skillbox/README.md

# mySkillbox

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)

## Development

### Server

- [Install](https://docs.pipenv.org/#install-pipenv-today) pipenv
- Create virtualenv in install dependencies `pipenv --python 3.8 install --dev`
- Create PostgreSQL database & user
- 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
-
- [Install](https://devcenter.heroku.com/articles/heroku-cli#download-and-install) Heroku cli, run `heroku login`
  and `heroku git:remote -a skillbox-hep`

#### 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
```

- 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

## Docker

Update the new docker image

- Edit `Dockerfile`
- `docker build --memory=1g --memory-swap=1g -t iterativ/skillbox-test:<tag> -f Dockerfile .`
- `docker push iterativ/skillbox-test:<tag>`
- Update the `bitbucket-pipelines.yml` to use the new tag

## 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

See [Docs](./docs/heroku-backup.md)

## 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

#### Update:

Please use one of the provided scripts in `bin`

`./bin/tag-release.sh`

or

`./bin/tag-hotfix.sh`

and follow the instructions.

Note: Please make sure you're one the master branch first.

#### Manual Way (deprecated)

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

    git tag -a 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 v2019-09-10

You can later see the metadata of the tag with

    git show release/v2019-09-10

or

    git tag -ln

NB: If there are two releases on the same day, use the pattern `v2020-03-01.x` eg. `v2020-03-01.1` for the subsequent
releases

#### Hotfixes

Please use the pattern `v2020-03-01.hotfix` for hotfix releases

## 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 export_schema_for_cypress
```

## GraphQL

### Generate GraphQL SDL Document


for linux:
```bash
cd server
./graphql-schema.sh && npm run codegen --../prefix client
```

For macOS: (there is a problem with the sed command) 

```bash
cd server
./macos-graphql-schema.sh && npm run codegen --../prefix client

```




## Backup to S3

From https://pawelurbanek.com/heroku-postgresql-s3-backup

### Initial setup per Heroku Dyno

```
heroku buildpacks:add heroku-community/awscli
heroku config:set BACKUP_AWS_ACCESS_KEY_ID=[Your AWS Access Key ID]
heroku config:set BACKUP_AWS_SECRET_ACCESS_KEY=[Your AWS Secret Access Key]
heroku config:set BACKUP_S3_BUCKET_NAME=[Your S3 bucket name]
```

```
heroku authorizations:create => TOKEN
heroku config:set HEROKU_API_KEY=[TOKEN]
heroku buildpacks:add heroku-community/cli
```

```
heroku config:set APP_NAME=app-name
```

```
heroku config:set PG_BACKUP_KEY=$(openssl rand -base64 32)
```

```
heroku addons:create scheduler:standard
heroku addons:open scheduler
```

Then schedule the backup for daily at 3:00 UTC, for example

Command:

```
./bin/pg-backup-to-s3
```

# Note on component

Our own components remain in kebap-case, imported components from third party libraries will be used in PascalCase.
E.g. `<password-change-form/>` vs. `<ValidationProvider/>`