# Updated introduction to S3, Boto, and NOAA Nexrad
Adapted from and thank you to Scott Collis, ARM precipitation radar instrument translator (see <a href="https://github.com/openradar/AMS_radar_in_the_cloud/blob/master/notebooks/introduction%20to%20S3%2C%20Boto%20and%20Nexrad%20on%20S3%20with%20a%20hurricane%20chaser.ipynb">here</a>) and the original tutorial by Valliappa Lakshmanan, formerly at Climate Corp now at Google.  This version is updated to use AWS SageMaker Studio Lab and Python 3.8.

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## AWS SageMaker Studio Lab
You can sign up for SageMaker Studio Lab and use it for free without an AWS account. You can run for 4 hours with GPU or 12 hours with CPU and then logout and log back in for another session. Your data and notebooks are persisted. After clicking the launch button below, choose "download whole repo" and then "build conda environment" when prompted.

When it's done installing and configuring the conda environment, open the "Nexrad_Demo.ipynb" notebook.  Click-Enter to run each row and wait a moment to see the results of each line before proceeding to the next. The line marker should change to a number when it's successfully run that line, ie "[5]" means that it has run line 5.

<a href="https://studiolab.sagemaker.aws/import/github/https://github.com/aws-samples/aws-nexrad-smsl-notebook/blob/main/Nexrad_Demo.ipynb" rel="nofollow"><img src="https://camo.githubusercontent.com/8c5378ff3bf6f71a57442940234293bd63c7ed2418d64f74f2bda3dc6f2904ed/68747470733a2f2f73747564696f6c61622e736167656d616b65722e6177732f73747564696f6c61622e737667" alt="Open In SageMaker Studio Lab" data-canonical-src="https://studiolab.sagemaker.aws/studiolab.svg" style="max-width: 100%;"></a></p>

## Security

See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.

## License

This library is licensed under the MIT-0 License. See the LICENSE file.