body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def thread_task(tasks_queue: Queue, events_queue: Queue, schema: BaseSchema, checks: Iterable[Callable], settings: hypothesis.settings, auth: Optional[RawAuth], auth_type: Optional[str], headers: Optional[Dict[(str, Any)]], seed: Optional[int], results: TestResultSet, kwargs: Any) -> None:
'A single task, that thre... | 8,466,409,781,368,943,000 | A single task, that threads do.
Pretty similar to the default one-thread flow, but includes communication with the main thread via the events queue. | src/schemathesis/runner/__init__.py | thread_task | hlobit/schemathesis | python | def thread_task(tasks_queue: Queue, events_queue: Queue, schema: BaseSchema, checks: Iterable[Callable], settings: hypothesis.settings, auth: Optional[RawAuth], auth_type: Optional[str], headers: Optional[Dict[(str, Any)]], seed: Optional[int], results: TestResultSet, kwargs: Any) -> None:
'A single task, that thre... |
def stop_worker(thread_id: int) -> None:
'Raise an error in a thread so it is possible to asynchronously stop thread execution.'
ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_long(thread_id), ctypes.py_object(SystemExit)) | -599,246,663,343,350,700 | Raise an error in a thread so it is possible to asynchronously stop thread execution. | src/schemathesis/runner/__init__.py | stop_worker | hlobit/schemathesis | python | def stop_worker(thread_id: int) -> None:
ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_long(thread_id), ctypes.py_object(SystemExit)) |
def execute_from_schema(schema: BaseSchema, checks: Iterable[Callable], *, workers_num: int=1, hypothesis_options: Optional[Dict[(str, Any)]]=None, auth: Optional[RawAuth]=None, auth_type: Optional[str]=None, headers: Optional[Dict[(str, Any)]]=None, request_timeout: Optional[int]=None, seed: Optional[int]=None) -> Gen... | 3,084,922,587,949,720,600 | Execute tests for the given schema.
Provides the main testing loop and preparation step. | src/schemathesis/runner/__init__.py | execute_from_schema | hlobit/schemathesis | python | def execute_from_schema(schema: BaseSchema, checks: Iterable[Callable], *, workers_num: int=1, hypothesis_options: Optional[Dict[(str, Any)]]=None, auth: Optional[RawAuth]=None, auth_type: Optional[str]=None, headers: Optional[Dict[(str, Any)]]=None, request_timeout: Optional[int]=None, seed: Optional[int]=None) -> Gen... |
def run_test(schema: BaseSchema, endpoint: Endpoint, test: Union[(Callable, InvalidSchema)], checks: Iterable[Callable], results: TestResultSet, **kwargs: Any) -> Generator[(events.ExecutionEvent, None, None)]:
'A single test run with all error handling needed.'
result = TestResult(endpoint=endpoint)
(yield... | 4,248,110,188,219,264,000 | A single test run with all error handling needed. | src/schemathesis/runner/__init__.py | run_test | hlobit/schemathesis | python | def run_test(schema: BaseSchema, endpoint: Endpoint, test: Union[(Callable, InvalidSchema)], checks: Iterable[Callable], results: TestResultSet, **kwargs: Any) -> Generator[(events.ExecutionEvent, None, None)]:
result = TestResult(endpoint=endpoint)
(yield events.BeforeExecution(results=results, schema=sch... |
def prepare(schema_uri: str, checks: Iterable[Callable]=DEFAULT_CHECKS, workers_num: int=1, api_options: Optional[Dict[(str, Any)]]=None, loader_options: Optional[Dict[(str, Any)]]=None, hypothesis_options: Optional[Dict[(str, Any)]]=None, loader: Callable=from_uri, seed: Optional[int]=None) -> Generator[(events.Execut... | 5,755,991,865,344,927,000 | Prepare a generator that will run test cases against the given API definition. | src/schemathesis/runner/__init__.py | prepare | hlobit/schemathesis | python | def prepare(schema_uri: str, checks: Iterable[Callable]=DEFAULT_CHECKS, workers_num: int=1, api_options: Optional[Dict[(str, Any)]]=None, loader_options: Optional[Dict[(str, Any)]]=None, hypothesis_options: Optional[Dict[(str, Any)]]=None, loader: Callable=from_uri, seed: Optional[int]=None) -> Generator[(events.Execut... |
def network_test(case: Case, checks: Iterable[Callable], result: TestResult, session: requests.Session, request_timeout: Optional[int]) -> None:
'A single test body that will be executed against the target.'
timeout = prepare_timeout(request_timeout)
response = case.call(session=session, timeout=timeout)
... | 788,102,240,383,414,400 | A single test body that will be executed against the target. | src/schemathesis/runner/__init__.py | network_test | hlobit/schemathesis | python | def network_test(case: Case, checks: Iterable[Callable], result: TestResult, session: requests.Session, request_timeout: Optional[int]) -> None:
timeout = prepare_timeout(request_timeout)
response = case.call(session=session, timeout=timeout)
_run_checks(case, checks, result, response) |
def prepare_timeout(timeout: Optional[int]) -> Optional[float]:
'Request timeout is in milliseconds, but `requests` uses seconds'
output: Optional[Union[(int, float)]] = timeout
if (timeout is not None):
output = (timeout / 1000)
return output | 2,219,370,182,692,796,400 | Request timeout is in milliseconds, but `requests` uses seconds | src/schemathesis/runner/__init__.py | prepare_timeout | hlobit/schemathesis | python | def prepare_timeout(timeout: Optional[int]) -> Optional[float]:
output: Optional[Union[(int, float)]] = timeout
if (timeout is not None):
output = (timeout / 1000)
return output |
def execute(self) -> Generator[(events.ExecutionEvent, None, None)]:
'Common logic for all runners.'
results = TestResultSet()
initialized = events.Initialized(results=results, schema=self.schema, checks=self.checks, hypothesis_settings=self.hypothesis_settings)
(yield initialized)
(yield from self.... | -4,920,484,788,315,777,000 | Common logic for all runners. | src/schemathesis/runner/__init__.py | execute | hlobit/schemathesis | python | def execute(self) -> Generator[(events.ExecutionEvent, None, None)]:
results = TestResultSet()
initialized = events.Initialized(results=results, schema=self.schema, checks=self.checks, hypothesis_settings=self.hypothesis_settings)
(yield initialized)
(yield from self._execute(results))
(yield e... |
def _execute(self, results: TestResultSet) -> Generator[(events.ExecutionEvent, None, None)]:
'All events come from a queue where different workers push their events.'
tasks_queue = self._get_tasks_queue()
events_queue: Queue = Queue()
workers = self._init_workers(tasks_queue, events_queue, results)
... | -649,910,977,915,766,500 | All events come from a queue where different workers push their events. | src/schemathesis/runner/__init__.py | _execute | hlobit/schemathesis | python | def _execute(self, results: TestResultSet) -> Generator[(events.ExecutionEvent, None, None)]:
tasks_queue = self._get_tasks_queue()
events_queue: Queue = Queue()
workers = self._init_workers(tasks_queue, events_queue, results)
def stop_workers() -> None:
for worker in workers:
... |
def _get_tasks_queue(self) -> Queue:
'All endpoints are distributed among all workers via a queue.'
tasks_queue: Queue = Queue()
tasks_queue.queue.extend(self.schema.get_all_endpoints())
return tasks_queue | 8,114,420,042,134,657,000 | All endpoints are distributed among all workers via a queue. | src/schemathesis/runner/__init__.py | _get_tasks_queue | hlobit/schemathesis | python | def _get_tasks_queue(self) -> Queue:
tasks_queue: Queue = Queue()
tasks_queue.queue.extend(self.schema.get_all_endpoints())
return tasks_queue |
def _init_workers(self, tasks_queue: Queue, events_queue: Queue, results: TestResultSet) -> List[threading.Thread]:
'Initialize & start workers that will execute tests.'
workers = [threading.Thread(target=self._get_task(), kwargs=self._get_worker_kwargs(tasks_queue, events_queue, results)) for _ in range(self.w... | 2,309,366,165,997,026,300 | Initialize & start workers that will execute tests. | src/schemathesis/runner/__init__.py | _init_workers | hlobit/schemathesis | python | def _init_workers(self, tasks_queue: Queue, events_queue: Queue, results: TestResultSet) -> List[threading.Thread]:
workers = [threading.Thread(target=self._get_task(), kwargs=self._get_worker_kwargs(tasks_queue, events_queue, results)) for _ in range(self.workers_num)]
for worker in workers:
worke... |
def __str__(self):
' print out some basic information about the BC object '
string = ('BCs: -x: %s +x: %s ' % (self.xlb, self.xrb))
return string | 469,757,932,280,750,660 | print out some basic information about the BC object | multigrid/patch1d.py | __str__ | python-hydro/hydro_examples | python | def __str__(self):
' '
string = ('BCs: -x: %s +x: %s ' % (self.xlb, self.xrb))
return string |
def __init__(self, nx, ng=1, xmin=0.0, xmax=1.0):
'\n The class constructor function.\n\n The only data that we require is the number of points that\n make up the mesh.\n\n We optionally take the extrema of the domain, number of ghost\n cells (assume 1)\n '
self.nx = nx... | 1,316,086,383,784,868,400 | The class constructor function.
The only data that we require is the number of points that
make up the mesh.
We optionally take the extrema of the domain, number of ghost
cells (assume 1) | multigrid/patch1d.py | __init__ | python-hydro/hydro_examples | python | def __init__(self, nx, ng=1, xmin=0.0, xmax=1.0):
'\n The class constructor function.\n\n The only data that we require is the number of points that\n make up the mesh.\n\n We optionally take the extrema of the domain, number of ghost\n cells (assume 1)\n '
self.nx = nx... |
def __str__(self):
' print out some basic information about the grid object '
return '1-d grid: nx = {}, ng = {}'.format(self.nx, self.ng) | -7,226,611,515,420,033,000 | print out some basic information about the grid object | multigrid/patch1d.py | __str__ | python-hydro/hydro_examples | python | def __str__(self):
' '
return '1-d grid: nx = {}, ng = {}'.format(self.nx, self.ng) |
def register_var(self, name, bc_object):
'\n register a variable with CellCenterData1d object. Here we pass in a\n BCObject that describes the boundary conditions for that\n variable.\n '
if (self.initialized == 1):
sys.exit('ERROR: grid already initialized')
self.vars.a... | 2,683,589,669,001,459,000 | register a variable with CellCenterData1d object. Here we pass in a
BCObject that describes the boundary conditions for that
variable. | multigrid/patch1d.py | register_var | python-hydro/hydro_examples | python | def register_var(self, name, bc_object):
'\n register a variable with CellCenterData1d object. Here we pass in a\n BCObject that describes the boundary conditions for that\n variable.\n '
if (self.initialized == 1):
sys.exit('ERROR: grid already initialized')
self.vars.a... |
def create(self):
'\n called after all the variables are registered and allocates\n the storage for the state data\n '
if (self.initialized == 1):
sys.exit('ERROR: grid already initialized')
self.data = numpy.zeros((self.nvar, self.grid.qx), dtype=self.dtype)
self.initialize... | -7,108,092,911,557,650,000 | called after all the variables are registered and allocates
the storage for the state data | multigrid/patch1d.py | create | python-hydro/hydro_examples | python | def create(self):
'\n called after all the variables are registered and allocates\n the storage for the state data\n '
if (self.initialized == 1):
sys.exit('ERROR: grid already initialized')
self.data = numpy.zeros((self.nvar, self.grid.qx), dtype=self.dtype)
self.initialize... |
def __str__(self):
' print out some basic information about the ccData2d object '
if (self.initialized == 0):
mystr = 'CellCenterData1d object not yet initialized'
return mystr
mystr = (('cc data: nx = {}, ng = {}\n'.format(self.grid.nx, self.grid.ng) + ' nvars = {}\n'.format(self.nv... | 8,466,030,980,728,462,000 | print out some basic information about the ccData2d object | multigrid/patch1d.py | __str__ | python-hydro/hydro_examples | python | def __str__(self):
' '
if (self.initialized == 0):
mystr = 'CellCenterData1d object not yet initialized'
return mystr
mystr = (('cc data: nx = {}, ng = {}\n'.format(self.grid.nx, self.grid.ng) + ' nvars = {}\n'.format(self.nvar)) + 'variables: \n')
ilo = self.grid.ilo
ihi = ... |
def get_var(self, name):
'\n return a data array the variable described by name. Any changes\n made to this are automatically reflected in the CellCenterData1d\n object.\n '
n = self.vars.index(name)
return self.data[n, :] | -905,601,490,949,444,400 | return a data array the variable described by name. Any changes
made to this are automatically reflected in the CellCenterData1d
object. | multigrid/patch1d.py | get_var | python-hydro/hydro_examples | python | def get_var(self, name):
'\n return a data array the variable described by name. Any changes\n made to this are automatically reflected in the CellCenterData1d\n object.\n '
n = self.vars.index(name)
return self.data[n, :] |
def fill_BC_all(self):
'\n fill boundary conditions on all variables\n '
for name in self.vars:
self.fill_BC(name) | -5,289,033,638,672,699,000 | fill boundary conditions on all variables | multigrid/patch1d.py | fill_BC_all | python-hydro/hydro_examples | python | def fill_BC_all(self):
'\n \n '
for name in self.vars:
self.fill_BC(name) |
def fill_BC(self, name):
'\n fill the boundary conditions. This operates on a single state\n variable at a time, to allow for maximum flexibility\n\n we do periodic, reflect-even, reflect-odd, and outflow\n\n each variable name has a corresponding bc_object stored in the\n ccData... | -1,690,921,127,078,352,400 | fill the boundary conditions. This operates on a single state
variable at a time, to allow for maximum flexibility
we do periodic, reflect-even, reflect-odd, and outflow
each variable name has a corresponding bc_object stored in the
ccData2d object -- we refer to this to figure out the action
to take at each boundar... | multigrid/patch1d.py | fill_BC | python-hydro/hydro_examples | python | def fill_BC(self, name):
'\n fill the boundary conditions. This operates on a single state\n variable at a time, to allow for maximum flexibility\n\n we do periodic, reflect-even, reflect-odd, and outflow\n\n each variable name has a corresponding bc_object stored in the\n ccData... |
def restrict(self, varname):
'\n restrict the variable varname to a coarser grid (factor of 2\n coarser) and return an array with the resulting data (and same\n number of ghostcells)\n '
fG = self.grid
fData = self.get_var(varname)
ng_c = fG.ng
nx_c = (fG.nx // 2)
cDa... | 7,760,059,069,005,052,000 | restrict the variable varname to a coarser grid (factor of 2
coarser) and return an array with the resulting data (and same
number of ghostcells) | multigrid/patch1d.py | restrict | python-hydro/hydro_examples | python | def restrict(self, varname):
'\n restrict the variable varname to a coarser grid (factor of 2\n coarser) and return an array with the resulting data (and same\n number of ghostcells)\n '
fG = self.grid
fData = self.get_var(varname)
ng_c = fG.ng
nx_c = (fG.nx // 2)
cDa... |
def prolong(self, varname):
"\n prolong the data in the current (coarse) grid to a finer\n (factor of 2 finer) grid. Return an array with the resulting\n data (and same number of ghostcells).\n\n We will reconstruct the data in the zone from the\n zone-averaged variables using th... | 3,561,002,186,046,957,600 | prolong the data in the current (coarse) grid to a finer
(factor of 2 finer) grid. Return an array with the resulting
data (and same number of ghostcells).
We will reconstruct the data in the zone from the
zone-averaged variables using the centered-difference slopes
(x)
f(x,y) = m x/dx + <f>
When avera... | multigrid/patch1d.py | prolong | python-hydro/hydro_examples | python | def prolong(self, varname):
"\n prolong the data in the current (coarse) grid to a finer\n (factor of 2 finer) grid. Return an array with the resulting\n data (and same number of ghostcells).\n\n We will reconstruct the data in the zone from the\n zone-averaged variables using th... |
def __init__(self, *, host: str='datastore.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Sequence[str]=None, channel: grpc.Channel=None, api_mtls_endpoint: str=None, client_cert_source: Callable[([], Tuple[(bytes, bytes)])]=None, ssl_channel_credentials: grpc.Channel... | -5,410,718,539,390,989,000 | Instantiate the transport.
Args:
host (Optional[str]):
The hostname to connect to.
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified,... | google/cloud/datastore_v1/services/datastore/transports/grpc.py | __init__ | LaudateCorpus1/python-datastore | python | def __init__(self, *, host: str='datastore.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Sequence[str]=None, channel: grpc.Channel=None, api_mtls_endpoint: str=None, client_cert_source: Callable[([], Tuple[(bytes, bytes)])]=None, ssl_channel_credentials: grpc.Channel... |
@classmethod
def create_channel(cls, host: str='datastore.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Optional[Sequence[str]]=None, quota_project_id: Optional[str]=None, **kwargs) -> grpc.Channel:
'Create and return a gRPC channel object.\n Args:\n ... | -3,592,603,047,120,177,700 | Create and return a gRPC channel object.
Args:
host (Optional[str]): The host for the channel to use.
credentials (Optional[~.Credentials]): The
authorization credentials to attach to requests. These
credentials identify this application to the service. If
none are specified, the client ... | google/cloud/datastore_v1/services/datastore/transports/grpc.py | create_channel | LaudateCorpus1/python-datastore | python | @classmethod
def create_channel(cls, host: str='datastore.googleapis.com', credentials: ga_credentials.Credentials=None, credentials_file: str=None, scopes: Optional[Sequence[str]]=None, quota_project_id: Optional[str]=None, **kwargs) -> grpc.Channel:
'Create and return a gRPC channel object.\n Args:\n ... |
@property
def grpc_channel(self) -> grpc.Channel:
'Return the channel designed to connect to this service.\n '
return self._grpc_channel | -1,956,682,971,687,930,400 | Return the channel designed to connect to this service. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | grpc_channel | LaudateCorpus1/python-datastore | python | @property
def grpc_channel(self) -> grpc.Channel:
'\n '
return self._grpc_channel |
@property
def lookup(self) -> Callable[([datastore.LookupRequest], datastore.LookupResponse)]:
'Return a callable for the lookup method over gRPC.\n\n Looks up entities by key.\n\n Returns:\n Callable[[~.LookupRequest],\n ~.LookupResponse]:\n A function tha... | 2,886,046,299,462,822,400 | Return a callable for the lookup method over gRPC.
Looks up entities by key.
Returns:
Callable[[~.LookupRequest],
~.LookupResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | lookup | LaudateCorpus1/python-datastore | python | @property
def lookup(self) -> Callable[([datastore.LookupRequest], datastore.LookupResponse)]:
'Return a callable for the lookup method over gRPC.\n\n Looks up entities by key.\n\n Returns:\n Callable[[~.LookupRequest],\n ~.LookupResponse]:\n A function tha... |
@property
def run_query(self) -> Callable[([datastore.RunQueryRequest], datastore.RunQueryResponse)]:
'Return a callable for the run query method over gRPC.\n\n Queries for entities.\n\n Returns:\n Callable[[~.RunQueryRequest],\n ~.RunQueryResponse]:\n A fu... | -1,087,091,090,104,806,400 | Return a callable for the run query method over gRPC.
Queries for entities.
Returns:
Callable[[~.RunQueryRequest],
~.RunQueryResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | run_query | LaudateCorpus1/python-datastore | python | @property
def run_query(self) -> Callable[([datastore.RunQueryRequest], datastore.RunQueryResponse)]:
'Return a callable for the run query method over gRPC.\n\n Queries for entities.\n\n Returns:\n Callable[[~.RunQueryRequest],\n ~.RunQueryResponse]:\n A fu... |
@property
def begin_transaction(self) -> Callable[([datastore.BeginTransactionRequest], datastore.BeginTransactionResponse)]:
'Return a callable for the begin transaction method over gRPC.\n\n Begins a new transaction.\n\n Returns:\n Callable[[~.BeginTransactionRequest],\n ... | 6,109,222,605,587,897,000 | Return a callable for the begin transaction method over gRPC.
Begins a new transaction.
Returns:
Callable[[~.BeginTransactionRequest],
~.BeginTransactionResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | begin_transaction | LaudateCorpus1/python-datastore | python | @property
def begin_transaction(self) -> Callable[([datastore.BeginTransactionRequest], datastore.BeginTransactionResponse)]:
'Return a callable for the begin transaction method over gRPC.\n\n Begins a new transaction.\n\n Returns:\n Callable[[~.BeginTransactionRequest],\n ... |
@property
def commit(self) -> Callable[([datastore.CommitRequest], datastore.CommitResponse)]:
'Return a callable for the commit method over gRPC.\n\n Commits a transaction, optionally creating, deleting\n or modifying some entities.\n\n Returns:\n Callable[[~.CommitRequest],\n ... | 4,309,621,428,806,862,000 | Return a callable for the commit method over gRPC.
Commits a transaction, optionally creating, deleting
or modifying some entities.
Returns:
Callable[[~.CommitRequest],
~.CommitResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | commit | LaudateCorpus1/python-datastore | python | @property
def commit(self) -> Callable[([datastore.CommitRequest], datastore.CommitResponse)]:
'Return a callable for the commit method over gRPC.\n\n Commits a transaction, optionally creating, deleting\n or modifying some entities.\n\n Returns:\n Callable[[~.CommitRequest],\n ... |
@property
def rollback(self) -> Callable[([datastore.RollbackRequest], datastore.RollbackResponse)]:
'Return a callable for the rollback method over gRPC.\n\n Rolls back a transaction.\n\n Returns:\n Callable[[~.RollbackRequest],\n ~.RollbackResponse]:\n A ... | 8,620,746,177,282,813,000 | Return a callable for the rollback method over gRPC.
Rolls back a transaction.
Returns:
Callable[[~.RollbackRequest],
~.RollbackResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | rollback | LaudateCorpus1/python-datastore | python | @property
def rollback(self) -> Callable[([datastore.RollbackRequest], datastore.RollbackResponse)]:
'Return a callable for the rollback method over gRPC.\n\n Rolls back a transaction.\n\n Returns:\n Callable[[~.RollbackRequest],\n ~.RollbackResponse]:\n A ... |
@property
def allocate_ids(self) -> Callable[([datastore.AllocateIdsRequest], datastore.AllocateIdsResponse)]:
'Return a callable for the allocate ids method over gRPC.\n\n Allocates IDs for the given keys, which is useful for\n referencing an entity before it is inserted.\n\n Returns:\n ... | 4,482,291,332,690,070,500 | Return a callable for the allocate ids method over gRPC.
Allocates IDs for the given keys, which is useful for
referencing an entity before it is inserted.
Returns:
Callable[[~.AllocateIdsRequest],
~.AllocateIdsResponse]:
A function that, when called, will call the underlying RPC
on th... | google/cloud/datastore_v1/services/datastore/transports/grpc.py | allocate_ids | LaudateCorpus1/python-datastore | python | @property
def allocate_ids(self) -> Callable[([datastore.AllocateIdsRequest], datastore.AllocateIdsResponse)]:
'Return a callable for the allocate ids method over gRPC.\n\n Allocates IDs for the given keys, which is useful for\n referencing an entity before it is inserted.\n\n Returns:\n ... |
@property
def reserve_ids(self) -> Callable[([datastore.ReserveIdsRequest], datastore.ReserveIdsResponse)]:
"Return a callable for the reserve ids method over gRPC.\n\n Prevents the supplied keys' IDs from being auto-\n llocated by Cloud Datastore.\n\n Returns:\n Callable[[~.ReserveI... | 5,990,443,636,854,899,000 | Return a callable for the reserve ids method over gRPC.
Prevents the supplied keys' IDs from being auto-
llocated by Cloud Datastore.
Returns:
Callable[[~.ReserveIdsRequest],
~.ReserveIdsResponse]:
A function that, when called, will call the underlying RPC
on the server. | google/cloud/datastore_v1/services/datastore/transports/grpc.py | reserve_ids | LaudateCorpus1/python-datastore | python | @property
def reserve_ids(self) -> Callable[([datastore.ReserveIdsRequest], datastore.ReserveIdsResponse)]:
"Return a callable for the reserve ids method over gRPC.\n\n Prevents the supplied keys' IDs from being auto-\n llocated by Cloud Datastore.\n\n Returns:\n Callable[[~.ReserveI... |
def _get_sample(sample_info):
" Get sample from SampleService\n sample_info - dict containing 'id' and 'version' of a sample\n "
headers = {'Authorization': config()['ws_token']}
params = {'id': sample_info['id']}
if sample_info.get('version'):
params['version'] = sample_info['version']
... | -5,702,704,638,798,731,000 | Get sample from SampleService
sample_info - dict containing 'id' and 'version' of a sample | src/index_runner/es_indexers/sample_set.py | _get_sample | slebras/index_runner | python | def _get_sample(sample_info):
" Get sample from SampleService\n sample_info - dict containing 'id' and 'version' of a sample\n "
headers = {'Authorization': config()['ws_token']}
params = {'id': sample_info['id']}
if sample_info.get('version'):
params['version'] = sample_info['version']
... |
def _flatten_meta(meta, prefix=None):
' Flattens metadata fields in a Sample object. Fields are concatenated into a\n single string field to save into an Elasticsearch index\n meta - Sample Metadata to be flattened\n prefix - (optional) prefix for the metadata values. default=None\n '
new_meta... | 1,436,780,520,164,271,400 | Flattens metadata fields in a Sample object. Fields are concatenated into a
single string field to save into an Elasticsearch index
meta - Sample Metadata to be flattened
prefix - (optional) prefix for the metadata values. default=None | src/index_runner/es_indexers/sample_set.py | _flatten_meta | slebras/index_runner | python | def _flatten_meta(meta, prefix=None):
' Flattens metadata fields in a Sample object. Fields are concatenated into a\n single string field to save into an Elasticsearch index\n meta - Sample Metadata to be flattened\n prefix - (optional) prefix for the metadata values. default=None\n '
new_meta... |
def _combine_meta(meta, flattened_meta, idx):
' Combine newly flattened metadata with existing metadata. This Function is designed to keep the indexing\n of the different metadata fields consistent for each node within the sample node tree s.t. all the\n fields in index (idx) 0 will be from item 0 in ... | -8,150,693,350,067,738,000 | Combine newly flattened metadata with existing metadata. This Function is designed to keep the indexing
of the different metadata fields consistent for each node within the sample node tree s.t. all the
fields in index (idx) 0 will be from item 0 in the node tree. Empty string ("") entries are Empty and
add... | src/index_runner/es_indexers/sample_set.py | _combine_meta | slebras/index_runner | python | def _combine_meta(meta, flattened_meta, idx):
' Combine newly flattened metadata with existing metadata. This Function is designed to keep the indexing\n of the different metadata fields consistent for each node within the sample node tree s.t. all the\n fields in index (idx) 0 will be from item 0 in ... |
def index_sample_set(obj_data, ws_info, obj_data_v1):
'Indexer for KBaseSets.SampleSet object type'
info = obj_data['info']
if (not obj_data.get('data')):
raise Exception('no data in object')
data = obj_data['data']
workspace_id = info[6]
object_id = info[0]
version = info[4]
sam... | 4,770,756,739,175,246,000 | Indexer for KBaseSets.SampleSet object type | src/index_runner/es_indexers/sample_set.py | index_sample_set | slebras/index_runner | python | def index_sample_set(obj_data, ws_info, obj_data_v1):
info = obj_data['info']
if (not obj_data.get('data')):
raise Exception('no data in object')
data = obj_data['data']
workspace_id = info[6]
object_id = info[0]
version = info[4]
sample_set_id = f'{_NAMESPACE}::{workspace_id}:{... |
def loginValid(func):
'\n :desc 闭包函数校验是否登录\n :param func:\n :return:\n '
def inner(request, *args, **kwargs):
email = request.COOKIES.get('user')
s_email = request.session.get('user')
if (email and s_email and (email == s_email)):
user = LoginUser.objects.filter(... | 4,984,156,748,269,809,000 | :desc 闭包函数校验是否登录
:param func:
:return: | Qshop/Buyer/views.py | loginValid | songdanlee/DjangoWorkSpace | python | def loginValid(func):
'\n :desc 闭包函数校验是否登录\n :param func:\n :return:\n '
def inner(request, *args, **kwargs):
email = request.COOKIES.get('user')
s_email = request.session.get('user')
if (email and s_email and (email == s_email)):
user = LoginUser.objects.filter(... |
@loginValid
def pay_order(request):
'\n get请求 商品详情页购买单个商品。传入商品id，数量。\n post请求 购物车购买多个商品。\n '
if (request.method == 'GET'):
num = request.GET.get('num')
id = request.GET.get('id')
if (num and id):
num = int(num)
id = int(id)
order = PayOrder()
... | 9,212,065,408,716,652,000 | get请求 商品详情页购买单个商品。传入商品id，数量。
post请求 购物车购买多个商品。 | Qshop/Buyer/views.py | pay_order | songdanlee/DjangoWorkSpace | python | @loginValid
def pay_order(request):
'\n get请求 商品详情页购买单个商品。传入商品id，数量。\n post请求 购物车购买多个商品。\n '
if (request.method == 'GET'):
num = request.GET.get('num')
id = request.GET.get('id')
if (num and id):
num = int(num)
id = int(id)
order = PayOrder()
... |
@loginValid
def alipayOrder(request):
'\n 阿里支付，传入交易订单号，总金额\n '
order_number = request.GET.get('order_number')
total = request.GET.get('total')
alipay = AliPay(appid='2016101200667714', app_notify_url=None, app_private_key_string=alipay_private_key_string, alipay_public_key_string=alipay_public_key... | -6,322,852,548,281,581,000 | 阿里支付，传入交易订单号，总金额 | Qshop/Buyer/views.py | alipayOrder | songdanlee/DjangoWorkSpace | python | @loginValid
def alipayOrder(request):
'\n \n '
order_number = request.GET.get('order_number')
total = request.GET.get('total')
alipay = AliPay(appid='2016101200667714', app_notify_url=None, app_private_key_string=alipay_private_key_string, alipay_public_key_string=alipay_public_key_string, sign_ty... |
@loginValid
def pay_result(request):
'\n 支付结果页\n 如果有out_trade_no，支付成功，修改订单状态\n '
out_trade_no = request.GET.get('out_trade_no')
if out_trade_no:
payorder = PayOrder.objects.get(order_number=out_trade_no)
payorder.orderinfo_set.all().update(order_status=1)
return render(request, ... | -7,832,803,620,661,841,000 | 支付结果页
如果有out_trade_no，支付成功，修改订单状态 | Qshop/Buyer/views.py | pay_result | songdanlee/DjangoWorkSpace | python | @loginValid
def pay_result(request):
'\n 支付结果页\n 如果有out_trade_no，支付成功，修改订单状态\n '
out_trade_no = request.GET.get('out_trade_no')
if out_trade_no:
payorder = PayOrder.objects.get(order_number=out_trade_no)
payorder.orderinfo_set.all().update(order_status=1)
return render(request, ... |
@loginValid
def add_cart(request):
'\n 处理ajax 请求，添加商品到购物车 ，成功保存到数据库。\n 传入商品id，数量\n '
sendData = {'code': 200, 'data': ''}
if (request.method == 'POST'):
id = int(request.POST.get('goods_id'))
count = int(request.POST.get('count', 1))
goods = Goods.objects.get(id=id)
... | 348,866,261,690,652,700 | 处理ajax 请求，添加商品到购物车 ，成功保存到数据库。
传入商品id，数量 | Qshop/Buyer/views.py | add_cart | songdanlee/DjangoWorkSpace | python | @loginValid
def add_cart(request):
'\n 处理ajax 请求，添加商品到购物车 ，成功保存到数据库。\n 传入商品id，数量\n '
sendData = {'code': 200, 'data': }
if (request.method == 'POST'):
id = int(request.POST.get('goods_id'))
count = int(request.POST.get('count', 1))
goods = Goods.objects.get(id=id)
ca... |
@databench.on
def run(self):
'Run when button is pressed.'
inside = 0
for draws in range(1, self.data['samples']):
r1 = random.random()
r2 = random.random()
if (((r1 ** 2) + (r2 ** 2)) < 1.0):
inside += 1
if ((draws % 1000) != 0):
continue
(yie... | -4,587,078,849,969,560,000 | Run when button is pressed. | databench/analyses_packaged/dummypi/analysis.py | run | phillipaug/Data-Analysis-General-repository | python | @databench.on
def run(self):
inside = 0
for draws in range(1, self.data['samples']):
r1 = random.random()
r2 = random.random()
if (((r1 ** 2) + (r2 ** 2)) < 1.0):
inside += 1
if ((draws % 1000) != 0):
continue
(yield self.emit('log', {'draws':... |
def generate_ui_test_task(dependencies, engine='Klar', device='ARM'):
'\n :param str engine: Klar, Webview\n :param str device: ARM, X86\n :return: uiWebviewARMTestTaskId, uiWebviewARMTestTask\n '
if (engine is 'Klar'):
engine = 'geckoview'
assemble_engine = engine
elif (engine i... | 7,921,102,924,883,363,000 | :param str engine: Klar, Webview
:param str device: ARM, X86
:return: uiWebviewARMTestTaskId, uiWebviewARMTestTask | tools/taskcluster/schedule-master-build.py | generate_ui_test_task | kglazko/focus-android | python | def generate_ui_test_task(dependencies, engine='Klar', device='ARM'):
'\n :param str engine: Klar, Webview\n :param str device: ARM, X86\n :return: uiWebviewARMTestTaskId, uiWebviewARMTestTask\n '
if (engine is 'Klar'):
engine = 'geckoview'
assemble_engine = engine
elif (engine i... |
def test_identity_expectation(self, device, shots, tol):
'Test that identity expectation value (i.e. the trace) is 1'
theta = 0.432
phi = 0.123
dev = device(2)
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi, wires=[1]), qml.CNOT(wires=[0, 1])])
O = ... | 7,841,059,412,821,732,000 | Test that identity expectation value (i.e. the trace) is 1 | tests/test_expval.py | test_identity_expectation | wongwsvincent/pennylane-cirq | python | def test_identity_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi, wires=[1]), qml.CNOT(wires=[0, 1])])
O = qml.Identity
name = 'Identity'
dev._obs_queue = [O(w... |
def test_pauliz_expectation(self, device, shots, tol):
'Test that PauliZ expectation value is correct'
theta = 0.432
phi = 0.123
dev = device(2)
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi, wires=[1]), qml.CNOT(wires=[0, 1])])
O = qml.PauliZ
... | 3,565,328,443,008,282,600 | Test that PauliZ expectation value is correct | tests/test_expval.py | test_pauliz_expectation | wongwsvincent/pennylane-cirq | python | def test_pauliz_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi, wires=[1]), qml.CNOT(wires=[0, 1])])
O = qml.PauliZ
name = 'PauliZ'
dev._obs_queue = [O(wires=[... |
def test_paulix_expectation(self, device, shots, tol):
'Test that PauliX expectation value is correct'
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.PauliX
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rota... | 5,108,788,294,049,689,000 | Test that PauliX expectation value is correct | tests/test_expval.py | test_paulix_expectation | wongwsvincent/pennylane-cirq | python | def test_paulix_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.PauliX
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rotations=(O(wires=[0], do_queue=False).diagonalizi... |
def test_pauliy_expectation(self, device, shots, tol):
'Test that PauliY expectation value is correct'
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.PauliY
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rota... | 4,112,659,539,980,843,500 | Test that PauliY expectation value is correct | tests/test_expval.py | test_pauliy_expectation | wongwsvincent/pennylane-cirq | python | def test_pauliy_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.PauliY
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rotations=(O(wires=[0], do_queue=False).diagonalizi... |
def test_hadamard_expectation(self, device, shots, tol):
'Test that Hadamard expectation value is correct'
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.Hadamard
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT(wires=[0, 1])]... | 4,595,716,068,264,793,600 | Test that Hadamard expectation value is correct | tests/test_expval.py | test_hadamard_expectation | wongwsvincent/pennylane-cirq | python | def test_hadamard_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.Hadamard
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rotations=(O(wires=[0], do_queue=False).diagona... |
def test_hermitian_expectation(self, device, shots, tol):
'Test that arbitrary Hermitian expectation values are correct'
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.Hermitian
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT... | 6,151,081,162,952,617,000 | Test that arbitrary Hermitian expectation values are correct | tests/test_expval.py | test_hermitian_expectation | wongwsvincent/pennylane-cirq | python | def test_hermitian_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.Hermitian
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rotations=(O(A, wires=[0], do_queue=False).di... |
def test_multi_mode_hermitian_expectation(self, device, shots, tol):
'Test that arbitrary multi-mode Hermitian expectation values are correct'
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.Hermitian
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi... | 2,659,470,803,272,884,700 | Test that arbitrary multi-mode Hermitian expectation values are correct | tests/test_expval.py | test_multi_mode_hermitian_expectation | wongwsvincent/pennylane-cirq | python | def test_multi_mode_hermitian_expectation(self, device, shots, tol):
theta = 0.432
phi = 0.123
dev = device(2)
O = qml.Hermitian
with mimic_execution_for_expval(dev):
dev.apply([qml.RY(theta, wires=[0]), qml.RY(phi, wires=[1]), qml.CNOT(wires=[0, 1])], rotations=O(B, wires=[0, 1], do_qu... |
def test_paulix_pauliy(self, device, shots, tol):
'Test that a tensor product involving PauliX and PauliY works correctly'
theta = 0.432
phi = 0.123
varphi = (- 0.543)
dev = device(3)
obs = (qml.PauliX(wires=[0], do_queue=False) @ qml.PauliY(wires=[2], do_queue=False))
with mimic_execution_f... | 3,162,494,482,914,384,000 | Test that a tensor product involving PauliX and PauliY works correctly | tests/test_expval.py | test_paulix_pauliy | wongwsvincent/pennylane-cirq | python | def test_paulix_pauliy(self, device, shots, tol):
theta = 0.432
phi = 0.123
varphi = (- 0.543)
dev = device(3)
obs = (qml.PauliX(wires=[0], do_queue=False) @ qml.PauliY(wires=[2], do_queue=False))
with mimic_execution_for_expval(dev):
dev.apply([qml.RX(theta, wires=[0]), qml.RX(phi,... |
def test_pauliz_hadamard(self, device, shots, tol):
'Test that a tensor product involving PauliZ and PauliY and hadamard works correctly'
theta = 0.432
phi = 0.123
varphi = (- 0.543)
dev = device(3)
obs = ((qml.PauliZ(wires=[0], do_queue=False) @ qml.Hadamard(wires=[1], do_queue=False)) @ qml.Pa... | -1,377,457,128,183,673,600 | Test that a tensor product involving PauliZ and PauliY and hadamard works correctly | tests/test_expval.py | test_pauliz_hadamard | wongwsvincent/pennylane-cirq | python | def test_pauliz_hadamard(self, device, shots, tol):
theta = 0.432
phi = 0.123
varphi = (- 0.543)
dev = device(3)
obs = ((qml.PauliZ(wires=[0], do_queue=False) @ qml.Hadamard(wires=[1], do_queue=False)) @ qml.PauliY(wires=[2], do_queue=False))
with mimic_execution_for_expval(dev):
de... |
def test_hermitian(self, device, shots, tol):
'Test that a tensor product involving qml.Hermitian works correctly'
theta = 0.432
phi = 0.123
varphi = (- 0.543)
dev = device(3)
A = np.array([[(- 6), (2 + 1j), (- 3), ((- 5) + 2j)], [(2 - 1j), 0, (2 - 1j), ((- 5) + 4j)], [(- 3), (2 + 1j), 0, ((- 4)... | 2,487,172,467,202,695,000 | Test that a tensor product involving qml.Hermitian works correctly | tests/test_expval.py | test_hermitian | wongwsvincent/pennylane-cirq | python | def test_hermitian(self, device, shots, tol):
theta = 0.432
phi = 0.123
varphi = (- 0.543)
dev = device(3)
A = np.array([[(- 6), (2 + 1j), (- 3), ((- 5) + 2j)], [(2 - 1j), 0, (2 - 1j), ((- 5) + 4j)], [(- 3), (2 + 1j), 0, ((- 4) + 3j)], [((- 5) - 2j), ((- 5) - 4j), ((- 4) - 3j), (- 6)]])
obs... |
def main(sys_argv: typing.List[str]) -> None:
'PV simulator execution entry point.\n\n Parameters\n ----------\n sys_argv : list\n contains the list of arguments passed to the CLI during its execution. The first argument contains the\n executed script name.\n '
main_logger: typing.Opti... | 795,831,813,431,906,000 | PV simulator execution entry point.
Parameters
----------
sys_argv : list
contains the list of arguments passed to the CLI during its execution. The first argument contains the
executed script name. | services/pv_simulator/main.py | main | reynierg/pv_simulator_challenge | python | def main(sys_argv: typing.List[str]) -> None:
'PV simulator execution entry point.\n\n Parameters\n ----------\n sys_argv : list\n contains the list of arguments passed to the CLI during its execution. The first argument contains the\n executed script name.\n '
main_logger: typing.Opti... |
def render_message_template(message_template: List[dict], **kwargs):
'Renders the jinja data included in the template itself.'
data = []
new_copy = copy.deepcopy(message_template)
for d in new_copy:
if d.get('status_mapping'):
d['text'] = d['status_mapping'][kwargs['status']]
... | 6,656,896,164,718,373,000 | Renders the jinja data included in the template itself. | src/dispatch/messaging.py | render_message_template | oliverzgy/dispatch | python | def render_message_template(message_template: List[dict], **kwargs):
data = []
new_copy = copy.deepcopy(message_template)
for d in new_copy:
if d.get('status_mapping'):
d['text'] = d['status_mapping'][kwargs['status']]
if d.get('datetime'):
d['datetime'] = Templa... |
def __init__(self, params=None):
'Initialization method.\n\n Args:\n params (dict): Contains key-value parameters to the meta-heuristics.\n\n '
logger.info('Overriding class: Optimizer -> QSA.')
super(QSA, self).__init__()
self.build(params)
logger.info('Class overrided.') | -3,367,765,822,090,985,000 | Initialization method.
Args:
params (dict): Contains key-value parameters to the meta-heuristics. | opytimizer/optimizers/social/qsa.py | __init__ | anukaal/opytimizer | python | def __init__(self, params=None):
'Initialization method.\n\n Args:\n params (dict): Contains key-value parameters to the meta-heuristics.\n\n '
logger.info('Overriding class: Optimizer -> QSA.')
super(QSA, self).__init__()
self.build(params)
logger.info('Class overrided.') |
def _calculate_queue(self, n_agents, t_1, t_2, t_3):
'Calculates the number of agents that belongs to each queue.\n\n Args:\n n_agents (int): Number of agents.\n t_1 (float): Fitness value of first agent in the population.\n t_2 (float): Fitness value of second agent in the p... | 2,714,208,289,195,568,000 | Calculates the number of agents that belongs to each queue.
Args:
n_agents (int): Number of agents.
t_1 (float): Fitness value of first agent in the population.
t_2 (float): Fitness value of second agent in the population.
t_3 (float): Fitness value of third agent in the population.
Returns:
The n... | opytimizer/optimizers/social/qsa.py | _calculate_queue | anukaal/opytimizer | python | def _calculate_queue(self, n_agents, t_1, t_2, t_3):
'Calculates the number of agents that belongs to each queue.\n\n Args:\n n_agents (int): Number of agents.\n t_1 (float): Fitness value of first agent in the population.\n t_2 (float): Fitness value of second agent in the p... |
def _business_one(self, agents, function, beta):
'Performs the first business phase.\n\n Args:\n agents (list): List of agents.\n function (Function): A Function object that will be used as the objective function.\n beta (float): Range of fluctuation.\n\n '
agents.... | 7,335,458,090,288,138,000 | Performs the first business phase.
Args:
agents (list): List of agents.
function (Function): A Function object that will be used as the objective function.
beta (float): Range of fluctuation. | opytimizer/optimizers/social/qsa.py | _business_one | anukaal/opytimizer | python | def _business_one(self, agents, function, beta):
'Performs the first business phase.\n\n Args:\n agents (list): List of agents.\n function (Function): A Function object that will be used as the objective function.\n beta (float): Range of fluctuation.\n\n '
agents.... |
def _business_two(self, agents, function):
'Performs the second business phase.\n\n Args:\n agents (list): List of agents.\n function (Function): A Function object that will be used as the objective function.\n\n '
agents.sort(key=(lambda x: x.fit))
(A_1, A_2, A_3) = (cop... | 8,086,955,353,914,416,000 | Performs the second business phase.
Args:
agents (list): List of agents.
function (Function): A Function object that will be used as the objective function. | opytimizer/optimizers/social/qsa.py | _business_two | anukaal/opytimizer | python | def _business_two(self, agents, function):
'Performs the second business phase.\n\n Args:\n agents (list): List of agents.\n function (Function): A Function object that will be used as the objective function.\n\n '
agents.sort(key=(lambda x: x.fit))
(A_1, A_2, A_3) = (cop... |
def _business_three(self, agents, function):
'Performs the third business phase.\n\n Args:\n agents (list): List of agents.\n function (Function): A Function object that will be used as the objective function.\n\n '
agents.sort(key=(lambda x: x.fit))
pr = [(i / len(agents... | -4,295,532,801,114,571,300 | Performs the third business phase.
Args:
agents (list): List of agents.
function (Function): A Function object that will be used as the objective function. | opytimizer/optimizers/social/qsa.py | _business_three | anukaal/opytimizer | python | def _business_three(self, agents, function):
'Performs the third business phase.\n\n Args:\n agents (list): List of agents.\n function (Function): A Function object that will be used as the objective function.\n\n '
agents.sort(key=(lambda x: x.fit))
pr = [(i / len(agents... |
def update(self, space, function, iteration, n_iterations):
'Wraps Queue Search Algorithm over all agents and variables.\n\n Args:\n space (Space): Space containing agents and update-related information.\n function (Function): A Function object that will be used as the objective functio... | 8,129,542,189,646,762,000 | Wraps Queue Search Algorithm over all agents and variables.
Args:
space (Space): Space containing agents and update-related information.
function (Function): A Function object that will be used as the objective function.
iteration (int): Current iteration.
n_iterations (int): Maximum number of iteratio... | opytimizer/optimizers/social/qsa.py | update | anukaal/opytimizer | python | def update(self, space, function, iteration, n_iterations):
'Wraps Queue Search Algorithm over all agents and variables.\n\n Args:\n space (Space): Space containing agents and update-related information.\n function (Function): A Function object that will be used as the objective functio... |
def __init__(self, **kwargs):
'\n Initializes a new WorkRequestLogEntryCollection object with values from keyword arguments.\n The following keyword arguments are supported (corresponding to the getters/setters of this class):\n\n :param items:\n The value to assign to the items prop... | 326,346,107,807,940,160 | Initializes a new WorkRequestLogEntryCollection object with values from keyword arguments.
The following keyword arguments are supported (corresponding to the getters/setters of this class):
:param items:
The value to assign to the items property of this WorkRequestLogEntryCollection.
:type items: list[oci.network... | src/oci/network_load_balancer/models/work_request_log_entry_collection.py | __init__ | LaudateCorpus1/oci-python-sdk | python | def __init__(self, **kwargs):
'\n Initializes a new WorkRequestLogEntryCollection object with values from keyword arguments.\n The following keyword arguments are supported (corresponding to the getters/setters of this class):\n\n :param items:\n The value to assign to the items prop... |
@property
def items(self):
'\n Gets the items of this WorkRequestLogEntryCollection.\n An array of WorkRequestLogEntry objects.\n\n\n :return: The items of this WorkRequestLogEntryCollection.\n :rtype: list[oci.network_load_balancer.models.WorkRequestLogEntry]\n '
return self.... | 6,000,403,713,483,571,000 | Gets the items of this WorkRequestLogEntryCollection.
An array of WorkRequestLogEntry objects.
:return: The items of this WorkRequestLogEntryCollection.
:rtype: list[oci.network_load_balancer.models.WorkRequestLogEntry] | src/oci/network_load_balancer/models/work_request_log_entry_collection.py | items | LaudateCorpus1/oci-python-sdk | python | @property
def items(self):
'\n Gets the items of this WorkRequestLogEntryCollection.\n An array of WorkRequestLogEntry objects.\n\n\n :return: The items of this WorkRequestLogEntryCollection.\n :rtype: list[oci.network_load_balancer.models.WorkRequestLogEntry]\n '
return self.... |
@items.setter
def items(self, items):
'\n Sets the items of this WorkRequestLogEntryCollection.\n An array of WorkRequestLogEntry objects.\n\n\n :param items: The items of this WorkRequestLogEntryCollection.\n :type: list[oci.network_load_balancer.models.WorkRequestLogEntry]\n '
... | -1,871,939,153,352,299,300 | Sets the items of this WorkRequestLogEntryCollection.
An array of WorkRequestLogEntry objects.
:param items: The items of this WorkRequestLogEntryCollection.
:type: list[oci.network_load_balancer.models.WorkRequestLogEntry] | src/oci/network_load_balancer/models/work_request_log_entry_collection.py | items | LaudateCorpus1/oci-python-sdk | python | @items.setter
def items(self, items):
'\n Sets the items of this WorkRequestLogEntryCollection.\n An array of WorkRequestLogEntry objects.\n\n\n :param items: The items of this WorkRequestLogEntryCollection.\n :type: list[oci.network_load_balancer.models.WorkRequestLogEntry]\n '
... |
def twoSum(self, nums, target):
'\n :type nums: List[int]\n :type target: int\n :rtype: List[int]\n '
lookup = dict(((v, i) for (i, v) in enumerate(nums)))
return next((((i + 1), (lookup.get((target - v)) + 1)) for (i, v) in enumerate(nums) if (lookup.get((target - v), i) != i)),... | -5,897,341,292,383,729,000 | :type nums: List[int]
:type target: int
:rtype: List[int] | array/twosum.py | twoSum | mengyangbai/leetcode | python | def twoSum(self, nums, target):
'\n :type nums: List[int]\n :type target: int\n :rtype: List[int]\n '
lookup = dict(((v, i) for (i, v) in enumerate(nums)))
return next((((i + 1), (lookup.get((target - v)) + 1)) for (i, v) in enumerate(nums) if (lookup.get((target - v), i) != i)),... |
def _parse_actions(actions):
' Actions come in as a combined list. This method separates the webhook actions into a\n separate collection and combines any number of email actions into a single email collection\n and a single value for `email_service_owners`. If any email action contains a True value\n... | 3,501,492,025,227,609,600 | Actions come in as a combined list. This method separates the webhook actions into a
separate collection and combines any number of email actions into a single email collection
and a single value for `email_service_owners`. If any email action contains a True value
for `send_to_service_owners` then it is assumed the en... | src/azure-cli/azure/cli/command_modules/monitor/operations/metric_alert.py | _parse_actions | 21m57/azure-cli | python | def _parse_actions(actions):
' Actions come in as a combined list. This method separates the webhook actions into a\n separate collection and combines any number of email actions into a single email collection\n and a single value for `email_service_owners`. If any email action contains a True value\n... |
def _parse_action_removals(actions):
' Separates the combined list of keys to remove into webhooks and emails. '
flattened = list({x for sublist in actions for x in sublist})
emails = []
webhooks = []
for item in flattened:
if (item.startswith('http://') or item.startswith('https://')):
... | -5,889,282,027,629,094,000 | Separates the combined list of keys to remove into webhooks and emails. | src/azure-cli/azure/cli/command_modules/monitor/operations/metric_alert.py | _parse_action_removals | 21m57/azure-cli | python | def _parse_action_removals(actions):
' '
flattened = list({x for sublist in actions for x in sublist})
emails = []
webhooks = []
for item in flattened:
if (item.startswith('http://') or item.startswith('https://')):
webhooks.append(item)
else:
emails.append(i... |
async def async_setup_entry(opp: OpenPeerPower, config_entry: ConfigEntry, async_add_entities) -> None:
'Set up discovered sensors.'
devs = []
for dev in opp.data[AQUALINK_DOMAIN][DOMAIN]:
devs.append(OppAqualinkSensor(dev))
async_add_entities(devs, True) | 6,281,085,809,589,287,000 | Set up discovered sensors. | openpeerpower/components/iaqualink/sensor.py | async_setup_entry | OpenPeerPower/core | python | async def async_setup_entry(opp: OpenPeerPower, config_entry: ConfigEntry, async_add_entities) -> None:
devs = []
for dev in opp.data[AQUALINK_DOMAIN][DOMAIN]:
devs.append(OppAqualinkSensor(dev))
async_add_entities(devs, True) |
@property
def name(self) -> str:
'Return the name of the sensor.'
return self.dev.label | -2,087,878,669,653,740,500 | Return the name of the sensor. | openpeerpower/components/iaqualink/sensor.py | name | OpenPeerPower/core | python | @property
def name(self) -> str:
return self.dev.label |
@property
def unit_of_measurement(self) -> (str | None):
'Return the measurement unit for the sensor.'
if self.dev.name.endswith('_temp'):
if (self.dev.system.temp_unit == 'F'):
return TEMP_FAHRENHEIT
return TEMP_CELSIUS
return None | 4,229,724,856,024,876,000 | Return the measurement unit for the sensor. | openpeerpower/components/iaqualink/sensor.py | unit_of_measurement | OpenPeerPower/core | python | @property
def unit_of_measurement(self) -> (str | None):
if self.dev.name.endswith('_temp'):
if (self.dev.system.temp_unit == 'F'):
return TEMP_FAHRENHEIT
return TEMP_CELSIUS
return None |
@property
def state(self) -> (str | None):
'Return the state of the sensor.'
if (self.dev.state == ''):
return None
try:
state = int(self.dev.state)
except ValueError:
state = float(self.dev.state)
return state | 9,126,054,177,930,050,000 | Return the state of the sensor. | openpeerpower/components/iaqualink/sensor.py | state | OpenPeerPower/core | python | @property
def state(self) -> (str | None):
if (self.dev.state == ):
return None
try:
state = int(self.dev.state)
except ValueError:
state = float(self.dev.state)
return state |
@property
def device_class(self) -> (str | None):
'Return the class of the sensor.'
if self.dev.name.endswith('_temp'):
return DEVICE_CLASS_TEMPERATURE
return None | -1,855,583,597,421,016,000 | Return the class of the sensor. | openpeerpower/components/iaqualink/sensor.py | device_class | OpenPeerPower/core | python | @property
def device_class(self) -> (str | None):
if self.dev.name.endswith('_temp'):
return DEVICE_CLASS_TEMPERATURE
return None |
def scanI2c(ip):
'\n scans devices on i2c bus\n :return: list of hex string addresses present on i2c bus\n '
try:
req_url = (('http://' + ip) + '/i2c/scan')
resp = requests.get(url=req_url)
return resp.content.decode('utf-8')
except ValueError:
print('i2c failed ... | -6,240,809,939,133,776,000 | scans devices on i2c bus
:return: list of hex string addresses present on i2c bus | python/papaya_i2chttpinst.py | scanI2c | papaya-iot/papaya-examples | python | def scanI2c(ip):
'\n scans devices on i2c bus\n :return: list of hex string addresses present on i2c bus\n '
try:
req_url = (('http://' + ip) + '/i2c/scan')
resp = requests.get(url=req_url)
return resp.content.decode('utf-8')
except ValueError:
print('i2c failed ... |
def read(self, reg_addr, len_read):
'\n read len_read bytes starting from register reg_addr\n :param reg_addr: (str) register address to read in hex\n :param len_read: (int) number of bytes to read\n :return: bytestring of data\n '
assert (len_read < 256), 'num of bytes to rea... | -222,386,349,693,098,020 | read len_read bytes starting from register reg_addr
:param reg_addr: (str) register address to read in hex
:param len_read: (int) number of bytes to read
:return: bytestring of data | python/papaya_i2chttpinst.py | read | papaya-iot/papaya-examples | python | def read(self, reg_addr, len_read):
'\n read len_read bytes starting from register reg_addr\n :param reg_addr: (str) register address to read in hex\n :param len_read: (int) number of bytes to read\n :return: bytestring of data\n '
assert (len_read < 256), 'num of bytes to rea... |
def write(self, reg_addr, data, len_data=0):
"\n :param reg_addr: (str) register address to write to in hex\n :param data: (str or bytes) hex-encoded bytes, ie: '014ce8'\n :param len_data: (optional int) dummy variable to support code portability\n :return: None\n "
hex_reg_ad... | -2,559,223,647,912,131,600 | :param reg_addr: (str) register address to write to in hex
:param data: (str or bytes) hex-encoded bytes, ie: '014ce8'
:param len_data: (optional int) dummy variable to support code portability
:return: None | python/papaya_i2chttpinst.py | write | papaya-iot/papaya-examples | python | def write(self, reg_addr, data, len_data=0):
"\n :param reg_addr: (str) register address to write to in hex\n :param data: (str or bytes) hex-encoded bytes, ie: '014ce8'\n :param len_data: (optional int) dummy variable to support code portability\n :return: None\n "
hex_reg_ad... |
@abc.abstractmethod
def __iter__(self) -> Iterator[Class]:
'Create an iterator for the class map values.' | 2,161,965,101,768,955,100 | Create an iterator for the class map values. | xsdata/codegen/mixins.py | __iter__ | amal-khailtash/xsdata | python | @abc.abstractmethod
def __iter__(self) -> Iterator[Class]:
|
@abc.abstractmethod
def find(self, qname: str, condition: Callable=return_true) -> Optional[Class]:
'Search by qualified name for a specific class with an optional\n condition callable.' | -7,627,424,956,996,297,000 | Search by qualified name for a specific class with an optional
condition callable. | xsdata/codegen/mixins.py | find | amal-khailtash/xsdata | python | @abc.abstractmethod
def find(self, qname: str, condition: Callable=return_true) -> Optional[Class]:
'Search by qualified name for a specific class with an optional\n condition callable.' |
@abc.abstractmethod
def find_inner(self, source: Class, qname: str) -> Class:
'Search by qualified name for a specific inner class or fail.' | -3,995,696,163,048,785,000 | Search by qualified name for a specific inner class or fail. | xsdata/codegen/mixins.py | find_inner | amal-khailtash/xsdata | python | @abc.abstractmethod
def find_inner(self, source: Class, qname: str) -> Class:
|
@abc.abstractmethod
def add(self, item: Class):
'Add class item to the container.' | 1,259,824,434,139,553,300 | Add class item to the container. | xsdata/codegen/mixins.py | add | amal-khailtash/xsdata | python | @abc.abstractmethod
def add(self, item: Class):
|
@abc.abstractmethod
def extend(self, items: List[Class]):
'Add a list of classes the container.' | 5,647,266,450,418,243,000 | Add a list of classes the container. | xsdata/codegen/mixins.py | extend | amal-khailtash/xsdata | python | @abc.abstractmethod
def extend(self, items: List[Class]):
|
@abc.abstractmethod
def reset(self, item: Class, qname: str):
'Update the given class qualified name.' | -8,610,711,932,646,473,000 | Update the given class qualified name. | xsdata/codegen/mixins.py | reset | amal-khailtash/xsdata | python | @abc.abstractmethod
def reset(self, item: Class, qname: str):
|
@abc.abstractmethod
def process(self, target: Class):
'Process the given target class.' | -781,199,706,564,020,600 | Process the given target class. | xsdata/codegen/mixins.py | process | amal-khailtash/xsdata | python | @abc.abstractmethod
def process(self, target: Class):
|
@abc.abstractmethod
def run(self):
'Run the process for the whole container.' | 8,029,094,563,809,355,000 | Run the process for the whole container. | xsdata/codegen/mixins.py | run | amal-khailtash/xsdata | python | @abc.abstractmethod
def run(self):
|
def __init__(self, db):
'\n :type db: datacube.index.postgres._api.PostgresDb\n '
self._db = db | 8,569,476,321,902,646,000 | :type db: datacube.index.postgres._api.PostgresDb | datacube/index/_datasets.py | __init__ | cronosnull/agdc-v2 | python | def __init__(self, db):
'\n \n '
self._db = db |
def add(self, definition, allow_table_lock=False):
"\n :type definition: dict\n :param allow_table_lock:\n Allow an exclusive lock to be taken on the table while creating the indexes.\n This will halt other user's requests until completed.\n\n If false, creation will b... | -8,154,873,849,997,148,000 | :type definition: dict
:param allow_table_lock:
Allow an exclusive lock to be taken on the table while creating the indexes.
This will halt other user's requests until completed.
If false, creation will be slightly slower and cannot be done in a transaction.
:rtype: datacube.model.MetadataType | datacube/index/_datasets.py | add | cronosnull/agdc-v2 | python | def add(self, definition, allow_table_lock=False):
"\n :type definition: dict\n :param allow_table_lock:\n Allow an exclusive lock to be taken on the table while creating the indexes.\n This will halt other user's requests until completed.\n\n If false, creation will b... |
@lru_cache()
def get(self, id_):
'\n :rtype: datacube.model.MetadataType\n '
return self._make(self._db.get_metadata_type(id_)) | -2,829,958,382,661,361,700 | :rtype: datacube.model.MetadataType | datacube/index/_datasets.py | get | cronosnull/agdc-v2 | python | @lru_cache()
def get(self, id_):
'\n \n '
return self._make(self._db.get_metadata_type(id_)) |
@lru_cache()
def get_by_name(self, name):
'\n :rtype: datacube.model.MetadataType\n '
record = self._db.get_metadata_type_by_name(name)
if (not record):
return None
return self._make(record) | 966,241,435,974,297,600 | :rtype: datacube.model.MetadataType | datacube/index/_datasets.py | get_by_name | cronosnull/agdc-v2 | python | @lru_cache()
def get_by_name(self, name):
'\n \n '
record = self._db.get_metadata_type_by_name(name)
if (not record):
return None
return self._make(record) |
def check_field_indexes(self, allow_table_lock=False, rebuild_all=False):
"\n Create or replace per-field indexes and views.\n :param allow_table_lock:\n Allow an exclusive lock to be taken on the table while creating the indexes.\n This will halt other user's requests until comp... | 3,272,245,721,149,252,000 | Create or replace per-field indexes and views.
:param allow_table_lock:
Allow an exclusive lock to be taken on the table while creating the indexes.
This will halt other user's requests until completed.
If false, creation will be slightly slower and cannot be done in a transaction. | datacube/index/_datasets.py | check_field_indexes | cronosnull/agdc-v2 | python | def check_field_indexes(self, allow_table_lock=False, rebuild_all=False):
"\n Create or replace per-field indexes and views.\n :param allow_table_lock:\n Allow an exclusive lock to be taken on the table while creating the indexes.\n This will halt other user's requests until comp... |
def _make(self, query_row):
'\n :rtype list[datacube.model.MetadataType]\n '
definition = query_row['definition']
dataset_ = definition['dataset']
return MetadataType(query_row['name'], dataset_, dataset_search_fields=self._db.get_dataset_fields(query_row), id_=query_row['id']) | 895,167,996,513,292,200 | :rtype list[datacube.model.MetadataType] | datacube/index/_datasets.py | _make | cronosnull/agdc-v2 | python | def _make(self, query_row):
'\n \n '
definition = query_row['definition']
dataset_ = definition['dataset']
return MetadataType(query_row['name'], dataset_, dataset_search_fields=self._db.get_dataset_fields(query_row), id_=query_row['id']) |
def __init__(self, db, metadata_type_resource):
'\n :type db: datacube.index.postgres._api.PostgresDb\n :type metadata_type_resource: MetadataTypeResource\n '
self._db = db
self.metadata_type_resource = metadata_type_resource | -6,762,795,850,044,275,000 | :type db: datacube.index.postgres._api.PostgresDb
:type metadata_type_resource: MetadataTypeResource | datacube/index/_datasets.py | __init__ | cronosnull/agdc-v2 | python | def __init__(self, db, metadata_type_resource):
'\n :type db: datacube.index.postgres._api.PostgresDb\n :type metadata_type_resource: MetadataTypeResource\n '
self._db = db
self.metadata_type_resource = metadata_type_resource |
def from_doc(self, definition):
'\n Create a Product from its definitions\n\n :param dict definition: product definition document\n :rtype: datacube.model.DatasetType\n '
DatasetType.validate(definition)
metadata_type = definition['metadata_type']
if isinstance(metadata_type,... | -8,327,443,222,895,981,000 | Create a Product from its definitions
:param dict definition: product definition document
:rtype: datacube.model.DatasetType | datacube/index/_datasets.py | from_doc | cronosnull/agdc-v2 | python | def from_doc(self, definition):
'\n Create a Product from its definitions\n\n :param dict definition: product definition document\n :rtype: datacube.model.DatasetType\n '
DatasetType.validate(definition)
metadata_type = definition['metadata_type']
if isinstance(metadata_type,... |
def add(self, type_):
'\n Add a Product\n\n :param datacube.model.DatasetType type_: Product to add\n :rtype: datacube.model.DatasetType\n '
DatasetType.validate(type_.definition)
existing = self._db.get_dataset_type_by_name(type_.name)
if existing:
check_doc_unchange... | 3,908,486,326,552,046,600 | Add a Product
:param datacube.model.DatasetType type_: Product to add
:rtype: datacube.model.DatasetType | datacube/index/_datasets.py | add | cronosnull/agdc-v2 | python | def add(self, type_):
'\n Add a Product\n\n :param datacube.model.DatasetType type_: Product to add\n :rtype: datacube.model.DatasetType\n '
DatasetType.validate(type_.definition)
existing = self._db.get_dataset_type_by_name(type_.name)
if existing:
check_doc_unchange... |
def update(self, type_, allow_unsafe_updates=False):
'\n Update a product. Unsafe changes will throw a ValueError by default.\n\n (An unsafe change is anything that may potentially make the product\n incompatible with existing datasets of that type)\n\n :param datacube.model.DatasetType ... | -881,313,504,314,386,600 | Update a product. Unsafe changes will throw a ValueError by default.
(An unsafe change is anything that may potentially make the product
incompatible with existing datasets of that type)
:param datacube.model.DatasetType type_: Product to add
:param allow_unsafe_updates bool: Allow unsafe changes. Use with caution.
:... | datacube/index/_datasets.py | update | cronosnull/agdc-v2 | python | def update(self, type_, allow_unsafe_updates=False):
'\n Update a product. Unsafe changes will throw a ValueError by default.\n\n (An unsafe change is anything that may potentially make the product\n incompatible with existing datasets of that type)\n\n :param datacube.model.DatasetType ... |
def update_document(self, definition, allow_unsafe_update=False):
'\n Update a Product using its difinition\n\n :param dict definition: product definition document\n :rtype: datacube.model.DatasetType\n '
type_ = self.from_doc(definition)
return self.update(type_, allow_unsafe_up... | 5,400,559,459,547,803,000 | Update a Product using its difinition
:param dict definition: product definition document
:rtype: datacube.model.DatasetType | datacube/index/_datasets.py | update_document | cronosnull/agdc-v2 | python | def update_document(self, definition, allow_unsafe_update=False):
'\n Update a Product using its difinition\n\n :param dict definition: product definition document\n :rtype: datacube.model.DatasetType\n '
type_ = self.from_doc(definition)
return self.update(type_, allow_unsafe_up... |
def add_document(self, definition):
'\n Add a Product using its difinition\n\n :param dict definition: product definition document\n :rtype: datacube.model.DatasetType\n '
type_ = self.from_doc(definition)
return self.add(type_) | 3,831,264,721,657,754,000 | Add a Product using its difinition
:param dict definition: product definition document
:rtype: datacube.model.DatasetType | datacube/index/_datasets.py | add_document | cronosnull/agdc-v2 | python | def add_document(self, definition):
'\n Add a Product using its difinition\n\n :param dict definition: product definition document\n :rtype: datacube.model.DatasetType\n '
type_ = self.from_doc(definition)
return self.add(type_) |
@lru_cache()
def get(self, id_):
'\n Retrieve Product by id\n\n :param int id_: id of the Product\n :rtype: datacube.model.DatasetType\n '
return self._make(self._db.get_dataset_type(id_)) | 4,528,030,748,589,950,000 | Retrieve Product by id
:param int id_: id of the Product
:rtype: datacube.model.DatasetType | datacube/index/_datasets.py | get | cronosnull/agdc-v2 | python | @lru_cache()
def get(self, id_):
'\n Retrieve Product by id\n\n :param int id_: id of the Product\n :rtype: datacube.model.DatasetType\n '
return self._make(self._db.get_dataset_type(id_)) |
@lru_cache()
def get_by_name(self, name):
'\n Retrieve Product by name\n\n :param str name: name of the Product\n :rtype: datacube.model.DatasetType\n '
result = self._db.get_dataset_type_by_name(name)
if (not result):
return None
return self._make(result) | 7,114,874,661,913,099,000 | Retrieve Product by name
:param str name: name of the Product
:rtype: datacube.model.DatasetType | datacube/index/_datasets.py | get_by_name | cronosnull/agdc-v2 | python | @lru_cache()
def get_by_name(self, name):
'\n Retrieve Product by name\n\n :param str name: name of the Product\n :rtype: datacube.model.DatasetType\n '
result = self._db.get_dataset_type_by_name(name)
if (not result):
return None
return self._make(result) |
def get_with_fields(self, field_names):
'\n Return dataset types that have all the given fields.\n\n :param tuple[str] field_names:\n :rtype: __generator[DatasetType]\n '
for type_ in self.get_all():
for name in field_names:
if (name not in type_.metadata_type.dat... | 8,910,857,798,950,001,000 | Return dataset types that have all the given fields.
:param tuple[str] field_names:
:rtype: __generator[DatasetType] | datacube/index/_datasets.py | get_with_fields | cronosnull/agdc-v2 | python | def get_with_fields(self, field_names):
'\n Return dataset types that have all the given fields.\n\n :param tuple[str] field_names:\n :rtype: __generator[DatasetType]\n '
for type_ in self.get_all():
for name in field_names:
if (name not in type_.metadata_type.dat... |
def search(self, **query):
'\n Return dataset types that have all the given fields.\n\n :param dict query:\n :rtype: __generator[DatasetType]\n '
for (type_, q) in self.search_robust(**query):
if (not q):
(yield type_) | 4,333,933,674,560,769,500 | Return dataset types that have all the given fields.
:param dict query:
:rtype: __generator[DatasetType] | datacube/index/_datasets.py | search | cronosnull/agdc-v2 | python | def search(self, **query):
'\n Return dataset types that have all the given fields.\n\n :param dict query:\n :rtype: __generator[DatasetType]\n '
for (type_, q) in self.search_robust(**query):
if (not q):
(yield type_) |
def search_robust(self, **query):
'\n Return dataset types that match match-able fields and dict of remaining un-matchable fields.\n\n :param dict query:\n :rtype: __generator[(DatasetType, dict)]\n '
for type_ in self.get_all():
q = query.copy()
if (q.pop('product', ... | -9,188,898,544,133,689,000 | Return dataset types that match match-able fields and dict of remaining un-matchable fields.
:param dict query:
:rtype: __generator[(DatasetType, dict)] | datacube/index/_datasets.py | search_robust | cronosnull/agdc-v2 | python | def search_robust(self, **query):
'\n Return dataset types that match match-able fields and dict of remaining un-matchable fields.\n\n :param dict query:\n :rtype: __generator[(DatasetType, dict)]\n '
for type_ in self.get_all():
q = query.copy()
if (q.pop('product', ... |
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