executor-args.md

Name	Description	Type	Default
name	The name of this object. This will be used in the following places: - how you refer to this object in Python/YAML/CLI - visualization - log message header - ... When not given, then the default naming strategy will apply.	string	None
workspace	The working directory for any IO operations in this object. If not set, then derive from its parent workspace.	string	None
log_config	The YAML config of the logger used in this object.	string	default
quiet	If set, then no log will be emitted from this object.	boolean	False
quiet_error	If set, then exception stack information will not be added to the log	boolean	False
timeout_ctrl	The timeout in milliseconds of the control request, -1 for waiting forever	number	60
polling	The polling strategy of the Deployment and its endpoints (when shards>1). Can be defined for all endpoints of a Deployment or by endpoint. Define per Deployment: - ANY: only one (whoever is idle) Pod polls the message - ALL: all Pods poll the message (like a broadcast) Define per Endpoint: JSON dict, {endpoint: PollingType} {'/custom': 'ALL', '/search': 'ANY', '*': 'ANY'}	string	ANY
uses	The config of the executor, it could be one of the followings: * the string literal of an Executor class name * an Executor YAML file (.yml, .yaml, .jaml) * a Jina Hub Executor (must start with jinahub:// or jinahub+docker://) * a docker image (must start with docker://) * the string literal of a YAML config (must start with ! or jtype: ) * the string literal of a JSON config When use it under Python, one can use the following values additionally: - a Python dict that represents the config - a text file stream has .read() interface	string	BaseExecutor
uses_with	Dictionary of keyword arguments that will override the with configuration in uses	object	None
uses_metas	Dictionary of keyword arguments that will override the metas configuration in uses	object	None
uses_requests	Dictionary of keyword arguments that will override the requests configuration in uses	object	None
py_modules	The customized python modules need to be imported before loading the executor Note that the recommended way is to only import a single module - a simple python file, if your executor can be defined in a single file, or an __init__.py file if you have multiple files, which should be structured as a python package. For more details, please see the Executor cookbook <https://docs.jina.ai/fundamentals/executor/executor-files/>__	array	None
port	The port for input data to bind to, default is a random port between [49152, 65535]. In the case of an external Executor (--external or external=True) this can be a list of ports, separated by commas. Then, every resulting address will be considered as one replica of the Executor.	string	random in [49152, 65535]
host_in	The host address for binding to, by default it is 0.0.0.0	string	0.0.0.0
native	If set, only native Executors is allowed, and the Executor is always run inside WorkerRuntime.	boolean	False
output_array_type	The type of array tensor and embedding will be serialized to. Supports the same types as docarray.to_protobuf(.., ndarray_type=...), which can be found here <https://docarray.jina.ai/fundamentals/document/serialization/#from-to-protobuf>. Defaults to retaining whatever type is returned by the Executor.	string	None
grpc_server_options	Dictionary of kwargs arguments that will be passed to the grpc server as options when starting the server, example : {'grpc.max_send_message_length': -1}	object	None
exit_on_exceptions	List of exceptions that will cause the Executor to shut down.	array	[]
entrypoint	The entrypoint command overrides the ENTRYPOINT in Docker image. when not set then the Docker image ENTRYPOINT takes effective.	string	None
docker_kwargs	Dictionary of kwargs arguments that will be passed to Docker SDK when starting the docker ' container. More details can be found in the Docker SDK docs: https://docker-py.readthedocs.io/en/stable/	object	None
volumes	The path on the host to be mounted inside the container. Note, - If separated by :, then the first part will be considered as the local host path and the second part is the path in the container system. - If no split provided, then the basename of that directory will be mounted into container's root path, e.g. --volumes="/user/test/my-workspace" will be mounted into /my-workspace inside the container. - All volumes are mounted with read-write mode.	array	None
gpus	This argument allows dockerized Jina executor discover local gpu devices. Note, - To access all gpus, use --gpus all. - To access multiple gpus, e.g. make use of 2 gpus, use --gpus 2. - To access specified gpus based on device id, use --gpus device=[YOUR-GPU-DEVICE-ID] - To access specified gpus based on multiple device id, use --gpus device=[YOUR-GPU-DEVICE-ID1],device=[YOUR-GPU-DEVICE-ID2] - To specify more parameters, use `--gpus device=[YOUR-GPU-DEVICE-ID],runtime=nvidia,capabilities=display	string	None
disable_auto_volume	Do not automatically mount a volume for dockerized Executors.	boolean	False
host	The host address of the runtime, by default it is 0.0.0.0. In the case of an external Executor (--external or external=True) this can be a list of hosts, separated by commas. Then, every resulting address will be considered as one replica of the Executor.	string	0.0.0.0
quiet_remote_logs	Do not display the streaming of remote logs on local console	boolean	False
upload_files	The files on the host to be uploaded to the remote workspace. This can be useful when your Deployment has more file dependencies beyond a single YAML file, e.g. Python files, data files. Note, - currently only flatten structure is supported, which means if you upload [./foo/a.py, ./foo/b.pp, ./bar/c.yml], then they will be put under the same workspace on the remote, losing all hierarchies. - by default, --uses YAML file is always uploaded. - uploaded files are by default isolated across the runs. To ensure files are submitted to the same workspace across different runs, use --workspace-id to specify the workspace.	array	None
runtime_cls	The runtime class to run inside the Pod	string	WorkerRuntime
timeout_ready	The timeout in milliseconds of a Pod waits for the runtime to be ready, -1 for waiting forever	number	600000
env	The map of environment variables that are available inside runtime	object	None
shards	The number of shards in the deployment running at the same time. For more details check https://docs.jina.ai/fundamentals/flow/create-flow/#complex-flow-topologies	number	1
replicas	The number of replicas in the deployment	number	1
monitoring	If set, spawn an http server with a prometheus endpoint to expose metrics	boolean	False
port_monitoring	The port on which the prometheus server is exposed, default is a random port between [49152, 65535]	string	random in [49152, 65535]
retries	Number of retries per gRPC call. If <0 it defaults to max(3, num_replicas)	number	-1
floating	If set, the current Pod/Deployment can not be further chained, and the next .add() will chain after the last Pod/Deployment not this current one.	boolean	False
tracing	If set, the sdk implementation of the OpenTelemetry tracer will be available and will be enabled for automatic tracing of requests and customer span creation. Otherwise a no-op implementation will be provided.	boolean	False
span_exporter_host	If tracing is enabled, this hostname will be used to configure the trace exporter agent.	string	None
span_exporter_port	If tracing is enabled, this port will be used to configure the trace exporter agent.	number	None
metrics	If set, the sdk implementation of the OpenTelemetry metrics will be available for default monitoring and custom measurements. Otherwise a no-op implementation will be provided.	boolean	False
metrics_exporter_host	If tracing is enabled, this hostname will be used to configure the metrics exporter agent.	string	None
metrics_exporter_port	If tracing is enabled, this port will be used to configure the metrics exporter agent.	number	None
install_requirements	If set, install requirements.txt in the Hub Executor bundle to local	boolean	False
force_update	If set, always pull the latest Hub Executor bundle even it exists on local	boolean	False
compression	The compression mechanism used when sending requests from the Head to the WorkerRuntimes. For more details, check https://grpc.github.io/grpc/python/grpc.html#compression.	string	None
uses_before_address	The address of the uses-before runtime	string	None
uses_after_address	The address of the uses-before runtime	string	None
connection_list	dictionary JSON with a list of connections to configure	string	None
disable_reduce	Disable the built-in reduce mechanism, set this if the reduction is to be handled by the Executor connected to this Head	boolean	False
timeout_send	The timeout in milliseconds used when sending data requests to Executors, -1 means no timeout, disabled by default	number	None