Access datastore uri with fsspec
This package can be installed using:
pip install azureml-fsspec
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')