_id
stringlengths
2
7
title
stringlengths
1
88
partition
stringclasses
3 values
text
stringlengths
31
13.1k
language
stringclasses
1 value
meta_information
dict
q247400
Plugin.load_plugins
train
def load_plugins(): """ Load all availabe plugins. Returns ------- plugin_cls : dict mapping from plugin names to plugin classes """ plugin_cls = {} for entry_point in pkg_resources.iter_entry_points('docker_interface.plugins'): cl...
python
{ "resource": "" }
q247401
SubstitutionPlugin.substitute_variables
train
def substitute_variables(cls, configuration, value, ref): """ Substitute variables in `value` from `configuration` where any path reference is relative to `ref`. Parameters ---------- configuration : dict configuration (required to resolve intra-document refe...
python
{ "resource": "" }
q247402
UserPlugin.get_user_group
train
def get_user_group(self, user=None, group=None): """ Get the user and group information. Parameters ---------- user : str User name or user id (default is the `os.getuid()`). group : str Group name or group id (default is the group of `user`). ...
python
{ "resource": "" }
q247403
pretty_str
train
def pretty_str(something, indent=0): """Return a human-readable string representation of an object. Uses `pretty_str` if the given value is an instance of `CodeEntity` and `repr` otherwise. Args: something: Some value to convert. Kwargs: indent (int): The
python
{ "resource": "" }
q247404
CodeEntity.walk_preorder
train
def walk_preorder(self): """Iterates the program tree starting from this object, going down."""
python
{ "resource": "" }
q247405
CodeEntity._lookup_parent
train
def _lookup_parent(self, cls): """Lookup a transitive parent object that is an instance of a given class.""" codeobj = self.parent
python
{ "resource": "" }
q247406
CodeEntity.ast_str
train
def ast_str(self, indent=0): """Return a minimal string to print a tree-like structure. Kwargs: indent (int): The number of indentation levels. """ line = self.line or 0 col = self.column or 0 name = type(self).__name__ spell = getattr(self, 'name', '...
python
{ "resource": "" }
q247407
CodeVariable.is_local
train
def is_local(self): """Whether this is a local variable. In general, a variable is *local* if its containing scope is a statement (e.g. a block), or a function, given that the variable is not one of the function's parameters. """
python
{ "resource": "" }
q247408
CodeVariable.is_parameter
train
def is_parameter(self): """Whether this is a function parameter.""" return
python
{ "resource": "" }
q247409
CodeFunction._afterpass
train
def _afterpass(self): """Assign a function-local index to each child object and register write operations to variables. This should only be called after the object is fully built. """ if hasattr(self, '_fi'): return fi = 0 for codeobj in self....
python
{ "resource": "" }
q247410
CodeControlFlow._set_condition
train
def _set_condition(self, condition): """Set the condition for this control flow structure."""
python
{ "resource": "" }
q247411
CodeControlFlow._set_body
train
def _set_body(self, body): """Set the main body for this control flow structure.""" assert isinstance(body, CodeStatement)
python
{ "resource": "" }
q247412
CodeConditional.get_branches
train
def get_branches(self): """Return a list with the conditional branch and the default branch.""" if self.else_branch:
python
{ "resource": "" }
q247413
list_files
train
def list_files(path): """Recursively collects a list of files at a path.""" files = [] if os.path.isdir(path): for stats in os.walk(path): for f in stats[2]:
python
{ "resource": "" }
q247414
ResultCollection.dump
train
def dump(self): """Returns the results in string format.""" text = '' for result in self.objects: if result.is_failure or result.is_error: text += '\n#{red}#{bright}' text += '{}\n'.format(''.ljust(79, '=')) status = 'FAILED' if resul...
python
{ "resource": "" }
q247415
ResultCollection.dump_junit
train
def dump_junit(self): """Returns a string containing XML mapped to the JUnit schema.""" testsuites = ElementTree.Element('testsuites', name='therapist', time=str(round(self.execution_time, 2)), tests=str(self.count()), failures=str(self.count(status=Result.FAILUR...
python
{ "resource": "" }
q247416
install
train
def install(**kwargs): """Install the pre-commit hook.""" force = kwargs.get('force') preserve_legacy = kwargs.get('preserve_legacy') colorama.init(strip=kwargs.get('no_color')) stdout = subprocess.check_output('which therapist', shell=True) therapist_bin = stdout.decode('utf-8').split()[0] ...
python
{ "resource": "" }
q247417
uninstall
train
def uninstall(**kwargs): """Uninstall the current pre-commit hook.""" force = kwargs.get('force') restore_legacy = kwargs.get('restore_legacy') colorama.init(strip=kwargs.get('no_color')) git_dir = current_git_dir() if git_dir is None: output(NOT_GIT_REPO_MSG) exit(1) hoo...
python
{ "resource": "" }
q247418
run
train
def run(**kwargs): """Run the Therapist suite.""" paths = kwargs.pop('paths', ()) action = kwargs.pop('action') plugin = kwargs.pop('plugin') junit_xml = kwargs.pop('junit_xml') use_tracked_files = kwargs.pop('use_tracked_files') quiet = kwargs.pop('quiet') colorama.init(strip=kwargs.po...
python
{ "resource": "" }
q247419
use
train
def use(ctx, shortcut): """Use a shortcut.""" git_dir = current_git_dir() if git_dir is None: output(NOT_GIT_REPO_MSG) exit(1) repo_root = os.path.dirname(git_dir) config = get_config(repo_root) try: use_shortcut = config.shortcuts.get(shortcut) while use_sho...
python
{ "resource": "" }
q247420
identify_hook
train
def identify_hook(path): """Verify that the file at path is the therapist hook and return the hash""" with open(path, 'r') as f: f.readline() # Discard the shebang line
python
{ "resource": "" }
q247421
hash_hook
train
def hash_hook(path, options): """Hash a hook file""" with open(path, 'r') as f: data = f.read() for key in sorted(iterkeys(options)):
python
{ "resource": "" }
q247422
Runner.run_process
train
def run_process(self, process): """Runs a single action.""" message = u'#{bright}' message += u'{} '.format(str(process)[:68]).ljust(69, '.') stashed = False if self.unstaged_changes and not self.include_unstaged_changes: out, err, code = self.git.stash(keep_index=Tr...
python
{ "resource": "" }
q247423
SOAP._extract_upnperror
train
def _extract_upnperror(self, err_xml): """ Extract the error code and error description from an error returned by the device. """ nsmap = {'s': list(err_xml.nsmap.values())[0]} fault_str = err_xml.findtext( 's:Body/s:Fault/faultstring', namespaces=nsmap) try: ...
python
{ "resource": "" }
q247424
SOAP._remove_extraneous_xml_declarations
train
def _remove_extraneous_xml_declarations(xml_str): """ Sometimes devices return XML with more than one XML declaration in, such as when returning their own XML config files. This removes the extra ones and preserves the first one. """ xml_declaration = '' if xml_str.starts...
python
{ "resource": "" }
q247425
SOAP.call
train
def call(self, action_name, arg_in=None, http_auth=None, http_headers=None): """ Construct the XML and make the call to the device. Parse the response values into a dict. """ if arg_in is None: arg_in = {} soap_env = '{%s}' % NS_SOAP_ENV m = '{%s}' % self.ser...
python
{ "resource": "" }
q247426
Device._read_services
train
def _read_services(self): """ Read the control XML file and populate self.services with a list of services in the form of Service class instances. """ # The double slash in the XPath is deliberate, as services can be # listed in two places (Section 2.3 of uPNP device arch...
python
{ "resource": "" }
q247427
Device.find_action
train
def find_action(self, action_name): """Find an action by name. Convenience method that searches through all the services offered by the Server for an action and returns an Action instance. If the action is not found, returns None. If multiple actions with the same name are found ...
python
{ "resource": "" }
q247428
Service.subscribe
train
def subscribe(self, callback_url, timeout=None): """ Set up a subscription to the events offered by this service. """ url = urljoin(self._url_base, self._event_sub_url) headers = dict( HOST=urlparse(url).netloc,
python
{ "resource": "" }
q247429
Service.renew_subscription
train
def renew_subscription(self, sid, timeout=None): """ Renews a previously configured subscription. """ url = urljoin(self._url_base, self._event_sub_url) headers = dict( HOST=urlparse(url).netloc, SID=sid ) if timeout is not None:
python
{ "resource": "" }
q247430
Service.cancel_subscription
train
def cancel_subscription(self, sid): """ Unsubscribes from a previously configured subscription. """ url = urljoin(self._url_base, self._event_sub_url) headers = dict( HOST=urlparse(url).netloc,
python
{ "resource": "" }
q247431
discover
train
def discover(timeout=5): """ Convenience method to discover UPnP devices on the network. Returns a list of `upnp.Device` instances. Any invalid servers are silently ignored. """ devices = {} for entry in scan(timeout): if entry.location in devices: continue
python
{ "resource": "" }
q247432
DFA.to_dot
train
def to_dot(self, path: str, title: Optional[str] = None): """ Print the automaton to a dot file :param path: the path where to save the file. :param title: :return: """ g = graphviz.Digraph(format='svg') g.node('fake', style='invisible') for state...
python
{ "resource": "" }
q247433
DFA.levels_to_accepting_states
train
def levels_to_accepting_states(self) -> dict: """Return a dict from states to level, i.e. the number of steps to reach any accepting state. level = -1 if the state cannot reach any accepting state""" res = {accepting_state: 0 for accepting_state in self._accepting_states} level = 0 ...
python
{ "resource": "" }
q247434
NFA.determinize
train
def determinize(self) -> DFA: """Determinize the NFA :return: the DFA equivalent to the DFA. """ nfa = self new_states = {macro_state for macro_state in powerset(nfa._states)} initial_state = frozenset([nfa._initial_state]) final_states = {q for q in new_states...
python
{ "resource": "" }
q247435
Client.req
train
def req(self, method, params=()): """send request to ppcoind""" response = self.session.post( self.url, data=json.dumps({"method": method, "params": params, "jsonrpc": "1.1"}), ).json()
python
{ "resource": "" }
q247436
Client.batch
train
def batch(self, reqs): """ send batch request using jsonrpc 2.0 """ batch_data = [] for req_id, req in enumerate(reqs): batch_data.append( {"method": req[0], "params": req[1], "jsonrpc": "2.0", "id": req_id}
python
{ "resource": "" }
q247437
Client.walletpassphrase
train
def walletpassphrase(self, passphrase, timeout=99999999, mint_only=True):
python
{ "resource": "" }
q247438
Client.getblock
train
def getblock(self, blockhash, decode=False): """returns detail block info.""" if not decode: decode = "false"
python
{ "resource": "" }
q247439
Client.sendfrom
train
def sendfrom(self, account, address, amount): """send outgoing tx from
python
{ "resource": "" }
q247440
Client.listtransactions
train
def listtransactions(self, account="", many=999, since=0): """list all transactions associated with this wallet"""
python
{ "resource": "" }
q247441
Client.verifymessage
train
def verifymessage(self, address, signature, message): """Verify a signed message."""
python
{ "resource": "" }
q247442
coroutine
train
def coroutine(f): """ A sink should be send `None` first, so that the coroutine arrives at the `yield` position. This wrapper takes care that this is done automatically when the coroutine is started.
python
{ "resource": "" }
q247443
Fail.add_call
train
def add_call(self, func): """Add a call to the trace.""" self.trace.append("{} ({}:{})".format( object_name(func),
python
{ "resource": "" }
q247444
all
train
def all(pred: Callable, xs: Iterable): """ Check whether all the elements of the iterable `xs` fullfill predicate `pred`. :param pred: predicate function :param xs: iterable object. :returns:
python
{ "resource": "" }
q247445
any
train
def any(pred: Callable, xs: Iterable): """ Check if at least one element of the iterable `xs` fullfills predicate `pred`.
python
{ "resource": "" }
q247446
map
train
def map(fun: Callable, xs: Iterable): """ Traverse an iterable object applying function `fun` to each element and finally creats a workflow from it. :param fun: function to call in each element of the iterable object. :param xs:
python
{ "resource": "" }
q247447
zip_with
train
def zip_with(fun: Callable, xs: Iterable, ys: Iterable): """ Fuse two Iterable object using the function `fun`. Notice that if the two objects have different len, the shortest object gives the result's shape. :param fun: function taking two argument use to process element x from `xs` ...
python
{ "resource": "" }
q247448
_arg_to_str
train
def _arg_to_str(arg): """Convert argument to a string.""" if isinstance(arg, str): return _sugar(repr(arg)) elif arg is
python
{ "resource": "" }
q247449
is_node_ready
train
def is_node_ready(node): """Returns True if none of the argument holders contain any `Empty` object. """
python
{ "resource": "" }
q247450
JobDB.add_job_to_db
train
def add_job_to_db(self, key, job): """Add job info to the database.""" job_msg = self.registry.deep_encode(job) prov = prov_key(job_msg) def set_link(duplicate_id): self.cur.execute( 'update "jobs" set "link" = ?, "status" = ? where "id" = ?', ...
python
{ "resource": "" }
q247451
JobDB.job_exists
train
def job_exists(self, prov): """Check if a job exists in the database.""" with self.lock: self.cur.execute('select * from "jobs" where "prov"
python
{ "resource": "" }
q247452
JobDB.store_result_in_db
train
def store_result_in_db(self, result, always_cache=True): """Store a result in the database.""" job = self[result.key] def extend_dependent_links(): with self.lock: new_workflow_id = id(get_workflow(result.value)) self.links[new_workflow_id].extend( ...
python
{ "resource": "" }
q247453
JobDB.add_time_stamp
train
def add_time_stamp(self, db_id, name): """Add a timestamp to the database.""" with self.lock:
python
{ "resource": "" }
q247454
static_sum
train
def static_sum(values, limit_n=1000): """Example of static sum routine.""" if len(values) < limit_n: return sum(values) else: half = len(values) // 2 return add(
python
{ "resource": "" }
q247455
dynamic_sum
train
def dynamic_sum(values, limit_n=1000, acc=0, depth=4): """Example of dynamic sum.""" if len(values) < limit_n: return acc + sum(values) if depth > 0: half = len(values) // 2 return add( dynamic_sum(values[:half], limit_n, acc, depth=depth-1),
python
{ "resource": "" }
q247456
Queue.flush
train
def flush(self): """Erases queue and set `end-of-queue` message.""" while not self._queue.empty():
python
{ "resource": "" }
q247457
find_links_to
train
def find_links_to(links, node): """Find links to a node. :param links: forward links of a workflow :type links: Mapping[NodeId, Set[(NodeId, ArgumentType, [int|str]])] :param node: index to a node :type node: int :returns: dictionary of
python
{ "resource": "" }
q247458
_all_valid
train
def _all_valid(links): """Iterates over all links, forgetting emtpy registers.""" for k, v
python
{ "resource": "" }
q247459
from_call
train
def from_call(foo, args, kwargs, hints, call_by_value=True): """Takes a function and a set of arguments it needs to run on. Returns a newly constructed workflow representing the promised value from the evaluation of the function with said arguments. These arguments are stored in a BoundArguments object...
python
{ "resource": "" }
q247460
make_logger
train
def make_logger(name, stream_type, jobs): """Create a logger component. :param name: name of logger child, i.e. logger will be named `noodles.<name>`. :type name: str :param stream_type: type of the stream that this logger will be inserted into, should be |pull_map| or |push_map|. :...
python
{ "resource": "" }
q247461
run_process
train
def run_process(workflow, *, n_processes, registry, verbose=False, jobdirs=False, init=None, finish=None, deref=False): """Run the workflow using a number of new python processes. Use this runner to test the workflow in a situation where data serial is needed. :param wor...
python
{ "resource": "" }
q247462
xenon_interactive_worker
train
def xenon_interactive_worker( machine, worker_config, input_queue=None, stderr_sink=None): """Uses Xenon to run a single remote interactive worker. Jobs are read from stdin, and results written to stdout. :param machine: Specification of the machine on which to run. :type machine: nood...
python
{ "resource": "" }
q247463
XenonInteractiveWorker.wait_until_running
train
def wait_until_running(self, callback=None): """Waits until the remote worker is running, then calls the callback. Usually, this method is passed to a different thread; the callback is then a function patching results through to the result queue."""
python
{ "resource": "" }
q247464
DynamicPool.add_xenon_worker
train
def add_xenon_worker(self, worker_config): """Adds a worker to the pool; sets gears in motion.""" c = XenonInteractiveWorker(self.machine, worker_config) w = RemoteWorker( worker_config.name, threading.Lock(), worker_config.n_threads, [], *c.setup()) with self.wl...
python
{ "resource": "" }
q247465
find_first
train
def find_first(pred, lst): """Find the first result of a list of promises `lst` that satisfies a predicate `pred`. :param pred: a function of one argument returning `True` or `False`. :param lst: a list of promises or values. :return: a promise of a value or `None`. This is a wrapper around :f...
python
{ "resource": "" }
q247466
s_find_first
train
def s_find_first(pred, first, lst): """Evaluate `first`; if predicate `pred` succeeds on the result of `first`, return the result; otherwise recur on the first element of `lst`. :param pred: a predicate.
python
{ "resource": "" }
q247467
run_online_mode
train
def run_online_mode(args): """Run jobs. :param args: arguments resulting from program ArgumentParser. :return: None This reads messages containing job descriptions from standard input, and writes messages to standard output containing the result. Messages can be encoded as either JSON or Mess...
python
{ "resource": "" }
q247468
_format_arg_list
train
def _format_arg_list(args, variadic=False): """Format a list of arguments for pretty printing. :param a: list of arguments. :type a: list :param v: tell if the function accepts variadic arguments :type v: bool """ def sugar(s): """Shorten strings that are too long for decency.""" ...
python
{ "resource": "" }
q247469
get_workflow_graph
train
def get_workflow_graph(promise): """Get a graph of a promise.""" workflow = get_workflow(promise) dot = Digraph() for i, n in workflow.nodes.items(): dot.node(str(i), label="{0} \n {1}".format( n.foo.__name__, _format_arg_list(n.bound_args.args))) for i
python
{ "resource": "" }
q247470
display_workflows
train
def display_workflows(prefix, **kwargs): """Display workflows in a table. This generates SVG files. Use this in a Jupyter notebook and ship the images :param prefix: name prefix for svg files generated. :param kwargs: keyword arguments containing a workflow each. """ from IPython.display import...
python
{ "resource": "" }
q247471
snip_line
train
def snip_line(line, max_width, split_at): """Shorten a line to a maximum length.""" if len(line) < max_width: return line
python
{ "resource": "" }
q247472
run_and_print_log
train
def run_and_print_log(workflow, highlight=None): """Run workflow on multi-threaded worker cached with Sqlite3. :param workflow: workflow to evaluate. :param highlight: highlight these lines. """ from noodles.run.threading.sqlite3 import run_parallel from noodles import serial import io ...
python
{ "resource": "" }
q247473
run_single_with_display
train
def run_single_with_display(wf, display): """Adds a display to the single runner. Everything still runs in a single thread. Every time a job is pulled by the worker, a message goes to the display routine; when
python
{ "resource": "" }
q247474
run_parallel_with_display
train
def run_parallel_with_display(wf, n_threads, display): """Adds a display to the parallel runner. Because messages come in asynchronously now, we start an extra thread just for the display routine.""" LogQ = Queue() S = Scheduler(error_handler=display.error_handler) threading.Thread( ta...
python
{ "resource": "" }
q247475
decorator
train
def decorator(f): """Creates a paramatric decorator from a function. The resulting decorator will optionally take keyword arguments.""" @functools.wraps(f) def decoratored_function(*args, **kwargs): if args and len(args) == 1: return f(*args, **kwargs)
python
{ "resource": "" }
q247476
Scheduler.run
train
def run(self, connection: Connection, master: Workflow): """Run a workflow. :param connection: A connection giving a sink to the job-queue and a source yielding results. :type connection: Connection :param master: The workflow. :type master: ...
python
{ "resource": "" }
q247477
ref_argument
train
def ref_argument(bound_args, address): """ Taking a bound_args object, and an ArgumentAddress, retrieves the data currently stored in bound_args for this particular address.""" if address.kind == ArgumentKind.regular:
python
{ "resource": "" }
q247478
set_argument
train
def set_argument(bound_args, address, value): """ Taking a bound_args object, and an |ArgumentAddress| and a value, sets the value pointed to by the address to `value`.""" if address.kind == ArgumentKind.regular: bound_args.arguments[address.name] = value return if address.kind == Argum...
python
{ "resource": "" }
q247479
format_address
train
def format_address(address): """Formats an ArgumentAddress for human reading."""
python
{ "resource": "" }
q247480
run_parallel
train
def run_parallel(workflow, n_threads): """Run a workflow in parallel threads. :param workflow: Workflow or PromisedObject to evaluate. :param n_threads: number of threads to use (in addition to the scheduler). :returns: evaluated workflow.
python
{ "resource": "" }
q247481
thread_counter
train
def thread_counter(finalize): """Modifies a thread target function, such that the number of active threads is counted. If the count reaches zero, a finalizer is called.""" n_threads = 0 lock = threading.Lock() def target_modifier(target): @functools.wraps(target) def modified_target...
python
{ "resource": "" }
q247482
thread_pool
train
def thread_pool(*workers, results=None, end_of_queue=EndOfQueue): """Returns a |pull| object, call it ``r``, starting a thread for each given worker. Each thread pulls from the source that ``r`` is connected to, and the returned results are pushed to a |Queue|. ``r`` yields from the other end of the s...
python
{ "resource": "" }
q247483
run
train
def run(wf, *, display, n_threads=1): """Run the workflow using the dynamic-exclusion worker.""" worker
python
{ "resource": "" }
q247484
create_object
train
def create_object(cls, members): """Promise an object of class `cls` with content `members`.""" obj =
python
{ "resource": "" }
q247485
lift
train
def lift(obj, memo=None): """Make a promise out of object `obj`, where `obj` may contain promises internally. :param obj: Any object. :param memo: used for internal caching (similar to :func:`deepcopy`). If the object is a :class:`PromisedObject`, or *pass-by-value* (:class:`str`, :class:`int`...
python
{ "resource": "" }
q247486
branch
train
def branch(*sinks_): """The |branch| decorator creates a |pull| object that pulls from a single source and then sends to all the sinks given. After all the sinks received the message, it is yielded. .. |branch| replace:: :py:func:`branch` """ @pull def junction(source):
python
{ "resource": "" }
q247487
broadcast
train
def broadcast(*sinks_): """The |broadcast| decorator creates a |push| object that receives a message by ``yield`` and then sends this message on to all the given sinks. .. |broadcast| replace:: :py:func:`broadcast` """ @push def bc(): sinks =
python
{ "resource": "" }
q247488
push_from
train
def push_from(iterable): """Creates a |push| object from an iterable. The resulting function is not a coroutine, but can be chained to another |push|. :param iterable: an iterable object. :type iterable: :py:class:`~collections.abc.Iterable` :rtype: |push|
python
{ "resource": "" }
q247489
patch
train
def patch(source, sink): """Create a direct link between a source and a sink. Implementation:: sink = sink() for value in source():
python
{ "resource": "" }
q247490
conditional
train
def conditional( b: bool, branch_true: Any, branch_false: Any=None) -> Any: """ Control statement to follow a branch in workflow. Equivalent to the `if` statement in standard Python. The quote function delay the evaluation of the branches until the boolean is evaluated. ...
python
{ "resource": "" }
q247491
schedule_branches
train
def schedule_branches(b: bool, quoted_true, quoted_false): """ Helper function to choose which workflow to execute based on the boolean `b`. :param b: promised boolean value :param quoted_true: quoted workflow to eval if the boolean is true. :param quoted_true:
python
{ "resource": "" }
q247492
array_sha256
train
def array_sha256(a): """Create a SHA256 hash from a Numpy array.""" dtype = str(a.dtype).encode() shape = numpy.array(a.shape) sha = hashlib.sha256()
python
{ "resource": "" }
q247493
arrays_to_file
train
def arrays_to_file(file_prefix=None): """Returns a serialisation registry for serialising NumPy data and as well as any UFuncs that have no normal way of retrieving
python
{ "resource": "" }
q247494
arrays_to_string
train
def arrays_to_string(file_prefix=None): """Returns registry for serialising arrays as a Base64 string.""" return Registry(
python
{ "resource": "" }
q247495
arrays_to_hdf5
train
def arrays_to_hdf5(filename="cache.hdf5"): """Returns registry for serialising arrays to a HDF5 reference.""" return Registry(
python
{ "resource": "" }
q247496
run_xenon_simple
train
def run_xenon_simple(workflow, machine, worker_config): """Run a workflow using a single Xenon remote worker. :param workflow: |Workflow| or |PromisedObject| to evaluate. :param machine: |Machine| instance. :param worker_config: Configuration for the pilot
python
{ "resource": "" }
q247497
run_xenon
train
def run_xenon( workflow, *, machine, worker_config, n_processes, deref=False, verbose=False): """Run the workflow using a number of online Xenon workers. :param workflow: |Workflow| or |PromisedObject| to evaluate. :param machine: The |Machine| instance. :param worker_config: Configurat...
python
{ "resource": "" }
q247498
pass_job
train
def pass_job(db: JobDB, result_queue: Queue, always_cache=False): """Create a pull stream that receives jobs and passes them on to the database. If the job already has a result, that result is pushed onto the `result_queue`. """ @pull def pass_job_stream(job_source): """Pull stream insta...
python
{ "resource": "" }
q247499
pass_result
train
def pass_result(db: JobDB, always_cache=False): """Creates a pull stream receiving results, storing them in the database, then sending them on. At this stage, the database may return a list of attached jobs which also need to be sent on to the scheduler.""" @pull def pass_result_stream(worker_source...
python
{ "resource": "" }