Migrate from Flask to FastAPI (#163)

* Migrate from Flask to FastAPI

 * FastAPI migration:
    - Use pydantic model classes as input parameters to the
      data/calculation classes.
    - Interface field names changed to constructor parameter names (for
      simplicity only during transition, should be updated in a followup
      PR).
    - Add basic interface requirements (e.g. some values > 0, etc.).
 * Update tests for new data format.
 * Python requirement down to 3.9 (TypeGuard no longer needed)
 * Makefile: Add helpful targets (e.g. development server with reload)

* Move API doc from README to pydantic model classes (swagger)

 * Link to swagger.io with own openapi.yml.
 * Commit openapi.json and check with pytest for changes so the
   documentation is always up-to-date.

* Streamline docker

* FastAPI: Run startup action on dev server

 * Fix config for /strompreis, endpoint still broken however.

* test_openapi: Compare against docs/.../openapi.json

* Move fastapi to server/ submodule

 * See #187 for new repository structure.

tests/test_class_optimize.py

@@ -5,7 +5,11 @@ from unittest.mock import patch
 
 import pytest
 
-from akkudoktoreos.class_optimize import optimization_problem
+from akkudoktoreos.class_optimize import (
+    OptimizationParameters,
+    OptimizeResponse,
+    optimization_problem,
+)
 from akkudoktoreos.config import AppConfig
 
 DIR_TESTDATA = Path(__file__).parent / "testdata"
@@ -46,7 +50,7 @@ def test_optimize(
     # Load input and output data
     file = DIR_TESTDATA / fn_in
     with file.open("r") as f_in:
-        input_data = json.load(f_in)
+        input_data = OptimizationParameters(**json.load(f_in))
 
     file = DIR_TESTDATA / fn_out
     with file.open("r") as f_out:
@@ -59,7 +63,7 @@ def test_optimize(
         pytest.skip()
 
     # Call the optimization function
-    ergebnis = opt_class.optimierung_ems(parameter=input_data, start_hour=start_hour, ngen=ngen)
+    ergebnis = opt_class.optimierung_ems(parameters=input_data, start_hour=start_hour, ngen=ngen)
     # with open(f"new_{fn_out}", "w") as f_out:
     #     from akkudoktoreos.class_numpy_encoder import NumpyEncoder
     #     json_data_str = NumpyEncoder.dumps(ergebnis)
@@ -72,3 +76,5 @@ def test_optimize(
 
     # The function creates a visualization result PDF as a side-effect.
     visualisiere_ergebnisse_patch.assert_called_once()
+
+    OptimizeResponse(**ergebnis)