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fe3422100c
## Changes
### Better logging
Switched from `print` statements to `logging` for a cleaner and more informative output - timestamps and log level are shown. The logging is now a bit more verbose, but it will help users to better understand what the script is doing.
### Add support for ES authentication using username/password or api key
Instead of being limited to passing credentials in the URL, there are now 2 additional methods:
- username/password using `--es-username` and `--es-password`
- API key using `--es-api-key`
Credentials can also be specified as environment variables with `ES_USERNAME`/`ES_PASSWORD` or `ES_API_KEY`
### Graceful handling of missing PyTorch requirements
In order to use the `eland_import_hub_model` script, PyTorch extras are required to be installed. If the user does not have the required packages installed, a helpful message is logged with a hint to install `eland[pytorch]` with `pip`.
### Graceful handling of already existing trained model
If a trained model with the same ID as the one we're trying to import already exists, and `--clear-previous` was not specified, we now log a clearer message about why the script can't proceed along with a hint to use the `--clear-previous` flag.
Prior to this change, we were letting the API exception seep through and the user was faced with a stack trace.
### `tqdm` added to main dependencies
If the user doesn't have `eland[pytorch]` extras installed, the first module to be reported as missing is `tqdm`. Since this module is [used in eland codebase](8294224e34/eland/ml/pytorch/_pytorch_model.py (L24)) directly, it makes sense to me to have it as part of the main set of requirements.
### Nit: Set tqdm unit to `parts` in `_pytorch_model.put_model`
The default unit is `it`, but `parts` better describes what the progress bar is tracking - uploading trained model definition parts.