skillbox/README.md

# skillBox

Sources

* [Django](https://docs.djangoproject.com/en/2.0/)
* [Wagtail](http://docs.wagtail.io/)
* [Graphene](https://github.com/graphql-python/graphene-django)
* [Vue-Apollo](https://github.com/Akryum/vue-apollo)
* [Vuetifyjs](https://vuetifyjs.com/en/getting-started/quick-start)

## Development

### Server

* [Install](https://docs.pipenv.org/#install-pipenv-today) pipenv
* Create virtualenv in install dependencies `pipenv --python 3.6 install --dev`
* Create PostgreSQL database & user, needs to be version 10, not 11
* [Install](https://devcenter.heroku.com/articles/heroku-cli#download-and-install) Heroku cli, run `heroku login` and `heroku git:remote -a skillbox-hep`
* Create .env in `server` file with `SECRET_KEY` and `DATABASE_URL` (or copy the existing .env.example file)
* Migrate databases: `pipenv run python manage.py migrate`
* Create super user: `pipenv run python manage.py createsuperuser`
* Run: `pipenv run python manage.py runserver`
* Dummy data: `pipenv run python manage.py dummy_data` (restart the development server afterwards) Recreates the db with test data and new superuser: test/test

#### Dockerize DB
* To dockerize the DB, after installing docker, run the following command:
```
docker run --name skillboxdb -d -p 5432:5432 -e POSTGRES_PASSWORD=skillbox -e POSTGRES_USER=skillbox -e POSTGRES_DB=skillbox postgres:10-alpine
```
* After a reboot, start the container again with `docker start skillboxdb`

#### Notes

* `DEBUG=True` enables the debug middleware http://docs.graphene-python.org/projects/django/en/latest/debug/

#### Commands

##### Create a new teacher demo account on prod
```
heroku login # if not already logged in
heroku run --remote heroku python server/manage.py create_teacher <firstname> <lastname> <email>
```
Tip: create and alias in ~/.bash_aliases:
```
alias create_teacher="heroku run --remote heroku python server/manage.py create_teacher"
```
Then you can just run in terminal:
```
create_teacher <firstname> <lastname> <email>
```

##### Import a CSV file

To import a CSV file locally, run:
```
python manage.py <csv-file>
```

To import a CSV file on prod, first upload the CSV file to some public S3 bucket (or make it publicly available some other way)

```
heroku login # if not already logged in
heroku run --remote heroku python server/manage.py import_users --s3 <csv-url>
```


### Client

``` bash
# install dependencies
npm install --prefix client

# serve with hot reload at localhost:3000
npm run dev --prefix client

# build
npm run build --prefix client

# build for production with minification
export NODE_ENV=production && npm install --prefix client && npm run build --prefix client
```

After running `npm run dev` login to the Django admin view on the same domain as the webpack dev server is running.
Example: The client runs on localhost:8080 and Django on localhost:8000. 
This way you will have a session and a csrf cookie set and the apollo client will 
be able to make requests.

Production Build

## Urls

(trailing slashes are required)

* Admin interface: http://127.0.0.1:8000/guru/
* Cms interface: http://127.0.0.1:8000/cms/
* GraphQL Interface: http://localhost:8000/api/graphiql/

## Heroku

`heroku run python server/manage.py <command> --app <appname>`

### Rollback

After doing a rollback under https://data.heroku.com/

`heroku pg:info --app=<appname>`

Change DATABASE URL (e.g after a rollback)

`heroku pg:promote HEROKU_POSTGRESQL_PINK`

### Backup

`heroku pg:backups:capture --app <appname>`

`heroku pg:backups:url b001 --app <appname>`

## AWS

1. Create user with API Access and add `access key id` and `access key` to `.env` and set `USE_AWS=True`
2. Create S3 Bucket in location EU Ireland.

Change bucket `Permissions` / `Bucket Policy`

```
{
    "Version": "2008-10-17",
    "Statement": [
        {
            "Sid": "PublicReadForGetBucketObjects",
            "Effect": "Allow",
            "Principal": {
                "AWS": "*"
            },
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::<bucket-name>/*"
        },
        {
            "Sid": "",
            "Effect": "Allow",
            "Principal": {
                "AWS": "<user arn>"
            },
            "Action": "s3:*",
            "Resource": [
                "arn:aws:s3:::<bucket-name>/*",
                "arn:aws:s3:::<bucket-name>"
            ]
        }
    ]
}

```

## Release

### Pushing to Production

Whenever you want to do a release, just merge develop into master and push to origin.
The current master will always be deployed in the evening, if there are new commits that are not yet on Heroku.

### Tagging

Whenever you do a new release, please tag the current commit after merging with the current date:

    git tag -a release/v2019-09-10

`git tag -a` creates an annotated tag, which must have a release message (like a commit message). For now, just repeat the current date, like:

    Release to production on 2019-09-10

You can and should then push the tag to the repo

    git push origin release/v2019-09-10

You can later see the metadata of the tag with

    git show release/v2019-09-10


## Testing

## Mocking GraphQL calls

We use [cypress-graphql-mock](https://github.com/tgriesser/cypress-graphql-mock) for mocking GraphQL calls in Cypress tests.

For an example, please see `spellcheck.spec.js`.

There is a schema.json in the fixtures folder. For now it has been generated once, and if there is a significant update to the schema on the server, it has to be regenerated.

To generate a new schema, use the management command

```
python manage.py graphql_schema --schema api.schema.schema --out schema.json --indent 4
```

Then, remove the `data` property from the generated `schema.json`, so the `__schema` property is on the top level.
Also remove the two objects with `"name": "__debug"` from the JSON file.