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Running the Möbius MOOC Generator

Important note:

WARNING: any existing contents in the output folder (i.e. in this case ./out/MOOC1) will be deleted.

WARNING: When you upload the .tar.gz file to Edx, any existing course contents in edx will be deleted.

Make sure to save backups!

Dependencies

This Python3 script requires three python modules. These can be installed with pip as follows:

  • pip install markdown
  • pip install lxml
  • pip install boto3

Markdown is processes using the python markdown module.

The following extensions are used:

extensions = ['extra', 'sane_lists']

Set AWS Credentials for S3 Upload

The .mob files need to be uploaded to an S3 bucket. In order for this to work, you need to specify some settings.

  • The settings for the s3 bucket are specified in the __SETTINGS__.py file in the MOOC root input folder.
  • The auth settings for accessing your AWS account are specified in the file __AWS__.py, in the aws_cred folder.

For the auth settings, got to the folder aws_cred, and you will find a file called __AWS__.template.py. Rename this file to __AWS__.py and add your ID and secret key.

Execution

There are two Python scripts:

  • edx_generator.py: Generates all the MOOC files, including the .tar.gz file that can be uploaded to directly to Edx.
  • mob_uploader.py: Uploads .mob files to your AWS s3 bucket.

Execute the generator:

python ./edx_generator.py "C:/xxxx/mooc1-procedural-modelling" "C:/Data/xxxx/mooc1"

Execute the uploader:

python ./mob_uploader.py "C:/xxxx/mooc1-procedural-modelling"

The __SETTINGS__.py file in the MOOC root input folder specifies a set of global settings that you can set for your context.

WARNING: any existing contents in the output folder (i.e. in this case ./out/MOOC1) will be deleted.

Upload the .tar.gz File

After running the edx generator (assuming no errors), a tar.gz file will be generated. This file can be uploaded to your MOOC.

WARNING: When you upload the .tar.gz file to Edx, any existing course contents in edx will be deleted.