741-L756
def get_details(self, language=None): """ Retrieves full information on the place matching the place_id. Stores the response in the `place` property. """ if self._place is None: if language is None: try: language = self._query_instance._request_params['language'] except KeyError: language = lang.ENGLISH place = _get_place_details( self.place_id, self._query_instance.api_key, self._query_instance.sensor, language=language) self._place = Place(self._query_instance, place)
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Retrieves full information on the place matching the place_id. Stores the response in the `place` property.
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python
train
dask/dask-ml
dask_ml/wrappers.py
https://github.com/dask/dask-ml/blob/cc4837c2c2101f9302cac38354b55754263cd1f3/dask_ml/wrappers.py#L511-L533
def _first_block(dask_object): """Extract the first block / partition from a dask object """ if isinstance(dask_object, da.Array): if dask_object.ndim > 1 and dask_object.numblocks[-1] != 1: raise NotImplementedError( "IID estimators require that the array " "blocked only along the first axis. " "Rechunk your array before fitting." ) shape = (dask_object.chunks[0][0],) if dask_object.ndim > 1: shape = shape + (dask_object.chunks[1][0],) return da.from_delayed( dask_object.to_delayed().flatten()[0], shape, dask_object.dtype ) if isinstance(dask_object, dd._Frame): return dask_object.get_partition(0) else: return dask_object
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Extract the first block / partition from a dask object
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python
train
pantsbuild/pants
src/python/pants/backend/jvm/tasks/coursier_resolve.py
https://github.com/pantsbuild/pants/blob/b72e650da0df685824ffdcc71988b8c282d0962d/src/python/pants/backend/jvm/tasks/coursier_resolve.py#L104-L185
def resolve(self, targets, compile_classpath, sources, javadoc, executor): """ This is the core function for coursier resolve. Validation strategy: 1. All targets are going through the `invalidated` to get fingerprinted in the target level. No cache is fetched at this stage because it is disabled. 2. Once each target is fingerprinted, we combine them into a `VersionedTargetSet` where they are fingerprinted together, because each run of 3rdparty resolve is context sensitive. Artifacts are stored in `VersionedTargetSet`'s results_dir, the contents are the aggregation of each coursier run happened within that context. Caching: (TODO): https://github.com/pantsbuild/pants/issues/5187 Currently it is disabled due to absolute paths in the coursier results. :param targets: a collection of targets to do 3rdparty resolve against :param compile_classpath: classpath product that holds the resolution result. IMPORTANT: this parameter will be changed. :param sources: if True, fetch sources for 3rdparty :param javadoc: if True, fetch javadoc for 3rdparty :param executor: An instance of `pants.java.executor.Executor`. If None, a subprocess executor will be assigned. :return: n/a """ manager = JarDependencyManagement.global_instance() jar_targets = manager.targets_by_artifact_set(targets) executor = executor or SubprocessExecutor(DistributionLocator.cached()) if not isinstance(executor, Executor): raise ValueError('The executor argument must be an Executor instance, given {} of type {}'.format( executor, type(executor))) for artifact_set, target_subset in jar_targets.items(): # TODO(wisechengyi): this is the only place we are using IvyUtil method, which isn't specific to ivy really. raw_jar_deps, global_excludes = IvyUtils.calculate_classpath(target_subset) # ['sources'] * False = [], ['sources'] * True = ['sources'] confs_for_fingerprint = ['sources'] * sources + ['javadoc'] * javadoc fp_strategy = CoursierResolveFingerprintStrategy(confs_for_fingerprint) compile_classpath.add_excludes_for_targets(target_subset) with self.invalidated(target_subset, invalidate_dependents=False, silent=False, fingerprint_strategy=fp_strategy) as invalidation_check: if not invalidation_check.all_vts: continue resolve_vts = VersionedTargetSet.from_versioned_targets(invalidation_check.all_vts) vt_set_results_dir = self._prepare_vts_results_dir(resolve_vts) pants_jar_base_dir = self._prepare_workdir() coursier_cache_dir = CoursierSubsystem.global_instance().get_options().cache_dir # If a report is requested, do not proceed with loading validated result. if not self.get_options().report: # Check each individual target without context first # If the individuals are valid, check them as a VersionedTargetSet if not invalidation_check.invalid_vts and resolve_vts.valid: # Load up from the results dir success = self._load_from_results_dir(compile_classpath, vt_set_results_dir, coursier_cache_dir, invalidation_check, pants_jar_base_dir) if success: return jars_to_resolve, pinned_coords = self._compute_jars_to_resolve_and_pin(raw_jar_deps, artifact_set, manager) results = self._get_result_from_coursier(jars_to_resolve, global_excludes, pinned_coords, coursier_cache_dir, sources, javadoc, executor) for conf, result_list in results.items(): for result in result_list: self._load_json_result(conf, compile_classpath, coursier_cache_dir, invalidation_check, pants_jar_base_dir, result, self._override_classifiers_for_conf(conf)) self._populate_results_dir(vt_set_results_dir, results) resolve_vts.update()
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This is the core function for coursier resolve. Validation strategy: 1. All targets are going through the `invalidated` to get fingerprinted in the target level. No cache is fetched at this stage because it is disabled. 2. Once each target is fingerprinted, we combine them into a `VersionedTargetSet` where they are fingerprinted together, because each run of 3rdparty resolve is context sensitive. Artifacts are stored in `VersionedTargetSet`'s results_dir, the contents are the aggregation of each coursier run happened within that context. Caching: (TODO): https://github.com/pantsbuild/pants/issues/5187 Currently it is disabled due to absolute paths in the coursier results. :param targets: a collection of targets to do 3rdparty resolve against :param compile_classpath: classpath product that holds the resolution result. IMPORTANT: this parameter will be changed. :param sources: if True, fetch sources for 3rdparty :param javadoc: if True, fetch javadoc for 3rdparty :param executor: An instance of `pants.java.executor.Executor`. If None, a subprocess executor will be assigned. :return: n/a
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python
train
mrstephenneal/dirutility
dirutility/walk/walk.py
https://github.com/mrstephenneal/dirutility/blob/339378659e2d7e09c53acfc51c5df745bb0cd517/dirutility/walk/walk.py#L35-L49
def pool_process(func, iterable, process_name='Pool processing', cpus=cpu_count()): """ Apply a function to each element in an iterable and return a result list. :param func: A function that returns a value :param iterable: A list or set of elements to be passed to the func as the singular parameter :param process_name: Name of the process, for printing purposes only :param cpus: Number of CPUs :return: Result list """ with Timer('\t{0} ({1}) completed in'.format(process_name, str(func))): pool = Pool(cpus) vals = pool.map(func, iterable) pool.close() return vals
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Apply a function to each element in an iterable and return a result list. :param func: A function that returns a value :param iterable: A list or set of elements to be passed to the func as the singular parameter :param process_name: Name of the process, for printing purposes only :param cpus: Number of CPUs :return: Result list
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python
train
Antidote1911/cryptoshop
cryptoshop/_chunk_engine.py
https://github.com/Antidote1911/cryptoshop/blob/0b7ff4a6848f2733f4737606957e8042a4d6ca0b/cryptoshop/_chunk_engine.py#L39-L64
def encry_decry_chunk(chunk, key, algo, bool_encry, assoc_data): """ When bool_encry is True, encrypt a chunk of the file with the key and a randomly generated nonce. When it is False, the function extract the nonce from the cipherchunk (first 16 bytes), and decrypt the rest of the chunk. :param chunk: a chunk in bytes to encrypt or decrypt. :param key: a 32 bytes key in bytes. :param algo: a string of algorithm. Can be "srp" , "AES" or "twf" :param bool_encry: if bool_encry is True, chunk is encrypted. Else, it will be decrypted. :param assoc_data: bytes string of additional data for GCM Authentication. :return: if bool_encry is True, corresponding nonce + cipherchunk else, a decrypted chunk. """ engine = botan.cipher(algo=algo, encrypt=bool_encry) engine.set_key(key=key) engine.set_assoc_data(assoc_data) if bool_encry is True: nonce = generate_nonce_timestamp() engine.start(nonce=nonce) return nonce + engine.finish(chunk) else: nonce = chunk[:__nonce_length__] encryptedchunk = chunk[__nonce_length__:__nonce_length__ + __gcmtag_length__ + __chunk_size__] engine.start(nonce=nonce) decryptedchunk = engine.finish(encryptedchunk) if decryptedchunk == b"": raise Exception("Integrity failure: Invalid passphrase or corrupted data") return decryptedchunk
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When bool_encry is True, encrypt a chunk of the file with the key and a randomly generated nonce. When it is False, the function extract the nonce from the cipherchunk (first 16 bytes), and decrypt the rest of the chunk. :param chunk: a chunk in bytes to encrypt or decrypt. :param key: a 32 bytes key in bytes. :param algo: a string of algorithm. Can be "srp" , "AES" or "twf" :param bool_encry: if bool_encry is True, chunk is encrypted. Else, it will be decrypted. :param assoc_data: bytes string of additional data for GCM Authentication. :return: if bool_encry is True, corresponding nonce + cipherchunk else, a decrypted chunk.
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python
train
tjcsl/cslbot
cslbot/helpers/handler.py
https://github.com/tjcsl/cslbot/blob/aebe07be47141f61d7c180706bddfb707f19b2b5/cslbot/helpers/handler.py#L376-L398
def do_args(self, modargs, send, nick, target, source, name, msgtype): """Handle the various args that modules need.""" realargs = {} args = { 'nick': nick, 'handler': self, 'db': None, 'config': self.config, 'source': source, 'name': name, 'type': msgtype, 'botnick': self.connection.real_nickname, 'target': target if target[0] == "#" else "private", 'do_kick': lambda target, nick, msg: self.do_kick(send, target, nick, msg), 'is_admin': lambda nick: self.is_admin(send, nick), 'abuse': lambda nick, limit, cmd: self.abusecheck(send, nick, target, limit, cmd) } for arg in modargs: if arg in args: realargs[arg] = args[arg] else: raise Exception("Invalid Argument: %s" % arg) return realargs
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Handle the various args that modules need.
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python
train
brocade/pynos
pynos/versions/ver_7/ver_7_1_0/yang/brocade_vswitch.py
https://github.com/brocade/pynos/blob/bd8a34e98f322de3fc06750827d8bbc3a0c00380/pynos/versions/ver_7/ver_7_1_0/yang/brocade_vswitch.py#L929-L940
def get_vnetwork_portgroups_output_instance_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vnetwork_portgroups = ET.Element("get_vnetwork_portgroups") config = get_vnetwork_portgroups output = ET.SubElement(get_vnetwork_portgroups, "output") instance_id = ET.SubElement(output, "instance-id") instance_id.text = kwargs.pop('instance_id') callback = kwargs.pop('callback', self._callback) return callback(config)
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Auto Generated Code
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python
train
sludgedesk/metoffer
metoffer.py
https://github.com/sludgedesk/metoffer/blob/449748d31f913d961d6f0406542bb784e931a95b/metoffer.py#L179-L188
def _query(self, data_category, resource_category, field, request, step, isotime=None): """ Request and return data from DataPoint RESTful API. """ rest_url = "/".join([HOST, data_category, resource_category, field, DATA_TYPE, request]) query_string = "?" + "&".join(["res=" + step, "time=" + isotime if isotime is not None else "", "key=" + self.key]) url = rest_url + query_string page = url_lib.urlopen(url) pg = page.read() return pg
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Request and return data from DataPoint RESTful API.
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python
train
SHDShim/pytheos
pytheos/eqn_hugoniot.py
https://github.com/SHDShim/pytheos/blob/be079624405e92fbec60c5ead253eb5917e55237/pytheos/eqn_hugoniot.py#L10-L22
def hugoniot_p(rho, rho0, c0, s): """ calculate pressure along a Hugoniot :param rho: density in g/cm^3 :param rho0: density at 1 bar in g/cm^3 :param c0: velocity at 1 bar in km/s :param s: slope of the velocity change :return: pressure in GPa """ eta = 1. - (rho0 / rho) Ph = rho0 * c0 * c0 * eta / np.power((1. - s * eta), 2.) return Ph
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calculate pressure along a Hugoniot :param rho: density in g/cm^3 :param rho0: density at 1 bar in g/cm^3 :param c0: velocity at 1 bar in km/s :param s: slope of the velocity change :return: pressure in GPa
[ "calculate", "pressure", "along", "a", "Hugoniot" ]
python
train
garnertb/django-classification-banner
django_classification_banner/context_processors.py
https://github.com/garnertb/django-classification-banner/blob/dfe47e510efcce7eb0023e0d756eb2a0906bf9af/django_classification_banner/context_processors.py#L4-L17
def classification(request): """ Adds classification context to views. """ ctx = { 'classification_text': getattr(settings, 'CLASSIFICATION_TEXT', 'UNCLASSIFIED'), 'classification_text_color': getattr(settings, 'CLASSIFICATION_TEXT_COLOR', 'white'), 'classification_background_color': getattr(settings, 'CLASSIFICATION_BACKGROUND_COLOR', 'green'), 'classification_banner_enabled': getattr(settings, 'CLASSIFICATION_BANNER_ENABLED', True), 'classification_link': getattr(settings, 'CLASSIFICATION_LINK', None) } return ctx
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Adds classification context to views.
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python
train
juju-solutions/charms.reactive
charms/reactive/relations.py
https://github.com/juju-solutions/charms.reactive/blob/e37e781432e77c12b63d2c739bd6cd70d3230c3a/charms/reactive/relations.py#L413-L436
def conversation(self, scope=None): """ Get a single conversation, by scope, that this relation is currently handling. If the scope is not given, the correct scope is inferred by the current hook execution context. If there is no current hook execution context, it is assume that there is only a single global conversation scope for this relation. If this relation's scope is not global and there is no current hook execution context, then an error is raised. """ if scope is None: if self.scope is scopes.UNIT: scope = hookenv.remote_unit() elif self.scope is scopes.SERVICE: scope = hookenv.remote_service_name() else: scope = self.scope if scope is None: raise ValueError('Unable to determine default scope: no current hook or global scope') for conversation in self._conversations: if conversation.scope == scope: return conversation else: raise ValueError("Conversation with scope '%s' not found" % scope)
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Get a single conversation, by scope, that this relation is currently handling. If the scope is not given, the correct scope is inferred by the current hook execution context. If there is no current hook execution context, it is assume that there is only a single global conversation scope for this relation. If this relation's scope is not global and there is no current hook execution context, then an error is raised.
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python
train
telminov/sw-django-rest-auth
sw_rest_auth/views.py
https://github.com/telminov/sw-django-rest-auth/blob/ba63b6d6c86e4325cac38ae8e2fde1501b47ce0a/sw_rest_auth/views.py#L14-L39
def check_token(request): """ Resource check is token valid. --- request_serializer: serializers.CheckToken type: username: required: true type: string description: token related user responseMessages: - code: 200 message: Token is valid - code: 400 message: Token is not valid - code: 401 message: Unauthorized """ serializer = serializers.CheckToken(data=request.data) serializer.is_valid(raise_exception=True) token = serializer.validated_data['token'] logger.debug('Token correct', extra={'token': token, 'username': token.user.username}) return Response({'username': token.user.username})
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Resource check is token valid. --- request_serializer: serializers.CheckToken type: username: required: true type: string description: token related user responseMessages: - code: 200 message: Token is valid - code: 400 message: Token is not valid - code: 401 message: Unauthorized
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python
train
brechtm/rinohtype
src/rinoh/backend/pdf/xobject/purepng.py
https://github.com/brechtm/rinohtype/blob/40a63c4e5ad7550f62b6860f1812cb67cafb9dc7/src/rinoh/backend/pdf/xobject/purepng.py#L2136-L2188
def chunk(self, seek=None, lenient=False): """ Read the next PNG chunk from the input file returns a (*chunk_type*, *data*) tuple. *chunk_type* is the chunk's type as a byte string (all PNG chunk types are 4 bytes long). *data* is the chunk's data content, as a byte string. If the optional `seek` argument is specified then it will keep reading chunks until it either runs out of file or finds the chunk_type specified by the argument. Note that in general the order of chunks in PNGs is unspecified, so using `seek` can cause you to miss chunks. If the optional `lenient` argument evaluates to `True`, checksum failures will raise warnings rather than exceptions. """ self.validate_signature() while True: # http://www.w3.org/TR/PNG/#5Chunk-layout if not self.atchunk: self.atchunk = self.chunklentype() length, chunk_type = self.atchunk self.atchunk = None data = self.file.read(length) if len(data) != length: raise ChunkError('Chunk %s too short for required %i octets.' % (chunk_type, length)) checksum = self.file.read(4) if len(checksum) != 4: raise ChunkError('Chunk %s too short for checksum.', chunk_type) if seek and chunk_type != seek: continue verify = zlib.crc32(strtobytes(chunk_type)) verify = zlib.crc32(data, verify) # Whether the output from zlib.crc32 is signed or not varies # according to hideous implementation details, see # http://bugs.python.org/issue1202 . # We coerce it to be positive here (in a way which works on # Python 2.3 and older). verify &= 2**32 - 1 verify = struct.pack('!I', verify) if checksum != verify: (a, ) = struct.unpack('!I', checksum) (b, ) = struct.unpack('!I', verify) message = "Checksum error in %s chunk: 0x%08X != 0x%08X." %\ (chunk_type, a, b) if lenient: warnings.warn(message, RuntimeWarning) else: raise ChunkError(message) return chunk_type, data
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python
train
fabaff/python-mystrom
pymystrom/bulb.py
https://github.com/fabaff/python-mystrom/blob/86410f8952104651ef76ad37c84c29740c50551e/pymystrom/bulb.py#L31-L42
def get_status(self): """Get the details from the bulb.""" try: request = requests.get( '{}/{}/'.format(self.resource, URI), timeout=self.timeout) raw_data = request.json() # Doesn't always work !!!!! #self._mac = next(iter(self.raw_data)) self.data = raw_data[self._mac] return self.data except (requests.exceptions.ConnectionError, ValueError): raise exceptions.MyStromConnectionError()
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Get the details from the bulb.
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python
train
studionow/pybrightcove
pybrightcove/video.py
https://github.com/studionow/pybrightcove/blob/19c946b689a80156e070fe9bc35589c4b768e614/pybrightcove/video.py#L701-L708
def find_by_text(text, _connection=None, page_size=100, page_number=0, sort_by=enums.DEFAULT_SORT_BY, sort_order=enums.DEFAULT_SORT_ORDER): """ List videos that match the ``text`` in title or description. """ return connection.ItemResultSet('find_videos_by_text', Video, _connection, page_size, page_number, sort_by, sort_order, text=text)
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List videos that match the ``text`` in title or description.
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python
train
auth0/auth0-python
auth0/v3/management/connections.py
https://github.com/auth0/auth0-python/blob/34adad3f342226aaaa6071387fa405ab840e5c02/auth0/v3/management/connections.py#L101-L115
def update(self, id, body): """Modifies a connection. Args: id: Id of the connection. body (dict): Specifies which fields are to be modified, and to what values. See: https://auth0.com/docs/api/management/v2#!/Connections/patch_connections_by_id Returns: The modified connection object. """ return self.client.patch(self._url(id), data=body)
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Modifies a connection. Args: id: Id of the connection. body (dict): Specifies which fields are to be modified, and to what values. See: https://auth0.com/docs/api/management/v2#!/Connections/patch_connections_by_id Returns: The modified connection object.
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python
train
m32/endesive
endesive/pdf/fpdf/fpdf.py
https://github.com/m32/endesive/blob/973091dc69847fe2df594c80ac9235a8d08460ff/endesive/pdf/fpdf/fpdf.py#L958-L1022
def image(self, name, x=None, y=None, w=0,h=0,type='',link=''): "Put an image on the page" if not name in self.images: #First use of image, get info if(type==''): pos=name.rfind('.') if(not pos): self.error('image file has no extension and no type was specified: '+name) type=substr(name,pos+1) type=type.lower() if(type=='jpg' or type=='jpeg'): info=self._parsejpg(name) elif(type=='png'): info=self._parsepng(name) else: #Allow for additional formats #maybe the image is not showing the correct extension, #but the header is OK, succeed_parsing = False #try all the parsing functions parsing_functions = [self._parsejpg,self._parsepng,self._parsegif] for pf in parsing_functions: try: info = pf(name) succeed_parsing = True break; except: pass #last resource if not succeed_parsing: mtd='_parse'+type if not hasattr(self,mtd): self.error('Unsupported image type: '+type) info=getattr(self, mtd)(name) mtd='_parse'+type if not hasattr(self,mtd): self.error('Unsupported image type: '+type) info=getattr(self, mtd)(name) info['i']=len(self.images)+1 self.images[name]=info else: info=self.images[name] #Automatic width and height calculation if needed if(w==0 and h==0): #Put image at 72 dpi w=info['w']/self.k h=info['h']/self.k elif(w==0): w=h*info['w']/info['h'] elif(h==0): h=w*info['h']/info['w'] # Flowing mode if y is None: if (self.y + h > self.page_break_trigger and not self.in_footer and self.accept_page_break()): #Automatic page break x = self.x self.add_page(self.cur_orientation) self.x = x y = self.y self.y += h if x is None: x = self.x self._out(sprintf('q %.2f 0 0 %.2f %.2f %.2f cm /I%d Do Q',w*self.k,h*self.k,x*self.k,(self.h-(y+h))*self.k,info['i'])) if(link): self.link(x,y,w,h,link)
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Put an image on the page
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python
train
UCL-INGI/INGInious
inginious/backend/backend.py
https://github.com/UCL-INGI/INGInious/blob/cbda9a9c7f2b8e8eb1e6d7d51f0d18092086300c/inginious/backend/backend.py#L103-L107
async def handle_client_hello(self, client_addr, _: ClientHello): """ Handle an ClientHello message. Send available containers to the client """ self._logger.info("New client connected %s", client_addr) self._registered_clients.add(client_addr) await self.send_container_update_to_client([client_addr])
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Handle an ClientHello message. Send available containers to the client
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python
train
insomnia-lab/libreant
libreantdb/api.py
https://github.com/insomnia-lab/libreant/blob/55d529435baf4c05a86b8341899e9f5e14e50245/libreantdb/api.py#L186-L209
def create_index(self, indexname=None, index_conf=None): ''' Create the index Create the index with given configuration. If `indexname` is provided it will be used as the new index name instead of the class one (:py:attr:`DB.index_name`) :param index_conf: configuration to be used in index creation. If this is not specified the default index configuration will be used. :raises Exception: if the index already exists. ''' if indexname is None: indexname = self.index_name log.debug("Creating new index: '{0}'".format(indexname)) if index_conf is None: index_conf = {'settings': self.settings, 'mappings': {'book': {'properties': self.properties}}} try: self.es.indices.create(index=indexname, body=index_conf) except TransportError as te: if te.error.startswith("IndexAlreadyExistsException"): raise Exception("Cannot create index '{}', already exists".format(indexname)) else: raise
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Create the index Create the index with given configuration. If `indexname` is provided it will be used as the new index name instead of the class one (:py:attr:`DB.index_name`) :param index_conf: configuration to be used in index creation. If this is not specified the default index configuration will be used. :raises Exception: if the index already exists.
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python
train
saltstack/salt
salt/loader.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/loader.py#L1067-L1076
def cache(opts, serial): ''' Returns the returner modules ''' return LazyLoader( _module_dirs(opts, 'cache', 'cache'), opts, tag='cache', pack={'__opts__': opts, '__context__': {'serial': serial}}, )
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Returns the returner modules
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python
train