A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
Path to a server directory of a running HyperQueue server.
Python environment which configures Python tasks created by function.
Returns True if all tasks were successfully finished
A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
Path to a server directory of a running HyperQueue server.
Python environment which configures Python tasks created by function.
Returns True if all tasks were successfully finished
A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
This exception is triggered if a task fails.
A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
This exception is triggered if a task fails.
Represents a local deployed HyperQueue infrastructure.
You can use LocalCluster to quickly spin up a HyperQueue server along with a set of workers locally.
The cluster can be used as a context manager. It will be stopped when the context ends:
with LocalCluster() as cluster:
+hyperqueue.cluster.LocalCluster Class LocalCluster
Represents a local deployed HyperQueue infrastructure.
Declaration
class LocalClustersource linkDocumentation
You can use LocalCluster to quickly spin up a HyperQueue server along with a set of workers locally.
The cluster can be used as a context manager. It will be stopped when the context ends:
with LocalCluster() as cluster:
client = cluster.client()
...
# The cluster was stopped
-
Methods
- ▶ def __init__(self, server_dir: Optional[Path] = None, ...)
- ▷ def start_worker(self, config: WorkerConfig = None)
Adds a new worker with the given config to the cluster.
Reexports
- Imported in hyperqueue.
\ No newline at end of file
+Adds a new worker with the given config to the cluster.
Represents a local deployed HyperQueue infrastructure.
Configuration of a worker spawned by a local cluster.
Represents a local deployed HyperQueue infrastructure.
Configuration of a worker spawned by a local cluster.
Blocks until jobs are finished. Returns the number of failed tasks
Blocks until jobs are finished. Returns the number of failed tasks
Opaque class returned from connect_to_server. Should be passed to FFI methods that require it.
Opaque class returned from connect_to_server. Should be passed to FFI methods that require it.
Opaque class returned from cluster_start. Should be passed to FFI methods that require it.
Opaque class returned from cluster_start. Should be passed to FFI methods that require it.
This is the Python API of HyperQueue.
Important classes:
Client serves for connecting to a HyperQueue server.LocalCluster can be used to spawn a local HyperQueue cluster.Job describes a job containing a directed acyclic graph of tasks. It can be submitted using a client.A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
Represents a HQ job.
Represents a local deployed HyperQueue infrastructure.
This is the Python API of HyperQueue.
Important classes:
Client serves for connecting to a HyperQueue server.LocalCluster can be used to spawn a local HyperQueue cluster.Job describes a job containing a directed acyclic graph of tasks. It can be submitted using a client.A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
Represents a HQ job.
Represents a local deployed HyperQueue infrastructure.
Represents a HQ job.
Default working directory for tasks.
How many tasks can fail before the whole job will be cancelled.
Environment variables that will be automatically set for each task in this job.
Creates a new task that will execute the provided Python function.
Positional arguments that will be passed to the Python function.
Keyword arguments that will be passed to the Python function.
Environment variables passed to the executed command.
Working directory of the executed command.
Path to a file that will store the standard output of the executed command.
Path to a file that will store the standard error output of the executed command.
A sequence of dependencies that have to be completed first before this task can start executing.
Name of the task.
Priority of the created task.
List of resource requests required by this task.
Creates a new task that will execute the provided command.
List of arguments will be executed. The arguments have to be strings.
Environment variables passed to the executed command.
Working directory of the executed command.
Path to a file that will store the standard output of the executed command.
Path to a file that will store the standard error output of the executed command.
If provided, these bytes will be passed as the standard input of the executed command.
A sequence of dependencies that have to be completed first before this task can start executing.
Name of the task.
If True, an isolated directory will be created for the task.
Priority of the created task.
List of resource requests required by this task.
Represents a HQ job.
Default working directory for tasks.
How many tasks can fail before the whole job will be cancelled.
Environment variables that will be automatically set for each task in this job.
Creates a new task that will execute the provided Python function.
Positional arguments that will be passed to the Python function.
Keyword arguments that will be passed to the Python function.
Environment variables passed to the executed command.
Working directory of the executed command.
Path to a file that will store the standard output of the executed command.
Path to a file that will store the standard error output of the executed command.
A sequence of dependencies that have to be completed first before this task can start executing.
Name of the task.
Priority of the created task.
List of resource requests required by this task.
Creates a new task that will execute the provided command.
List of arguments will be executed. The arguments have to be strings.
Environment variables passed to the executed command.
Working directory of the executed command.
Path to a file that will store the standard output of the executed command.
Path to a file that will store the standard error output of the executed command.
If provided, these bytes will be passed as the standard input of the executed command.
A sequence of dependencies that have to be completed first before this task can start executing.
Name of the task.
If True, an isolated directory will be created for the task.
Priority of the created task.
List of resource requests required by this task.
Successfully submitted job.
Successfully submitted job.
Represents a HQ job.
Successfully submitted job.
Represents a HQ job.
Successfully submitted job.
Describes an environment for spawning Python interpreters.
Describes an environment for spawning Python interpreters.
Python binary that will be executed.
Shell command that will be executed prior to launching the Python interpreter.
Shell used for executing prologue.
Describes an environment for spawning Python interpreters.
Describes an environment for spawning Python interpreters.
Python binary that will be executed.
Shell command that will be executed prior to launching the Python interpreter.
Shell used for executing prologue.
Task that represents the execution of a Python function.
This method overrides hyperqueue.task.task.Task.__init__.
Task that represents the execution of a Python function.
This method overrides hyperqueue.task.task.Task.__init__.
Describes an environment for spawning Python interpreters.
Task that represents the execution of a Python function.
Wraps a callable so that cloudpickle is used to pickle it, caching the pickle.
Describes an environment for spawning Python interpreters.
Task that represents the execution of a Python function.
Wraps a callable so that cloudpickle is used to pickle it, caching the pickle.
Wraps a callable so that cloudpickle is used to pickle it, caching the pickle.
Wraps a callable so that cloudpickle is used to pickle it, caching the pickle.
Wraps a callable so that cloudpickle is used to pickle it, caching the pickle.
Wraps a callable so that cloudpickle is used to pickle it, caching the pickle.
Task that represents the execution of an executable binary.
This method overrides hyperqueue.task.task.Task.__init__.
Task that represents the execution of an executable binary.
This method overrides hyperqueue.task.task.Task.__init__.
Task that represents the execution of an executable binary.
Task that represents the execution of an executable binary.
This method is overriden in:
This method is overriden in:
Visualizes the task graph of the passed job in the DOT format. The result is written to a file located at path.
Visualizes the task graph of the passed job in the DOT format. The result is written to a file located at path.
This is the Python API of HyperQueue.
Important classes:
Client serves for connecting to a HyperQueue server.LocalCluster can be used to spawn a local HyperQueue cluster.Job describes a job containing a directed acyclic graph of tasks. It can be submitted using a client.A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
Represents a HQ job.
Represents a local deployed HyperQueue infrastructure.
This is the Python API of HyperQueue.
Important classes:
Client serves for connecting to a HyperQueue server.LocalCluster can be used to spawn a local HyperQueue cluster.Job describes a job containing a directed acyclic graph of tasks. It can be submitted using a client.A client serves as a gateway for submitting jobs and querying information about a running HyperQueue server.
Represents a HQ job.
Represents a local deployed HyperQueue infrastructure.
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