flytekit.Resources

class flytekit.Resources(cpu=None, mem=None, gpu=None, ephemeral_storage=None)

This class is used to specify both resource requests and resource limits.

Resources(cpu="1", mem="2048")  # This is 1 CPU and 2 KB of memory
Resources(cpu="100m", mem="2Gi")  # This is 1/10th of a CPU and 2 gigabytes of memory
Resources(cpu=0.5, mem=1024) # This is 500m CPU and 1 KB of memory

# For Kubernetes-based tasks, pods use ephemeral local storage for scratch space, caching, and for logs.
# This allocates 1Gi of such local storage.
Resources(ephemeral_storage="1Gi")

Note

Persistent storage is not currently supported on the Flyte backend.

Please see the User Guide for detailed examples. Also refer to the K8s conventions.

Methods

Parameters:

• cpu (str | int | float | None)

• mem (int | str | None)

• gpu (int | str | None)

• ephemeral_storage (int | str | None)

classmethod from_dict(d, *, dialect=None)

classmethod from_json(data, decoder=<function loads>, **from_dict_kwargs)

Parameters:

• data (str | bytes | bytearray)

• decoder (Callable[[str | bytes | bytearray], Dict[Any, Any]])

• from_dict_kwargs (Any)

Return type:

T

to_dict()

to_json(encoder=<function dumps>, **to_dict_kwargs)

Parameters:

• self (T)

• encoder (Callable[[Any], str | bytes | bytearray])

• to_dict_kwargs (Any)

Return type:

str | bytes | bytearray

Attributes

cpu: str | int | float | None = None

ephemeral_storage: int | str | None = None

gpu: int | str | None = None

mem: int | str | None = None