How can I read a local file from an R or Python script in Azure Machine Learning Studio?

Question

I need to read a csv file, which is saved in my local computer, from code within an "Execute R/Python Script" in an experiment of Azure Machine Learning Studio. I don't have to upload the data as usually, ie from Datasets -> New -> Load from local file or with an Import Data module. I must do it with code. In principle this is not possible, neither from an experiment nor from a notebook, and in fact I always got error. But I'm confused because the documentation about Execute Python Script module says (among other things):

Limitations

The Execute Python Script currently has the following limitations:

Sandboxed execution. The Python runtime is currently sandboxed and, as a result, does not allow access to the network or to the local file system in a persistent manner. All files saved locally are isolated and deleted once the module finishes. The Python code cannot access most directories on the machine it runs on, the exception being the current directory and its subdirectories.

According to the highlighted text, it should be possible to access and load a file from current directory, using for instance the pandas function read_csv. But actually no. There is some trick to accomplish this?

Thanks.

Answer 1

You need to remember that Azure ML Studio is an online tool, and it's not running any code on your local machine.

All the work is being done in the cloud, including running the Execute Python Script, and this is what the text you've highlighted refers to: the directories and subdirectories of the cloud machine running your machine learning experiment, and not your own, local, computer.