This enables mass export of all activities and sequences from LARA.
Before running this script it is recommended to use ssh port forwarding to connect to the LARA db through an ECS host as follows:
ssh -L 127.0.0.1:3800:LARA-DB-HOSTNAME:3306 USERNAME@ECS-HOSTNAME
for example:
ssh -L 127.0.0.1:3800:lara-staging-vpc.cheea3ib6y8u.us-east-1.rds.amazonaws.com:3306 dmartin@ec2-54-172-190-159.compute-1.amazonaws.com
and then create a .env file (optionaly starting with the included .env.sample file) with the following contents:
LARA_URL= ; example: https://authoring.concord.org/
LARA_SESSION= ; the `_lightweight-standalone_session` cookie value (see below)
DB_HOSTNAME= ; example: localhost if using port forwarding or lara-vpc.cheea3ib6y8u.us-east-1.rds.amazonaws.com if direct connect
DB_USERNAME= ; example: master
DB_PASSWORD= ; example: nice-try-haxxors
DB_PORT= ; example: 3800 if using the port forwarding line above or 3306 if directly connecting
WAIT_BETWEEN_REQUESTS= ; example: 1000 to wait 1 second between export requests
The _lightweight-standalone_session cookie value can be copied from Chrome Developer Tools in the Application tab under the Cookies storage menu entry after you login as an admin to the LARA_URL specified in the .env file. Make sure you check the "Show url decoded" checkbox before copying the value. This cookie is needed as export is behind a permisssion check.
This script is split into two steps where each previous step feeds into the next.
The first step is invoked via: npm run generate-csvs which will generate a csv of all the activites and a csv of all the sequences. The csv files will be placed in a subfolder named data/DD-Mon-YYY.
The second step is invoked with npm run export-json which will export all the activies and sequences found in the csv files. The json files will be placed in the same subfolder as the previous step.
Once exported the json files can be uploaded to S3 via the aws CLI. An upload step has not been added to the script as the CLI handles this well. To use the aws CLI first copy over your credentials and then run:
aws s3 cp data/DATE s3://cc-project-resources/lara-exports/production/DATE --recursive
where DATE is a date string in the form of DD-MMM-YYYY created by the export script.
NOTE: you can add --dryrun to the aws cli command to see what it will upload without actually uploading the files.