ray.runtime_env.RuntimeEnvConfig#

class ray.runtime_env.RuntimeEnvConfig(setup_timeout_seconds: int = 600, eager_install: bool = True)[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.

PublicAPI: This API is stable across Ray releases.

Methods

clear()

copy()

fromkeys([value])

Create a new dictionary with keys from iterable and values set to value.

get(key[, default])

Return the value for key if key is in the dictionary, else default.

items()

keys()

pop(k[,d])

If key is not found, d is returned if given, otherwise KeyError is raised

popitem()

Remove and return a (key, value) pair as a 2-tuple.

setdefault(key[, default])

Insert key with a value of default if key is not in the dictionary.

update([E, ]**F)

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values()

Attributes

known_fields