A controller to manage commerce workflows and services
Commerce Coordinator is intended to be a highly decoupled, modular, asynchronous platform for handling a wide variety of use cases and workflows. In order to allow for flexibility in configuration and extensibility the Coordinator needs to have a loosely coupled internal architecture that allows for pluggable components to work with the same events.
Individual Django apps will act as plugins to implement specific functionality, for example a webhook for a payment service provider to call when a purchase is successful, that plugin can then signal one that performs the fulfillment in the LMS.
The core of the Coordinator will allow commerce workflows to be tailored by combining plugins and routing signals, and will eventually include tools for validating configurations and tracing signal flows.
For more details, please see the architectural decision docs
(TODO: Set up documentation)
Note: this setup process is temporary; we will be working on a Tutor plugin
# Clone the repository
git clone [email protected]:edx/commerce-coordinator.git
cd commerce-coordinator
# if you wish to use a mysql daemon, install mysql, otherwise, start along with redis
# brew install mysql
# Set up a virtualenv and activate it
python3 -m venv .venv
source .venv/bin/activate
# Install/update the dev requirements (run inside the venv)
make requirements
# If you get 'Unsupported architecture' errors above, instead use: CFLAGS='-D__x86_64__' make requirements
# Expose the redis port for devstack (needed until commerce coordinator is part of devstack)
# (redis is the backend that Celery is using for persisting the message queue)
# In your local Devstack directory, edit docker-compose.yml: go to the redis service line and add a ports section
# ports:
# - "6379:6379"
# Start redis/mysql in devstack from your local devstack directory
make dev.up.redis
# If youd prefer to reuse mysql from devstack, start it now.
# make dev.up.mysql57
# Start ecommerce and lms in devstack from your local devstack directory
make dev.up.ecommerce+lms
# Return to the commerce-coordinator repo directory and provision credentials:
bash local-provision-commerce-coordinator.sh
# compile static assets
python manage.py collectstatic
# run commerce-coordinator locally (run inside the venv)
python manage.py runserver localhost:8140 --settings=commerce_coordinator.settings.local
# You should see output ending with "Quit the server with CONTROL-C"
# In your browser, hit the URL: http://localhost:8140/demo_lms/test/
# You should see JSON output indicating that two receivers were called, one successful, and one with exception/traceback information.
# In the shell where the server is running you should see log output indicating that two test receivers were called with the sender argument "Something".
- Update the following inside `commerce_coordinator/settings/base.py` file:
- COMMERCETOOLS_CONFIG, The values can be found at: https://twou.frontastic.io/configuraaton?environment=development&project=checkout&locale=en_US
- COMMERCETOOLS_FRONTEND_URL = 'http://localhost:3000/en/add-to-cart/'
- Update the following waffle flags:
- Go to http://localhost:8140/admin/waffle/flag/ and add these flags
- transition_to_commercetools.redirect_to_commercetools_checkout flag with the Everyone attribute set to Yes.
- Go to http://localhost:18000/admin/waffle/flag/ and add these flags
- commerce.transition_to_coordinator.checkout flag with the Everyone attribute set to Yes
- commerce.transition_to_coordinator.refunds flag with the Everyone attribute set to Yes
- Update the following inside your 'edx-platform/lms/envs/private.py' file:
- COMMERCE_COORDINATOR_REFUND_SOURCE_SYSTEMS = ('commercetools',)
- COMMERCE_COORDINATOR_URL_ROOT = 'http://localhost:8140'
- For refunds flow, update this value and revert back after running refunds flow
- COMMERCE_COORDINATOR_URL_ROOT = 'http://host.docker.internal:8140'
# Grab the latest code
git checkout main
git pull
# Activate the virtualenv
source .venv/bin/activate
# Install/update the dev requirements (run inside the venv)
make requirements
# If you get 'Unsupported architecture' errors above, instead use: CFLAGS='-D__x86_64__' make requirements
# Make a new branch for your changes
git checkout -b <your_github_username>/<short_description>
# Start redis and the webserver as in previous section
# Run the tests and quality checks (before and after your changes)
make validate
# Commit your changes
git commit …
git push
# Open a PR and ask for review.
# Start redis in devstack from your local devstack directory
make dev.up.redis
# Update the CELERY_BROKER_URL flag
Update CELERY_BROKER_URL to "redis://:password@localhost:6379/0" inside `commerce_coordinator/settings/local.py`
# Start celery from the commerce-coordinator venv; this management command will auto-reload celery when python files are changed
python manage.py celery
# More test URLs you can hit in the browser or pipe through jq (https://stedolan.github.io/jq/) to make the output more readable:
⫸ curl -s "http://localhost:8140/demo_lms/test_celery_signal/" | jq '.'
{
"<function test_celery_signal_task at 0x10e17a9d0>": ""
}
⫸ curl -s "http://localhost:8140/demo_lms/demo_purchase_complete/" | jq '.'
{
"<function demo_purchase_complete_order_history at 0x10e18a430>": "",
"<function demo_purchase_complete_send_confirmation_email at 0x10e18a5e0>": "",
"<function demo_purchase_complete_enroll_in_course at 0x10e18a670>": ""
}
As of the time of this writing, you must have run make dev.up.ecommerce+lms+redis in edX's devstack as a prerequisite to this one.
Execute make dev.provision_docker
This will attempt to connect to LMS and create the required superusers, please ensure you have the edX devstack setup first.
After you can manage the stack by calling make dev.up, make dev.down (delete) or make dev.stop.
The code in this repository is licensed under the AGPL 3.0 unless otherwise noted.
Please see LICENSE.txt for details.
So far, this is very preliminary work proving out our ability to confirm and control Django signal / receiver mappings using the settings file. It is not yet a fully robust implementation, but is just a guidepost showing that our intended implementation can work.
Note: We expect that the system will be easier to reason about if signals are only confined to the primary IDA; other environments (e.g. Celery workers) could call API endpoints to trigger workflows if necessary.
Contributions are very welcome.
Please read How To Contribute for details. Even though they were written with edx-platform
in mind, the guidelines should be followed for all Open edX projects.
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