ray.runtime_env.RuntimeEnvConfig#

class ray.runtime_env.RuntimeEnvConfig(setup_timeout_seconds: int = 600, eager_install: bool = True, log_files: List[str] | None = None)[source]#

Bases: dict

Used to specify configuration options for a runtime environment.

The config is not included when calculating the runtime_env hash, which means that two runtime_envs with the same options but different configs are considered the same for caching purposes.

Parameters:

setup_timeout_seconds – The timeout of runtime environment creation, timeout is in seconds. The value -1 means disable timeout logic, except -1, setup_timeout_seconds cannot be less than or equal to 0. The default value of setup_timeout_seconds is 600 seconds.
eager_install – Indicates whether to install the runtime environment on the cluster at ray.init() time, before the workers are leased. This flag is set to True by default.
log_files – An optional list of log files to surface in the dashboard for this runtime environment.

Methods

`clear`	D.clear() -> None.
`copy`	D.copy() -> a shallow copy of D
`fromkeys`	Create a new dictionary with keys from iterable and values set to value.
`get`	Return the value for key if key is in the dictionary, else default.
`items`	D.items() -> a set-like object providing a view on D's items
`keys`	D.keys() -> a set-like object providing a view on D's keys
`pop`	D.pop(k[,d]) -> v, remove specified key and return the corresponding value.
`popitem`	Remove and return a (key, value) pair as a 2-tuple.
`setdefault`	Insert key with a value of default if key is not in the dictionary.
`update`	D.update([E, ]**F) -> None.
`values`	D.values() -> an object providing a view on D's values

Attributes

known_fields