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def _create_values_table(self): """Create table lexem_type->{identificator->vocabulary}, and return it with sizes of an identificator as lexem_type->identificator_size""" # number of existing character, and returned dicts len_alph = len(self.alphabet) identificators_table = {k:{} for k in self.voc_values.keys()} identificators_sizes = {k:-1 for k in self.voc_values.keys()} for lexem_type, vocabulary in self.voc_values.items(): # find number of different values that can be found, # and size of an identificator. len_vocb = len(vocabulary) identificators_sizes[lexem_type] = ceil(log(len_vocb, len_alph)) # create list of possible identificators num2alph = lambda x, n: self.alphabet[(x // len_alph**n) % len_alph] identificators = [[str(num2alph(x, n)) for n in range(identificators_sizes[lexem_type]) ] # this list is an identificator for x in range(len_alph**identificators_sizes[lexem_type]) ] # this one is a list of identificator # initialize iterable zip_id_voc = zip_longest( identificators, vocabulary, fillvalue=None ) # create dict {identificator:word} for idt, voc in zip_id_voc: identificators_table[lexem_type][''.join(idt)] = voc # return all return identificators_table, identificators_sizes
Create table lexem_type->{identificator->vocabulary}, and return it with sizes of an identificator as lexem_type->identificator_size
Below is the the instruction that describes the task: ### Input: Create table lexem_type->{identificator->vocabulary}, and return it with sizes of an identificator as lexem_type->identificator_size ### Response: def _create_values_table(self): """Create table lexem_type->{identificator->vocabulary}, and return it with sizes of an identificator as lexem_type->identificator_size""" # number of existing character, and returned dicts len_alph = len(self.alphabet) identificators_table = {k:{} for k in self.voc_values.keys()} identificators_sizes = {k:-1 for k in self.voc_values.keys()} for lexem_type, vocabulary in self.voc_values.items(): # find number of different values that can be found, # and size of an identificator. len_vocb = len(vocabulary) identificators_sizes[lexem_type] = ceil(log(len_vocb, len_alph)) # create list of possible identificators num2alph = lambda x, n: self.alphabet[(x // len_alph**n) % len_alph] identificators = [[str(num2alph(x, n)) for n in range(identificators_sizes[lexem_type]) ] # this list is an identificator for x in range(len_alph**identificators_sizes[lexem_type]) ] # this one is a list of identificator # initialize iterable zip_id_voc = zip_longest( identificators, vocabulary, fillvalue=None ) # create dict {identificator:word} for idt, voc in zip_id_voc: identificators_table[lexem_type][''.join(idt)] = voc # return all return identificators_table, identificators_sizes
def _parse_summary_frames(self, file_obj): """Iterate through the byte data and fill the summary_frames""" for _ in range(self.n_summary_frames): dom_id = unpack('<i', file_obj.read(4))[0] dq_status = file_obj.read(4) # probably dom status? # noqa dom_status = unpack('<iiii', file_obj.read(16)) raw_rates = unpack('b' * 31, file_obj.read(31)) pmt_rates = [self._get_rate(value) for value in raw_rates] self.summary_frames[dom_id] = pmt_rates self.dq_status[dom_id] = dq_status self.dom_status[dom_id] = dom_status self.dom_rates[dom_id] = np.sum(pmt_rates)
Iterate through the byte data and fill the summary_frames
Below is the the instruction that describes the task: ### Input: Iterate through the byte data and fill the summary_frames ### Response: def _parse_summary_frames(self, file_obj): """Iterate through the byte data and fill the summary_frames""" for _ in range(self.n_summary_frames): dom_id = unpack('<i', file_obj.read(4))[0] dq_status = file_obj.read(4) # probably dom status? # noqa dom_status = unpack('<iiii', file_obj.read(16)) raw_rates = unpack('b' * 31, file_obj.read(31)) pmt_rates = [self._get_rate(value) for value in raw_rates] self.summary_frames[dom_id] = pmt_rates self.dq_status[dom_id] = dq_status self.dom_status[dom_id] = dom_status self.dom_rates[dom_id] = np.sum(pmt_rates)
def val_xml(self): """ Return the unicode XML snippet for the ``<c:val>`` element describing this series, containing the series values and their spreadsheet range reference. """ return self._val_tmpl.format(**{ 'nsdecls': '', 'values_ref': self._series.values_ref, 'number_format': self._series.number_format, 'val_count': len(self._series), 'val_pt_xml': self._val_pt_xml, })
Return the unicode XML snippet for the ``<c:val>`` element describing this series, containing the series values and their spreadsheet range reference.
Below is the the instruction that describes the task: ### Input: Return the unicode XML snippet for the ``<c:val>`` element describing this series, containing the series values and their spreadsheet range reference. ### Response: def val_xml(self): """ Return the unicode XML snippet for the ``<c:val>`` element describing this series, containing the series values and their spreadsheet range reference. """ return self._val_tmpl.format(**{ 'nsdecls': '', 'values_ref': self._series.values_ref, 'number_format': self._series.number_format, 'val_count': len(self._series), 'val_pt_xml': self._val_pt_xml, })
def detect_cid_in_current_path(i): """ Input: { (path) - path, otherwise current directory } Output: { return - return code = 0, if successful > 0, if error (error) - error text if return > 0 repo_uoa - repo UOA repo_uid - repo UID repo_alias - repo alias (module_uoa) - module UOA (module_uid) - module UID (module_alias) - module alias (data_uoa) - data UOA (data_uid) - data UID (data_alias) - data alias } """ p=i.get('path','') if p=='': p=os.getcwd() p=os.path.normpath(p) dirs=[] p1='' pr='*' found=False while pr!='': p1=os.path.join(p, cfg['repo_file']) if os.path.isfile(p1): found=True break p2=os.path.split(p) p=p2[0] pr=p2[1] dirs.append(pr) if not found: return {'return':16, 'error':'repository is not detected in the current path'} # Find info about repo (prepared as return dict) r=find_repo_by_path({'path':p}) if r['return']>0: return r # Check info about module ld=len(dirs) if ld>0: m=dirs[ld-1] rx=find_path_to_entry({'path':p, 'data_uoa':m}) if rx['return']>0 and rx['return']!=16: return rx elif rx['return']==0: r['module_uoa']=rx['data_uoa'] r['module_uid']=rx['data_uid'] r['module_alias']=rx['data_alias'] # Check info about data if ld>1: d=dirs[ld-2] rx=find_path_to_entry({'path':os.path.join(p,m), 'data_uoa':d}) if rx['return']>0 and rx['return']!=16: return rx elif rx['return']==0: r['data_uoa']=rx['data_uoa'] r['data_uid']=rx['data_uid'] r['data_alias']=rx['data_alias'] return r
Input: { (path) - path, otherwise current directory } Output: { return - return code = 0, if successful > 0, if error (error) - error text if return > 0 repo_uoa - repo UOA repo_uid - repo UID repo_alias - repo alias (module_uoa) - module UOA (module_uid) - module UID (module_alias) - module alias (data_uoa) - data UOA (data_uid) - data UID (data_alias) - data alias }
Below is the the instruction that describes the task: ### Input: Input: { (path) - path, otherwise current directory } Output: { return - return code = 0, if successful > 0, if error (error) - error text if return > 0 repo_uoa - repo UOA repo_uid - repo UID repo_alias - repo alias (module_uoa) - module UOA (module_uid) - module UID (module_alias) - module alias (data_uoa) - data UOA (data_uid) - data UID (data_alias) - data alias } ### Response: def detect_cid_in_current_path(i): """ Input: { (path) - path, otherwise current directory } Output: { return - return code = 0, if successful > 0, if error (error) - error text if return > 0 repo_uoa - repo UOA repo_uid - repo UID repo_alias - repo alias (module_uoa) - module UOA (module_uid) - module UID (module_alias) - module alias (data_uoa) - data UOA (data_uid) - data UID (data_alias) - data alias } """ p=i.get('path','') if p=='': p=os.getcwd() p=os.path.normpath(p) dirs=[] p1='' pr='*' found=False while pr!='': p1=os.path.join(p, cfg['repo_file']) if os.path.isfile(p1): found=True break p2=os.path.split(p) p=p2[0] pr=p2[1] dirs.append(pr) if not found: return {'return':16, 'error':'repository is not detected in the current path'} # Find info about repo (prepared as return dict) r=find_repo_by_path({'path':p}) if r['return']>0: return r # Check info about module ld=len(dirs) if ld>0: m=dirs[ld-1] rx=find_path_to_entry({'path':p, 'data_uoa':m}) if rx['return']>0 and rx['return']!=16: return rx elif rx['return']==0: r['module_uoa']=rx['data_uoa'] r['module_uid']=rx['data_uid'] r['module_alias']=rx['data_alias'] # Check info about data if ld>1: d=dirs[ld-2] rx=find_path_to_entry({'path':os.path.join(p,m), 'data_uoa':d}) if rx['return']>0 and rx['return']!=16: return rx elif rx['return']==0: r['data_uoa']=rx['data_uoa'] r['data_uid']=rx['data_uid'] r['data_alias']=rx['data_alias'] return r
def add_from_child(self, resource, **kwargs): """ Add a resource with its all children resources to the current resource. """ new_resource = self.add( resource.member_name, resource.collection_name, **kwargs) for child in resource.children: new_resource.add_from_child(child, **kwargs)
Add a resource with its all children resources to the current resource.
Below is the the instruction that describes the task: ### Input: Add a resource with its all children resources to the current resource. ### Response: def add_from_child(self, resource, **kwargs): """ Add a resource with its all children resources to the current resource. """ new_resource = self.add( resource.member_name, resource.collection_name, **kwargs) for child in resource.children: new_resource.add_from_child(child, **kwargs)
def do_query(self, args): """Query resource in use: query *IDN? """ if not self.current: print('There are no resources in use. Use the command "open".') return try: print('Response: {}'.format(self.current.query(args))) except Exception as e: print(e)
Query resource in use: query *IDN?
Below is the the instruction that describes the task: ### Input: Query resource in use: query *IDN? ### Response: def do_query(self, args): """Query resource in use: query *IDN? """ if not self.current: print('There are no resources in use. Use the command "open".') return try: print('Response: {}'.format(self.current.query(args))) except Exception as e: print(e)
def _create_producer(self): """Tries to establish a Kafka consumer connection""" if not self.closed: try: self.logger.debug("Creating new kafka producer using brokers: " + str(self.settings['KAFKA_HOSTS'])) return KafkaProducer(bootstrap_servers=self.settings['KAFKA_HOSTS'], value_serializer=lambda v: json.dumps(v).encode('utf-8'), retries=3, linger_ms=self.settings['KAFKA_PRODUCER_BATCH_LINGER_MS'], buffer_memory=self.settings['KAFKA_PRODUCER_BUFFER_BYTES']) except KeyError as e: self.logger.error('Missing setting named ' + str(e), {'ex': traceback.format_exc()}) except: self.logger.error("Couldn't initialize kafka producer.", {'ex': traceback.format_exc()}) raise
Tries to establish a Kafka consumer connection
Below is the the instruction that describes the task: ### Input: Tries to establish a Kafka consumer connection ### Response: def _create_producer(self): """Tries to establish a Kafka consumer connection""" if not self.closed: try: self.logger.debug("Creating new kafka producer using brokers: " + str(self.settings['KAFKA_HOSTS'])) return KafkaProducer(bootstrap_servers=self.settings['KAFKA_HOSTS'], value_serializer=lambda v: json.dumps(v).encode('utf-8'), retries=3, linger_ms=self.settings['KAFKA_PRODUCER_BATCH_LINGER_MS'], buffer_memory=self.settings['KAFKA_PRODUCER_BUFFER_BYTES']) except KeyError as e: self.logger.error('Missing setting named ' + str(e), {'ex': traceback.format_exc()}) except: self.logger.error("Couldn't initialize kafka producer.", {'ex': traceback.format_exc()}) raise
def allowance(self, filename): """Preconditions: - our agent applies to this entry - filename is URL decoded""" for line in self.rulelines: if line.applies_to(filename): return line.allowance return True
Preconditions: - our agent applies to this entry - filename is URL decoded
Below is the the instruction that describes the task: ### Input: Preconditions: - our agent applies to this entry - filename is URL decoded ### Response: def allowance(self, filename): """Preconditions: - our agent applies to this entry - filename is URL decoded""" for line in self.rulelines: if line.applies_to(filename): return line.allowance return True
def find_company(cmp_id=None, cmp_name=None): """ find the company according company id (prioritary) or company name :param cmp_id: the company id :param cmp_name: the company name :return: found company or None if not found """ LOGGER.debug("CompanyService.find_company") if (cmp_id is None or not cmp_id) and (cmp_name is None or not cmp_name): raise exceptions.ArianeCallParametersError('id and name') if (cmp_id is not None and cmp_id) and (cmp_name is not None and cmp_name): LOGGER.warn('CompanyService.find_company - Both id and name are defined. Will give you search on id.') cmp_name = None params = None if cmp_id is not None and cmp_id: params = {'id': cmp_id} elif cmp_name is not None and cmp_name: params = {'name': cmp_name} ret = None if params is not None: args = {'http_operation': 'GET', 'operation_path': 'get', 'parameters': params} response = CompanyService.requester.call(args) if response.rc == 0: ret = Company.json_2_company(response.response_content) elif response.rc != 404: err_msg = 'CompanyService.find_company - Problem while finding company (id:' + str(cmp_id) + \ ', name:' + str(cmp_name) + '). ' + \ 'Reason: ' + str(response.response_content) + '-' + str(response.error_message) + \ " (" + str(response.rc) + ")" LOGGER.warning( err_msg ) return ret
find the company according company id (prioritary) or company name :param cmp_id: the company id :param cmp_name: the company name :return: found company or None if not found
Below is the the instruction that describes the task: ### Input: find the company according company id (prioritary) or company name :param cmp_id: the company id :param cmp_name: the company name :return: found company or None if not found ### Response: def find_company(cmp_id=None, cmp_name=None): """ find the company according company id (prioritary) or company name :param cmp_id: the company id :param cmp_name: the company name :return: found company or None if not found """ LOGGER.debug("CompanyService.find_company") if (cmp_id is None or not cmp_id) and (cmp_name is None or not cmp_name): raise exceptions.ArianeCallParametersError('id and name') if (cmp_id is not None and cmp_id) and (cmp_name is not None and cmp_name): LOGGER.warn('CompanyService.find_company - Both id and name are defined. Will give you search on id.') cmp_name = None params = None if cmp_id is not None and cmp_id: params = {'id': cmp_id} elif cmp_name is not None and cmp_name: params = {'name': cmp_name} ret = None if params is not None: args = {'http_operation': 'GET', 'operation_path': 'get', 'parameters': params} response = CompanyService.requester.call(args) if response.rc == 0: ret = Company.json_2_company(response.response_content) elif response.rc != 404: err_msg = 'CompanyService.find_company - Problem while finding company (id:' + str(cmp_id) + \ ', name:' + str(cmp_name) + '). ' + \ 'Reason: ' + str(response.response_content) + '-' + str(response.error_message) + \ " (" + str(response.rc) + ")" LOGGER.warning( err_msg ) return ret
def options_handler(self, sock, cmd, opt): "Negotiate options" if cmd == NOP: self.sendcommand(NOP) elif cmd == WILL or cmd == WONT: if self.WILLACK.has_key(opt): self.sendcommand(self.WILLACK[opt], opt) else: self.sendcommand(DONT, opt) if cmd == WILL and opt == TTYPE: self.writecooked(IAC + SB + TTYPE + SEND + IAC + SE) elif cmd == DO or cmd == DONT: if self.DOACK.has_key(opt): self.sendcommand(self.DOACK[opt], opt) else: self.sendcommand(WONT, opt) if opt == ECHO: self.DOECHO = (cmd == DO) elif cmd == SE: subreq = self.read_sb_data() if subreq[0] == TTYPE and subreq[1] == IS: try: self.setterm(subreq[2:]) except: log.debug("Terminal type not known") elif subreq[0] == NAWS: self.setnaws(subreq[1:]) elif cmd == SB: pass else: log.debug("Unhandled option: %s %s" % (cmdtxt, opttxt, ))
Negotiate options
Below is the the instruction that describes the task: ### Input: Negotiate options ### Response: def options_handler(self, sock, cmd, opt): "Negotiate options" if cmd == NOP: self.sendcommand(NOP) elif cmd == WILL or cmd == WONT: if self.WILLACK.has_key(opt): self.sendcommand(self.WILLACK[opt], opt) else: self.sendcommand(DONT, opt) if cmd == WILL and opt == TTYPE: self.writecooked(IAC + SB + TTYPE + SEND + IAC + SE) elif cmd == DO or cmd == DONT: if self.DOACK.has_key(opt): self.sendcommand(self.DOACK[opt], opt) else: self.sendcommand(WONT, opt) if opt == ECHO: self.DOECHO = (cmd == DO) elif cmd == SE: subreq = self.read_sb_data() if subreq[0] == TTYPE and subreq[1] == IS: try: self.setterm(subreq[2:]) except: log.debug("Terminal type not known") elif subreq[0] == NAWS: self.setnaws(subreq[1:]) elif cmd == SB: pass else: log.debug("Unhandled option: %s %s" % (cmdtxt, opttxt, ))
def create_attribute_query(self, destination, name_id=None, attribute=None, message_id=0, consent=None, extensions=None, sign=False, sign_prepare=False, sign_alg=None, digest_alg=None, **kwargs): """ Constructs an AttributeQuery :param destination: To whom the query should be sent :param name_id: The identifier of the subject :param attribute: A dictionary of attributes and values that is asked for. The key are one of 4 variants: 3-tuple of name_format,name and friendly_name, 2-tuple of name_format and name, 1-tuple with name or just the name as a string. :param sp_name_qualifier: The unique identifier of the service provider or affiliation of providers for whom the identifier was generated. :param name_qualifier: The unique identifier of the identity provider that generated the identifier. :param format: The format of the name ID :param message_id: The identifier of the session :param consent: Whether the principal have given her consent :param extensions: Possible extensions :param sign: Whether the query should be signed or not. :param sign_prepare: Whether the Signature element should be added. :return: Tuple of request ID and an AttributeQuery instance """ if name_id is None: if "subject_id" in kwargs: name_id = saml.NameID(text=kwargs["subject_id"]) for key in ["sp_name_qualifier", "name_qualifier", "format"]: try: setattr(name_id, key, kwargs[key]) except KeyError: pass else: raise AttributeError("Missing required parameter") elif isinstance(name_id, six.string_types): name_id = saml.NameID(text=name_id) for key in ["sp_name_qualifier", "name_qualifier", "format"]: try: setattr(name_id, key, kwargs[key]) except KeyError: pass subject = saml.Subject(name_id=name_id) if attribute: attribute = do_attributes(attribute) try: nsprefix = kwargs["nsprefix"] except KeyError: nsprefix = None return self._message(AttributeQuery, destination, message_id, consent, extensions, sign, sign_prepare, subject=subject, attribute=attribute, nsprefix=nsprefix, sign_alg=sign_alg, digest_alg=digest_alg)
Constructs an AttributeQuery :param destination: To whom the query should be sent :param name_id: The identifier of the subject :param attribute: A dictionary of attributes and values that is asked for. The key are one of 4 variants: 3-tuple of name_format,name and friendly_name, 2-tuple of name_format and name, 1-tuple with name or just the name as a string. :param sp_name_qualifier: The unique identifier of the service provider or affiliation of providers for whom the identifier was generated. :param name_qualifier: The unique identifier of the identity provider that generated the identifier. :param format: The format of the name ID :param message_id: The identifier of the session :param consent: Whether the principal have given her consent :param extensions: Possible extensions :param sign: Whether the query should be signed or not. :param sign_prepare: Whether the Signature element should be added. :return: Tuple of request ID and an AttributeQuery instance
Below is the the instruction that describes the task: ### Input: Constructs an AttributeQuery :param destination: To whom the query should be sent :param name_id: The identifier of the subject :param attribute: A dictionary of attributes and values that is asked for. The key are one of 4 variants: 3-tuple of name_format,name and friendly_name, 2-tuple of name_format and name, 1-tuple with name or just the name as a string. :param sp_name_qualifier: The unique identifier of the service provider or affiliation of providers for whom the identifier was generated. :param name_qualifier: The unique identifier of the identity provider that generated the identifier. :param format: The format of the name ID :param message_id: The identifier of the session :param consent: Whether the principal have given her consent :param extensions: Possible extensions :param sign: Whether the query should be signed or not. :param sign_prepare: Whether the Signature element should be added. :return: Tuple of request ID and an AttributeQuery instance ### Response: def create_attribute_query(self, destination, name_id=None, attribute=None, message_id=0, consent=None, extensions=None, sign=False, sign_prepare=False, sign_alg=None, digest_alg=None, **kwargs): """ Constructs an AttributeQuery :param destination: To whom the query should be sent :param name_id: The identifier of the subject :param attribute: A dictionary of attributes and values that is asked for. The key are one of 4 variants: 3-tuple of name_format,name and friendly_name, 2-tuple of name_format and name, 1-tuple with name or just the name as a string. :param sp_name_qualifier: The unique identifier of the service provider or affiliation of providers for whom the identifier was generated. :param name_qualifier: The unique identifier of the identity provider that generated the identifier. :param format: The format of the name ID :param message_id: The identifier of the session :param consent: Whether the principal have given her consent :param extensions: Possible extensions :param sign: Whether the query should be signed or not. :param sign_prepare: Whether the Signature element should be added. :return: Tuple of request ID and an AttributeQuery instance """ if name_id is None: if "subject_id" in kwargs: name_id = saml.NameID(text=kwargs["subject_id"]) for key in ["sp_name_qualifier", "name_qualifier", "format"]: try: setattr(name_id, key, kwargs[key]) except KeyError: pass else: raise AttributeError("Missing required parameter") elif isinstance(name_id, six.string_types): name_id = saml.NameID(text=name_id) for key in ["sp_name_qualifier", "name_qualifier", "format"]: try: setattr(name_id, key, kwargs[key]) except KeyError: pass subject = saml.Subject(name_id=name_id) if attribute: attribute = do_attributes(attribute) try: nsprefix = kwargs["nsprefix"] except KeyError: nsprefix = None return self._message(AttributeQuery, destination, message_id, consent, extensions, sign, sign_prepare, subject=subject, attribute=attribute, nsprefix=nsprefix, sign_alg=sign_alg, digest_alg=digest_alg)
def granular_markings_circular_refs(instance): """Ensure that marking definitions do not contain circular references (ie. they do not reference themselves in the `granular_markings` property). """ if instance['type'] != 'marking-definition': return if 'granular_markings' in instance: for marking in instance['granular_markings']: if 'marking_ref' in marking and marking['marking_ref'] == instance['id']: yield JSONError("`granular_markings` cannot contain any " "references to this marking definition object" " (no circular references).", instance['id'])
Ensure that marking definitions do not contain circular references (ie. they do not reference themselves in the `granular_markings` property).
Below is the the instruction that describes the task: ### Input: Ensure that marking definitions do not contain circular references (ie. they do not reference themselves in the `granular_markings` property). ### Response: def granular_markings_circular_refs(instance): """Ensure that marking definitions do not contain circular references (ie. they do not reference themselves in the `granular_markings` property). """ if instance['type'] != 'marking-definition': return if 'granular_markings' in instance: for marking in instance['granular_markings']: if 'marking_ref' in marking and marking['marking_ref'] == instance['id']: yield JSONError("`granular_markings` cannot contain any " "references to this marking definition object" " (no circular references).", instance['id'])
def fetch_captcha_store(self, name, value, attrs=None, generator=None): """ Fetches a new CaptchaStore This has to be called inside render """ try: reverse('captcha-image', args=('dummy',)) except NoReverseMatch: raise ImproperlyConfigured('Make sure you\'ve included captcha.urls as explained in the INSTALLATION section on http://readthedocs.org/docs/django-simple-captcha/en/latest/usage.html#installation') if settings.CAPTCHA_GET_FROM_POOL: key = CaptchaStore.pick() else: key = CaptchaStore.generate_key(generator) # these can be used by format_output and render self._value = [key, u('')] self._key = key self.id_ = self.build_attrs(attrs).get('id', None)
Fetches a new CaptchaStore This has to be called inside render
Below is the the instruction that describes the task: ### Input: Fetches a new CaptchaStore This has to be called inside render ### Response: def fetch_captcha_store(self, name, value, attrs=None, generator=None): """ Fetches a new CaptchaStore This has to be called inside render """ try: reverse('captcha-image', args=('dummy',)) except NoReverseMatch: raise ImproperlyConfigured('Make sure you\'ve included captcha.urls as explained in the INSTALLATION section on http://readthedocs.org/docs/django-simple-captcha/en/latest/usage.html#installation') if settings.CAPTCHA_GET_FROM_POOL: key = CaptchaStore.pick() else: key = CaptchaStore.generate_key(generator) # these can be used by format_output and render self._value = [key, u('')] self._key = key self.id_ = self.build_attrs(attrs).get('id', None)
def convert_table(shell_output, delimiter='\t|\s{2,}', output='dict'): ''' a method to convert a STDOUT shell table into a python data structure :param shell_output: string from STDOUT with headers :param delimiter: string with regex pattern delimiting headers :param output: string with type of structure to output (dict, list or csv) :return: list of dictionaries or list of lists or string with csv format ''' # retrieve header columns import re gap_pattern = re.compile(delimiter) output_lines = shell_output.splitlines() column_headers = gap_pattern.split(output_lines[0]) blank_index = column_headers.index('') if blank_index > -1: column_headers.pop(blank_index) # generate indices tuples indices = [] for i in range(len(column_headers)): if i + 1 < len(column_headers): indices.append(( output_lines[0].find(column_headers[i]), output_lines[0].find(column_headers[i + 1]) )) else: indices.append(( output_lines[0].find(column_headers[i]), -1 )) # add headers to output python_list = [] csv_string = '' if output == 'dict': pass elif output == 'list': python_list.append(column_headers) elif output == 'csv': for i in range(len(column_headers)): if i: csv_string += ',' csv_string += column_headers[i] else: raise ValueError('output argument must be one of dict, list or csv values.') # add rows to output for i in range(1, len(output_lines)): if output == 'dict': row_details = {} for j in range(len(column_headers)): row_details[column_headers[j]] = output_lines[i][indices[j][0]:indices[j][1]].rstrip() python_list.append(row_details) elif output == 'list': row_list = [] for j in range(len(column_headers)): row_list.append(output_lines[i][indices[j][0]:indices[j][1]]).rstrip() python_list.append(row_list) elif output == 'csv': csv_string += '\n' for j in range(len(column_headers)): if j: csv_string += ',' csv_string += output_lines[i][indices[j][0]:indices[j][1]].rstrip() # return output if csv_string: return csv_string return python_list
a method to convert a STDOUT shell table into a python data structure :param shell_output: string from STDOUT with headers :param delimiter: string with regex pattern delimiting headers :param output: string with type of structure to output (dict, list or csv) :return: list of dictionaries or list of lists or string with csv format
Below is the the instruction that describes the task: ### Input: a method to convert a STDOUT shell table into a python data structure :param shell_output: string from STDOUT with headers :param delimiter: string with regex pattern delimiting headers :param output: string with type of structure to output (dict, list or csv) :return: list of dictionaries or list of lists or string with csv format ### Response: def convert_table(shell_output, delimiter='\t|\s{2,}', output='dict'): ''' a method to convert a STDOUT shell table into a python data structure :param shell_output: string from STDOUT with headers :param delimiter: string with regex pattern delimiting headers :param output: string with type of structure to output (dict, list or csv) :return: list of dictionaries or list of lists or string with csv format ''' # retrieve header columns import re gap_pattern = re.compile(delimiter) output_lines = shell_output.splitlines() column_headers = gap_pattern.split(output_lines[0]) blank_index = column_headers.index('') if blank_index > -1: column_headers.pop(blank_index) # generate indices tuples indices = [] for i in range(len(column_headers)): if i + 1 < len(column_headers): indices.append(( output_lines[0].find(column_headers[i]), output_lines[0].find(column_headers[i + 1]) )) else: indices.append(( output_lines[0].find(column_headers[i]), -1 )) # add headers to output python_list = [] csv_string = '' if output == 'dict': pass elif output == 'list': python_list.append(column_headers) elif output == 'csv': for i in range(len(column_headers)): if i: csv_string += ',' csv_string += column_headers[i] else: raise ValueError('output argument must be one of dict, list or csv values.') # add rows to output for i in range(1, len(output_lines)): if output == 'dict': row_details = {} for j in range(len(column_headers)): row_details[column_headers[j]] = output_lines[i][indices[j][0]:indices[j][1]].rstrip() python_list.append(row_details) elif output == 'list': row_list = [] for j in range(len(column_headers)): row_list.append(output_lines[i][indices[j][0]:indices[j][1]]).rstrip() python_list.append(row_list) elif output == 'csv': csv_string += '\n' for j in range(len(column_headers)): if j: csv_string += ',' csv_string += output_lines[i][indices[j][0]:indices[j][1]].rstrip() # return output if csv_string: return csv_string return python_list
def plural_adj(self, text, count=None): """ Return the plural of text, where text is an adjective. If count supplied, then return text if count is one of: 1, a, an, one, each, every, this, that otherwise return the plural. Whitespace at the start and end is preserved. """ pre, word, post = self.partition_word(text) if not word: return text plural = self.postprocess(word, self._pl_special_adjective(word, count) or word) return "{}{}{}".format(pre, plural, post)
Return the plural of text, where text is an adjective. If count supplied, then return text if count is one of: 1, a, an, one, each, every, this, that otherwise return the plural. Whitespace at the start and end is preserved.
Below is the the instruction that describes the task: ### Input: Return the plural of text, where text is an adjective. If count supplied, then return text if count is one of: 1, a, an, one, each, every, this, that otherwise return the plural. Whitespace at the start and end is preserved. ### Response: def plural_adj(self, text, count=None): """ Return the plural of text, where text is an adjective. If count supplied, then return text if count is one of: 1, a, an, one, each, every, this, that otherwise return the plural. Whitespace at the start and end is preserved. """ pre, word, post = self.partition_word(text) if not word: return text plural = self.postprocess(word, self._pl_special_adjective(word, count) or word) return "{}{}{}".format(pre, plural, post)
def randdate(self, start=date(1970, 1, 1), end=date.today()): """Generate a random date between ``start`` to ``end``. :param start: Left bound :type start: string or datetime.date, (default date(1970, 1, 1)) :param end: Right bound :type end: string or datetime.date, (default date.today()) :return: a datetime.date object **中文文档** 随机生成一个位于 ``start`` 和 ``end`` 之间的日期。 """ if isinstance(start, str): start = self.str2date(start) if isinstance(end, str): end = self.str2date(end) if start > end: raise Exception("start must be smaller than end! " "your start=%s, end=%s" % (start, end)) return date.fromordinal(random.randint(start.toordinal(), end.toordinal()))
Generate a random date between ``start`` to ``end``. :param start: Left bound :type start: string or datetime.date, (default date(1970, 1, 1)) :param end: Right bound :type end: string or datetime.date, (default date.today()) :return: a datetime.date object **中文文档** 随机生成一个位于 ``start`` 和 ``end`` 之间的日期。
Below is the the instruction that describes the task: ### Input: Generate a random date between ``start`` to ``end``. :param start: Left bound :type start: string or datetime.date, (default date(1970, 1, 1)) :param end: Right bound :type end: string or datetime.date, (default date.today()) :return: a datetime.date object **中文文档** 随机生成一个位于 ``start`` 和 ``end`` 之间的日期。 ### Response: def randdate(self, start=date(1970, 1, 1), end=date.today()): """Generate a random date between ``start`` to ``end``. :param start: Left bound :type start: string or datetime.date, (default date(1970, 1, 1)) :param end: Right bound :type end: string or datetime.date, (default date.today()) :return: a datetime.date object **中文文档** 随机生成一个位于 ``start`` 和 ``end`` 之间的日期。 """ if isinstance(start, str): start = self.str2date(start) if isinstance(end, str): end = self.str2date(end) if start > end: raise Exception("start must be smaller than end! " "your start=%s, end=%s" % (start, end)) return date.fromordinal(random.randint(start.toordinal(), end.toordinal()))
def require(self, lock, guard_func, *guard_args, **guard_kw): """Decorate a function to be run only when a lock is acquired. The lock is requested if the guard function returns True. The decorated function is called if the lock has been granted. """ def decorator(f): @wraps(f) def wrapper(*args, **kw): if self.granted(lock): self.msg('Granted {}'.format(lock)) return f(*args, **kw) if guard_func(*guard_args, **guard_kw) and self.acquire(lock): return f(*args, **kw) return None return wrapper return decorator
Decorate a function to be run only when a lock is acquired. The lock is requested if the guard function returns True. The decorated function is called if the lock has been granted.
Below is the the instruction that describes the task: ### Input: Decorate a function to be run only when a lock is acquired. The lock is requested if the guard function returns True. The decorated function is called if the lock has been granted. ### Response: def require(self, lock, guard_func, *guard_args, **guard_kw): """Decorate a function to be run only when a lock is acquired. The lock is requested if the guard function returns True. The decorated function is called if the lock has been granted. """ def decorator(f): @wraps(f) def wrapper(*args, **kw): if self.granted(lock): self.msg('Granted {}'.format(lock)) return f(*args, **kw) if guard_func(*guard_args, **guard_kw) and self.acquire(lock): return f(*args, **kw) return None return wrapper return decorator
def image_task(self): """ Returns a json-schema document that represents an task entity. """ uri = "/%s/task" % self.uri_base resp, resp_body = self.api.method_get(uri) return resp_body
Returns a json-schema document that represents an task entity.
Below is the the instruction that describes the task: ### Input: Returns a json-schema document that represents an task entity. ### Response: def image_task(self): """ Returns a json-schema document that represents an task entity. """ uri = "/%s/task" % self.uri_base resp, resp_body = self.api.method_get(uri) return resp_body
def state_category(value): """Parse categories.""" if value == re.sre_parse.CATEGORY_DIGIT: return (yield '0') if value == re.sre_parse.CATEGORY_WORD: return (yield 'x')
Parse categories.
Below is the the instruction that describes the task: ### Input: Parse categories. ### Response: def state_category(value): """Parse categories.""" if value == re.sre_parse.CATEGORY_DIGIT: return (yield '0') if value == re.sre_parse.CATEGORY_WORD: return (yield 'x')
def run(self, config, workflow_id, signal, *, data=None): """ Run the dag by calling the tasks in the correct order. Args: config (Config): Reference to the configuration object from which the settings for the dag are retrieved. workflow_id (str): The unique ID of the workflow that runs this dag. signal (DagSignal): The signal object for dags. It wraps the construction and sending of signals into easy to use methods. data (MultiTaskData): The initial data that is passed on to the start tasks. Raises: DirectedAcyclicGraphInvalid: If the graph is not a dag (e.g. contains loops). ConfigNotDefinedError: If the configuration for the dag is empty. """ graph = self.make_graph(self._schema) # pre-checks self.validate(graph) if config is None: raise ConfigNotDefinedError() # create the celery app for submitting tasks celery_app = create_app(config) # the task queue for managing the current state of the tasks tasks = [] stopped = False # add all tasks without predecessors to the task list for task in nx.topological_sort(graph): task.workflow_name = self.workflow_name task.dag_name = self.name if len(list(graph.predecessors(task))) == 0: task.state = TaskState.Waiting tasks.append(task) def set_task_completed(completed_task): """ For each completed task, add all successor tasks to the task list. If they are not in the task list yet, flag them as 'waiting'. """ completed_task.state = TaskState.Completed for successor in graph.successors(completed_task): if successor not in tasks: successor.state = TaskState.Waiting tasks.append(successor) # process the task queue as long as there are tasks in it while tasks: if not stopped: stopped = signal.is_stopped # delay the execution by the polling time if config.dag_polling_time > 0.0: sleep(config.dag_polling_time) for i in range(len(tasks) - 1, -1, -1): task = tasks[i] # for each waiting task, wait for all predecessor tasks to be # completed. Then check whether the task should be skipped by # interrogating the predecessor tasks. if task.is_waiting: if stopped: task.state = TaskState.Stopped else: pre_tasks = list(graph.predecessors(task)) if all([p.is_completed for p in pre_tasks]): # check whether the task should be skipped run_task = task.has_to_run or len(pre_tasks) == 0 for pre in pre_tasks: if run_task: break # predecessor task is skipped and flag should # not be propagated if pre.is_skipped and not pre.propagate_skip: run_task = True # limits of a non-skipped predecessor task if not pre.is_skipped: if pre.celery_result.result.limit is not None: if task.name in [ n.name if isinstance(n, BaseTask) else n for n in pre.celery_result.result.limit]: run_task = True else: run_task = True task.is_skipped = not run_task # send the task to celery or, if skipped, mark it as completed if task.is_skipped: set_task_completed(task) else: # compose the input data from the predecessor tasks # output. Data from skipped predecessor tasks do not # contribute to the input data if len(pre_tasks) == 0: input_data = data else: input_data = MultiTaskData() for pt in [p for p in pre_tasks if not p.is_skipped]: slot = graph[pt][task]['slot'] input_data.add_dataset( pt.name, pt.celery_result.result.data.default_dataset, aliases=[slot] if slot is not None else None) task.state = TaskState.Running task.celery_result = celery_app.send_task( JobExecPath.Task, args=(task, workflow_id, input_data), queue=task.queue, routing_key=task.queue ) # flag task as completed elif task.is_running: if task.celery_completed: set_task_completed(task) elif task.celery_failed: task.state = TaskState.Aborted signal.stop_workflow() # cleanup task results that are not required anymore elif task.is_completed: if all([s.is_completed or s.is_stopped or s.is_aborted for s in graph.successors(task)]): if celery_app.conf.result_expires == 0: task.clear_celery_result() tasks.remove(task) # cleanup and remove stopped and aborted tasks elif task.is_stopped or task.is_aborted: if celery_app.conf.result_expires == 0: task.clear_celery_result() tasks.remove(task)
Run the dag by calling the tasks in the correct order. Args: config (Config): Reference to the configuration object from which the settings for the dag are retrieved. workflow_id (str): The unique ID of the workflow that runs this dag. signal (DagSignal): The signal object for dags. It wraps the construction and sending of signals into easy to use methods. data (MultiTaskData): The initial data that is passed on to the start tasks. Raises: DirectedAcyclicGraphInvalid: If the graph is not a dag (e.g. contains loops). ConfigNotDefinedError: If the configuration for the dag is empty.
Below is the the instruction that describes the task: ### Input: Run the dag by calling the tasks in the correct order. Args: config (Config): Reference to the configuration object from which the settings for the dag are retrieved. workflow_id (str): The unique ID of the workflow that runs this dag. signal (DagSignal): The signal object for dags. It wraps the construction and sending of signals into easy to use methods. data (MultiTaskData): The initial data that is passed on to the start tasks. Raises: DirectedAcyclicGraphInvalid: If the graph is not a dag (e.g. contains loops). ConfigNotDefinedError: If the configuration for the dag is empty. ### Response: def run(self, config, workflow_id, signal, *, data=None): """ Run the dag by calling the tasks in the correct order. Args: config (Config): Reference to the configuration object from which the settings for the dag are retrieved. workflow_id (str): The unique ID of the workflow that runs this dag. signal (DagSignal): The signal object for dags. It wraps the construction and sending of signals into easy to use methods. data (MultiTaskData): The initial data that is passed on to the start tasks. Raises: DirectedAcyclicGraphInvalid: If the graph is not a dag (e.g. contains loops). ConfigNotDefinedError: If the configuration for the dag is empty. """ graph = self.make_graph(self._schema) # pre-checks self.validate(graph) if config is None: raise ConfigNotDefinedError() # create the celery app for submitting tasks celery_app = create_app(config) # the task queue for managing the current state of the tasks tasks = [] stopped = False # add all tasks without predecessors to the task list for task in nx.topological_sort(graph): task.workflow_name = self.workflow_name task.dag_name = self.name if len(list(graph.predecessors(task))) == 0: task.state = TaskState.Waiting tasks.append(task) def set_task_completed(completed_task): """ For each completed task, add all successor tasks to the task list. If they are not in the task list yet, flag them as 'waiting'. """ completed_task.state = TaskState.Completed for successor in graph.successors(completed_task): if successor not in tasks: successor.state = TaskState.Waiting tasks.append(successor) # process the task queue as long as there are tasks in it while tasks: if not stopped: stopped = signal.is_stopped # delay the execution by the polling time if config.dag_polling_time > 0.0: sleep(config.dag_polling_time) for i in range(len(tasks) - 1, -1, -1): task = tasks[i] # for each waiting task, wait for all predecessor tasks to be # completed. Then check whether the task should be skipped by # interrogating the predecessor tasks. if task.is_waiting: if stopped: task.state = TaskState.Stopped else: pre_tasks = list(graph.predecessors(task)) if all([p.is_completed for p in pre_tasks]): # check whether the task should be skipped run_task = task.has_to_run or len(pre_tasks) == 0 for pre in pre_tasks: if run_task: break # predecessor task is skipped and flag should # not be propagated if pre.is_skipped and not pre.propagate_skip: run_task = True # limits of a non-skipped predecessor task if not pre.is_skipped: if pre.celery_result.result.limit is not None: if task.name in [ n.name if isinstance(n, BaseTask) else n for n in pre.celery_result.result.limit]: run_task = True else: run_task = True task.is_skipped = not run_task # send the task to celery or, if skipped, mark it as completed if task.is_skipped: set_task_completed(task) else: # compose the input data from the predecessor tasks # output. Data from skipped predecessor tasks do not # contribute to the input data if len(pre_tasks) == 0: input_data = data else: input_data = MultiTaskData() for pt in [p for p in pre_tasks if not p.is_skipped]: slot = graph[pt][task]['slot'] input_data.add_dataset( pt.name, pt.celery_result.result.data.default_dataset, aliases=[slot] if slot is not None else None) task.state = TaskState.Running task.celery_result = celery_app.send_task( JobExecPath.Task, args=(task, workflow_id, input_data), queue=task.queue, routing_key=task.queue ) # flag task as completed elif task.is_running: if task.celery_completed: set_task_completed(task) elif task.celery_failed: task.state = TaskState.Aborted signal.stop_workflow() # cleanup task results that are not required anymore elif task.is_completed: if all([s.is_completed or s.is_stopped or s.is_aborted for s in graph.successors(task)]): if celery_app.conf.result_expires == 0: task.clear_celery_result() tasks.remove(task) # cleanup and remove stopped and aborted tasks elif task.is_stopped or task.is_aborted: if celery_app.conf.result_expires == 0: task.clear_celery_result() tasks.remove(task)
def create_can_publish_and_can_republish_permissions(sender, **kwargs): """ Add `can_publish` and `ca_nrepublish` permissions for each publishable model in the system. """ for model in sender.get_models(): if not issubclass(model, PublishingModel): continue content_type = ContentType.objects.get_for_model(model) permission, created = Permission.objects.get_or_create( content_type=content_type, codename='can_publish', defaults=dict(name='Can Publish %s' % model.__name__)) permission, created = Permission.objects.get_or_create( content_type=content_type, codename='can_republish', defaults=dict(name='Can Republish %s' % model.__name__))
Add `can_publish` and `ca_nrepublish` permissions for each publishable model in the system.
Below is the the instruction that describes the task: ### Input: Add `can_publish` and `ca_nrepublish` permissions for each publishable model in the system. ### Response: def create_can_publish_and_can_republish_permissions(sender, **kwargs): """ Add `can_publish` and `ca_nrepublish` permissions for each publishable model in the system. """ for model in sender.get_models(): if not issubclass(model, PublishingModel): continue content_type = ContentType.objects.get_for_model(model) permission, created = Permission.objects.get_or_create( content_type=content_type, codename='can_publish', defaults=dict(name='Can Publish %s' % model.__name__)) permission, created = Permission.objects.get_or_create( content_type=content_type, codename='can_republish', defaults=dict(name='Can Republish %s' % model.__name__))
def get_datacenter(self, datacenter_id, depth=1): """ Retrieves a data center by its ID. :param datacenter_id: The unique ID of the data center. :type datacenter_id: ``str`` :param depth: The depth of the response data. :type depth: ``int`` """ response = self._perform_request( '/datacenters/%s?depth=%s' % (datacenter_id, str(depth))) return response
Retrieves a data center by its ID. :param datacenter_id: The unique ID of the data center. :type datacenter_id: ``str`` :param depth: The depth of the response data. :type depth: ``int``
Below is the the instruction that describes the task: ### Input: Retrieves a data center by its ID. :param datacenter_id: The unique ID of the data center. :type datacenter_id: ``str`` :param depth: The depth of the response data. :type depth: ``int`` ### Response: def get_datacenter(self, datacenter_id, depth=1): """ Retrieves a data center by its ID. :param datacenter_id: The unique ID of the data center. :type datacenter_id: ``str`` :param depth: The depth of the response data. :type depth: ``int`` """ response = self._perform_request( '/datacenters/%s?depth=%s' % (datacenter_id, str(depth))) return response
def get_course_details(self, course_id): """ Query the Enrollment API for the course details of the given course_id. Args: course_id (str): The string value of the course's unique identifier Returns: dict: A dictionary containing details about the course, in an enrollment context (allowed modes, etc.) """ try: return self.client.course(course_id).get() except (SlumberBaseException, ConnectionError, Timeout) as exc: LOGGER.exception( 'Failed to retrieve course enrollment details for course [%s] due to: [%s]', course_id, str(exc) ) return {}
Query the Enrollment API for the course details of the given course_id. Args: course_id (str): The string value of the course's unique identifier Returns: dict: A dictionary containing details about the course, in an enrollment context (allowed modes, etc.)
Below is the the instruction that describes the task: ### Input: Query the Enrollment API for the course details of the given course_id. Args: course_id (str): The string value of the course's unique identifier Returns: dict: A dictionary containing details about the course, in an enrollment context (allowed modes, etc.) ### Response: def get_course_details(self, course_id): """ Query the Enrollment API for the course details of the given course_id. Args: course_id (str): The string value of the course's unique identifier Returns: dict: A dictionary containing details about the course, in an enrollment context (allowed modes, etc.) """ try: return self.client.course(course_id).get() except (SlumberBaseException, ConnectionError, Timeout) as exc: LOGGER.exception( 'Failed to retrieve course enrollment details for course [%s] due to: [%s]', course_id, str(exc) ) return {}
def forum_post_list(self, creator_id=None, creator_name=None, topic_id=None, topic_title_matches=None, topic_category_id=None, body_matches=None): """Return a list of forum posts. Parameters: creator_id (int): creator_name (str): topic_id (int): topic_title_matches (str): topic_category_id (int): Can be: 0, 1, 2 (General, Tags, Bugs & Features respectively). body_matches (str): Can be part of the post content. """ params = { 'search[creator_id]': creator_id, 'search[creator_name]': creator_name, 'search[topic_id]': topic_id, 'search[topic_title_matches]': topic_title_matches, 'search[topic_category_id]': topic_category_id, 'search[body_matches]': body_matches } return self._get('forum_posts.json', params)
Return a list of forum posts. Parameters: creator_id (int): creator_name (str): topic_id (int): topic_title_matches (str): topic_category_id (int): Can be: 0, 1, 2 (General, Tags, Bugs & Features respectively). body_matches (str): Can be part of the post content.
Below is the the instruction that describes the task: ### Input: Return a list of forum posts. Parameters: creator_id (int): creator_name (str): topic_id (int): topic_title_matches (str): topic_category_id (int): Can be: 0, 1, 2 (General, Tags, Bugs & Features respectively). body_matches (str): Can be part of the post content. ### Response: def forum_post_list(self, creator_id=None, creator_name=None, topic_id=None, topic_title_matches=None, topic_category_id=None, body_matches=None): """Return a list of forum posts. Parameters: creator_id (int): creator_name (str): topic_id (int): topic_title_matches (str): topic_category_id (int): Can be: 0, 1, 2 (General, Tags, Bugs & Features respectively). body_matches (str): Can be part of the post content. """ params = { 'search[creator_id]': creator_id, 'search[creator_name]': creator_name, 'search[topic_id]': topic_id, 'search[topic_title_matches]': topic_title_matches, 'search[topic_category_id]': topic_category_id, 'search[body_matches]': body_matches } return self._get('forum_posts.json', params)
def __remove_args_first_item(self): """ # Todo: finding a better solution This is a dirty solution Because the first argument of inspectors' args will be itself For current implementation, it should be ignore """ if len(self.args) > 0: new_args_list = [] for item in self.args: if len(item) > 0 and self.obj == item[0].__class__: new_args_list.append(item[1:]) else: new_args_list.append(item[:]) self.__set_args_list(new_args_list)
# Todo: finding a better solution This is a dirty solution Because the first argument of inspectors' args will be itself For current implementation, it should be ignore
Below is the the instruction that describes the task: ### Input: # Todo: finding a better solution This is a dirty solution Because the first argument of inspectors' args will be itself For current implementation, it should be ignore ### Response: def __remove_args_first_item(self): """ # Todo: finding a better solution This is a dirty solution Because the first argument of inspectors' args will be itself For current implementation, it should be ignore """ if len(self.args) > 0: new_args_list = [] for item in self.args: if len(item) > 0 and self.obj == item[0].__class__: new_args_list.append(item[1:]) else: new_args_list.append(item[:]) self.__set_args_list(new_args_list)
def create(self, environment, target_name): """ Sends "create project" command to the remote server """ remote_server_command( ["ssh", environment.deploy_target, "create", target_name], environment, self, clean_up=True, )
Sends "create project" command to the remote server
Below is the the instruction that describes the task: ### Input: Sends "create project" command to the remote server ### Response: def create(self, environment, target_name): """ Sends "create project" command to the remote server """ remote_server_command( ["ssh", environment.deploy_target, "create", target_name], environment, self, clean_up=True, )
def _has_not_qual(ntd): """Return True if the qualifiers contain a 'NOT'""" for qual in ntd.Qualifier: if 'not' in qual: return True if 'NOT' in qual: return True return False
Return True if the qualifiers contain a 'NOT
Below is the the instruction that describes the task: ### Input: Return True if the qualifiers contain a 'NOT ### Response: def _has_not_qual(ntd): """Return True if the qualifiers contain a 'NOT'""" for qual in ntd.Qualifier: if 'not' in qual: return True if 'NOT' in qual: return True return False
def _get_device_group(self, device): '''Get the device group through a device. :param device: bigip object -- device :returns: tm.cm.device_groups.device_group object ''' return device.tm.cm.device_groups.device_group.load( name=self.name, partition=self.partition )
Get the device group through a device. :param device: bigip object -- device :returns: tm.cm.device_groups.device_group object
Below is the the instruction that describes the task: ### Input: Get the device group through a device. :param device: bigip object -- device :returns: tm.cm.device_groups.device_group object ### Response: def _get_device_group(self, device): '''Get the device group through a device. :param device: bigip object -- device :returns: tm.cm.device_groups.device_group object ''' return device.tm.cm.device_groups.device_group.load( name=self.name, partition=self.partition )
def to_er7(self, encoding_chars=None, trailing_children=False): """ Returns the HL7 representation of the :class:`Element <hl7apy.core.Element>`. It adds the appropriate separator at the end if needed :type encoding_chars: ``dict`` :param encoding_chars: The encoding chars to use. If it is ``None`` it uses :attr:`self.encoding_chars`, which by default is the ones return by :func:`get_default_encoding_chars <hl7apy.get_default_encoding_chars>` values :rtype: ``str`` :return: the HL7 representation of the :class:`Element <hl7apy.core.Element>` """ if encoding_chars is None: encoding_chars = self.encoding_chars child_class = list(self.child_classes.values())[0] separator = encoding_chars.get(child_class.__name__.upper(), '') s = [] for child in self._get_children(trailing_children): if child: s.extend(repetition.to_er7(encoding_chars, trailing_children) for repetition in child) else: try: s.append(self._handle_empty_children(encoding_chars)) except NotImplementedError: pass return separator.join(s)
Returns the HL7 representation of the :class:`Element <hl7apy.core.Element>`. It adds the appropriate separator at the end if needed :type encoding_chars: ``dict`` :param encoding_chars: The encoding chars to use. If it is ``None`` it uses :attr:`self.encoding_chars`, which by default is the ones return by :func:`get_default_encoding_chars <hl7apy.get_default_encoding_chars>` values :rtype: ``str`` :return: the HL7 representation of the :class:`Element <hl7apy.core.Element>`
Below is the the instruction that describes the task: ### Input: Returns the HL7 representation of the :class:`Element <hl7apy.core.Element>`. It adds the appropriate separator at the end if needed :type encoding_chars: ``dict`` :param encoding_chars: The encoding chars to use. If it is ``None`` it uses :attr:`self.encoding_chars`, which by default is the ones return by :func:`get_default_encoding_chars <hl7apy.get_default_encoding_chars>` values :rtype: ``str`` :return: the HL7 representation of the :class:`Element <hl7apy.core.Element>` ### Response: def to_er7(self, encoding_chars=None, trailing_children=False): """ Returns the HL7 representation of the :class:`Element <hl7apy.core.Element>`. It adds the appropriate separator at the end if needed :type encoding_chars: ``dict`` :param encoding_chars: The encoding chars to use. If it is ``None`` it uses :attr:`self.encoding_chars`, which by default is the ones return by :func:`get_default_encoding_chars <hl7apy.get_default_encoding_chars>` values :rtype: ``str`` :return: the HL7 representation of the :class:`Element <hl7apy.core.Element>` """ if encoding_chars is None: encoding_chars = self.encoding_chars child_class = list(self.child_classes.values())[0] separator = encoding_chars.get(child_class.__name__.upper(), '') s = [] for child in self._get_children(trailing_children): if child: s.extend(repetition.to_er7(encoding_chars, trailing_children) for repetition in child) else: try: s.append(self._handle_empty_children(encoding_chars)) except NotImplementedError: pass return separator.join(s)
def eval_string_type(self, text, is_string=False): """Evaluate string type.""" stype = set() wstype = set() for m in RE_ITER_STRING_TYPES.finditer(text): value = m.group(0) if value == '*': wstype.add('u') wstype.add('f') wstype.add('r') wstype.add('b') elif value.endswith('*'): wstype.add(value[0].lower()) else: stype.add(value.lower()) if is_string and 'b' not in stype and 'f' not in stype: stype.add('u') return stype, wstype
Evaluate string type.
Below is the the instruction that describes the task: ### Input: Evaluate string type. ### Response: def eval_string_type(self, text, is_string=False): """Evaluate string type.""" stype = set() wstype = set() for m in RE_ITER_STRING_TYPES.finditer(text): value = m.group(0) if value == '*': wstype.add('u') wstype.add('f') wstype.add('r') wstype.add('b') elif value.endswith('*'): wstype.add(value[0].lower()) else: stype.add(value.lower()) if is_string and 'b' not in stype and 'f' not in stype: stype.add('u') return stype, wstype
def _notify_remove(self, slice_): """Notify about a RemoveChange.""" change = RemoveChange(self, slice_) self.notify_observers(change)
Notify about a RemoveChange.
Below is the the instruction that describes the task: ### Input: Notify about a RemoveChange. ### Response: def _notify_remove(self, slice_): """Notify about a RemoveChange.""" change = RemoveChange(self, slice_) self.notify_observers(change)
def deprecated(fun_name=None, msg=""): '''Issue a deprecation warning for a function''' def _deprecated(fun): '''Issue a deprecation warning for a function''' @wraps(fun) def _wrapper(*args, **kwargs): '''Issue deprecation warning and forward arguments to fun''' name = fun_name if fun_name is not None else fun.__name__ _warn_deprecated('Call to deprecated function %s. %s' % (name, msg)) return fun(*args, **kwargs) return _wrapper return _deprecated
Issue a deprecation warning for a function
Below is the the instruction that describes the task: ### Input: Issue a deprecation warning for a function ### Response: def deprecated(fun_name=None, msg=""): '''Issue a deprecation warning for a function''' def _deprecated(fun): '''Issue a deprecation warning for a function''' @wraps(fun) def _wrapper(*args, **kwargs): '''Issue deprecation warning and forward arguments to fun''' name = fun_name if fun_name is not None else fun.__name__ _warn_deprecated('Call to deprecated function %s. %s' % (name, msg)) return fun(*args, **kwargs) return _wrapper return _deprecated
def get_all(self, paths: Union[str, Sequence[str]]) -> Union[IrodsMetadata, List[IrodsMetadata]]: """ Gets all of the metadata for the iRODS entities at the given path or paths. If multiple paths are given, the metadata collection at index `i` on the output corresponds to the path at index `i` on the input. i.e. ``` output = mapper.get_all(["path_1", "path_2"]) metadata_for_path_1 = output[0] metadata_for_path_2 = output[1] ``` A `ValueError` will be raised will be raised if the path does not correspond to a valid entity. :param path: the path of the entity or entities to get the metadata for :return: metadata for the given entity or entities """
Gets all of the metadata for the iRODS entities at the given path or paths. If multiple paths are given, the metadata collection at index `i` on the output corresponds to the path at index `i` on the input. i.e. ``` output = mapper.get_all(["path_1", "path_2"]) metadata_for_path_1 = output[0] metadata_for_path_2 = output[1] ``` A `ValueError` will be raised will be raised if the path does not correspond to a valid entity. :param path: the path of the entity or entities to get the metadata for :return: metadata for the given entity or entities
Below is the the instruction that describes the task: ### Input: Gets all of the metadata for the iRODS entities at the given path or paths. If multiple paths are given, the metadata collection at index `i` on the output corresponds to the path at index `i` on the input. i.e. ``` output = mapper.get_all(["path_1", "path_2"]) metadata_for_path_1 = output[0] metadata_for_path_2 = output[1] ``` A `ValueError` will be raised will be raised if the path does not correspond to a valid entity. :param path: the path of the entity or entities to get the metadata for :return: metadata for the given entity or entities ### Response: def get_all(self, paths: Union[str, Sequence[str]]) -> Union[IrodsMetadata, List[IrodsMetadata]]: """ Gets all of the metadata for the iRODS entities at the given path or paths. If multiple paths are given, the metadata collection at index `i` on the output corresponds to the path at index `i` on the input. i.e. ``` output = mapper.get_all(["path_1", "path_2"]) metadata_for_path_1 = output[0] metadata_for_path_2 = output[1] ``` A `ValueError` will be raised will be raised if the path does not correspond to a valid entity. :param path: the path of the entity or entities to get the metadata for :return: metadata for the given entity or entities """
def _pfp__set_packer(self, pack_type, packer=None, pack=None, unpack=None, func_call_info=None): """Set the packer/pack/unpack functions for this field, as well as the pack type. :pack_type: The data type of the packed data :packer: A function that can handle packing and unpacking. First arg is true/false (to pack or unpack). Second arg is the stream. Must return an array of chars. :pack: A function that packs data. It must accept an array of chars and return an array of chars that is a packed form of the input. :unpack: A function that unpacks data. It must accept an array of chars and return an array of chars """ self._pfp__pack_type = pack_type self._pfp__unpack = unpack self._pfp__pack = pack self._pfp__packer = packer self._pfp__pack_func_call_info = func_call_info
Set the packer/pack/unpack functions for this field, as well as the pack type. :pack_type: The data type of the packed data :packer: A function that can handle packing and unpacking. First arg is true/false (to pack or unpack). Second arg is the stream. Must return an array of chars. :pack: A function that packs data. It must accept an array of chars and return an array of chars that is a packed form of the input. :unpack: A function that unpacks data. It must accept an array of chars and return an array of chars
Below is the the instruction that describes the task: ### Input: Set the packer/pack/unpack functions for this field, as well as the pack type. :pack_type: The data type of the packed data :packer: A function that can handle packing and unpacking. First arg is true/false (to pack or unpack). Second arg is the stream. Must return an array of chars. :pack: A function that packs data. It must accept an array of chars and return an array of chars that is a packed form of the input. :unpack: A function that unpacks data. It must accept an array of chars and return an array of chars ### Response: def _pfp__set_packer(self, pack_type, packer=None, pack=None, unpack=None, func_call_info=None): """Set the packer/pack/unpack functions for this field, as well as the pack type. :pack_type: The data type of the packed data :packer: A function that can handle packing and unpacking. First arg is true/false (to pack or unpack). Second arg is the stream. Must return an array of chars. :pack: A function that packs data. It must accept an array of chars and return an array of chars that is a packed form of the input. :unpack: A function that unpacks data. It must accept an array of chars and return an array of chars """ self._pfp__pack_type = pack_type self._pfp__unpack = unpack self._pfp__pack = pack self._pfp__packer = packer self._pfp__pack_func_call_info = func_call_info
def _parse_resource(resource): """ Parses and completes resource information """ resource = resource.strip() if resource else resource if resource in {ME_RESOURCE, USERS_RESOURCE}: return resource elif '@' in resource and not resource.startswith(USERS_RESOURCE): # when for example accessing a shared mailbox the # resource is set to the email address. we have to prefix # the email with the resource 'users/' so --> 'users/email_address' return '{}/{}'.format(USERS_RESOURCE, resource) else: return resource
Parses and completes resource information
Below is the the instruction that describes the task: ### Input: Parses and completes resource information ### Response: def _parse_resource(resource): """ Parses and completes resource information """ resource = resource.strip() if resource else resource if resource in {ME_RESOURCE, USERS_RESOURCE}: return resource elif '@' in resource and not resource.startswith(USERS_RESOURCE): # when for example accessing a shared mailbox the # resource is set to the email address. we have to prefix # the email with the resource 'users/' so --> 'users/email_address' return '{}/{}'.format(USERS_RESOURCE, resource) else: return resource
def project_update_sponsorship(object_id, input_params={}, always_retry=True, **kwargs): """ Invokes the /project-xxxx/updateSponsorship API method. For more info, see: https://wiki.dnanexus.com/API-Specification-v1.0.0/Projects#API-method%3A-%2Fproject-xxxx%2FupdateSponsorship """ return DXHTTPRequest('/%s/updateSponsorship' % object_id, input_params, always_retry=always_retry, **kwargs)
Invokes the /project-xxxx/updateSponsorship API method. For more info, see: https://wiki.dnanexus.com/API-Specification-v1.0.0/Projects#API-method%3A-%2Fproject-xxxx%2FupdateSponsorship
Below is the the instruction that describes the task: ### Input: Invokes the /project-xxxx/updateSponsorship API method. For more info, see: https://wiki.dnanexus.com/API-Specification-v1.0.0/Projects#API-method%3A-%2Fproject-xxxx%2FupdateSponsorship ### Response: def project_update_sponsorship(object_id, input_params={}, always_retry=True, **kwargs): """ Invokes the /project-xxxx/updateSponsorship API method. For more info, see: https://wiki.dnanexus.com/API-Specification-v1.0.0/Projects#API-method%3A-%2Fproject-xxxx%2FupdateSponsorship """ return DXHTTPRequest('/%s/updateSponsorship' % object_id, input_params, always_retry=always_retry, **kwargs)
def compare(orderby_item1, orderby_item2): """compares the two orderby item pairs. :param dict orderby_item1: :param dict orderby_item2: :return: Integer comparison result. The comparator acts such that - if the types are different we get: Undefined value < Null < booleans < Numbers < Strings - if both arguments are of the same type: it simply compares the values. :rtype: int """ type1_ord = _OrderByHelper.getTypeOrd(orderby_item1) type2_ord = _OrderByHelper.getTypeOrd(orderby_item2) type_ord_diff = type1_ord - type2_ord if type_ord_diff: return type_ord_diff # the same type, if type1_ord == 0: return 0 return _compare_helper(orderby_item1['item'], orderby_item2['item'])
compares the two orderby item pairs. :param dict orderby_item1: :param dict orderby_item2: :return: Integer comparison result. The comparator acts such that - if the types are different we get: Undefined value < Null < booleans < Numbers < Strings - if both arguments are of the same type: it simply compares the values. :rtype: int
Below is the the instruction that describes the task: ### Input: compares the two orderby item pairs. :param dict orderby_item1: :param dict orderby_item2: :return: Integer comparison result. The comparator acts such that - if the types are different we get: Undefined value < Null < booleans < Numbers < Strings - if both arguments are of the same type: it simply compares the values. :rtype: int ### Response: def compare(orderby_item1, orderby_item2): """compares the two orderby item pairs. :param dict orderby_item1: :param dict orderby_item2: :return: Integer comparison result. The comparator acts such that - if the types are different we get: Undefined value < Null < booleans < Numbers < Strings - if both arguments are of the same type: it simply compares the values. :rtype: int """ type1_ord = _OrderByHelper.getTypeOrd(orderby_item1) type2_ord = _OrderByHelper.getTypeOrd(orderby_item2) type_ord_diff = type1_ord - type2_ord if type_ord_diff: return type_ord_diff # the same type, if type1_ord == 0: return 0 return _compare_helper(orderby_item1['item'], orderby_item2['item'])
def date_to_long_form_string(dt, locale_ = 'en_US.utf8'): '''dt should be a datetime.date object.''' if locale_: old_locale = locale.getlocale() locale.setlocale(locale.LC_ALL, locale_) v = dt.strftime("%A %B %d %Y") if locale_: locale.setlocale(locale.LC_ALL, old_locale) return v
dt should be a datetime.date object.
Below is the the instruction that describes the task: ### Input: dt should be a datetime.date object. ### Response: def date_to_long_form_string(dt, locale_ = 'en_US.utf8'): '''dt should be a datetime.date object.''' if locale_: old_locale = locale.getlocale() locale.setlocale(locale.LC_ALL, locale_) v = dt.strftime("%A %B %d %Y") if locale_: locale.setlocale(locale.LC_ALL, old_locale) return v
def fetch_internal(item, request): """Fetches the given request by using the local Flask context.""" # Break client dependence on Flask if internal fetches aren't being used. from flask import make_response from werkzeug.test import EnvironBuilder # Break circular dependencies. from dpxdt.server import app # Attempt to create a Flask environment from a urllib2.Request object. environ_base = { 'REMOTE_ADDR': '127.0.0.1', } # The data object may be a generator from poster.multipart_encode, so we # need to convert that to raw bytes here. Unfortunately EnvironBuilder # only works with the whole request buffered in memory. data = request.get_data() if data and not isinstance(data, str): data = ''.join(list(data)) builder = EnvironBuilder( path=request.get_selector(), base_url='%s://%s' % (request.get_type(), request.get_host()), method=request.get_method(), data=data, headers=request.header_items(), environ_base=environ_base) with app.request_context(builder.get_environ()): response = make_response(app.dispatch_request()) LOGGER.info('"%s" %s via internal routing', request.get_selector(), response.status_code) item.status_code = response.status_code item.content_type = response.mimetype if item.result_path: # TODO: Is there a better way to access the response stream? with open(item.result_path, 'wb') as result_file: for piece in response.iter_encoded(): result_file.write(piece) else: item.data = response.get_data() return item
Fetches the given request by using the local Flask context.
Below is the the instruction that describes the task: ### Input: Fetches the given request by using the local Flask context. ### Response: def fetch_internal(item, request): """Fetches the given request by using the local Flask context.""" # Break client dependence on Flask if internal fetches aren't being used. from flask import make_response from werkzeug.test import EnvironBuilder # Break circular dependencies. from dpxdt.server import app # Attempt to create a Flask environment from a urllib2.Request object. environ_base = { 'REMOTE_ADDR': '127.0.0.1', } # The data object may be a generator from poster.multipart_encode, so we # need to convert that to raw bytes here. Unfortunately EnvironBuilder # only works with the whole request buffered in memory. data = request.get_data() if data and not isinstance(data, str): data = ''.join(list(data)) builder = EnvironBuilder( path=request.get_selector(), base_url='%s://%s' % (request.get_type(), request.get_host()), method=request.get_method(), data=data, headers=request.header_items(), environ_base=environ_base) with app.request_context(builder.get_environ()): response = make_response(app.dispatch_request()) LOGGER.info('"%s" %s via internal routing', request.get_selector(), response.status_code) item.status_code = response.status_code item.content_type = response.mimetype if item.result_path: # TODO: Is there a better way to access the response stream? with open(item.result_path, 'wb') as result_file: for piece in response.iter_encoded(): result_file.write(piece) else: item.data = response.get_data() return item
def get_run_events(cls, crawler, run_id, start, end, level=None): """Events from a particular run""" key = make_key(crawler, "events", run_id, level) return cls.event_list(key, start, end)
Events from a particular run
Below is the the instruction that describes the task: ### Input: Events from a particular run ### Response: def get_run_events(cls, crawler, run_id, start, end, level=None): """Events from a particular run""" key = make_key(crawler, "events", run_id, level) return cls.event_list(key, start, end)
def resources(ctx, gpu): """Get build job resources. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon build -b 2 resources ``` For GPU resources \b ```bash $ polyaxon build -b 2 resources --gpu ``` """ user, project_name, _build = get_build_or_local(ctx.obj.get('project'), ctx.obj.get('build')) try: message_handler = Printer.gpu_resources if gpu else Printer.resources PolyaxonClient().build_job.resources(user, project_name, _build, message_handler=message_handler) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get resources for build job `{}`.'.format(_build)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1)
Get build job resources. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon build -b 2 resources ``` For GPU resources \b ```bash $ polyaxon build -b 2 resources --gpu ```
Below is the the instruction that describes the task: ### Input: Get build job resources. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon build -b 2 resources ``` For GPU resources \b ```bash $ polyaxon build -b 2 resources --gpu ``` ### Response: def resources(ctx, gpu): """Get build job resources. Uses [Caching](/references/polyaxon-cli/#caching) Examples: \b ```bash $ polyaxon build -b 2 resources ``` For GPU resources \b ```bash $ polyaxon build -b 2 resources --gpu ``` """ user, project_name, _build = get_build_or_local(ctx.obj.get('project'), ctx.obj.get('build')) try: message_handler = Printer.gpu_resources if gpu else Printer.resources PolyaxonClient().build_job.resources(user, project_name, _build, message_handler=message_handler) except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e: Printer.print_error('Could not get resources for build job `{}`.'.format(_build)) Printer.print_error('Error message `{}`.'.format(e)) sys.exit(1)
def get_py_impl(): """Return what kind of Python this is""" if hasattr(sys, 'pypy_version_info'): pyimpl = 'PyPy' elif sys.platform.startswith('java'): pyimpl = 'Jython' elif sys.platform == 'cli': pyimpl = 'IronPython' else: pyimpl = 'CPython' return pyimpl
Return what kind of Python this is
Below is the the instruction that describes the task: ### Input: Return what kind of Python this is ### Response: def get_py_impl(): """Return what kind of Python this is""" if hasattr(sys, 'pypy_version_info'): pyimpl = 'PyPy' elif sys.platform.startswith('java'): pyimpl = 'Jython' elif sys.platform == 'cli': pyimpl = 'IronPython' else: pyimpl = 'CPython' return pyimpl
def tex_emitter_core(target, source, env, graphics_extensions): """An emitter for TeX and LaTeX sources. For LaTeX sources we try and find the common created files that are needed on subsequent runs of latex to finish tables of contents, bibliographies, indices, lists of figures, and hyperlink references. """ basename = SCons.Util.splitext(str(source[0]))[0] basefile = os.path.split(str(basename))[1] targetdir = os.path.split(str(target[0]))[0] targetbase = os.path.join(targetdir, basefile) basedir = os.path.split(str(source[0]))[0] abspath = os.path.abspath(basedir) target[0].attributes.path = abspath # # file names we will make use of in searching the sources and log file # emit_suffixes = ['.aux', '.log', '.ilg', '.blg', '.nls', '.nlg', '.gls', '.glg', '.alg'] + all_suffixes auxfilename = targetbase + '.aux' logfilename = targetbase + '.log' flsfilename = targetbase + '.fls' syncfilename = targetbase + '.synctex.gz' env.SideEffect(auxfilename,target[0]) env.SideEffect(logfilename,target[0]) env.SideEffect(flsfilename,target[0]) env.SideEffect(syncfilename,target[0]) if Verbose: print("side effect :",auxfilename,logfilename,flsfilename,syncfilename) env.Clean(target[0],auxfilename) env.Clean(target[0],logfilename) env.Clean(target[0],flsfilename) env.Clean(target[0],syncfilename) content = source[0].get_text_contents() # set up list with the regular expressions # we use to find features used file_tests_search = [auxfile_re, makeindex_re, bibliography_re, bibunit_re, multibib_re, addbibresource_re, tableofcontents_re, listoffigures_re, listoftables_re, hyperref_re, makenomenclature_re, makeglossary_re, makeglossaries_re, makeacronyms_re, beamer_re, newglossary_re, biblatex_re ] # set up list with the file suffixes that need emitting # when a feature is found file_tests_suff = [['.aux','aux_file'], ['.idx', '.ind', '.ilg','makeindex'], ['.bbl', '.blg','bibliography'], ['.bbl', '.blg','bibunit'], ['.bbl', '.blg','multibib'], ['.bbl', '.blg','.bcf','addbibresource'], ['.toc','contents'], ['.lof','figures'], ['.lot','tables'], ['.out','hyperref'], ['.nlo', '.nls', '.nlg','nomenclature'], ['.glo', '.gls', '.glg','glossary'], ['.glo', '.gls', '.glg','glossaries'], ['.acn', '.acr', '.alg','acronyms'], ['.nav', '.snm', '.out', '.toc','beamer'], ['newglossary',], ['.bcf', '.blg','biblatex'] ] # for newglossary the suffixes are added as we find the command # build the list of lists file_tests = [] for i in range(len(file_tests_search)): file_tests.append( [None, file_tests_suff[i]] ) # TO-DO: need to add a way for the user to extend this list for whatever # auxiliary files they create in other (or their own) packages # get path list from both env['TEXINPUTS'] and env['ENV']['TEXINPUTS'] savedpath = modify_env_var(env, 'TEXINPUTS', abspath) paths = env['ENV']['TEXINPUTS'] if SCons.Util.is_List(paths): pass else: # Split at os.pathsep to convert into absolute path paths = paths.split(os.pathsep) # now that we have the path list restore the env if savedpath is _null: try: del env['ENV']['TEXINPUTS'] except KeyError: pass # was never set else: env['ENV']['TEXINPUTS'] = savedpath if Verbose: print("search path ",paths) # scan all sources for side effect files aux_files = [] file_tests = ScanFiles(source[0], target, paths, file_tests, file_tests_search, env, graphics_extensions, targetdir, aux_files) for (theSearch,suffix_list) in file_tests: # add side effects if feature is present.If file is to be generated,add all side effects if Verbose and theSearch: print("check side effects for ",suffix_list[-1]) if (theSearch != None) or (not source[0].exists() ): file_list = [targetbase,] # for bibunit we need a list of files if suffix_list[-1] == 'bibunit': file_basename = os.path.join(targetdir, 'bu*.aux') file_list = glob.glob(file_basename) # remove the suffix '.aux' for i in range(len(file_list)): file_list.append(SCons.Util.splitext(file_list[i])[0]) # for multibib we need a list of files if suffix_list[-1] == 'multibib': for multibibmatch in multibib_re.finditer(content): if Verbose: print("multibib match ",multibibmatch.group(1)) if multibibmatch != None: baselist = multibibmatch.group(1).split(',') if Verbose: print("multibib list ", baselist) for i in range(len(baselist)): file_list.append(os.path.join(targetdir, baselist[i])) # now define the side effects for file_name in file_list: for suffix in suffix_list[:-1]: env.SideEffect(file_name + suffix,target[0]) if Verbose: print("side effect tst :",file_name + suffix, " target is ",str(target[0])) env.Clean(target[0],file_name + suffix) for aFile in aux_files: aFile_base = SCons.Util.splitext(aFile)[0] env.SideEffect(aFile_base + '.aux',target[0]) if Verbose: print("side effect aux :",aFile_base + '.aux') env.Clean(target[0],aFile_base + '.aux') # read fls file to get all other files that latex creates and will read on the next pass # remove files from list that we explicitly dealt with above if os.path.isfile(flsfilename): content = open(flsfilename, "r").read() out_files = openout_re.findall(content) myfiles = [auxfilename, logfilename, flsfilename, targetbase+'.dvi',targetbase+'.pdf'] for filename in out_files[:]: if filename in myfiles: out_files.remove(filename) env.SideEffect(out_files,target[0]) if Verbose: print("side effect fls :",out_files) env.Clean(target[0],out_files) return (target, source)
An emitter for TeX and LaTeX sources. For LaTeX sources we try and find the common created files that are needed on subsequent runs of latex to finish tables of contents, bibliographies, indices, lists of figures, and hyperlink references.
Below is the the instruction that describes the task: ### Input: An emitter for TeX and LaTeX sources. For LaTeX sources we try and find the common created files that are needed on subsequent runs of latex to finish tables of contents, bibliographies, indices, lists of figures, and hyperlink references. ### Response: def tex_emitter_core(target, source, env, graphics_extensions): """An emitter for TeX and LaTeX sources. For LaTeX sources we try and find the common created files that are needed on subsequent runs of latex to finish tables of contents, bibliographies, indices, lists of figures, and hyperlink references. """ basename = SCons.Util.splitext(str(source[0]))[0] basefile = os.path.split(str(basename))[1] targetdir = os.path.split(str(target[0]))[0] targetbase = os.path.join(targetdir, basefile) basedir = os.path.split(str(source[0]))[0] abspath = os.path.abspath(basedir) target[0].attributes.path = abspath # # file names we will make use of in searching the sources and log file # emit_suffixes = ['.aux', '.log', '.ilg', '.blg', '.nls', '.nlg', '.gls', '.glg', '.alg'] + all_suffixes auxfilename = targetbase + '.aux' logfilename = targetbase + '.log' flsfilename = targetbase + '.fls' syncfilename = targetbase + '.synctex.gz' env.SideEffect(auxfilename,target[0]) env.SideEffect(logfilename,target[0]) env.SideEffect(flsfilename,target[0]) env.SideEffect(syncfilename,target[0]) if Verbose: print("side effect :",auxfilename,logfilename,flsfilename,syncfilename) env.Clean(target[0],auxfilename) env.Clean(target[0],logfilename) env.Clean(target[0],flsfilename) env.Clean(target[0],syncfilename) content = source[0].get_text_contents() # set up list with the regular expressions # we use to find features used file_tests_search = [auxfile_re, makeindex_re, bibliography_re, bibunit_re, multibib_re, addbibresource_re, tableofcontents_re, listoffigures_re, listoftables_re, hyperref_re, makenomenclature_re, makeglossary_re, makeglossaries_re, makeacronyms_re, beamer_re, newglossary_re, biblatex_re ] # set up list with the file suffixes that need emitting # when a feature is found file_tests_suff = [['.aux','aux_file'], ['.idx', '.ind', '.ilg','makeindex'], ['.bbl', '.blg','bibliography'], ['.bbl', '.blg','bibunit'], ['.bbl', '.blg','multibib'], ['.bbl', '.blg','.bcf','addbibresource'], ['.toc','contents'], ['.lof','figures'], ['.lot','tables'], ['.out','hyperref'], ['.nlo', '.nls', '.nlg','nomenclature'], ['.glo', '.gls', '.glg','glossary'], ['.glo', '.gls', '.glg','glossaries'], ['.acn', '.acr', '.alg','acronyms'], ['.nav', '.snm', '.out', '.toc','beamer'], ['newglossary',], ['.bcf', '.blg','biblatex'] ] # for newglossary the suffixes are added as we find the command # build the list of lists file_tests = [] for i in range(len(file_tests_search)): file_tests.append( [None, file_tests_suff[i]] ) # TO-DO: need to add a way for the user to extend this list for whatever # auxiliary files they create in other (or their own) packages # get path list from both env['TEXINPUTS'] and env['ENV']['TEXINPUTS'] savedpath = modify_env_var(env, 'TEXINPUTS', abspath) paths = env['ENV']['TEXINPUTS'] if SCons.Util.is_List(paths): pass else: # Split at os.pathsep to convert into absolute path paths = paths.split(os.pathsep) # now that we have the path list restore the env if savedpath is _null: try: del env['ENV']['TEXINPUTS'] except KeyError: pass # was never set else: env['ENV']['TEXINPUTS'] = savedpath if Verbose: print("search path ",paths) # scan all sources for side effect files aux_files = [] file_tests = ScanFiles(source[0], target, paths, file_tests, file_tests_search, env, graphics_extensions, targetdir, aux_files) for (theSearch,suffix_list) in file_tests: # add side effects if feature is present.If file is to be generated,add all side effects if Verbose and theSearch: print("check side effects for ",suffix_list[-1]) if (theSearch != None) or (not source[0].exists() ): file_list = [targetbase,] # for bibunit we need a list of files if suffix_list[-1] == 'bibunit': file_basename = os.path.join(targetdir, 'bu*.aux') file_list = glob.glob(file_basename) # remove the suffix '.aux' for i in range(len(file_list)): file_list.append(SCons.Util.splitext(file_list[i])[0]) # for multibib we need a list of files if suffix_list[-1] == 'multibib': for multibibmatch in multibib_re.finditer(content): if Verbose: print("multibib match ",multibibmatch.group(1)) if multibibmatch != None: baselist = multibibmatch.group(1).split(',') if Verbose: print("multibib list ", baselist) for i in range(len(baselist)): file_list.append(os.path.join(targetdir, baselist[i])) # now define the side effects for file_name in file_list: for suffix in suffix_list[:-1]: env.SideEffect(file_name + suffix,target[0]) if Verbose: print("side effect tst :",file_name + suffix, " target is ",str(target[0])) env.Clean(target[0],file_name + suffix) for aFile in aux_files: aFile_base = SCons.Util.splitext(aFile)[0] env.SideEffect(aFile_base + '.aux',target[0]) if Verbose: print("side effect aux :",aFile_base + '.aux') env.Clean(target[0],aFile_base + '.aux') # read fls file to get all other files that latex creates and will read on the next pass # remove files from list that we explicitly dealt with above if os.path.isfile(flsfilename): content = open(flsfilename, "r").read() out_files = openout_re.findall(content) myfiles = [auxfilename, logfilename, flsfilename, targetbase+'.dvi',targetbase+'.pdf'] for filename in out_files[:]: if filename in myfiles: out_files.remove(filename) env.SideEffect(out_files,target[0]) if Verbose: print("side effect fls :",out_files) env.Clean(target[0],out_files) return (target, source)
def open_grindstone(self): """ Opens a grindstone file and populates the grindstone with it's contents. Returns an empty grindstone json object if a file does not exist. """ try: with open(self.grindstone_path, 'r') as f: # Try opening the file return json.loads(f.read()) # If the file is empty except json.decoder.JSONDecodeError: # Default return empty object with empty tasks list return {'tasks': []} # The file does not yet exist except FileNotFoundError: # Default return empty object with empty tasks list return {'tasks': []}
Opens a grindstone file and populates the grindstone with it's contents. Returns an empty grindstone json object if a file does not exist.
Below is the the instruction that describes the task: ### Input: Opens a grindstone file and populates the grindstone with it's contents. Returns an empty grindstone json object if a file does not exist. ### Response: def open_grindstone(self): """ Opens a grindstone file and populates the grindstone with it's contents. Returns an empty grindstone json object if a file does not exist. """ try: with open(self.grindstone_path, 'r') as f: # Try opening the file return json.loads(f.read()) # If the file is empty except json.decoder.JSONDecodeError: # Default return empty object with empty tasks list return {'tasks': []} # The file does not yet exist except FileNotFoundError: # Default return empty object with empty tasks list return {'tasks': []}
def brightness(level=100, group=0): """ Assumes level is out of 100 """ if level not in range(0,101): raise Exception("Brightness must be value between 0 and 100") b = int(floor(level / 4.0) + 2) #lights want values 2-27 return (COMMANDS['ON'][group], Command(0x4E, b))
Assumes level is out of 100
Below is the the instruction that describes the task: ### Input: Assumes level is out of 100 ### Response: def brightness(level=100, group=0): """ Assumes level is out of 100 """ if level not in range(0,101): raise Exception("Brightness must be value between 0 and 100") b = int(floor(level / 4.0) + 2) #lights want values 2-27 return (COMMANDS['ON'][group], Command(0x4E, b))
def process_tsuite(tsuite): """Goes through the tsuite and processes "*.log" """ # scoop of output from all run-logs tsuite["log_content"] = runlogs_to_html(tsuite["res_root"]) tsuite["aux_list"] = aux_listing(tsuite["aux_root"]) tsuite["hnames"] = extract_hook_names(tsuite) return True
Goes through the tsuite and processes "*.log"
Below is the the instruction that describes the task: ### Input: Goes through the tsuite and processes "*.log" ### Response: def process_tsuite(tsuite): """Goes through the tsuite and processes "*.log" """ # scoop of output from all run-logs tsuite["log_content"] = runlogs_to_html(tsuite["res_root"]) tsuite["aux_list"] = aux_listing(tsuite["aux_root"]) tsuite["hnames"] = extract_hook_names(tsuite) return True
def fire(self, name, operation, args=None, **kwargs): """Send a message without waiting for a reply @param name: name of destination service queue @param operation: name of service operation to invoke @param args: dictionary of keyword args to pass to operation. Use this OR kwargs. @param kwargs: additional args to pass to operation """ if args: if kwargs: raise TypeError("specify args dict or keyword arguments, not both") else: args = kwargs d = dict(op=operation, args=args) headers = {'sender': self.add_sysname(self.name)} dest = self.add_sysname(name) def _fire(channel): with Producer(channel) as producer: producer.publish(d, routing_key=dest, headers=headers, serializer=self._serializer, exchange=self._exchange, declare=[self._exchange]) log.debug("sending message to %s", dest) with connections[self._pool_conn].acquire(block=True) as conn: _, channel = self.ensure(conn, _fire) conn.maybe_close_channel(channel)
Send a message without waiting for a reply @param name: name of destination service queue @param operation: name of service operation to invoke @param args: dictionary of keyword args to pass to operation. Use this OR kwargs. @param kwargs: additional args to pass to operation
Below is the the instruction that describes the task: ### Input: Send a message without waiting for a reply @param name: name of destination service queue @param operation: name of service operation to invoke @param args: dictionary of keyword args to pass to operation. Use this OR kwargs. @param kwargs: additional args to pass to operation ### Response: def fire(self, name, operation, args=None, **kwargs): """Send a message without waiting for a reply @param name: name of destination service queue @param operation: name of service operation to invoke @param args: dictionary of keyword args to pass to operation. Use this OR kwargs. @param kwargs: additional args to pass to operation """ if args: if kwargs: raise TypeError("specify args dict or keyword arguments, not both") else: args = kwargs d = dict(op=operation, args=args) headers = {'sender': self.add_sysname(self.name)} dest = self.add_sysname(name) def _fire(channel): with Producer(channel) as producer: producer.publish(d, routing_key=dest, headers=headers, serializer=self._serializer, exchange=self._exchange, declare=[self._exchange]) log.debug("sending message to %s", dest) with connections[self._pool_conn].acquire(block=True) as conn: _, channel = self.ensure(conn, _fire) conn.maybe_close_channel(channel)
def output(self, resource): """Wrap a resource (as a flask view function). This is for cases where the resource does not directly return a response object. Now everything should be a Response object. :param resource: The resource as a flask view function """ @wraps(resource) def wrapper(*args, **kwargs): rv = resource(*args, **kwargs) rv = self.responder(rv) return rv return wrapper
Wrap a resource (as a flask view function). This is for cases where the resource does not directly return a response object. Now everything should be a Response object. :param resource: The resource as a flask view function
Below is the the instruction that describes the task: ### Input: Wrap a resource (as a flask view function). This is for cases where the resource does not directly return a response object. Now everything should be a Response object. :param resource: The resource as a flask view function ### Response: def output(self, resource): """Wrap a resource (as a flask view function). This is for cases where the resource does not directly return a response object. Now everything should be a Response object. :param resource: The resource as a flask view function """ @wraps(resource) def wrapper(*args, **kwargs): rv = resource(*args, **kwargs) rv = self.responder(rv) return rv return wrapper
def batch(data, batch_size, batch_size_fn=None): """Yield elements from data in chunks of batch_size.""" if batch_size_fn is None: def batch_size_fn(new, count, sofar): return count minibatch, size_so_far = [], 0 for ex in data: minibatch.append(ex) size_so_far = batch_size_fn(ex, len(minibatch), size_so_far) if size_so_far == batch_size: yield minibatch minibatch, size_so_far = [], 0 elif size_so_far > batch_size: yield minibatch[:-1] minibatch, size_so_far = minibatch[-1:], batch_size_fn(ex, 1, 0) if minibatch: yield minibatch
Yield elements from data in chunks of batch_size.
Below is the the instruction that describes the task: ### Input: Yield elements from data in chunks of batch_size. ### Response: def batch(data, batch_size, batch_size_fn=None): """Yield elements from data in chunks of batch_size.""" if batch_size_fn is None: def batch_size_fn(new, count, sofar): return count minibatch, size_so_far = [], 0 for ex in data: minibatch.append(ex) size_so_far = batch_size_fn(ex, len(minibatch), size_so_far) if size_so_far == batch_size: yield minibatch minibatch, size_so_far = [], 0 elif size_so_far > batch_size: yield minibatch[:-1] minibatch, size_so_far = minibatch[-1:], batch_size_fn(ex, 1, 0) if minibatch: yield minibatch
def parse_coach_ec_df(infile): """Parse the EC.dat output file of COACH and return a dataframe of results EC.dat contains the predicted EC number and active residues. The columns are: PDB_ID, TM-score, RMSD, Sequence identity, Coverage, Confidence score, EC number, and Active site residues Args: infile (str): Path to EC.dat Returns: DataFrame: Pandas DataFrame summarizing EC number predictions """ ec_df = pd.read_table(infile, delim_whitespace=True, names=['pdb_template', 'tm_score', 'rmsd', 'seq_ident', 'seq_coverage', 'c_score', 'ec_number', 'binding_residues']) ec_df['pdb_template_id'] = ec_df['pdb_template'].apply(lambda x: x[:4]) ec_df['pdb_template_chain'] = ec_df['pdb_template'].apply(lambda x: x[4]) ec_df = ec_df[['pdb_template_id', 'pdb_template_chain', 'tm_score', 'rmsd', 'seq_ident', 'seq_coverage', 'c_score', 'ec_number', 'binding_residues']] ec_df['c_score'] = pd.to_numeric(ec_df.c_score, errors='coerce') return ec_df
Parse the EC.dat output file of COACH and return a dataframe of results EC.dat contains the predicted EC number and active residues. The columns are: PDB_ID, TM-score, RMSD, Sequence identity, Coverage, Confidence score, EC number, and Active site residues Args: infile (str): Path to EC.dat Returns: DataFrame: Pandas DataFrame summarizing EC number predictions
Below is the the instruction that describes the task: ### Input: Parse the EC.dat output file of COACH and return a dataframe of results EC.dat contains the predicted EC number and active residues. The columns are: PDB_ID, TM-score, RMSD, Sequence identity, Coverage, Confidence score, EC number, and Active site residues Args: infile (str): Path to EC.dat Returns: DataFrame: Pandas DataFrame summarizing EC number predictions ### Response: def parse_coach_ec_df(infile): """Parse the EC.dat output file of COACH and return a dataframe of results EC.dat contains the predicted EC number and active residues. The columns are: PDB_ID, TM-score, RMSD, Sequence identity, Coverage, Confidence score, EC number, and Active site residues Args: infile (str): Path to EC.dat Returns: DataFrame: Pandas DataFrame summarizing EC number predictions """ ec_df = pd.read_table(infile, delim_whitespace=True, names=['pdb_template', 'tm_score', 'rmsd', 'seq_ident', 'seq_coverage', 'c_score', 'ec_number', 'binding_residues']) ec_df['pdb_template_id'] = ec_df['pdb_template'].apply(lambda x: x[:4]) ec_df['pdb_template_chain'] = ec_df['pdb_template'].apply(lambda x: x[4]) ec_df = ec_df[['pdb_template_id', 'pdb_template_chain', 'tm_score', 'rmsd', 'seq_ident', 'seq_coverage', 'c_score', 'ec_number', 'binding_residues']] ec_df['c_score'] = pd.to_numeric(ec_df.c_score, errors='coerce') return ec_df
def _tool_to_dict(tool): """Parse a tool definition into a cwl2wdl style dictionary. """ out = {"name": _id_to_name(tool.tool["id"]), "baseCommand": " ".join(tool.tool["baseCommand"]), "arguments": [], "inputs": [_input_to_dict(i) for i in tool.tool["inputs"]], "outputs": [_output_to_dict(o) for o in tool.tool["outputs"]], "requirements": _requirements_to_dict(tool.requirements + tool.hints), "stdin": None, "stdout": None} return out
Parse a tool definition into a cwl2wdl style dictionary.
Below is the the instruction that describes the task: ### Input: Parse a tool definition into a cwl2wdl style dictionary. ### Response: def _tool_to_dict(tool): """Parse a tool definition into a cwl2wdl style dictionary. """ out = {"name": _id_to_name(tool.tool["id"]), "baseCommand": " ".join(tool.tool["baseCommand"]), "arguments": [], "inputs": [_input_to_dict(i) for i in tool.tool["inputs"]], "outputs": [_output_to_dict(o) for o in tool.tool["outputs"]], "requirements": _requirements_to_dict(tool.requirements + tool.hints), "stdin": None, "stdout": None} return out
def feature_info(self): """ Returns information about the features available for this CPC. Authorization requirements: * Object-access permission to this CPC. Returns: :term:`iterable`: An iterable where each item represents one feature that is available for this CPC. Each item is a dictionary with the following items: * `name` (:term:`unicode string`): Name of the feature. * `description` (:term:`unicode string`): Short description of the feature. * `state` (bool): Enablement state of the feature (`True` if the enabled, `False` if disabled). Raises: :exc:`ValueError`: Features are not supported on the HMC. :exc:`~zhmcclient.HTTPError` :exc:`~zhmcclient.ParseError` :exc:`~zhmcclient.AuthError` :exc:`~zhmcclient.ConnectionError` """ feature_list = self.prop('available-features-list', None) if feature_list is None: raise ValueError("Firmware features are not supported on CPC %s" % self.name) return feature_list
Returns information about the features available for this CPC. Authorization requirements: * Object-access permission to this CPC. Returns: :term:`iterable`: An iterable where each item represents one feature that is available for this CPC. Each item is a dictionary with the following items: * `name` (:term:`unicode string`): Name of the feature. * `description` (:term:`unicode string`): Short description of the feature. * `state` (bool): Enablement state of the feature (`True` if the enabled, `False` if disabled). Raises: :exc:`ValueError`: Features are not supported on the HMC. :exc:`~zhmcclient.HTTPError` :exc:`~zhmcclient.ParseError` :exc:`~zhmcclient.AuthError` :exc:`~zhmcclient.ConnectionError`
Below is the the instruction that describes the task: ### Input: Returns information about the features available for this CPC. Authorization requirements: * Object-access permission to this CPC. Returns: :term:`iterable`: An iterable where each item represents one feature that is available for this CPC. Each item is a dictionary with the following items: * `name` (:term:`unicode string`): Name of the feature. * `description` (:term:`unicode string`): Short description of the feature. * `state` (bool): Enablement state of the feature (`True` if the enabled, `False` if disabled). Raises: :exc:`ValueError`: Features are not supported on the HMC. :exc:`~zhmcclient.HTTPError` :exc:`~zhmcclient.ParseError` :exc:`~zhmcclient.AuthError` :exc:`~zhmcclient.ConnectionError` ### Response: def feature_info(self): """ Returns information about the features available for this CPC. Authorization requirements: * Object-access permission to this CPC. Returns: :term:`iterable`: An iterable where each item represents one feature that is available for this CPC. Each item is a dictionary with the following items: * `name` (:term:`unicode string`): Name of the feature. * `description` (:term:`unicode string`): Short description of the feature. * `state` (bool): Enablement state of the feature (`True` if the enabled, `False` if disabled). Raises: :exc:`ValueError`: Features are not supported on the HMC. :exc:`~zhmcclient.HTTPError` :exc:`~zhmcclient.ParseError` :exc:`~zhmcclient.AuthError` :exc:`~zhmcclient.ConnectionError` """ feature_list = self.prop('available-features-list', None) if feature_list is None: raise ValueError("Firmware features are not supported on CPC %s" % self.name) return feature_list
def add_routes(fapp, routes, prefix=""): """Batch routes registering Register routes to a blueprint/flask_app previously collected with :func:`routes_collector`. :param fapp: bluprint or flask_app to whom attach new routes. :param routes: dict of routes collected by :func:`routes_collector` :param prefix: url prefix under which register all routes """ for r in routes: r['rule'] = prefix + r['rule'] fapp.add_url_rule(**r)
Batch routes registering Register routes to a blueprint/flask_app previously collected with :func:`routes_collector`. :param fapp: bluprint or flask_app to whom attach new routes. :param routes: dict of routes collected by :func:`routes_collector` :param prefix: url prefix under which register all routes
Below is the the instruction that describes the task: ### Input: Batch routes registering Register routes to a blueprint/flask_app previously collected with :func:`routes_collector`. :param fapp: bluprint or flask_app to whom attach new routes. :param routes: dict of routes collected by :func:`routes_collector` :param prefix: url prefix under which register all routes ### Response: def add_routes(fapp, routes, prefix=""): """Batch routes registering Register routes to a blueprint/flask_app previously collected with :func:`routes_collector`. :param fapp: bluprint or flask_app to whom attach new routes. :param routes: dict of routes collected by :func:`routes_collector` :param prefix: url prefix under which register all routes """ for r in routes: r['rule'] = prefix + r['rule'] fapp.add_url_rule(**r)
def theme(name='readthedocs'): """set name to 'bootstrap' in case you want to use bootstrap. This also requires the template sto be in the main dir""" os.environ['SPHINX_THEME'] = name if os.environ['SPHINX_THEME'] == 'bootstrap': local('cp docs/source/_templates/layout_bootstrap.html docs/source/_templates/layout.html') elif name is 'readthedocs': return else: local('cp docs/source/_templates/layout_simple.html docs/source/_templates/layout.html')
set name to 'bootstrap' in case you want to use bootstrap. This also requires the template sto be in the main dir
Below is the the instruction that describes the task: ### Input: set name to 'bootstrap' in case you want to use bootstrap. This also requires the template sto be in the main dir ### Response: def theme(name='readthedocs'): """set name to 'bootstrap' in case you want to use bootstrap. This also requires the template sto be in the main dir""" os.environ['SPHINX_THEME'] = name if os.environ['SPHINX_THEME'] == 'bootstrap': local('cp docs/source/_templates/layout_bootstrap.html docs/source/_templates/layout.html') elif name is 'readthedocs': return else: local('cp docs/source/_templates/layout_simple.html docs/source/_templates/layout.html')
def view(self, rec): ''' View the page. ''' kwd = { 'pager': '', } self.render('wiki_page/page_view.html', postinfo=rec, kwd=kwd, author=rec.user_name, format_date=tools.format_date, userinfo=self.userinfo, cfg=CMS_CFG)
View the page.
Below is the the instruction that describes the task: ### Input: View the page. ### Response: def view(self, rec): ''' View the page. ''' kwd = { 'pager': '', } self.render('wiki_page/page_view.html', postinfo=rec, kwd=kwd, author=rec.user_name, format_date=tools.format_date, userinfo=self.userinfo, cfg=CMS_CFG)
def QA_SU_save_future_min(engine, client=DATABASE): """save future_min Arguments: engine {[type]} -- [description] Keyword Arguments: client {[type]} -- [description] (default: {DATABASE}) """ engine = select_save_engine(engine) engine.QA_SU_save_future_min(client=client)
save future_min Arguments: engine {[type]} -- [description] Keyword Arguments: client {[type]} -- [description] (default: {DATABASE})
Below is the the instruction that describes the task: ### Input: save future_min Arguments: engine {[type]} -- [description] Keyword Arguments: client {[type]} -- [description] (default: {DATABASE}) ### Response: def QA_SU_save_future_min(engine, client=DATABASE): """save future_min Arguments: engine {[type]} -- [description] Keyword Arguments: client {[type]} -- [description] (default: {DATABASE}) """ engine = select_save_engine(engine) engine.QA_SU_save_future_min(client=client)
def _remove_fronts_that_are_too_small(fronts, size): """ Removes all fronts from `fronts` which are strictly smaller than `size` consecutive frequencies in length. """ ids = np.unique(fronts) for id in ids: if id == 0 or id == -1: continue front = _get_front_idxs_from_id(fronts, id) if len(front) < size: indexes = ([f for f, _ in front], [s for _, s in front]) fronts[indexes] = 0
Removes all fronts from `fronts` which are strictly smaller than `size` consecutive frequencies in length.
Below is the the instruction that describes the task: ### Input: Removes all fronts from `fronts` which are strictly smaller than `size` consecutive frequencies in length. ### Response: def _remove_fronts_that_are_too_small(fronts, size): """ Removes all fronts from `fronts` which are strictly smaller than `size` consecutive frequencies in length. """ ids = np.unique(fronts) for id in ids: if id == 0 or id == -1: continue front = _get_front_idxs_from_id(fronts, id) if len(front) < size: indexes = ([f for f, _ in front], [s for _, s in front]) fronts[indexes] = 0
def reset(self, params, repetition): """ Take the steps necessary to reset the experiment before each repetition: - Make sure random seed is different for each repetition - Create the L2-L4-L6a network - Generate objects used by the experiment - Learn all objects used by the experiment """ print params["name"], ":", repetition self.debug = params.get("debug", False) L2Params = json.loads('{' + params["l2_params"] + '}') L4Params = json.loads('{' + params["l4_params"] + '}') L6aParams = json.loads('{' + params["l6a_params"] + '}') # Make sure random seed is different for each repetition seed = params.get("seed", 42) np.random.seed(seed + repetition) random.seed(seed + repetition) L2Params["seed"] = seed + repetition L4Params["seed"] = seed + repetition L6aParams["seed"] = seed + repetition # Configure L6a params numModules = params["num_modules"] L6aParams["scale"] = [params["scale"]] * numModules angle = params["angle"] / numModules orientation = range(angle / 2, angle * numModules, angle) L6aParams["orientation"] = np.radians(orientation).tolist() # Create multi-column L2-L4-L6a network self.numColumns = params["num_cortical_columns"] network = Network() network = createMultipleL246aLocationColumn(network=network, numberOfColumns=self.numColumns, L2Params=L2Params, L4Params=L4Params, L6aParams=L6aParams) network.initialize() self.network = network self.sensorInput = [] self.motorInput = [] self.L2Regions = [] self.L4Regions = [] self.L6aRegions = [] for i in xrange(self.numColumns): col = str(i) self.sensorInput.append(network.regions["sensorInput_" + col].getSelf()) self.motorInput.append(network.regions["motorInput_" + col].getSelf()) self.L2Regions.append(network.regions["L2_" + col]) self.L4Regions.append(network.regions["L4_" + col]) self.L6aRegions.append(network.regions["L6a_" + col]) # Use the number of iterations as the number of objects. This will allow us # to execute one iteration per object and use the "iteration" parameter as # the object index numObjects = params["iterations"] # Generate feature SDRs numFeatures = params["num_features"] numOfMinicolumns = L4Params["columnCount"] numOfActiveMinicolumns = params["num_active_minicolumns"] self.featureSDR = [{ str(f): sorted(np.random.choice(numOfMinicolumns, numOfActiveMinicolumns)) for f in xrange(numFeatures) } for _ in xrange(self.numColumns)] # Generate objects used in the experiment self.objects = generateObjects(numObjects=numObjects, featuresPerObject=params["features_per_object"], objectWidth=params["object_width"], numFeatures=numFeatures, distribution=params["feature_distribution"]) # Make sure the objects are unique uniqueObjs = np.unique([{"features": obj["features"]} for obj in self.objects]) assert len(uniqueObjs) == len(self.objects) self.sdrSize = L2Params["sdrSize"] # Learn objects self.numLearningPoints = params["num_learning_points"] self.numOfSensations = params["num_sensations"] self.learnedObjects = {} self.learn()
Take the steps necessary to reset the experiment before each repetition: - Make sure random seed is different for each repetition - Create the L2-L4-L6a network - Generate objects used by the experiment - Learn all objects used by the experiment
Below is the the instruction that describes the task: ### Input: Take the steps necessary to reset the experiment before each repetition: - Make sure random seed is different for each repetition - Create the L2-L4-L6a network - Generate objects used by the experiment - Learn all objects used by the experiment ### Response: def reset(self, params, repetition): """ Take the steps necessary to reset the experiment before each repetition: - Make sure random seed is different for each repetition - Create the L2-L4-L6a network - Generate objects used by the experiment - Learn all objects used by the experiment """ print params["name"], ":", repetition self.debug = params.get("debug", False) L2Params = json.loads('{' + params["l2_params"] + '}') L4Params = json.loads('{' + params["l4_params"] + '}') L6aParams = json.loads('{' + params["l6a_params"] + '}') # Make sure random seed is different for each repetition seed = params.get("seed", 42) np.random.seed(seed + repetition) random.seed(seed + repetition) L2Params["seed"] = seed + repetition L4Params["seed"] = seed + repetition L6aParams["seed"] = seed + repetition # Configure L6a params numModules = params["num_modules"] L6aParams["scale"] = [params["scale"]] * numModules angle = params["angle"] / numModules orientation = range(angle / 2, angle * numModules, angle) L6aParams["orientation"] = np.radians(orientation).tolist() # Create multi-column L2-L4-L6a network self.numColumns = params["num_cortical_columns"] network = Network() network = createMultipleL246aLocationColumn(network=network, numberOfColumns=self.numColumns, L2Params=L2Params, L4Params=L4Params, L6aParams=L6aParams) network.initialize() self.network = network self.sensorInput = [] self.motorInput = [] self.L2Regions = [] self.L4Regions = [] self.L6aRegions = [] for i in xrange(self.numColumns): col = str(i) self.sensorInput.append(network.regions["sensorInput_" + col].getSelf()) self.motorInput.append(network.regions["motorInput_" + col].getSelf()) self.L2Regions.append(network.regions["L2_" + col]) self.L4Regions.append(network.regions["L4_" + col]) self.L6aRegions.append(network.regions["L6a_" + col]) # Use the number of iterations as the number of objects. This will allow us # to execute one iteration per object and use the "iteration" parameter as # the object index numObjects = params["iterations"] # Generate feature SDRs numFeatures = params["num_features"] numOfMinicolumns = L4Params["columnCount"] numOfActiveMinicolumns = params["num_active_minicolumns"] self.featureSDR = [{ str(f): sorted(np.random.choice(numOfMinicolumns, numOfActiveMinicolumns)) for f in xrange(numFeatures) } for _ in xrange(self.numColumns)] # Generate objects used in the experiment self.objects = generateObjects(numObjects=numObjects, featuresPerObject=params["features_per_object"], objectWidth=params["object_width"], numFeatures=numFeatures, distribution=params["feature_distribution"]) # Make sure the objects are unique uniqueObjs = np.unique([{"features": obj["features"]} for obj in self.objects]) assert len(uniqueObjs) == len(self.objects) self.sdrSize = L2Params["sdrSize"] # Learn objects self.numLearningPoints = params["num_learning_points"] self.numOfSensations = params["num_sensations"] self.learnedObjects = {} self.learn()
def raw_html(self) -> _RawHTML: """Bytes representation of the HTML content. (`learn more <http://www.diveintopython3.net/strings.html>`_). """ if self._html: return self._html else: return etree.tostring(self.element, encoding='unicode').strip().encode(self.encoding)
Bytes representation of the HTML content. (`learn more <http://www.diveintopython3.net/strings.html>`_).
Below is the the instruction that describes the task: ### Input: Bytes representation of the HTML content. (`learn more <http://www.diveintopython3.net/strings.html>`_). ### Response: def raw_html(self) -> _RawHTML: """Bytes representation of the HTML content. (`learn more <http://www.diveintopython3.net/strings.html>`_). """ if self._html: return self._html else: return etree.tostring(self.element, encoding='unicode').strip().encode(self.encoding)
def delete_namespace(self, namespace): """ Delete the specified CIM namespace in the WBEM server and update this WBEMServer object to reflect the removed namespace there. The specified namespace must be empty (i.e. must not contain any classes, instances, or qualifier types. This method attempts the following approaches for deleting the namespace, in order, until an approach succeeds: 1. Issuing the `DeleteInstance` operation using the CIM class representing namespaces ('PG_Namespace' for OpenPegasus, and 'CIM_Namespace' otherwise), against the Interop namespace. This approach is typically supported in WBEM servers that support the creation of CIM namespaces. This approach is similar to the approach described in :term:`DSP0200`. The approach described in the WBEM Server profile (:term:`DSP1092`) via deleting the `CIM_WBEMServerNamespace` instance is not implemented because that would also delete any classes, instances, and qualifier types in the namespace. Deleting namespaces using the `__Namespace` pseudo-class has been deprecated already in DSP0200 1.1.0 (released in 01/2003), and pywbem does not implement that approach. Parameters: namespace (:term:`string`): CIM namespace name. Must not be `None`. The namespace may contain leading and a trailing slash, both of which will be ignored. Returns: :term:`unicode string`: The specified CIM namespace name in its standard format (i.e. without leading or trailing slash characters). Raises: Exceptions raised by :class:`~pywbem.WBEMConnection`. ModelError: An issue with the model implemented by the WBEM server. CIMError: CIM_ERR_NOT_FOUND, Specified namespace does not exist. CIMError: CIM_ERR_NAMESPACE_NOT_EMPTY, Specified namespace is not empty. Additional CIM errors. """ std_namespace = _ensure_unicode(namespace.strip('/')) # Use approach 1: DeleteInstance of CIM class for namespaces # Refresh the list of namespaces in this object to make sure # it is up to date. self._determine_namespaces() if std_namespace not in self.namespaces: raise CIMError( CIM_ERR_NOT_FOUND, _format("Specified namespace does not exist: {0!A}", std_namespace), conn_id=self.conn.conn_id) ns_path = None for p in self.namespace_paths: if p.keybindings['Name'] == std_namespace: ns_path = p assert ns_path is not None # Ensure the namespace is empty. We do not check for instances, because # classes are a prerequisite for instances, so if no classes exist, # no instances will exist. # WBEM servers that do not support class operations (e.g. SFCB) will # raise a CIMError with status CIM_ERR_NOT_SUPPORTED. class_paths = self.conn.EnumerateClassNames( namespace=std_namespace, ClassName=None, DeepInheritance=False) quals = self.conn.EnumerateQualifiers(namespace=std_namespace) if class_paths or quals: raise CIMError( CIM_ERR_NAMESPACE_NOT_EMPTY, _format("Specified namespace {0!A} is not empty; it contains " "{1} top-level classes and {2} qualifier types", std_namespace, len(class_paths), len(quals)), conn_id=self.conn.conn_id) self.conn.DeleteInstance(ns_path) # Refresh the list of namespaces in this object to remove the one # we just deleted. self._determine_namespaces() return std_namespace
Delete the specified CIM namespace in the WBEM server and update this WBEMServer object to reflect the removed namespace there. The specified namespace must be empty (i.e. must not contain any classes, instances, or qualifier types. This method attempts the following approaches for deleting the namespace, in order, until an approach succeeds: 1. Issuing the `DeleteInstance` operation using the CIM class representing namespaces ('PG_Namespace' for OpenPegasus, and 'CIM_Namespace' otherwise), against the Interop namespace. This approach is typically supported in WBEM servers that support the creation of CIM namespaces. This approach is similar to the approach described in :term:`DSP0200`. The approach described in the WBEM Server profile (:term:`DSP1092`) via deleting the `CIM_WBEMServerNamespace` instance is not implemented because that would also delete any classes, instances, and qualifier types in the namespace. Deleting namespaces using the `__Namespace` pseudo-class has been deprecated already in DSP0200 1.1.0 (released in 01/2003), and pywbem does not implement that approach. Parameters: namespace (:term:`string`): CIM namespace name. Must not be `None`. The namespace may contain leading and a trailing slash, both of which will be ignored. Returns: :term:`unicode string`: The specified CIM namespace name in its standard format (i.e. without leading or trailing slash characters). Raises: Exceptions raised by :class:`~pywbem.WBEMConnection`. ModelError: An issue with the model implemented by the WBEM server. CIMError: CIM_ERR_NOT_FOUND, Specified namespace does not exist. CIMError: CIM_ERR_NAMESPACE_NOT_EMPTY, Specified namespace is not empty. Additional CIM errors.
Below is the the instruction that describes the task: ### Input: Delete the specified CIM namespace in the WBEM server and update this WBEMServer object to reflect the removed namespace there. The specified namespace must be empty (i.e. must not contain any classes, instances, or qualifier types. This method attempts the following approaches for deleting the namespace, in order, until an approach succeeds: 1. Issuing the `DeleteInstance` operation using the CIM class representing namespaces ('PG_Namespace' for OpenPegasus, and 'CIM_Namespace' otherwise), against the Interop namespace. This approach is typically supported in WBEM servers that support the creation of CIM namespaces. This approach is similar to the approach described in :term:`DSP0200`. The approach described in the WBEM Server profile (:term:`DSP1092`) via deleting the `CIM_WBEMServerNamespace` instance is not implemented because that would also delete any classes, instances, and qualifier types in the namespace. Deleting namespaces using the `__Namespace` pseudo-class has been deprecated already in DSP0200 1.1.0 (released in 01/2003), and pywbem does not implement that approach. Parameters: namespace (:term:`string`): CIM namespace name. Must not be `None`. The namespace may contain leading and a trailing slash, both of which will be ignored. Returns: :term:`unicode string`: The specified CIM namespace name in its standard format (i.e. without leading or trailing slash characters). Raises: Exceptions raised by :class:`~pywbem.WBEMConnection`. ModelError: An issue with the model implemented by the WBEM server. CIMError: CIM_ERR_NOT_FOUND, Specified namespace does not exist. CIMError: CIM_ERR_NAMESPACE_NOT_EMPTY, Specified namespace is not empty. Additional CIM errors. ### Response: def delete_namespace(self, namespace): """ Delete the specified CIM namespace in the WBEM server and update this WBEMServer object to reflect the removed namespace there. The specified namespace must be empty (i.e. must not contain any classes, instances, or qualifier types. This method attempts the following approaches for deleting the namespace, in order, until an approach succeeds: 1. Issuing the `DeleteInstance` operation using the CIM class representing namespaces ('PG_Namespace' for OpenPegasus, and 'CIM_Namespace' otherwise), against the Interop namespace. This approach is typically supported in WBEM servers that support the creation of CIM namespaces. This approach is similar to the approach described in :term:`DSP0200`. The approach described in the WBEM Server profile (:term:`DSP1092`) via deleting the `CIM_WBEMServerNamespace` instance is not implemented because that would also delete any classes, instances, and qualifier types in the namespace. Deleting namespaces using the `__Namespace` pseudo-class has been deprecated already in DSP0200 1.1.0 (released in 01/2003), and pywbem does not implement that approach. Parameters: namespace (:term:`string`): CIM namespace name. Must not be `None`. The namespace may contain leading and a trailing slash, both of which will be ignored. Returns: :term:`unicode string`: The specified CIM namespace name in its standard format (i.e. without leading or trailing slash characters). Raises: Exceptions raised by :class:`~pywbem.WBEMConnection`. ModelError: An issue with the model implemented by the WBEM server. CIMError: CIM_ERR_NOT_FOUND, Specified namespace does not exist. CIMError: CIM_ERR_NAMESPACE_NOT_EMPTY, Specified namespace is not empty. Additional CIM errors. """ std_namespace = _ensure_unicode(namespace.strip('/')) # Use approach 1: DeleteInstance of CIM class for namespaces # Refresh the list of namespaces in this object to make sure # it is up to date. self._determine_namespaces() if std_namespace not in self.namespaces: raise CIMError( CIM_ERR_NOT_FOUND, _format("Specified namespace does not exist: {0!A}", std_namespace), conn_id=self.conn.conn_id) ns_path = None for p in self.namespace_paths: if p.keybindings['Name'] == std_namespace: ns_path = p assert ns_path is not None # Ensure the namespace is empty. We do not check for instances, because # classes are a prerequisite for instances, so if no classes exist, # no instances will exist. # WBEM servers that do not support class operations (e.g. SFCB) will # raise a CIMError with status CIM_ERR_NOT_SUPPORTED. class_paths = self.conn.EnumerateClassNames( namespace=std_namespace, ClassName=None, DeepInheritance=False) quals = self.conn.EnumerateQualifiers(namespace=std_namespace) if class_paths or quals: raise CIMError( CIM_ERR_NAMESPACE_NOT_EMPTY, _format("Specified namespace {0!A} is not empty; it contains " "{1} top-level classes and {2} qualifier types", std_namespace, len(class_paths), len(quals)), conn_id=self.conn.conn_id) self.conn.DeleteInstance(ns_path) # Refresh the list of namespaces in this object to remove the one # we just deleted. self._determine_namespaces() return std_namespace
def v(*args, **kwargs): ''' print the name = values of any passed in variables this prints out the passed in name, the value, and the file:line where the v() method was called so you can easily find it and remove it later example -- foo = 1 bar = [1, 2, 3] out.v(foo, bar) """ prints out: foo = 1 bar = [ 0: 1, 1: 2, 2: 3 ] (/file:line) """ *args -- list -- the variables you want to see pretty printed for humans ''' if not args: raise ValueError("you didn't pass any arguments to print out") with Reflect.context(args, **kwargs) as r: instance = V_CLASS(r, stream, **kwargs) instance()
print the name = values of any passed in variables this prints out the passed in name, the value, and the file:line where the v() method was called so you can easily find it and remove it later example -- foo = 1 bar = [1, 2, 3] out.v(foo, bar) """ prints out: foo = 1 bar = [ 0: 1, 1: 2, 2: 3 ] (/file:line) """ *args -- list -- the variables you want to see pretty printed for humans
Below is the the instruction that describes the task: ### Input: print the name = values of any passed in variables this prints out the passed in name, the value, and the file:line where the v() method was called so you can easily find it and remove it later example -- foo = 1 bar = [1, 2, 3] out.v(foo, bar) """ prints out: foo = 1 bar = [ 0: 1, 1: 2, 2: 3 ] (/file:line) """ *args -- list -- the variables you want to see pretty printed for humans ### Response: def v(*args, **kwargs): ''' print the name = values of any passed in variables this prints out the passed in name, the value, and the file:line where the v() method was called so you can easily find it and remove it later example -- foo = 1 bar = [1, 2, 3] out.v(foo, bar) """ prints out: foo = 1 bar = [ 0: 1, 1: 2, 2: 3 ] (/file:line) """ *args -- list -- the variables you want to see pretty printed for humans ''' if not args: raise ValueError("you didn't pass any arguments to print out") with Reflect.context(args, **kwargs) as r: instance = V_CLASS(r, stream, **kwargs) instance()
def sendEmail(self, subject, body, toAddress=False): """ sends an email using the agrcpythonemailer@gmail.com account """ if not toAddress: toAddress = self.toAddress toAddress = toAddress.split(';') message = MIMEText(body) message['Subject'] = subject message['From'] = self.fromAddress message['To'] = ','.join(toAddress) if not self.testing: s = SMTP(self.server, self.port) s.sendmail(self.fromAddress, toAddress, message.as_string()) s.quit() print('email sent') else: print('***Begin Test Email Message***') print(message) print('***End Test Email Message***')
sends an email using the agrcpythonemailer@gmail.com account
Below is the the instruction that describes the task: ### Input: sends an email using the agrcpythonemailer@gmail.com account ### Response: def sendEmail(self, subject, body, toAddress=False): """ sends an email using the agrcpythonemailer@gmail.com account """ if not toAddress: toAddress = self.toAddress toAddress = toAddress.split(';') message = MIMEText(body) message['Subject'] = subject message['From'] = self.fromAddress message['To'] = ','.join(toAddress) if not self.testing: s = SMTP(self.server, self.port) s.sendmail(self.fromAddress, toAddress, message.as_string()) s.quit() print('email sent') else: print('***Begin Test Email Message***') print(message) print('***End Test Email Message***')
def validate_adapter_class(validate_class, adapter_class): """ Raises an exception if validate_class is not a subclass of adapter_class. :param validate_class: The class to be validated. :type validate_class: class :param adapter_class: The class type to check against. :type adapter_class: class :raises: Adapter.InvalidAdapterTypeException """ from chatterbot.adapters import Adapter # If a dictionary was passed in, check if it has an import_path attribute if isinstance(validate_class, dict): if 'import_path' not in validate_class: raise Adapter.InvalidAdapterTypeException( 'The dictionary {} must contain a value for "import_path"'.format( str(validate_class) ) ) # Set the class to the import path for the next check validate_class = validate_class.get('import_path') if not issubclass(import_module(validate_class), adapter_class): raise Adapter.InvalidAdapterTypeException( '{} must be a subclass of {}'.format( validate_class, adapter_class.__name__ ) )
Raises an exception if validate_class is not a subclass of adapter_class. :param validate_class: The class to be validated. :type validate_class: class :param adapter_class: The class type to check against. :type adapter_class: class :raises: Adapter.InvalidAdapterTypeException
Below is the the instruction that describes the task: ### Input: Raises an exception if validate_class is not a subclass of adapter_class. :param validate_class: The class to be validated. :type validate_class: class :param adapter_class: The class type to check against. :type adapter_class: class :raises: Adapter.InvalidAdapterTypeException ### Response: def validate_adapter_class(validate_class, adapter_class): """ Raises an exception if validate_class is not a subclass of adapter_class. :param validate_class: The class to be validated. :type validate_class: class :param adapter_class: The class type to check against. :type adapter_class: class :raises: Adapter.InvalidAdapterTypeException """ from chatterbot.adapters import Adapter # If a dictionary was passed in, check if it has an import_path attribute if isinstance(validate_class, dict): if 'import_path' not in validate_class: raise Adapter.InvalidAdapterTypeException( 'The dictionary {} must contain a value for "import_path"'.format( str(validate_class) ) ) # Set the class to the import path for the next check validate_class = validate_class.get('import_path') if not issubclass(import_module(validate_class), adapter_class): raise Adapter.InvalidAdapterTypeException( '{} must be a subclass of {}'.format( validate_class, adapter_class.__name__ ) )
def export(self, timestamp=None): """ Get the current notebook data and export. """ if self._timestamp is None: raise Exception("No timestamp set. Has the archive been initialized?") if self.skip_notebook_export: super(NotebookArchive, self).export(timestamp=self._timestamp, info={'notebook':self.notebook_name}) return self.export_success = None name = self.get_namespace() # Unfortunate javascript hacks to get at notebook data capture_cmd = ((r"var capture = '%s._notebook_data=r\"\"\"'" % name) + r"+json_string+'\"\"\"'; ") cmd = (r'var kernel = IPython.notebook.kernel; ' + r'var json_data = IPython.notebook.toJSON(); ' + r'var json_string = JSON.stringify(json_data); ' + capture_cmd + "var pycmd = capture + ';%s._export_with_html()'; " % name + r"kernel.execute(pycmd)") tstamp = time.strftime(self.timestamp_format, self._timestamp) export_name = self._format(self.export_name, {'timestamp':tstamp, 'notebook':self.notebook_name}) print(('Export name: %r\nDirectory %r' % (export_name, os.path.join(os.path.abspath(self.root)))) + '\n\nIf no output appears, please check holoviews.archive.last_export_status()') display(Javascript(cmd))
Get the current notebook data and export.
Below is the the instruction that describes the task: ### Input: Get the current notebook data and export. ### Response: def export(self, timestamp=None): """ Get the current notebook data and export. """ if self._timestamp is None: raise Exception("No timestamp set. Has the archive been initialized?") if self.skip_notebook_export: super(NotebookArchive, self).export(timestamp=self._timestamp, info={'notebook':self.notebook_name}) return self.export_success = None name = self.get_namespace() # Unfortunate javascript hacks to get at notebook data capture_cmd = ((r"var capture = '%s._notebook_data=r\"\"\"'" % name) + r"+json_string+'\"\"\"'; ") cmd = (r'var kernel = IPython.notebook.kernel; ' + r'var json_data = IPython.notebook.toJSON(); ' + r'var json_string = JSON.stringify(json_data); ' + capture_cmd + "var pycmd = capture + ';%s._export_with_html()'; " % name + r"kernel.execute(pycmd)") tstamp = time.strftime(self.timestamp_format, self._timestamp) export_name = self._format(self.export_name, {'timestamp':tstamp, 'notebook':self.notebook_name}) print(('Export name: %r\nDirectory %r' % (export_name, os.path.join(os.path.abspath(self.root)))) + '\n\nIf no output appears, please check holoviews.archive.last_export_status()') display(Javascript(cmd))
def parse_annotations( self, annotation_file, genes, db_sel='UniProtKB', select_evidence=None, exclude_evidence=None, exclude_ref=None, strip_species=False, ignore_case=False): """Parse a GO annotation file (in GAF 2.0 format). GO annotation files can be downloaded from the `UniProt-GOA download site`__ or from their `FTP server`__. __ goa_download_ __ goa_ftp_ .. _goa_download: http://www.ebi.ac.uk/GOA/downloads .. _goa_ftp: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/ Parameters ---------- annotation_file: str Path of the annotation file (in GAF 2.0 format). genes: List (tuple, set) of str List of valid gene names. db_sel: str, optional Select only annotations with this ``DB`` (column 1) value. If empty, disable filtering based on the ``DB`` value. select_evidence: list of str, optional Only include annotations with the given evidence codes. It not specified, allow all evidence codes, except for those listed in ``exclude_evidence``. exclude_evidence: list of str, optional Exclude all annotations with any of the given evidence codes. If ``select_evidence`` is specified, this parameter is ignored. If not specified, allow all evidence codes. exclude_ref: list of str, optional Exclude all annotations with the given DB:reference (column 6). Example: ``["PMID:2676709"]``. Note: This filter is currently ignored if an annotation has more than one reference. strip_species: bool, optional Undocumented. ignore_case: bool, optional Undocumented. Returns ------- None """ assert isinstance(annotation_file, str) assert isinstance(genes, (list, tuple)) if not self.terms: raise ValueError('You need to first parse an OBO file!') if select_evidence is None: select_evidence = [] if exclude_evidence is None: exclude_evidence = [] if exclude_ref is None: exclude_ref = [] # always overwrite all previously parsed annotations self.clear_annotation_data() # store genes self.genes = set(genes) # store the list of genes for later use genes_upper = dict((g.upper(), g) for g in genes) logger.info('Read %d genes.', len(genes)) # read annotations self.term_annotations = dict((id_, []) for id_ in self.terms) self.gene_annotations = dict((g, []) for g in self.genes) # gene_terms is used for statistics gene_terms = dict((g, set()) for g in self.genes) # isoform_pattern = re.compile(r"UniProtKB:([A-Z][0-9A-Z]{5}-\d+)") # gene_pattern = re.compile(r"[a-zA-Z0-9]+\.\d+$") # pmid_pattern = re.compile(r"(?:PMID:\d+|DOI:[^\s]+)") # uniprot_pattern = re.compile(r"UniProtKB:([A-Z][0-9A-Z]{5}(?:-\d+)?)") unknown_gene_names = Counter() unknown_gene_annotations = 0 unknown_term_ids = Counter() unknown_term_annotations = 0 # Parsing! logger.info('Parsing annotations...') n = 0 excluded_evidence_annotations = 0 excluded_reference_annotations = 0 valid_annotations = 0 with misc.smart_open_read(annotation_file, mode='rb', try_gzip=True) as fh: reader = csv.reader(fh, dialect='excel-tab', encoding='UTF-8') for i, l in enumerate(reader): # gene = None if not l: continue if ((not db_sel) or l[0] == db_sel) and l[3] != 'NOT': n += 1 # test if evidence code is excluded if (select_evidence and l[6] not in select_evidence) \ or l[6] in exclude_evidence: excluded_evidence_annotations += 1 continue # test if reference is excluded db_ref = [] if l[5]: db_ref = l[5].split('|') if len(db_ref) == 1 and db_ref[0] in exclude_ref: excluded_reference_annotations += 1 continue # determine target gene if not l[2]: raise Exception('Missing target gene in line %d:\n%s' % (i+1, '\t'.join(l))) gene = l[2] # db = l[0] db_id = l[1] if strip_species: try: gene = gene[:gene.rindex('_')] except ValueError: pass term_id = l[4] evidence = l[6] invalid = False if (ignore_case and gene.upper() not in genes_upper) \ or ((not ignore_case) and gene not in self.genes): unknown_gene_annotations += 1 unknown_gene_names[l[2]] += 1 invalid = True if term_id not in self.terms: unknown_term_annotations += 1 unknown_term_ids[term_id] += 1 invalid = True if not invalid: valid_annotations += 1 # if ignore_case, convert gene to "original" name if ignore_case: gene = genes_upper[gene.upper()] term = self.terms[term_id] # parse secondary information # (associated UniProt and PubMed entries) # pmid = pmid_pattern.search(l[5]) # if pmid is not None: pmid = pmid.group(0) # uniprot = uniprot_pattern.search(l[7]) # if uniprot is not None: uniprot = uniprot.group(1) with_ = [] if l[7]: with_ = l[7].split('|') # generate annotation ann = GOAnnotation( gene=gene, term=term, evidence=evidence, db_id=db_id, db_ref=db_ref, with_=with_) # add annotation to global list self.annotations.append(ann) # add annotation under term ID self.term_annotations[term_id].append(ann) # add annotation under gene self.gene_annotations[gene].append(ann) gene_terms[gene].add(term_id) # output some statistics if n > 0: logger.info('Parsed %d positive GO annotations ' '(%d = %.1f%% excluded based on evidence type).', n, excluded_evidence_annotations, 100*(excluded_evidence_annotations/float(n))) if unknown_gene_annotations > 0: logger.warning('Warning: %d annotations with %d unkonwn gene ' 'names.', unknown_gene_annotations, len(unknown_gene_names)) if unknown_term_annotations > 0: logger.warning('Warning: %d annotations with %d unkonwn term IDs.', unknown_term_annotations, len(unknown_term_ids)) logger.info('Found a total of %d valid annotations.', valid_annotations) logger.info('%d unique Gene-Term associations.', sum(len(gene_terms[g]) for g in genes))
Parse a GO annotation file (in GAF 2.0 format). GO annotation files can be downloaded from the `UniProt-GOA download site`__ or from their `FTP server`__. __ goa_download_ __ goa_ftp_ .. _goa_download: http://www.ebi.ac.uk/GOA/downloads .. _goa_ftp: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/ Parameters ---------- annotation_file: str Path of the annotation file (in GAF 2.0 format). genes: List (tuple, set) of str List of valid gene names. db_sel: str, optional Select only annotations with this ``DB`` (column 1) value. If empty, disable filtering based on the ``DB`` value. select_evidence: list of str, optional Only include annotations with the given evidence codes. It not specified, allow all evidence codes, except for those listed in ``exclude_evidence``. exclude_evidence: list of str, optional Exclude all annotations with any of the given evidence codes. If ``select_evidence`` is specified, this parameter is ignored. If not specified, allow all evidence codes. exclude_ref: list of str, optional Exclude all annotations with the given DB:reference (column 6). Example: ``["PMID:2676709"]``. Note: This filter is currently ignored if an annotation has more than one reference. strip_species: bool, optional Undocumented. ignore_case: bool, optional Undocumented. Returns ------- None
Below is the the instruction that describes the task: ### Input: Parse a GO annotation file (in GAF 2.0 format). GO annotation files can be downloaded from the `UniProt-GOA download site`__ or from their `FTP server`__. __ goa_download_ __ goa_ftp_ .. _goa_download: http://www.ebi.ac.uk/GOA/downloads .. _goa_ftp: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/ Parameters ---------- annotation_file: str Path of the annotation file (in GAF 2.0 format). genes: List (tuple, set) of str List of valid gene names. db_sel: str, optional Select only annotations with this ``DB`` (column 1) value. If empty, disable filtering based on the ``DB`` value. select_evidence: list of str, optional Only include annotations with the given evidence codes. It not specified, allow all evidence codes, except for those listed in ``exclude_evidence``. exclude_evidence: list of str, optional Exclude all annotations with any of the given evidence codes. If ``select_evidence`` is specified, this parameter is ignored. If not specified, allow all evidence codes. exclude_ref: list of str, optional Exclude all annotations with the given DB:reference (column 6). Example: ``["PMID:2676709"]``. Note: This filter is currently ignored if an annotation has more than one reference. strip_species: bool, optional Undocumented. ignore_case: bool, optional Undocumented. Returns ------- None ### Response: def parse_annotations( self, annotation_file, genes, db_sel='UniProtKB', select_evidence=None, exclude_evidence=None, exclude_ref=None, strip_species=False, ignore_case=False): """Parse a GO annotation file (in GAF 2.0 format). GO annotation files can be downloaded from the `UniProt-GOA download site`__ or from their `FTP server`__. __ goa_download_ __ goa_ftp_ .. _goa_download: http://www.ebi.ac.uk/GOA/downloads .. _goa_ftp: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/ Parameters ---------- annotation_file: str Path of the annotation file (in GAF 2.0 format). genes: List (tuple, set) of str List of valid gene names. db_sel: str, optional Select only annotations with this ``DB`` (column 1) value. If empty, disable filtering based on the ``DB`` value. select_evidence: list of str, optional Only include annotations with the given evidence codes. It not specified, allow all evidence codes, except for those listed in ``exclude_evidence``. exclude_evidence: list of str, optional Exclude all annotations with any of the given evidence codes. If ``select_evidence`` is specified, this parameter is ignored. If not specified, allow all evidence codes. exclude_ref: list of str, optional Exclude all annotations with the given DB:reference (column 6). Example: ``["PMID:2676709"]``. Note: This filter is currently ignored if an annotation has more than one reference. strip_species: bool, optional Undocumented. ignore_case: bool, optional Undocumented. Returns ------- None """ assert isinstance(annotation_file, str) assert isinstance(genes, (list, tuple)) if not self.terms: raise ValueError('You need to first parse an OBO file!') if select_evidence is None: select_evidence = [] if exclude_evidence is None: exclude_evidence = [] if exclude_ref is None: exclude_ref = [] # always overwrite all previously parsed annotations self.clear_annotation_data() # store genes self.genes = set(genes) # store the list of genes for later use genes_upper = dict((g.upper(), g) for g in genes) logger.info('Read %d genes.', len(genes)) # read annotations self.term_annotations = dict((id_, []) for id_ in self.terms) self.gene_annotations = dict((g, []) for g in self.genes) # gene_terms is used for statistics gene_terms = dict((g, set()) for g in self.genes) # isoform_pattern = re.compile(r"UniProtKB:([A-Z][0-9A-Z]{5}-\d+)") # gene_pattern = re.compile(r"[a-zA-Z0-9]+\.\d+$") # pmid_pattern = re.compile(r"(?:PMID:\d+|DOI:[^\s]+)") # uniprot_pattern = re.compile(r"UniProtKB:([A-Z][0-9A-Z]{5}(?:-\d+)?)") unknown_gene_names = Counter() unknown_gene_annotations = 0 unknown_term_ids = Counter() unknown_term_annotations = 0 # Parsing! logger.info('Parsing annotations...') n = 0 excluded_evidence_annotations = 0 excluded_reference_annotations = 0 valid_annotations = 0 with misc.smart_open_read(annotation_file, mode='rb', try_gzip=True) as fh: reader = csv.reader(fh, dialect='excel-tab', encoding='UTF-8') for i, l in enumerate(reader): # gene = None if not l: continue if ((not db_sel) or l[0] == db_sel) and l[3] != 'NOT': n += 1 # test if evidence code is excluded if (select_evidence and l[6] not in select_evidence) \ or l[6] in exclude_evidence: excluded_evidence_annotations += 1 continue # test if reference is excluded db_ref = [] if l[5]: db_ref = l[5].split('|') if len(db_ref) == 1 and db_ref[0] in exclude_ref: excluded_reference_annotations += 1 continue # determine target gene if not l[2]: raise Exception('Missing target gene in line %d:\n%s' % (i+1, '\t'.join(l))) gene = l[2] # db = l[0] db_id = l[1] if strip_species: try: gene = gene[:gene.rindex('_')] except ValueError: pass term_id = l[4] evidence = l[6] invalid = False if (ignore_case and gene.upper() not in genes_upper) \ or ((not ignore_case) and gene not in self.genes): unknown_gene_annotations += 1 unknown_gene_names[l[2]] += 1 invalid = True if term_id not in self.terms: unknown_term_annotations += 1 unknown_term_ids[term_id] += 1 invalid = True if not invalid: valid_annotations += 1 # if ignore_case, convert gene to "original" name if ignore_case: gene = genes_upper[gene.upper()] term = self.terms[term_id] # parse secondary information # (associated UniProt and PubMed entries) # pmid = pmid_pattern.search(l[5]) # if pmid is not None: pmid = pmid.group(0) # uniprot = uniprot_pattern.search(l[7]) # if uniprot is not None: uniprot = uniprot.group(1) with_ = [] if l[7]: with_ = l[7].split('|') # generate annotation ann = GOAnnotation( gene=gene, term=term, evidence=evidence, db_id=db_id, db_ref=db_ref, with_=with_) # add annotation to global list self.annotations.append(ann) # add annotation under term ID self.term_annotations[term_id].append(ann) # add annotation under gene self.gene_annotations[gene].append(ann) gene_terms[gene].add(term_id) # output some statistics if n > 0: logger.info('Parsed %d positive GO annotations ' '(%d = %.1f%% excluded based on evidence type).', n, excluded_evidence_annotations, 100*(excluded_evidence_annotations/float(n))) if unknown_gene_annotations > 0: logger.warning('Warning: %d annotations with %d unkonwn gene ' 'names.', unknown_gene_annotations, len(unknown_gene_names)) if unknown_term_annotations > 0: logger.warning('Warning: %d annotations with %d unkonwn term IDs.', unknown_term_annotations, len(unknown_term_ids)) logger.info('Found a total of %d valid annotations.', valid_annotations) logger.info('%d unique Gene-Term associations.', sum(len(gene_terms[g]) for g in genes))
def create_asset_class(self, item: AssetClass): """ Inserts the record """ session = self.open_session() session.add(item) session.commit()
Inserts the record
Below is the the instruction that describes the task: ### Input: Inserts the record ### Response: def create_asset_class(self, item: AssetClass): """ Inserts the record """ session = self.open_session() session.add(item) session.commit()
def search(self, search_string): '''Finds every occurrence (including overlapping ones) of the search_string, including on the reverse strand. Returns a list where each element is a tuple (position, strand) where strand is in ['-', '+']. Positions are zero-based''' seq = self.seq.upper() search_string = search_string.upper() pos = 0 found = seq.find(search_string, pos) hits = [] while found != -1: hits.append((found, '+')) pos = found + 1 found = seq.find(search_string, pos) pos = 0 search_string = Fasta('x', search_string) search_string.revcomp() search_string = search_string.seq found = seq.find(search_string, pos) while found != -1: hits.append((found, '-')) pos = found + 1 found = seq.find(search_string, pos) return hits
Finds every occurrence (including overlapping ones) of the search_string, including on the reverse strand. Returns a list where each element is a tuple (position, strand) where strand is in ['-', '+']. Positions are zero-based
Below is the the instruction that describes the task: ### Input: Finds every occurrence (including overlapping ones) of the search_string, including on the reverse strand. Returns a list where each element is a tuple (position, strand) where strand is in ['-', '+']. Positions are zero-based ### Response: def search(self, search_string): '''Finds every occurrence (including overlapping ones) of the search_string, including on the reverse strand. Returns a list where each element is a tuple (position, strand) where strand is in ['-', '+']. Positions are zero-based''' seq = self.seq.upper() search_string = search_string.upper() pos = 0 found = seq.find(search_string, pos) hits = [] while found != -1: hits.append((found, '+')) pos = found + 1 found = seq.find(search_string, pos) pos = 0 search_string = Fasta('x', search_string) search_string.revcomp() search_string = search_string.seq found = seq.find(search_string, pos) while found != -1: hits.append((found, '-')) pos = found + 1 found = seq.find(search_string, pos) return hits
def _normalize_window(window, nfft, library, dtype): """Normalise a window specification for a PSD calculation Parameters ---------- window : `str`, `numpy.ndarray`, `None` the input window specification nfft : `int` the length of the Fourier transform, in samples library : `str` the name of the library that provides the PSD routine dtype : `type` the required type of the window array, only used if `library='lal'` is given Returns ------- window : `numpy.ndarray`, `lal.REAL8Window` a numpy-, or `LAL`-format window array """ if library == '_lal' and isinstance(window, numpy.ndarray): from ._lal import window_from_array return window_from_array(window) if library == '_lal': from ._lal import generate_window return generate_window(nfft, window=window, dtype=dtype) if isinstance(window, string_types): window = canonical_name(window) if isinstance(window, string_types + (tuple,)): return get_window(window, nfft) return None
Normalise a window specification for a PSD calculation Parameters ---------- window : `str`, `numpy.ndarray`, `None` the input window specification nfft : `int` the length of the Fourier transform, in samples library : `str` the name of the library that provides the PSD routine dtype : `type` the required type of the window array, only used if `library='lal'` is given Returns ------- window : `numpy.ndarray`, `lal.REAL8Window` a numpy-, or `LAL`-format window array
Below is the the instruction that describes the task: ### Input: Normalise a window specification for a PSD calculation Parameters ---------- window : `str`, `numpy.ndarray`, `None` the input window specification nfft : `int` the length of the Fourier transform, in samples library : `str` the name of the library that provides the PSD routine dtype : `type` the required type of the window array, only used if `library='lal'` is given Returns ------- window : `numpy.ndarray`, `lal.REAL8Window` a numpy-, or `LAL`-format window array ### Response: def _normalize_window(window, nfft, library, dtype): """Normalise a window specification for a PSD calculation Parameters ---------- window : `str`, `numpy.ndarray`, `None` the input window specification nfft : `int` the length of the Fourier transform, in samples library : `str` the name of the library that provides the PSD routine dtype : `type` the required type of the window array, only used if `library='lal'` is given Returns ------- window : `numpy.ndarray`, `lal.REAL8Window` a numpy-, or `LAL`-format window array """ if library == '_lal' and isinstance(window, numpy.ndarray): from ._lal import window_from_array return window_from_array(window) if library == '_lal': from ._lal import generate_window return generate_window(nfft, window=window, dtype=dtype) if isinstance(window, string_types): window = canonical_name(window) if isinstance(window, string_types + (tuple,)): return get_window(window, nfft) return None
def ls(system, user, local, include_missing): """List configuration files detected (and/or examined paths).""" # default action is to list *all* auto-detected files if not (system or user or local): system = user = local = True for path in get_configfile_paths(system=system, user=user, local=local, only_existing=not include_missing): click.echo(path)
List configuration files detected (and/or examined paths).
Below is the the instruction that describes the task: ### Input: List configuration files detected (and/or examined paths). ### Response: def ls(system, user, local, include_missing): """List configuration files detected (and/or examined paths).""" # default action is to list *all* auto-detected files if not (system or user or local): system = user = local = True for path in get_configfile_paths(system=system, user=user, local=local, only_existing=not include_missing): click.echo(path)
def add(self, subcmd_cb): """Add subcmd to the available subcommands for this object. It will have the supplied docstring, and subcmd_cb will be called when we want to run the command. min_len is the minimum length allowed to abbreviate the command. in_list indicates with the show command will be run when giving a list of all sub commands of this object. Some commands have long output like "show commands" so we might not want to show that. """ subcmd_name = subcmd_cb.name self.subcmds[subcmd_name] = subcmd_cb # We keep a list of subcommands to assist command completion self.cmdlist.append(subcmd_name)
Add subcmd to the available subcommands for this object. It will have the supplied docstring, and subcmd_cb will be called when we want to run the command. min_len is the minimum length allowed to abbreviate the command. in_list indicates with the show command will be run when giving a list of all sub commands of this object. Some commands have long output like "show commands" so we might not want to show that.
Below is the the instruction that describes the task: ### Input: Add subcmd to the available subcommands for this object. It will have the supplied docstring, and subcmd_cb will be called when we want to run the command. min_len is the minimum length allowed to abbreviate the command. in_list indicates with the show command will be run when giving a list of all sub commands of this object. Some commands have long output like "show commands" so we might not want to show that. ### Response: def add(self, subcmd_cb): """Add subcmd to the available subcommands for this object. It will have the supplied docstring, and subcmd_cb will be called when we want to run the command. min_len is the minimum length allowed to abbreviate the command. in_list indicates with the show command will be run when giving a list of all sub commands of this object. Some commands have long output like "show commands" so we might not want to show that. """ subcmd_name = subcmd_cb.name self.subcmds[subcmd_name] = subcmd_cb # We keep a list of subcommands to assist command completion self.cmdlist.append(subcmd_name)
def connected_sites( self, site_labels=None ): """ Searches the lattice to find sets of sites that are contiguously neighbouring. Mutually exclusive sets of contiguous sites are returned as Cluster objects. Args: site_labels (:obj:(List(Str)|Set(Str)|Str), optional): Labels for sites to be considered in the search. This can be a list:: [ 'A', 'B' ] a set:: ( 'A', 'B' ) or a string:: 'A'. Returns: (List(Cluster)): List of Cluster objects for groups of contiguous sites. """ if site_labels: selected_sites = self.select_sites( site_labels ) else: selected_sites = self.sites initial_clusters = [ cluster.Cluster( [ site ] ) for site in selected_sites ] if site_labels: blocking_sites = self.site_labels - set( site_labels ) for c in initial_clusters: c.remove_sites_from_neighbours( blocking_sites ) final_clusters = [] while initial_clusters: # loop until initial_clusters is empty this_cluster = initial_clusters.pop(0) while this_cluster.neighbours: neighbouring_clusters = [ c for c in initial_clusters if this_cluster.is_neighbouring( c ) ] for nc in neighbouring_clusters: initial_clusters.remove( nc ) this_cluster = this_cluster.merge( nc ) final_clusters.append( this_cluster ) return final_clusters
Searches the lattice to find sets of sites that are contiguously neighbouring. Mutually exclusive sets of contiguous sites are returned as Cluster objects. Args: site_labels (:obj:(List(Str)|Set(Str)|Str), optional): Labels for sites to be considered in the search. This can be a list:: [ 'A', 'B' ] a set:: ( 'A', 'B' ) or a string:: 'A'. Returns: (List(Cluster)): List of Cluster objects for groups of contiguous sites.
Below is the the instruction that describes the task: ### Input: Searches the lattice to find sets of sites that are contiguously neighbouring. Mutually exclusive sets of contiguous sites are returned as Cluster objects. Args: site_labels (:obj:(List(Str)|Set(Str)|Str), optional): Labels for sites to be considered in the search. This can be a list:: [ 'A', 'B' ] a set:: ( 'A', 'B' ) or a string:: 'A'. Returns: (List(Cluster)): List of Cluster objects for groups of contiguous sites. ### Response: def connected_sites( self, site_labels=None ): """ Searches the lattice to find sets of sites that are contiguously neighbouring. Mutually exclusive sets of contiguous sites are returned as Cluster objects. Args: site_labels (:obj:(List(Str)|Set(Str)|Str), optional): Labels for sites to be considered in the search. This can be a list:: [ 'A', 'B' ] a set:: ( 'A', 'B' ) or a string:: 'A'. Returns: (List(Cluster)): List of Cluster objects for groups of contiguous sites. """ if site_labels: selected_sites = self.select_sites( site_labels ) else: selected_sites = self.sites initial_clusters = [ cluster.Cluster( [ site ] ) for site in selected_sites ] if site_labels: blocking_sites = self.site_labels - set( site_labels ) for c in initial_clusters: c.remove_sites_from_neighbours( blocking_sites ) final_clusters = [] while initial_clusters: # loop until initial_clusters is empty this_cluster = initial_clusters.pop(0) while this_cluster.neighbours: neighbouring_clusters = [ c for c in initial_clusters if this_cluster.is_neighbouring( c ) ] for nc in neighbouring_clusters: initial_clusters.remove( nc ) this_cluster = this_cluster.merge( nc ) final_clusters.append( this_cluster ) return final_clusters
def remove(self, iterable, data=None, index=0): """Remove an element from the trie Args iterable(hashable): key used to find what is to be removed data(object): data associated with the key index(int): index of what is to me removed Returns: bool: True: if it was removed False: if it was not removed """ if index == len(iterable): if self.is_terminal: if data: self.data.remove(data) if len(self.data) == 0: self.is_terminal = False else: self.data.clear() self.is_terminal = False return True else: return False elif iterable[index] in self.children: return self.children[iterable[index]].remove(iterable, index=index+1, data=data) else: return False
Remove an element from the trie Args iterable(hashable): key used to find what is to be removed data(object): data associated with the key index(int): index of what is to me removed Returns: bool: True: if it was removed False: if it was not removed
Below is the the instruction that describes the task: ### Input: Remove an element from the trie Args iterable(hashable): key used to find what is to be removed data(object): data associated with the key index(int): index of what is to me removed Returns: bool: True: if it was removed False: if it was not removed ### Response: def remove(self, iterable, data=None, index=0): """Remove an element from the trie Args iterable(hashable): key used to find what is to be removed data(object): data associated with the key index(int): index of what is to me removed Returns: bool: True: if it was removed False: if it was not removed """ if index == len(iterable): if self.is_terminal: if data: self.data.remove(data) if len(self.data) == 0: self.is_terminal = False else: self.data.clear() self.is_terminal = False return True else: return False elif iterable[index] in self.children: return self.children[iterable[index]].remove(iterable, index=index+1, data=data) else: return False
def optimize_structure_handler(rule, handler): """ Produce an "optimized" version of handler for the dispatcher to limit reference lookups. """ def runner(walk, dispatcher, node): handler(dispatcher, node) return yield # pragma: no cover return runner
Produce an "optimized" version of handler for the dispatcher to limit reference lookups.
Below is the the instruction that describes the task: ### Input: Produce an "optimized" version of handler for the dispatcher to limit reference lookups. ### Response: def optimize_structure_handler(rule, handler): """ Produce an "optimized" version of handler for the dispatcher to limit reference lookups. """ def runner(walk, dispatcher, node): handler(dispatcher, node) return yield # pragma: no cover return runner
def meid(number, separator=u' '): ''' Printable Mobile Equipment Identifier (MEID) number. >>> print(meid(123456789012345678)) 1B 69B4BA 630F34 6 >>> print(meid('1B69B4BA630F34')) 1B 69B4BA 630F34 6 ''' if isinstance(number, six.string_types): number = re.sub(r'[\s-]', '', number) try: number = '%014X' % int(number, 16) except ValueError: if len(number) < 18 and number.isdigit(): return meid('%014X' % int(number), separator) else: raise ValueError(_('Invalid MEID, size mismatch')) else: if len(number) not in (14, 15): raise ValueError(_('Invalid MEID, size mismatch')) elif isinstance(number, six.integer_types): if number > 0xfffffffffffffff: raise ValueError(_('Invalid MEID, size mismatch')) return meid(('%014X' % number)[:14], separator) else: raise TypeError(_('Invalid MEID, input type invalid')) number = number.upper() region = number[:2] manufacturer = number[2:8] serial_number = number[8:14] check_digit = number[14:] if check_digit == '': check_digit = luhn_calc(number, chars='0123456789ABCDEF') groups = (region, manufacturer, serial_number, check_digit) return separator.join(list(filter(None, groups)))
Printable Mobile Equipment Identifier (MEID) number. >>> print(meid(123456789012345678)) 1B 69B4BA 630F34 6 >>> print(meid('1B69B4BA630F34')) 1B 69B4BA 630F34 6
Below is the the instruction that describes the task: ### Input: Printable Mobile Equipment Identifier (MEID) number. >>> print(meid(123456789012345678)) 1B 69B4BA 630F34 6 >>> print(meid('1B69B4BA630F34')) 1B 69B4BA 630F34 6 ### Response: def meid(number, separator=u' '): ''' Printable Mobile Equipment Identifier (MEID) number. >>> print(meid(123456789012345678)) 1B 69B4BA 630F34 6 >>> print(meid('1B69B4BA630F34')) 1B 69B4BA 630F34 6 ''' if isinstance(number, six.string_types): number = re.sub(r'[\s-]', '', number) try: number = '%014X' % int(number, 16) except ValueError: if len(number) < 18 and number.isdigit(): return meid('%014X' % int(number), separator) else: raise ValueError(_('Invalid MEID, size mismatch')) else: if len(number) not in (14, 15): raise ValueError(_('Invalid MEID, size mismatch')) elif isinstance(number, six.integer_types): if number > 0xfffffffffffffff: raise ValueError(_('Invalid MEID, size mismatch')) return meid(('%014X' % number)[:14], separator) else: raise TypeError(_('Invalid MEID, input type invalid')) number = number.upper() region = number[:2] manufacturer = number[2:8] serial_number = number[8:14] check_digit = number[14:] if check_digit == '': check_digit = luhn_calc(number, chars='0123456789ABCDEF') groups = (region, manufacturer, serial_number, check_digit) return separator.join(list(filter(None, groups)))
def set_provider_links(self, resource_ids=None): """Sets a provider chain in order from the most recent source to the originating source. :param resource_ids: the new source :type resource_ids: ``osid.id.Id[]`` :raise: ``InvalidArgument`` -- ``resource_ids`` is invalid :raise: ``NoAccess`` -- ``Metadata.isReadOnly()`` is ``true`` :raise: ``NullArgument`` -- ``resource_ids`` is ``null`` *compliance: mandatory -- This method must be implemented.* """ if resource_ids is None: raise NullArgument() metadata = Metadata(**settings.METADATA['provider_link_ids']) if metadata.is_read_only(): raise NoAccess() if self._is_valid_input(resource_ids, metadata, array=True): self._my_map['providerLinkIds'] = [] for i in resource_ids: self._my_map['providerLinkIds'].append(str(i)) else: raise InvalidArgument()
Sets a provider chain in order from the most recent source to the originating source. :param resource_ids: the new source :type resource_ids: ``osid.id.Id[]`` :raise: ``InvalidArgument`` -- ``resource_ids`` is invalid :raise: ``NoAccess`` -- ``Metadata.isReadOnly()`` is ``true`` :raise: ``NullArgument`` -- ``resource_ids`` is ``null`` *compliance: mandatory -- This method must be implemented.*
Below is the the instruction that describes the task: ### Input: Sets a provider chain in order from the most recent source to the originating source. :param resource_ids: the new source :type resource_ids: ``osid.id.Id[]`` :raise: ``InvalidArgument`` -- ``resource_ids`` is invalid :raise: ``NoAccess`` -- ``Metadata.isReadOnly()`` is ``true`` :raise: ``NullArgument`` -- ``resource_ids`` is ``null`` *compliance: mandatory -- This method must be implemented.* ### Response: def set_provider_links(self, resource_ids=None): """Sets a provider chain in order from the most recent source to the originating source. :param resource_ids: the new source :type resource_ids: ``osid.id.Id[]`` :raise: ``InvalidArgument`` -- ``resource_ids`` is invalid :raise: ``NoAccess`` -- ``Metadata.isReadOnly()`` is ``true`` :raise: ``NullArgument`` -- ``resource_ids`` is ``null`` *compliance: mandatory -- This method must be implemented.* """ if resource_ids is None: raise NullArgument() metadata = Metadata(**settings.METADATA['provider_link_ids']) if metadata.is_read_only(): raise NoAccess() if self._is_valid_input(resource_ids, metadata, array=True): self._my_map['providerLinkIds'] = [] for i in resource_ids: self._my_map['providerLinkIds'].append(str(i)) else: raise InvalidArgument()
def iflatten_dict_values(node, depth=0): """ >>> from utool.util_dict import * # NOQA """ if isinstance(node, dict): _iter = (iflatten_dict_values(value) for value in six.itervalues(node)) return util_iter.iflatten(_iter) else: return node
>>> from utool.util_dict import * # NOQA
Below is the the instruction that describes the task: ### Input: >>> from utool.util_dict import * # NOQA ### Response: def iflatten_dict_values(node, depth=0): """ >>> from utool.util_dict import * # NOQA """ if isinstance(node, dict): _iter = (iflatten_dict_values(value) for value in six.itervalues(node)) return util_iter.iflatten(_iter) else: return node
def re_initiate_model_list(self, model_list_or_dict, core_objects_dict, model_name, model_class, model_key): """Recreate model list The method re-initiate a handed list or dictionary of models with the new dictionary of core-objects. :param model_list_or_dict: could be a list or dictionary of one model type :param core_objects_dict: new dictionary of one type of core-elements (rafcon.core) :param model_name: prop_name for the core-element hold by the model, this core-element is covered by the model :param model_class: model-class of the elements that should be insert :param model_key: if model_list_or_dict is a dictionary the key is the id of the respective element (e.g. 'state_id') :return: """ if model_name == "income": if self.income.income != self.state.income: self._add_model(self.income, self.state.income, IncomeModel) return for _ in range(len(model_list_or_dict)): self.remove_additional_model(model_list_or_dict, core_objects_dict, model_name, model_key) if core_objects_dict: for _ in core_objects_dict: self.add_missing_model(model_list_or_dict, core_objects_dict, model_name, model_class, model_key)
Recreate model list The method re-initiate a handed list or dictionary of models with the new dictionary of core-objects. :param model_list_or_dict: could be a list or dictionary of one model type :param core_objects_dict: new dictionary of one type of core-elements (rafcon.core) :param model_name: prop_name for the core-element hold by the model, this core-element is covered by the model :param model_class: model-class of the elements that should be insert :param model_key: if model_list_or_dict is a dictionary the key is the id of the respective element (e.g. 'state_id') :return:
Below is the the instruction that describes the task: ### Input: Recreate model list The method re-initiate a handed list or dictionary of models with the new dictionary of core-objects. :param model_list_or_dict: could be a list or dictionary of one model type :param core_objects_dict: new dictionary of one type of core-elements (rafcon.core) :param model_name: prop_name for the core-element hold by the model, this core-element is covered by the model :param model_class: model-class of the elements that should be insert :param model_key: if model_list_or_dict is a dictionary the key is the id of the respective element (e.g. 'state_id') :return: ### Response: def re_initiate_model_list(self, model_list_or_dict, core_objects_dict, model_name, model_class, model_key): """Recreate model list The method re-initiate a handed list or dictionary of models with the new dictionary of core-objects. :param model_list_or_dict: could be a list or dictionary of one model type :param core_objects_dict: new dictionary of one type of core-elements (rafcon.core) :param model_name: prop_name for the core-element hold by the model, this core-element is covered by the model :param model_class: model-class of the elements that should be insert :param model_key: if model_list_or_dict is a dictionary the key is the id of the respective element (e.g. 'state_id') :return: """ if model_name == "income": if self.income.income != self.state.income: self._add_model(self.income, self.state.income, IncomeModel) return for _ in range(len(model_list_or_dict)): self.remove_additional_model(model_list_or_dict, core_objects_dict, model_name, model_key) if core_objects_dict: for _ in core_objects_dict: self.add_missing_model(model_list_or_dict, core_objects_dict, model_name, model_class, model_key)
def _ssh_state(chunks, st_kwargs, kwargs, test=False): ''' Function to run a state with the given chunk via salt-ssh ''' file_refs = salt.client.ssh.state.lowstate_file_refs( chunks, _merge_extra_filerefs( kwargs.get('extra_filerefs', ''), __opts__.get('extra_filerefs', '') ) ) # Create the tar containing the state pkg and relevant files. trans_tar = salt.client.ssh.state.prep_trans_tar( __context__['fileclient'], chunks, file_refs, __pillar__, st_kwargs['id_']) trans_tar_sum = salt.utils.hashutils.get_hash(trans_tar, __opts__['hash_type']) cmd = 'state.pkg {0}/salt_state.tgz test={1} pkg_sum={2} hash_type={3}'.format( __opts__['thin_dir'], test, trans_tar_sum, __opts__['hash_type']) single = salt.client.ssh.Single( __opts__, cmd, fsclient=__context__['fileclient'], minion_opts=__salt__.minion_opts, **st_kwargs) single.shell.send( trans_tar, '{0}/salt_state.tgz'.format(__opts__['thin_dir'])) stdout, stderr, _ = single.cmd_block() # Clean up our tar try: os.remove(trans_tar) except (OSError, IOError): pass # Read in the JSON data and return the data structure try: return salt.utils.data.decode(salt.utils.json.loads(stdout, object_hook=salt.utils.data.encode_dict)) except Exception as e: log.error("JSON Render failed for: %s\n%s", stdout, stderr) log.error(str(e)) # If for some reason the json load fails, return the stdout return salt.utils.data.decode(stdout)
Function to run a state with the given chunk via salt-ssh
Below is the the instruction that describes the task: ### Input: Function to run a state with the given chunk via salt-ssh ### Response: def _ssh_state(chunks, st_kwargs, kwargs, test=False): ''' Function to run a state with the given chunk via salt-ssh ''' file_refs = salt.client.ssh.state.lowstate_file_refs( chunks, _merge_extra_filerefs( kwargs.get('extra_filerefs', ''), __opts__.get('extra_filerefs', '') ) ) # Create the tar containing the state pkg and relevant files. trans_tar = salt.client.ssh.state.prep_trans_tar( __context__['fileclient'], chunks, file_refs, __pillar__, st_kwargs['id_']) trans_tar_sum = salt.utils.hashutils.get_hash(trans_tar, __opts__['hash_type']) cmd = 'state.pkg {0}/salt_state.tgz test={1} pkg_sum={2} hash_type={3}'.format( __opts__['thin_dir'], test, trans_tar_sum, __opts__['hash_type']) single = salt.client.ssh.Single( __opts__, cmd, fsclient=__context__['fileclient'], minion_opts=__salt__.minion_opts, **st_kwargs) single.shell.send( trans_tar, '{0}/salt_state.tgz'.format(__opts__['thin_dir'])) stdout, stderr, _ = single.cmd_block() # Clean up our tar try: os.remove(trans_tar) except (OSError, IOError): pass # Read in the JSON data and return the data structure try: return salt.utils.data.decode(salt.utils.json.loads(stdout, object_hook=salt.utils.data.encode_dict)) except Exception as e: log.error("JSON Render failed for: %s\n%s", stdout, stderr) log.error(str(e)) # If for some reason the json load fails, return the stdout return salt.utils.data.decode(stdout)
def create(self, environments): """ Method to create environments vip :param environments vip: Dict containing environments vip desired to be created on database :return: None """ data = {'environments_vip': environments} uri = 'api/v3/environment-vip/' return super(ApiEnvironmentVip, self).post(uri, data)
Method to create environments vip :param environments vip: Dict containing environments vip desired to be created on database :return: None
Below is the the instruction that describes the task: ### Input: Method to create environments vip :param environments vip: Dict containing environments vip desired to be created on database :return: None ### Response: def create(self, environments): """ Method to create environments vip :param environments vip: Dict containing environments vip desired to be created on database :return: None """ data = {'environments_vip': environments} uri = 'api/v3/environment-vip/' return super(ApiEnvironmentVip, self).post(uri, data)
def _getOneMatchingRowNoRetries(self, tableInfo, conn, fieldsToMatch, selectFieldNames): """ Return a single matching row with the requested field values from the the requested table or None if nothing matched. tableInfo: Table information: a ClientJobsDAO._TableInfoBase instance conn: Owned connection acquired from ConnectionFactory.get() fieldsToMatch: Dictionary of internal fieldName/value mappings that identify the desired rows. If a value is an instance of ClientJobsDAO._SEQUENCE_TYPES (list/set/tuple), then the operator 'IN' will be used in the corresponding SQL predicate; if the value is bool: "IS TRUE/FALSE"; if the value is None: "IS NULL"; '=' will be used for all other cases. selectFieldNames: list of fields to return, using internal field names retval: A sequence of field values of the matching row in the order of the given field names; or None if there was no match. """ rows = self._getMatchingRowsNoRetries(tableInfo, conn, fieldsToMatch, selectFieldNames, maxRows=1) if rows: assert len(rows) == 1, repr(len(rows)) result = rows[0] else: result = None return result
Return a single matching row with the requested field values from the the requested table or None if nothing matched. tableInfo: Table information: a ClientJobsDAO._TableInfoBase instance conn: Owned connection acquired from ConnectionFactory.get() fieldsToMatch: Dictionary of internal fieldName/value mappings that identify the desired rows. If a value is an instance of ClientJobsDAO._SEQUENCE_TYPES (list/set/tuple), then the operator 'IN' will be used in the corresponding SQL predicate; if the value is bool: "IS TRUE/FALSE"; if the value is None: "IS NULL"; '=' will be used for all other cases. selectFieldNames: list of fields to return, using internal field names retval: A sequence of field values of the matching row in the order of the given field names; or None if there was no match.
Below is the the instruction that describes the task: ### Input: Return a single matching row with the requested field values from the the requested table or None if nothing matched. tableInfo: Table information: a ClientJobsDAO._TableInfoBase instance conn: Owned connection acquired from ConnectionFactory.get() fieldsToMatch: Dictionary of internal fieldName/value mappings that identify the desired rows. If a value is an instance of ClientJobsDAO._SEQUENCE_TYPES (list/set/tuple), then the operator 'IN' will be used in the corresponding SQL predicate; if the value is bool: "IS TRUE/FALSE"; if the value is None: "IS NULL"; '=' will be used for all other cases. selectFieldNames: list of fields to return, using internal field names retval: A sequence of field values of the matching row in the order of the given field names; or None if there was no match. ### Response: def _getOneMatchingRowNoRetries(self, tableInfo, conn, fieldsToMatch, selectFieldNames): """ Return a single matching row with the requested field values from the the requested table or None if nothing matched. tableInfo: Table information: a ClientJobsDAO._TableInfoBase instance conn: Owned connection acquired from ConnectionFactory.get() fieldsToMatch: Dictionary of internal fieldName/value mappings that identify the desired rows. If a value is an instance of ClientJobsDAO._SEQUENCE_TYPES (list/set/tuple), then the operator 'IN' will be used in the corresponding SQL predicate; if the value is bool: "IS TRUE/FALSE"; if the value is None: "IS NULL"; '=' will be used for all other cases. selectFieldNames: list of fields to return, using internal field names retval: A sequence of field values of the matching row in the order of the given field names; or None if there was no match. """ rows = self._getMatchingRowsNoRetries(tableInfo, conn, fieldsToMatch, selectFieldNames, maxRows=1) if rows: assert len(rows) == 1, repr(len(rows)) result = rows[0] else: result = None return result
def from_image(cls, img_filename, mipmap=False, **kwargs): """Uses Pyglet's image.load function to generate a Texture from an image file. If 'mipmap', then texture will have mipmap layers calculated.""" img = pyglet.image.load(img_filename) tex = img.get_mipmapped_texture() if mipmap else img.get_texture() gl.glBindTexture(gl.GL_TEXTURE_2D, 0) return cls(id=tex.id, data=tex, mipmap=mipmap, **kwargs)
Uses Pyglet's image.load function to generate a Texture from an image file. If 'mipmap', then texture will have mipmap layers calculated.
Below is the the instruction that describes the task: ### Input: Uses Pyglet's image.load function to generate a Texture from an image file. If 'mipmap', then texture will have mipmap layers calculated. ### Response: def from_image(cls, img_filename, mipmap=False, **kwargs): """Uses Pyglet's image.load function to generate a Texture from an image file. If 'mipmap', then texture will have mipmap layers calculated.""" img = pyglet.image.load(img_filename) tex = img.get_mipmapped_texture() if mipmap else img.get_texture() gl.glBindTexture(gl.GL_TEXTURE_2D, 0) return cls(id=tex.id, data=tex, mipmap=mipmap, **kwargs)
def init(name, *args, **kwargs): """Instantiate a plugin from the catalog. """ if name in _PLUGIN_CATALOG: if rapport.config.get_int("rapport", "verbosity") >= 2: print("Initialize plugin {0}: {1} {2}".format(name, args, kwargs)) try: return _PLUGIN_CATALOG[name](*args, **kwargs) except (ValueError, TypeError) as e: print("Failed to initialize plugin {0}: {1}!".format(name, e), file=sys.stderr) else: print("Failed to initialize plugin {0}: Not in catalog!".format(name), file=sys.stderr)
Instantiate a plugin from the catalog.
Below is the the instruction that describes the task: ### Input: Instantiate a plugin from the catalog. ### Response: def init(name, *args, **kwargs): """Instantiate a plugin from the catalog. """ if name in _PLUGIN_CATALOG: if rapport.config.get_int("rapport", "verbosity") >= 2: print("Initialize plugin {0}: {1} {2}".format(name, args, kwargs)) try: return _PLUGIN_CATALOG[name](*args, **kwargs) except (ValueError, TypeError) as e: print("Failed to initialize plugin {0}: {1}!".format(name, e), file=sys.stderr) else: print("Failed to initialize plugin {0}: Not in catalog!".format(name), file=sys.stderr)
def draw(self): """Draws ASCII canvas on the screen.""" if sys.stdout.isatty(): # pragma: no cover from asciimatics.screen import Screen Screen.wrapper(self._do_draw) else: for line in self.canvas: print("".join(line))
Draws ASCII canvas on the screen.
Below is the the instruction that describes the task: ### Input: Draws ASCII canvas on the screen. ### Response: def draw(self): """Draws ASCII canvas on the screen.""" if sys.stdout.isatty(): # pragma: no cover from asciimatics.screen import Screen Screen.wrapper(self._do_draw) else: for line in self.canvas: print("".join(line))
def builder_from_source(source, filename, system_includes, nonsystem_includes, quiet=False): """Utility method that returns an ASTBuilder from source code. Args: source: 'C++ source code' filename: 'file1' Returns: ASTBuilder """ return ASTBuilder(tokenize.get_tokens(source), filename, system_includes, nonsystem_includes, quiet=quiet)
Utility method that returns an ASTBuilder from source code. Args: source: 'C++ source code' filename: 'file1' Returns: ASTBuilder
Below is the the instruction that describes the task: ### Input: Utility method that returns an ASTBuilder from source code. Args: source: 'C++ source code' filename: 'file1' Returns: ASTBuilder ### Response: def builder_from_source(source, filename, system_includes, nonsystem_includes, quiet=False): """Utility method that returns an ASTBuilder from source code. Args: source: 'C++ source code' filename: 'file1' Returns: ASTBuilder """ return ASTBuilder(tokenize.get_tokens(source), filename, system_includes, nonsystem_includes, quiet=quiet)
def to_dict(self): """Converts the set of values into a dictionary. Unset values are excluded.""" return {value.label: value.value for value in self.__values if not value.unset}
Converts the set of values into a dictionary. Unset values are excluded.
Below is the the instruction that describes the task: ### Input: Converts the set of values into a dictionary. Unset values are excluded. ### Response: def to_dict(self): """Converts the set of values into a dictionary. Unset values are excluded.""" return {value.label: value.value for value in self.__values if not value.unset}
def ip_bracket(addr): ''' Convert IP address representation to ZMQ (URL) format. ZMQ expects brackets around IPv6 literals, since they are used in URLs. ''' addr = ipaddress.ip_address(addr) return ('[{}]' if addr.version == 6 else '{}').format(addr)
Convert IP address representation to ZMQ (URL) format. ZMQ expects brackets around IPv6 literals, since they are used in URLs.
Below is the the instruction that describes the task: ### Input: Convert IP address representation to ZMQ (URL) format. ZMQ expects brackets around IPv6 literals, since they are used in URLs. ### Response: def ip_bracket(addr): ''' Convert IP address representation to ZMQ (URL) format. ZMQ expects brackets around IPv6 literals, since they are used in URLs. ''' addr = ipaddress.ip_address(addr) return ('[{}]' if addr.version == 6 else '{}').format(addr)
def pre_fork(self, process_manager): ''' Pre-fork we need to create the zmq router device ''' salt.transport.mixins.auth.AESReqServerMixin.pre_fork(self, process_manager) if USE_LOAD_BALANCER: self.socket_queue = multiprocessing.Queue() process_manager.add_process( LoadBalancerServer, args=(self.opts, self.socket_queue) ) elif not salt.utils.platform.is_windows(): self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self._socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) _set_tcp_keepalive(self._socket, self.opts) self._socket.setblocking(0) self._socket.bind((self.opts['interface'], int(self.opts['ret_port'])))
Pre-fork we need to create the zmq router device
Below is the the instruction that describes the task: ### Input: Pre-fork we need to create the zmq router device ### Response: def pre_fork(self, process_manager): ''' Pre-fork we need to create the zmq router device ''' salt.transport.mixins.auth.AESReqServerMixin.pre_fork(self, process_manager) if USE_LOAD_BALANCER: self.socket_queue = multiprocessing.Queue() process_manager.add_process( LoadBalancerServer, args=(self.opts, self.socket_queue) ) elif not salt.utils.platform.is_windows(): self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) self._socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) _set_tcp_keepalive(self._socket, self.opts) self._socket.setblocking(0) self._socket.bind((self.opts['interface'], int(self.opts['ret_port'])))
def _get_connection(self): """Return native connection object.""" kwargs = { 'username': self.account, 'api_key': self.secret_key, } # Only add kwarg for servicenet if True because user could set # environment variable 'RACKSPACE_SERVICENET' separately. if self.servicenet: kwargs['servicenet'] = True if self.authurl: kwargs['authurl'] = self.authurl return cloudfiles.get_connection(**kwargs)
Return native connection object.
Below is the the instruction that describes the task: ### Input: Return native connection object. ### Response: def _get_connection(self): """Return native connection object.""" kwargs = { 'username': self.account, 'api_key': self.secret_key, } # Only add kwarg for servicenet if True because user could set # environment variable 'RACKSPACE_SERVICENET' separately. if self.servicenet: kwargs['servicenet'] = True if self.authurl: kwargs['authurl'] = self.authurl return cloudfiles.get_connection(**kwargs)
def get_blobstore(layout): """Return Blobstore instance for a given storage layout Args: layout (StorageLayout): Target storage layout. """ if layout.is_s3: from wal_e.blobstore import s3 blobstore = s3 elif layout.is_wabs: from wal_e.blobstore import wabs blobstore = wabs elif layout.is_swift: from wal_e.blobstore import swift blobstore = swift elif layout.is_gs: from wal_e.blobstore import gs blobstore = gs elif layout.is_file: from wal_e.blobstore import file blobstore = file return blobstore
Return Blobstore instance for a given storage layout Args: layout (StorageLayout): Target storage layout.
Below is the the instruction that describes the task: ### Input: Return Blobstore instance for a given storage layout Args: layout (StorageLayout): Target storage layout. ### Response: def get_blobstore(layout): """Return Blobstore instance for a given storage layout Args: layout (StorageLayout): Target storage layout. """ if layout.is_s3: from wal_e.blobstore import s3 blobstore = s3 elif layout.is_wabs: from wal_e.blobstore import wabs blobstore = wabs elif layout.is_swift: from wal_e.blobstore import swift blobstore = swift elif layout.is_gs: from wal_e.blobstore import gs blobstore = gs elif layout.is_file: from wal_e.blobstore import file blobstore = file return blobstore
def upgrade(): """Upgrade database.""" op.create_table( 'records_metadata', sa.Column('created', sa.DateTime(), nullable=False), sa.Column('updated', sa.DateTime(), nullable=False), sa.Column( 'id', sqlalchemy_utils.types.uuid.UUIDType(), nullable=False), sa.Column('json', sqlalchemy_utils.JSONType().with_variant( sa.dialects.postgresql.JSON( none_as_null=True), 'postgresql', ), nullable=True), sa.Column('version_id', sa.Integer(), nullable=False), sa.PrimaryKeyConstraint('id') ) op.create_table( 'records_metadata_version', sa.Column('created', sa.DateTime(), autoincrement=False, nullable=True), sa.Column('updated', sa.DateTime(), autoincrement=False, nullable=True), sa.Column('id', sqlalchemy_utils.types.uuid.UUIDType(), autoincrement=False, nullable=False), sa.Column('json', sqlalchemy_utils.JSONType().with_variant( sa.dialects.postgresql.JSON( none_as_null=True), 'postgresql', ), autoincrement=False, nullable=True), sa.Column('version_id', sa.Integer(), autoincrement=False, nullable=True), sa.Column('transaction_id', sa.BigInteger(), autoincrement=False, nullable=False), sa.Column('end_transaction_id', sa.BigInteger(), nullable=True), sa.Column('operation_type', sa.SmallInteger(), nullable=False), sa.PrimaryKeyConstraint('id', 'transaction_id') ) op.create_index( op.f('ix_records_metadata_version_end_transaction_id'), 'records_metadata_version', ['end_transaction_id'], unique=False ) op.create_index( op.f('ix_records_metadata_version_operation_type'), 'records_metadata_version', ['operation_type'], unique=False ) op.create_index( op.f('ix_records_metadata_version_transaction_id'), 'records_metadata_version', ['transaction_id'], unique=False )
Upgrade database.
Below is the the instruction that describes the task: ### Input: Upgrade database. ### Response: def upgrade(): """Upgrade database.""" op.create_table( 'records_metadata', sa.Column('created', sa.DateTime(), nullable=False), sa.Column('updated', sa.DateTime(), nullable=False), sa.Column( 'id', sqlalchemy_utils.types.uuid.UUIDType(), nullable=False), sa.Column('json', sqlalchemy_utils.JSONType().with_variant( sa.dialects.postgresql.JSON( none_as_null=True), 'postgresql', ), nullable=True), sa.Column('version_id', sa.Integer(), nullable=False), sa.PrimaryKeyConstraint('id') ) op.create_table( 'records_metadata_version', sa.Column('created', sa.DateTime(), autoincrement=False, nullable=True), sa.Column('updated', sa.DateTime(), autoincrement=False, nullable=True), sa.Column('id', sqlalchemy_utils.types.uuid.UUIDType(), autoincrement=False, nullable=False), sa.Column('json', sqlalchemy_utils.JSONType().with_variant( sa.dialects.postgresql.JSON( none_as_null=True), 'postgresql', ), autoincrement=False, nullable=True), sa.Column('version_id', sa.Integer(), autoincrement=False, nullable=True), sa.Column('transaction_id', sa.BigInteger(), autoincrement=False, nullable=False), sa.Column('end_transaction_id', sa.BigInteger(), nullable=True), sa.Column('operation_type', sa.SmallInteger(), nullable=False), sa.PrimaryKeyConstraint('id', 'transaction_id') ) op.create_index( op.f('ix_records_metadata_version_end_transaction_id'), 'records_metadata_version', ['end_transaction_id'], unique=False ) op.create_index( op.f('ix_records_metadata_version_operation_type'), 'records_metadata_version', ['operation_type'], unique=False ) op.create_index( op.f('ix_records_metadata_version_transaction_id'), 'records_metadata_version', ['transaction_id'], unique=False )
def merge_replacement_files(tmpdir, mergefile): """Merge all replacement files in a directory into a single file""" # The fixes suggested by clang-tidy >= 4.0.0 are given under # the top level key 'Diagnostics' in the output yaml files mergekey="Diagnostics" merged=[] for replacefile in glob.iglob(os.path.join(tmpdir, '*.yaml')): content = yaml.safe_load(open(replacefile, 'r')) if not content: continue # Skip empty files. merged.extend(content.get(mergekey, [])) if merged: # MainSourceFile: The key is required by the definition inside # include/clang/Tooling/ReplacementsYaml.h, but the value # is actually never used inside clang-apply-replacements, # so we set it to '' here. output = { 'MainSourceFile': '', mergekey: merged } with open(mergefile, 'w') as out: yaml.safe_dump(output, out) else: # Empty the file: open(mergefile, 'w').close()
Merge all replacement files in a directory into a single file
Below is the the instruction that describes the task: ### Input: Merge all replacement files in a directory into a single file ### Response: def merge_replacement_files(tmpdir, mergefile): """Merge all replacement files in a directory into a single file""" # The fixes suggested by clang-tidy >= 4.0.0 are given under # the top level key 'Diagnostics' in the output yaml files mergekey="Diagnostics" merged=[] for replacefile in glob.iglob(os.path.join(tmpdir, '*.yaml')): content = yaml.safe_load(open(replacefile, 'r')) if not content: continue # Skip empty files. merged.extend(content.get(mergekey, [])) if merged: # MainSourceFile: The key is required by the definition inside # include/clang/Tooling/ReplacementsYaml.h, but the value # is actually never used inside clang-apply-replacements, # so we set it to '' here. output = { 'MainSourceFile': '', mergekey: merged } with open(mergefile, 'w') as out: yaml.safe_dump(output, out) else: # Empty the file: open(mergefile, 'w').close()
def delete(self, force=False): """ Deletes this hosted zone. After this method is ran, you won't be able to add records, or do anything else with the zone. You'd need to re-create it, as zones are read-only after creation. :keyword bool force: If ``True``, delete the :py:class:`HostedZone <route53.hosted_zone.HostedZone>`, even if it means nuking all associated record sets. If ``False``, an exception is raised if this :py:class:`HostedZone <route53.hosted_zone.HostedZone>` has record sets. :rtype: dict :returns: A dict of change info, which contains some details about the request. """ self._halt_if_already_deleted() if force: # Forcing deletion by cleaning up all record sets first. We'll # do it all in one change set. cset = ChangeSet(connection=self.connection, hosted_zone_id=self.id) for rrset in self.record_sets: # You can delete a HostedZone if there are only SOA and NS # entries left. So delete everything but SOA/NS entries. if rrset.rrset_type not in ['SOA', 'NS']: cset.add_change('DELETE', rrset) if cset.deletions or cset.creations: # Bombs away. self.connection._change_resource_record_sets(cset) # Now delete the HostedZone. retval = self.connection.delete_hosted_zone_by_id(self.id) # Used to protect against modifying a deleted HostedZone. self._is_deleted = True return retval
Deletes this hosted zone. After this method is ran, you won't be able to add records, or do anything else with the zone. You'd need to re-create it, as zones are read-only after creation. :keyword bool force: If ``True``, delete the :py:class:`HostedZone <route53.hosted_zone.HostedZone>`, even if it means nuking all associated record sets. If ``False``, an exception is raised if this :py:class:`HostedZone <route53.hosted_zone.HostedZone>` has record sets. :rtype: dict :returns: A dict of change info, which contains some details about the request.
Below is the the instruction that describes the task: ### Input: Deletes this hosted zone. After this method is ran, you won't be able to add records, or do anything else with the zone. You'd need to re-create it, as zones are read-only after creation. :keyword bool force: If ``True``, delete the :py:class:`HostedZone <route53.hosted_zone.HostedZone>`, even if it means nuking all associated record sets. If ``False``, an exception is raised if this :py:class:`HostedZone <route53.hosted_zone.HostedZone>` has record sets. :rtype: dict :returns: A dict of change info, which contains some details about the request. ### Response: def delete(self, force=False): """ Deletes this hosted zone. After this method is ran, you won't be able to add records, or do anything else with the zone. You'd need to re-create it, as zones are read-only after creation. :keyword bool force: If ``True``, delete the :py:class:`HostedZone <route53.hosted_zone.HostedZone>`, even if it means nuking all associated record sets. If ``False``, an exception is raised if this :py:class:`HostedZone <route53.hosted_zone.HostedZone>` has record sets. :rtype: dict :returns: A dict of change info, which contains some details about the request. """ self._halt_if_already_deleted() if force: # Forcing deletion by cleaning up all record sets first. We'll # do it all in one change set. cset = ChangeSet(connection=self.connection, hosted_zone_id=self.id) for rrset in self.record_sets: # You can delete a HostedZone if there are only SOA and NS # entries left. So delete everything but SOA/NS entries. if rrset.rrset_type not in ['SOA', 'NS']: cset.add_change('DELETE', rrset) if cset.deletions or cset.creations: # Bombs away. self.connection._change_resource_record_sets(cset) # Now delete the HostedZone. retval = self.connection.delete_hosted_zone_by_id(self.id) # Used to protect against modifying a deleted HostedZone. self._is_deleted = True return retval
def _configure_logger(): """Configure the logging module.""" if not app.debug: _configure_logger_for_production(logging.getLogger()) elif not app.testing: _configure_logger_for_debugging(logging.getLogger())
Configure the logging module.
Below is the the instruction that describes the task: ### Input: Configure the logging module. ### Response: def _configure_logger(): """Configure the logging module.""" if not app.debug: _configure_logger_for_production(logging.getLogger()) elif not app.testing: _configure_logger_for_debugging(logging.getLogger())
def _compute_block_attributes(function): """ :param function: A normalized function object. :returns: A dictionary of basic block addresses to tuples of attributes. """ # The attributes we use are the distance form function start, distance from function exit and whether # or not it has a subfunction call distances_from_start = FunctionDiff._distances_from_function_start(function) distances_from_exit = FunctionDiff._distances_from_function_exit(function) call_sites = function.call_sites attributes = {} for block in function.graph.nodes(): if block in call_sites: number_of_subfunction_calls = len(call_sites[block]) else: number_of_subfunction_calls = 0 # there really shouldn't be blocks that can't be reached from the start, but there are for now dist_start = distances_from_start[block] if block in distances_from_start else 10000 dist_exit = distances_from_exit[block] if block in distances_from_exit else 10000 attributes[block] = (dist_start, dist_exit, number_of_subfunction_calls) return attributes
:param function: A normalized function object. :returns: A dictionary of basic block addresses to tuples of attributes.
Below is the the instruction that describes the task: ### Input: :param function: A normalized function object. :returns: A dictionary of basic block addresses to tuples of attributes. ### Response: def _compute_block_attributes(function): """ :param function: A normalized function object. :returns: A dictionary of basic block addresses to tuples of attributes. """ # The attributes we use are the distance form function start, distance from function exit and whether # or not it has a subfunction call distances_from_start = FunctionDiff._distances_from_function_start(function) distances_from_exit = FunctionDiff._distances_from_function_exit(function) call_sites = function.call_sites attributes = {} for block in function.graph.nodes(): if block in call_sites: number_of_subfunction_calls = len(call_sites[block]) else: number_of_subfunction_calls = 0 # there really shouldn't be blocks that can't be reached from the start, but there are for now dist_start = distances_from_start[block] if block in distances_from_start else 10000 dist_exit = distances_from_exit[block] if block in distances_from_exit else 10000 attributes[block] = (dist_start, dist_exit, number_of_subfunction_calls) return attributes
def add_item(self, item): """ Add a new script or phrase to the folder. """ item.parent = self #self.phrases[phrase.description] = phrase self.items.append(item)
Add a new script or phrase to the folder.
Below is the the instruction that describes the task: ### Input: Add a new script or phrase to the folder. ### Response: def add_item(self, item): """ Add a new script or phrase to the folder. """ item.parent = self #self.phrases[phrase.description] = phrase self.items.append(item)
def list_kadastrale_afdelingen(self): ''' List all `kadastrale afdelingen` in Flanders. :param integer sort: Field to sort on. :rtype: A :class:`list` of :class:`Afdeling`. ''' def creator(): gemeentes = self.list_gemeenten() res = [] for g in gemeentes: res += self.list_kadastrale_afdelingen_by_gemeente(g) return res if self.caches['permanent'].is_configured: key = 'list_afdelingen_rest' afdelingen = self.caches['permanent'].get_or_create(key, creator) else: afdelingen = creator() return afdelingen
List all `kadastrale afdelingen` in Flanders. :param integer sort: Field to sort on. :rtype: A :class:`list` of :class:`Afdeling`.
Below is the the instruction that describes the task: ### Input: List all `kadastrale afdelingen` in Flanders. :param integer sort: Field to sort on. :rtype: A :class:`list` of :class:`Afdeling`. ### Response: def list_kadastrale_afdelingen(self): ''' List all `kadastrale afdelingen` in Flanders. :param integer sort: Field to sort on. :rtype: A :class:`list` of :class:`Afdeling`. ''' def creator(): gemeentes = self.list_gemeenten() res = [] for g in gemeentes: res += self.list_kadastrale_afdelingen_by_gemeente(g) return res if self.caches['permanent'].is_configured: key = 'list_afdelingen_rest' afdelingen = self.caches['permanent'].get_or_create(key, creator) else: afdelingen = creator() return afdelingen
def get_structure_by_id(self, cod_id, **kwargs): """ Queries the COD for a structure by id. Args: cod_id (int): COD id. kwargs: All kwargs supported by :func:`pymatgen.core.structure.Structure.from_str`. Returns: A Structure. """ r = requests.get("http://www.crystallography.net/cod/%s.cif" % cod_id) return Structure.from_str(r.text, fmt="cif", **kwargs)
Queries the COD for a structure by id. Args: cod_id (int): COD id. kwargs: All kwargs supported by :func:`pymatgen.core.structure.Structure.from_str`. Returns: A Structure.
Below is the the instruction that describes the task: ### Input: Queries the COD for a structure by id. Args: cod_id (int): COD id. kwargs: All kwargs supported by :func:`pymatgen.core.structure.Structure.from_str`. Returns: A Structure. ### Response: def get_structure_by_id(self, cod_id, **kwargs): """ Queries the COD for a structure by id. Args: cod_id (int): COD id. kwargs: All kwargs supported by :func:`pymatgen.core.structure.Structure.from_str`. Returns: A Structure. """ r = requests.get("http://www.crystallography.net/cod/%s.cif" % cod_id) return Structure.from_str(r.text, fmt="cif", **kwargs)
def setCurrentRecord(self, record, autoAdd=False): """ Sets the index for this combobox to the inputed record instance. :param record <orb.Table> :return <bool> success """ if record is not None and not Table.recordcheck(record): return False # don't reassign the current record # clear the record if record is None: self._currentRecord = None blocked = self.signalsBlocked() self.blockSignals(True) self.setCurrentIndex(-1) self.blockSignals(blocked) if not blocked: self.currentRecordChanged.emit(None) return True elif record == self.currentRecord(): return False self._currentRecord = record found = False blocked = self.signalsBlocked() self.blockSignals(True) for i in range(self.count()): stored = unwrapVariant(self.itemData(i, Qt.UserRole)) if stored == record: self.setCurrentIndex(i) found = True break if not found and autoAdd: self.addRecord(record) self.setCurrentIndex(self.count() - 1) self.blockSignals(blocked) if not blocked: self.currentRecordChanged.emit(record) return False
Sets the index for this combobox to the inputed record instance. :param record <orb.Table> :return <bool> success
Below is the the instruction that describes the task: ### Input: Sets the index for this combobox to the inputed record instance. :param record <orb.Table> :return <bool> success ### Response: def setCurrentRecord(self, record, autoAdd=False): """ Sets the index for this combobox to the inputed record instance. :param record <orb.Table> :return <bool> success """ if record is not None and not Table.recordcheck(record): return False # don't reassign the current record # clear the record if record is None: self._currentRecord = None blocked = self.signalsBlocked() self.blockSignals(True) self.setCurrentIndex(-1) self.blockSignals(blocked) if not blocked: self.currentRecordChanged.emit(None) return True elif record == self.currentRecord(): return False self._currentRecord = record found = False blocked = self.signalsBlocked() self.blockSignals(True) for i in range(self.count()): stored = unwrapVariant(self.itemData(i, Qt.UserRole)) if stored == record: self.setCurrentIndex(i) found = True break if not found and autoAdd: self.addRecord(record) self.setCurrentIndex(self.count() - 1) self.blockSignals(blocked) if not blocked: self.currentRecordChanged.emit(record) return False
def find_attacker_slider(dest_list, occ_bb, piece_bb, target_bb, pos, domain): """ Find a slider attacker Parameters ---------- dest_list : list To store the results. occ_bb : int, bitboard Occupancy bitboard. piece_bb : int, bitboard Bitboard with the position of the attacker piece. target_bb : int, bitboard Occupancy bitboard without any of the sliders in question. pos : int Target position. pos_map : function Mapping between a board position and its position in a single rotated/translated rank produced with domain_trans. domain_trans : function Transformation from a rank/file/diagonal/anti-diagonal containing pos to a single rank pos_inv_map : function Inverse of pos_map """ pos_map, domain_trans, pos_inv_map = domain r = reach[pos_map(pos)][domain_trans(target_bb, pos)] m = r & domain_trans(piece_bb, pos) while m: r = m&-m rpos = r.bit_length()-1 if not (ray[rpos][pos_map(pos)] & domain_trans(occ_bb, pos)): dest_list.append(pos_inv_map(rpos, pos)) m ^= r
Find a slider attacker Parameters ---------- dest_list : list To store the results. occ_bb : int, bitboard Occupancy bitboard. piece_bb : int, bitboard Bitboard with the position of the attacker piece. target_bb : int, bitboard Occupancy bitboard without any of the sliders in question. pos : int Target position. pos_map : function Mapping between a board position and its position in a single rotated/translated rank produced with domain_trans. domain_trans : function Transformation from a rank/file/diagonal/anti-diagonal containing pos to a single rank pos_inv_map : function Inverse of pos_map
Below is the the instruction that describes the task: ### Input: Find a slider attacker Parameters ---------- dest_list : list To store the results. occ_bb : int, bitboard Occupancy bitboard. piece_bb : int, bitboard Bitboard with the position of the attacker piece. target_bb : int, bitboard Occupancy bitboard without any of the sliders in question. pos : int Target position. pos_map : function Mapping between a board position and its position in a single rotated/translated rank produced with domain_trans. domain_trans : function Transformation from a rank/file/diagonal/anti-diagonal containing pos to a single rank pos_inv_map : function Inverse of pos_map ### Response: def find_attacker_slider(dest_list, occ_bb, piece_bb, target_bb, pos, domain): """ Find a slider attacker Parameters ---------- dest_list : list To store the results. occ_bb : int, bitboard Occupancy bitboard. piece_bb : int, bitboard Bitboard with the position of the attacker piece. target_bb : int, bitboard Occupancy bitboard without any of the sliders in question. pos : int Target position. pos_map : function Mapping between a board position and its position in a single rotated/translated rank produced with domain_trans. domain_trans : function Transformation from a rank/file/diagonal/anti-diagonal containing pos to a single rank pos_inv_map : function Inverse of pos_map """ pos_map, domain_trans, pos_inv_map = domain r = reach[pos_map(pos)][domain_trans(target_bb, pos)] m = r & domain_trans(piece_bb, pos) while m: r = m&-m rpos = r.bit_length()-1 if not (ray[rpos][pos_map(pos)] & domain_trans(occ_bb, pos)): dest_list.append(pos_inv_map(rpos, pos)) m ^= r
async def forward_to(self, *args, **kwargs): """ Forwards the message. Shorthand for `telethon.client.messages.MessageMethods.forward_messages` with both ``messages`` and ``from_peer`` already set. If you need to forward more than one message at once, don't use this `forward_to` method. Use a `telethon.client.telegramclient.TelegramClient` instance directly. """ kwargs['messages'] = self.id kwargs['from_peer'] = await self.get_input_chat() return await self._client.forward_messages(*args, **kwargs)
Forwards the message. Shorthand for `telethon.client.messages.MessageMethods.forward_messages` with both ``messages`` and ``from_peer`` already set. If you need to forward more than one message at once, don't use this `forward_to` method. Use a `telethon.client.telegramclient.TelegramClient` instance directly.
Below is the the instruction that describes the task: ### Input: Forwards the message. Shorthand for `telethon.client.messages.MessageMethods.forward_messages` with both ``messages`` and ``from_peer`` already set. If you need to forward more than one message at once, don't use this `forward_to` method. Use a `telethon.client.telegramclient.TelegramClient` instance directly. ### Response: async def forward_to(self, *args, **kwargs): """ Forwards the message. Shorthand for `telethon.client.messages.MessageMethods.forward_messages` with both ``messages`` and ``from_peer`` already set. If you need to forward more than one message at once, don't use this `forward_to` method. Use a `telethon.client.telegramclient.TelegramClient` instance directly. """ kwargs['messages'] = self.id kwargs['from_peer'] = await self.get_input_chat() return await self._client.forward_messages(*args, **kwargs)