Source code for runhouse.resources.blobs.blob

import logging
from typing import Any, Dict, Optional, Union

from runhouse.resources.envs import _get_env_from, Env
from runhouse.resources.hardware import _current_cluster, _get_cluster_from, Cluster

from runhouse.resources.module import Module
from runhouse.rns.utils.names import _generate_default_name, _generate_default_path

logger = logging.getLogger(__name__)

[docs]class Blob(Module): RESOURCE_TYPE = "blob" DEFAULT_FOLDER_PATH = "/runhouse-blob" DEFAULT_CACHE_FOLDER = ".cache/runhouse/blobs"
[docs] def __init__( self, name: Optional[str] = None, system: Union[Cluster] = None, env: Optional[Env] = None, dryrun: bool = False, **kwargs, ): """ Runhouse Blob object .. note:: To build a Blob, please use the factory method :func:`blob`. """ = None super().__init__(name=name, system=system, env=env, dryrun=dryrun, **kwargs)
[docs] def to( self, system: Union[str, Cluster], env: Optional[Union[str, Env]] = None, path: Optional[str] = None, data_config: Optional[dict] = None, ): """Return a copy of the blob on the destination system, and optionally path. Example: >>> local_blob = rh.blob(data) >>> s3_blob ="s3") >>> cluster_blob = """ if system == "here": if not path: current_cluster_config = _current_cluster(key="config") if current_cluster_config: system = Cluster.from_config(current_cluster_config) else: system = None else: system = "file" system = _get_cluster_from(system) if (not system or isinstance(system, Cluster)) and not path: = or _generate_default_name(prefix="blob") # TODO [DG] if system is the same, bounces off the laptop for no reason. Change to write through a # call_module_method rpc (and same for similar file cases) return super().to(system, env) path = str( path or self.default_path(self.rns_address, system) ) # Make sure it's a string and not a Path from runhouse.resources.blobs.file import File new_blob = File(path=path, system=system, data_config=data_config) new_blob.write(self.fetch()) return new_blob
# TODO delete
[docs] def write(self, data): """Save the underlying blob to its cluster's store. Example: >>> rh.blob(data).write() """ = data
[docs] def rm(self): """Delete the blob from wherever it's stored. Example: >>> blob = rh.blob(data) >>> blob.rm() """ = None
[docs] def exists_in_system(self): """Check whether the blob exists in the file system Example: >>> blob = rh.blob(data) >>> blob.exists_in_system() """ if is not None: return True
[docs] def resolved_state(self, _state_dict=None): """Return the resolved state of the blob, which is the data. Primarily used to define the behavior of the ``fetch`` method. Example: >>> blob = rh.blob(data) >>> blob.resolved_state() """ return
[docs]def blob( data: [Any] = None, name: Optional[str] = None, path: Optional[str] = None, system: Optional[str] = None, env: Optional[Union[str, Env]] = None, data_config: Optional[Dict] = None, load: bool = True, dryrun: bool = False, ): """Returns a Blob object, which can be used to interact with the resource at the given path Args: data: Blob data. The data to persist either on the cluster or in the filesystem. name (Optional[str]): Name to give the blob object, to be reused later on. path (Optional[str]): Path (or path) to the blob object. Specfying a path will force the blob to be saved to the filesystem rather than persist in the cluster's object store. system (Optional[str or Cluster]): File system or cluster name. If providing a file system this must be one of: [``file``, ``github``, ``sftp``, ``ssh``, ``s3``, ``gs``, ``azure``]. We are working to add additional file system support. If providing a cluster, this must be a cluster object or name, and whether the data is saved to the object store or filesystem depends on whether a path is specified. env (Optional[Env or str]): Environment for the blob. If left empty, defaults to base environment. (Default: ``None``) data_config (Optional[Dict]): The data config to pass to the underlying fsspec handler (in the case of saving the the filesystem). load (bool): Whether to try to load the Blob object from RNS. (Default: ``True``) dryrun (bool): Whether to create the Blob if it doesn't exist, or load a Blob object as a dryrun. (Default: ``False``) Returns: Blob: The resulting blob. Example: >>> import runhouse as rh >>> import json >>> >>> data = list(range(50) >>> serialized_data = json.dumps(data) >>> >>> # Local blob with name and no path (saved to Runhouse object store) >>> rh.blob(name="@/my-blob", data=data) >>> >>> # Remote blob with name and no path (saved to cluster's Runhouse object store) >>> rh.blob(name="@/my-blob", data=data, system=my_cluster) >>> >>> # Remote blob with name, filesystem, and no path (saved to filesystem with default path) >>> rh.blob(name="@/my-blob", data=serialized_data, system="s3") >>> >>> # Remote blob with name and path (saved to remote filesystem) >>> rh.blob(name='@/my-blob', data=serialized_data, path='/runhouse-tests/my_blob.pickle', system='s3') >>> >>> # Local blob with path and no system (saved to local filesystem) >>> rh.blob(data=serialized_data, path=str(Path.cwd() / "my_blob.pickle")) >>> # Loading a blob >>> my_local_blob = rh.blob(name="~/my_blob") >>> my_s3_blob = rh.blob(name="@/my_blob") """ if name and load and not any([data is not None, path, system, data_config]): # Try reloading existing blob try: return Blob.from_name(name, dryrun) except ValueError: # This is a rare instance where passing no constructor params is actually valid # (e.g. rh.blob(name=key).write(data)), so if we don't find the name, we still want to # create a new blob. pass system = _get_cluster_from(system or _current_cluster(key="config"), dryrun=dryrun) env = env or _get_env_from(env) if (not system or isinstance(system, Cluster)) and not path and data_config is None: # Blobs must be named, or we don't have a key for the kv store name = name or _generate_default_name(prefix="blob") new_blob = Blob(name=name, dryrun=dryrun).to(system, env) if data is not None: = data return new_blob path = str(path or _generate_default_path(Blob, name, system)) from runhouse.resources.blobs.file import File name = name or _generate_default_name(prefix="file") new_blob = File( name=name, path=path, system=system, env=env, data_config=data_config, dryrun=dryrun, ) if isinstance(system, Cluster): system.put_resource(new_blob) if data is not None: new_blob.write(data) return new_blob