juggl/backend/docs/installation.md

# Installation

First, install Python in version ≥ 3.9

There are several ways to run Juggl api.

- [Directly via virtual environment](#virtual-environment)
- [In an automatically managed docker container](#docker-compose)
- [In a manually created docker container](#manual-container)

## Virtual Environment

Go to the backend directory.

```bash
$ cd backend
```

Create virtual environment:

```bash
$ python -m venv/ ./venv/
```

Activate virtual environment (Linux):

```bash
$ source venv/bin/activate
```

Activate virtual environment (Windows):

```bash
$ .venv\Scripts\activate
```

Run `src/main.py`:

> Note: When executing, you must be in the `backend/` directory! Executing the program from another directory will 
> fail, because Python then can not resolve imports correctly. Why? Don't know.

```bash
$ python src/main.py
```

## Docker

Install [Docker](https://docs.docker.com/get-docker/) and [Docker-Compose](https://docs.docker.com/compose/install/).

### Docker-compose

Automatically set up all dependencies, export ports and start container(s) with docker-compose.

Build composed container setup:
```bash
$ docker-compose build
```

Start and block terminal with output
```bash
$ docker-compose up
```

Start in background (as deamon)
```bash
$ docker-compose up -d
```

Stop all containers
```bash
$ docker-compose down
```

### Manual container

Build and execute the docker container manually.

#### Build container

```bash
docker build -t juggl-api .
```

#### Start container

Execute the previously bild container.

Don't forget to export the port from the container to your host system with `-p HOST_PORT:CONTAINER_PORT`.

```bash
docker run -p 8192:8192 juggl-api
```