Oracle Machine Learning for Python Known Issues

Learn about the issues you may encounter when using Oracle Machine Learning for Python and how to work around them.

Topics:

Running oml.dir() in Oracle Machine Learning notebooks returns an empty list.

Running the oml.dir() function in a notebook should return the oml.* objects in the current workspace. However, at present, running oml.dir returns an empty list: 

%python
import oml
...
oml.dir()
[]

Workaround

To work around this problem, use dir() and check if the objects belong to the oml module. For example, use dir() to return the objects. 

%python
dir()
['__builtins__', '__zeppelin__', 'datasets', 'linear_model', 'oml',
    'inv_objects', 'inv_wine', 'inv_wine_columns', 'pd', 'wine', 'x', 'y',  'z']

Then use <obj>.__class__.__module__ to return the module name for an object <obj>; for example: 

%python
inv_wine.__class__.__module__
'oml.core.frame'

If the returned string starts with oml., the object belongs to the oml module.

If you have many objects to check, you can iterate through the objects; for example:

%python
[t for t in dir() if eval(t).__class__.__module__[0:4] == 'oml.']
['inv_wine']

See oml.dir() and dir() in Oracle Machine Learning for Python API Reference and see Get Started with Notebooks for Data Analysis and Data Visualization in Using Oracle Machine Learning on Autonomous Database.

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