# VBV Lernwelt

Project setup is based
on [cookiecutter-django](https://github.com/cookiecutter/cookiecutter-django) project
template.

## Run for development

```bash
# run vue vite dev server
cd client && npm run dev

# reset db and run django dev server
./prepare_server.sh

# if you only want to create some specific courses to speed up the script,
# you can use the '--courses' parameter
# see consts.py for available course ids
# ./prepare_server.sh --courses -3 -5
```

## Installation

See `.tool-versions` file for used django and node version

You have to set up at least the following environment variables:

```bash
export IT_APP_ENVIRONMENT=local
```

See `.env_secrets/local_daniel.env` for more possible environment variables.
Especially set correct values for `POSTGRES_*` and `DATABASE_URL`

Install git-lfs

```bash
brew install git-lfs
git lfs install
```

### Server part

Install python dependencies:

```bash
pip install -r server/requirements/requirements-dev.txt
```

The "prepare_server.sh" script will create the database according to `POSTGRES_*`
environment variables.
It will also setup the tables for django and run the django development server.

```bash
# will run `migrate` and `runserver` etc...
./prepare_server.sh

# or async server
# uvicorn config.asgi:application --host 0.0.0.0 --reload
```

### Client part

```bash
cd client

npm install

# run dev server
npm run dev
```

### General part

Cypress is installed for client and server, so there is this package.json on the project
root directory

```bash
# in project root directory
npm install
```

### Git hooks

```bash
# install pre-push git hook
# add this line to the existing script in .git/hooks/pre-push
./git-pre-push.sh
```

### Actions on Save

You can enable some useful "Actions on Save" in your JetBrains IDE:

Preferences -> Tools -> Actions on Save

* Reformat Code
* Optimize Imports
* Run eslint --fix
* Run prettier

## Translations

We use the [i18next](https://www.i18next.com/) library for translations.
Please add `a.` prefix for new translation keys in the code:

```
<h4>{{ $t("a.Demo mit Daniel") }}</h4>
```

With [i18next-parser](https://github.com/i18next/i18next-parser) we can extraxt the
new translation keys directly from the code to the language files in `./client/src/locales`.

```bash
# extract new translation keys
# in `./client` directory
npm run i18next:parse
```

The new keys will end up in the `./client/src/locales/de/translation.json` file.

You can translate the keys directly in the files.

#### Bonus: Translate with BabelEdit desktop app

The [BabelEdit](https://www.codeandweb.com/babeledit) desktop can help directly with
the translation.

![](./docs/assets/babeledit01.png)

Here are the settings that I use in BabelEdit:
![](./docs/assets/babeledit02.png)

Run the `npm run i18next:sort` to get a "clean" sorted file after edit with BabelEdit.


### "_many" plural form in French and Italian

See https://github.com/i18next/i18next/issues/1691#issuecomment-968063348
for an explanation why this plural form is needed in French and Italian.
But not in German and English.

## Deployment and Environments

### Prod Environment on Azure

Bitbucket Pipelines name: prod-azure
https://my.vbv-afa.ch/

Deployment step on Bitbucket Pipelines will build the Docker container for Azure.
It seems that right now, you have to make a manual step on Azure to use this new
Docker container and update it on Azure.
Please ask Lorenz for more information.

#### Prod Monitoring on New Relic

See docs/new-relic.md

### CapRover vbv-develop

Bitbucket Pipelines name: develop
https://vbv-develop.control.iterativ.ch/

Deployment happens automatically on every push to develop branch.

### CapRover vbv-master

Bitbucket Pipelines name: master
https://vbv-master.control.iterativ.ch/
Deployment happens automatically on every push to master branch.

### CapRover myvbv-stage

Bitbucket Pipelines name: stage
https://myvbv-stage.control.iterativ.ch/
https://myvbv-stage.iterativ.ch/

Deployment happens manually via Bitbucket Pipelines

### CapRover myvbv (old prod)

Bitbucket Pipelines name: myvbv
https://myvbv.control.iterativ.ch/
https://myvbv.iterativ.ch/

Deployment happens manually via Bitbucket Pipelines


### CapRover feature branch deployment

You can deploy every feature branch to CapRover directly from Bitbucket Pipelines
with a manual step.

When you run caprover_deploy.sh without arguments, it will deploy the current branch

```
./caprover_deploy.sh
```

### Cleanup caprover feature branch deployments

```bash
# by default it will delete all vbv-feature-* apps
python caprover_cleanup.py

# or specify a specific app regex and delete without confirmation
python caprover_cleanup.py --automated -a 'vbv-bugfix*'
```

## IntelliJ Configuration

* In the .idea/vbv_lernwelt.iml file change the module type to "PYTHON_MODULE".
* Add django facet in "Project Structure".
* Run configuration with "Python -> server.py" to have async debugging support.

### Optional

#### Install the EnvFile Plugin

![](docs/envfile_plugin_settings.png)

#### Install the tailwind css Plugin from Jetbrains

## currents.dev

This project uses [currents.dev](https://currents.dev) to run the Cypress tests
concurrently.  
The following steps were taken to set it up:

- Create a new project on currents.dev
- Add the generated `projectId` to the cypress configuration file
- Install `@currents/cli` as a dev dependency
- Add the following script to the `package.json` file:
  ```json
  "cypress:ci": "currents run --parallel --record --key $CURRENTS_KEY",
  ```
- Create a new Bitbucket pipelines job that exports the `CURRENTS_KEY` and runs
  the `cypress:ci` script
- Refactor the pipeline steps so that the dependencies are installed first and then the
  other steps are run in
  parallel.  
  You can then run multiple instances of the previously created job in parallel.  
  See `.bitbucket-pipelines.yml` for an example.

> 💡 The number of cypress worker jobs depends on the number of cypress tests.
> Too many workers for too few tests will result in a lot of idle workers.

## Frontend folder structure

There are some rules when it comes to the folder structure of the frontend.

- Every page should have its own folder in the `pages` folder.
- A page component name must have the `Page` suffix. E.g. `MyPage.vue`.
- A page is defined by being a routing target.
- The components solely being used in a page should be in the same folder as the page.

```
📦 client
└─ pages
   ├─ AbcPage.vue
   ├─ AbcButton.vue
   └─ AbcListTile.vue
```

## GraphQL

```bash
python manage.py graphql_schema 
```

On the client side you have to run the following command to update the
generated code

```bash
npm run codegen

# `npm run dev` includes `npm run codegen` as step...
npm run dev
```

If you run `npm run dev`, the codegen command will be run automatically in watch mode.

For the `ObjectTypes` on the server, please use the postfix `ObjectType` for types,
like `LearningContentAttendanceCourseObjectType`.

This will prevent problems with the hand written types on the client side,
when `npm run codegen` will create the types automatically.

When you change something on the server side run the following command to update the
graphql schema.

### Open Questions

- The `id` field has to be a string?
- What about the generated types from `codegen`? Hand written types seem to be better.
- The functions in `cacheExchange` should be nearer the concrete implementation...

## Test users
### Local development
If `prepare_server.sh` was run, the following users are available (password: `test` and found in `create_default_users.py`):

- Trainer
  - test-trainer1@example.com
  - test-trainer2@example.com 
- Teilnehmer
  - test-student1@example.com 
  - test-student2@example.com 
  - test-student3@example.com 
- Regionenleiter
  - test-supervisor1@example.com 
- Berufsbildner
  - test-berufsbildner1@example.com
- Ausbildungsverantwortlicher
  - test-ausbildungsverantwortlicher1@example.com

### Load prod data for local testing

1. Checkout the [vbv-devops](https://bitbucket.org/iterativ/iterativ-devops/src/master/) repository
2. Change into the `backups` directory
3. Run `python3 check_vbv_backup.py`. This downloads the latest backup from S3 and restores it to the `vbv-lernwelt` database.
4. Reset all user passwords. Open `shell_plus` in the `server` directory of the `vbv_lernwelt` repository and run

   ```python
    for csu in CourseSessionUser.objects.all():
        csu.user.set_password("test")
   ```
### Test users on production
On production there are CourseSessions in the VV and üK courses with test users. The data can be rested via the admin
interface ("Iterativ Testdurchführungen zurücksetzen"). All users use local login and can be found in 1password.