Add documentation

backend/.dockerignore

@@ -0,0 +1,138 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/

backend/Dockerfile

@@ -0,0 +1,12 @@
+FROM python:3.10
+
+WORKDIR /usr/src/app
+
+# Install requirements before copying the rest of data to make use of docker's cache layers
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy files from host to workdir in container
+COPY . .
+
+CMD ["python", "src/main.py"]

backend/README.md

@@ -1,32 +1,10 @@
 # Juggl API
 
-## Installation
+This is the new Juggl API created with FastAPI as http framework and SQLModel as ORM.
 
-Minimum Python version: 3.10
+The documentation is split in several files for better structure.
 
-Create virtual environment:
+Table of Contents:
 
-```
-$ python3.10 -m venv/ ./venv/
-```
-
-Activate virtual environment (Linux):
-
-```
-$ source venv/bin/activate
-```
-
-
-Activate virtual environment (Windows):
-
-```
-$ .venv\Scripts\activate
-```
-
-## Guidelines
-
-All routes and should be async for maximum performance
-
-Always specify the `response_model` in the route decorator and use the same type as type hint for the function return
-type. FastAPI is unfortunately not yet smart enough to determine the `response_model` from the return type hint.
-Maybe we should consider making a pull request...
+- [Installation](docs/installation.md)
+- [Guidelines](docs/guidelines.md)

backend/docker-compose.yml

@@ -0,0 +1,7 @@
+version: "3.9"
+services:
+  api:
+    build: .
+    restart: always
+    ports:
+      - "8192:8192"

backend/docs/guidelines.md

@@ -0,0 +1,11 @@
+# Guidelines
+
+Guidelines we want and should follow for Juggl API.
+
+---
+
+- All routes and should be `async` for maximum performance
+
+- All routes should specify a `response_model` in the route decorator if they return anything. The same type should 
+  be used as type hint for the function return type. FastAPI is unfortunately not yet smart enough to determine the 
+  `response_model` from the return type hint. Maybe we should consider making a pull request...

backend/docs/installation.md

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+# 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
+```

backend/src/main.py

@@ -1,3 +1,10 @@
+
+# Modify python's import path to include the current directory so that the imports get resolved correctly
+import os
+import sys
+sys.path.extend([os.getcwd()])
+
+
 import argparse
 
 import uvicorn
@@ -69,13 +76,15 @@ def parse_args() -> argparse.Namespace:
 def start_dev_server(port: int):
     """Starts a development server with auto-reloading on port."""
 
-    uvicorn.run("main:app", reload=True, port=port)
+    # Host="0.0.0.0" makes the application accessible from other IPs. Necessary when running inside docker
+    uvicorn.run("main:app", reload=True, port=port, host="0.0.0.0")
 
 
 def start_production_server(port: int):
     """Starts a production, i.e. performance-optimized server on port."""
 
-    uvicorn.run("main:app", port=port)
+    # Host="0.0.0.0" makes the application accessible from other IPs. Necessary when running inside docker
+    uvicorn.run("main:app", port=port, host="0.0.0.0")
 
 
 if __name__ == "__main__":