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Getting Started With SCEDC AWS Public Dataset
This page describes some quick examples in python to start using the SCEDC dataset.
import boto3, botocore
BUCKET_NAME = 'scedc-pds'
except botocore.exceptions.ClientError as e:
if e.response['Error']['Code'] == "404":
print("The object does not exist.")
This example shows how to run a Docker image with ObsPy and Jupyter Notebook. You can then run the python snippet and start using classes from the Obspy framework.
run from os prompt:
~ $: docker pull crleblanc/obspy-notebook
~ $: docker run -e AWS_ACCESS_KEY_ID= -e AWS_SECRET_ACCESS_KEY= -p 8888:8888 crleblanc/obspy-notebook:latest
~ $: docker exec pip install boto3
Using an Amazon Machine Image (AMI)There is a public AMI image called scedc-demo that has a Linux OS, python, boto3 and botocore installed.
- from your AWS management console, choose "EC2"
- Under "Instances" choose to launch an instance. Select existing AMI named "scedc-demo" (under Community AMIs)
- SCEDC Cloud Scripts Scripts to download continuous waveforms, event based waveforms, and phases from the AWS public dataset.
- Cactus to Clouds: Processing The SCEDC Open Data Set on AWS A conference paper (2019 SCEC Annual Meeting) by Tim Clements and Marine Denolle at Harvard University detailing their work using the SCEDC dataset
- Julia API for downloading data from the SCEDC Open Dataset a Julia API for the SCEDC dataset by Tim Clements
- Boto 3 Documentation
- AWS CLI User Guide AWS Command Line Interface. An open source tool for working with AWS via command line.
- AWS Getting Started Resource Center Starter page for learning about what types of AWS resources are available.