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Access datastore uri with fsspec

Project description

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

1.1.0 (06-01-2023)

Features Added

  • upload/download performance improvement

1.0.0 (04-07-2023)

Features Added

  • Added upload/download API
  • bugfix(root behavior)

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

Project details


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