azureml-fsspec 0.1.0b3

Access datastore uri with fsspec

Filesystem interface to Azure Machine Learning defined URIs

Getting started

This package can be installed using:

pip install azureml-fsspec

Examples

Accepted uri format is Azure Machcine Learning defined datastore uri: azureml://subscriptions/([^/]+)/resourcegroups/([^/]+)/workspaces/([^/]+)/datastores/([^/]+)/paths/([^/]+)

# load parquet file to pandas
import pandas
df = pandas.read_parquet('azureml://subscriptions/{sub_id}/resourcegroups/{rs_group}/workspaces/{ws}
                          /datastores/workspaceblobstore/paths/myfolder/mydata.parquet')

# load csv file to pandas
import pandas
df = pandas.read_csv('azureml://subscriptions/{sub_id}/resourcegroups/{rs_group}/workspaces/{ws}
                          /datastores/workspaceblobstore/paths/myfolder/mydata.csv')

# load parquet file to dask
import dask.dataframe as dd
df = dd.read_parquet('azureml://subscriptions/{sub_id}/resourcegroups/{rs_group}/workspaces/{ws}
                          /datastores/workspaceblobstore/paths/myfolder/mydata.parquet')

# load csv file to dask
import dask.dataframe as dd
df = dd.read_csv('azureml://subscriptions/{sub_id}/resourcegroups/{rs_group}/workspaces/{ws}
                          /datastores/workspaceblobstore/paths/myfolder/mydata.csv')

Release History

0.1.0b1

Features Added

• Initial public preview release of FileSystem for Azure Machine Learning defined datastore uri

0.1.0b2

Features Added

• Fix release notes

0.1.0b3

Features Added

• Add mode in open API
• Add validation
• Upgrade dataprep to 4.8