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- Integration with NeptuneML feature set in AWS Neptune
- Add helper library to perform Sigv4 signing for `%neptune_ml export ...`, we will move our other signing at a later date.
- Swap how credentials are obtained for `ROLE` iam credentials provider such that it uses a botocore session now instead of calling the ec2 metadata service. This should make the module more usable outside of Sagemaker.
New Line magics:
- `%neptune_ml export status`
- `%neptune_ml dataprocessing start`
- `%neptune_ml dataprocessing status`
- `%neptune_ml training start`
- `%neptune_ml training status`
- `%neptune_ml endpoint create`
- `%neptune_ml endpoint status`
New Cell magics:
- `%%neptune_ml export start`
- `%%neptune_ml dataprocessing start`
- `%%neptune_ml training start`
- `%%neptune_ml endpoint create`
NOTE: If a cell magic is used, its line inputs for specifying parts of the command will be ignore such as `--job-id` as a line-param.
Inject variable as cell input:
Currently this will only work for our new cell magic commands details above. You can now specify a variable to use as the cell input received by our `neptune_ml` magics using the syntax ${var_name}. For example...
```
# in one notebook cell:
foo = {'foo', 'bar'}
# in another notebook cell:
%%neptune_ml export start
${foo}
```
NOTE: The above will only work if it is the sole content of the cell body. You cannot inline multiple variables at this time.
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