AzureMachineLearningFileSystem Class
Access Azure Machine Learning defined URI as if it were a file system. This exposes a filesystem-like API on top of Azure Machine Learning defined URI
Initialize a new AzureMachineLearningFileSystem object
- Inheritance
-
fsspec.asyn.AsyncFileSystemAzureMachineLearningFileSystem
Constructor
AzureMachineLearningFileSystem(*args, **kwargs)
Parameters
Name | Description |
---|---|
uri
Required
|
Azure Machine Learning defined URI Supports both datastore URIs, data asset URIs, and registry URIs.
Where:
Where:
Note: The segment "providers/Microsoft.MachineLearningServices/" is optional in both URI formats. We support URIs both with and without this segment.
|
uri
Required
|
the uri to initialize AzureMachineLearningFileSystem. |
Remarks
This will enable pandas/dask to load Azure Machine Learning defined URI.
Methods
get |
Copy file(s) to local. |
glob |
globbing result for the uri |
put |
Copy file(s) to local. |
to_absolute_path |
Convert relative path in filesystem root to absolute path |
get
Copy file(s) to local.
get(rpath, lpath, recursive=False, callback=<fsspec.callbacks.NoOpCallback object>, **kwargs)
glob
globbing result for the uri
glob(path=None, **kwargs)
Parameters
Name | Description |
---|---|
path
Required
|
path to glob, it can be long form datastore uri or just relative path in the format of {datastore}/{relative_path} |
Returns
Type | Description |
---|---|
A list of file paths |
put
Copy file(s) to local.
put(lpath, rpath, recursive=False, callback=<fsspec.callbacks.NoOpCallback object>, **kwargs)
to_absolute_path
Convert relative path in filesystem root to absolute path
static to_absolute_path(path: str)
Parameters
Name | Description |
---|---|
path
Required
|
|
Attributes
protocol
protocol: ClassVar[str | tuple[str, ...]] = 'azureml'