Added mypy

.github/workflows/ci.yml

@@ -7,15 +7,17 @@ on:
     branches: [ "master" ]
 
 jobs:
-  test:
-
+  checkup:
     runs-on: ubuntu-latest
 
     steps:
     - uses: actions/checkout@v3
 
     - name: install dependencies
-      run: pip install .[tests]
+      run: pip install .[dev]
 
     - name: Run Tests with pytest
-      run: pytest ./tests
+      run: pytest ./tests
+
+    - name: Type checking with mypy
+      run: mypy building_energy_storage_simulation

.gitignore

@@ -2,4 +2,6 @@
 __pycache__
 **.egg-info
 .ipynb_checkpoints
-docs/build
+docs/build
+build/
+dist/

.mypy.ini

@@ -0,0 +1,2 @@
+[mypy]
+disallow_untyped_defs = True

README.md

@@ -23,7 +23,7 @@ or if you want to continue developing the package:
 
 ```
 git clone https://github.com/tobirohrer/building-energy-storage-simulation.git && cd building-energy-storage-simulation
-pip install -e .[docs,tests]
+pip install -e .[dev]
 ```
 
 ## Usage

building_energy_storage_simulation/battery.py

@@ -20,9 +20,8 @@ def __init__(self,
         self.capacity = capacity
         self.initial_state_of_charge = initial_state_of_charge
         self.state_of_charge = initial_state_of_charge
-        pass
 
-    def use(self, amount: float):
+    def use(self, amount: float) -> float:
         """
         Using means charging or discharging the battery.
 
@@ -52,7 +51,7 @@ def use(self, amount: float):
             self.state_of_charge += amount
         return electricity_used
 
-    def reset(self):
+    def reset(self) -> None:
         """
         Resetting the `state_of_charge` of the battery to the `initial_state_of_charge`.
         """

building_energy_storage_simulation/building_simulation.py

@@ -46,9 +46,8 @@ def __init__(self,
 
         self.step_count = 0
         self.start_index = 0
-        pass
 
-    def reset(self):
+    def reset(self) -> None:
         """
 
         1. Resetting the state of the building by calling `reset()` method from the battery class.
@@ -59,7 +58,6 @@ def reset(self):
 
         self.battery.reset()
         self.step_count = 0
-        pass
 
     def simulate_one_step(self, action: float) -> Tuple[float, float]:
         """
@@ -97,7 +95,7 @@ def simulate_one_step(self, action: float) -> Tuple[float, float]:
         self.step_count += 1
         return electricity_consumption_this_timestep, electricity_price_this_timestep
 
-    def _check_data_profiles_same_length(self):
+    def _check_data_profiles_same_length(self) -> None:
         if len(self.solar_generation_profile) == len(self.electricity_load_profile) == len(self.electricity_price):
             pass
         else:

building_energy_storage_simulation/environment.py

@@ -1,4 +1,4 @@
-from typing import Tuple, Optional, Union, List
+from typing import Tuple, Optional, Union, List, Iterable, Any
 from collections.abc import MutableSequence
 
 import gymnasium as gym
@@ -50,7 +50,6 @@ def __init__(self,
                                                 low=-np.inf,
                                                 high=np.inf,
                                                 dtype=np.float32)
-        pass
 
     def render(self) -> Optional[Union[RenderFrame, List[RenderFrame]]]:
         """
@@ -59,7 +58,7 @@ def render(self) -> Optional[Union[RenderFrame, List[RenderFrame]]]:
 
         pass
 
-    def reset(self, seed=None, options=None) -> Tuple[ObsType, dict]:
+    def reset(self, seed: Union[int, None] = None, options: Any = None) -> Tuple[np.ndarray, dict]:
         """
         Resetting the state of the simulation by calling `reset()` method from the simulation class.
 
@@ -77,7 +76,7 @@ def reset(self, seed=None, options=None) -> Tuple[ObsType, dict]:
             self.building_simulation.start_index = int(np.random.uniform(0, latest_possible_start_time_step))
         return self.get_observation(), {}
 
-    def step(self, action: ActType) -> Tuple[ObsType, float, bool, bool, dict]:
+    def step(self, action: Union[float, Iterable[float]]) -> Tuple[np.ndarray, float, bool, bool, dict]:
         """
         Perform one step, which is done by:
 
@@ -89,7 +88,7 @@ def step(self, action: ActType) -> Tuple[ObsType, float, bool, bool, dict]:
             action represents the fraction of `max_battery_charge_per_timestep` which should be used to charge or
             discharge the battery. 1 represents the maximum possible amount of energy which can be used to charge the
             battery per time step.
-        :type action: float
+        :type action: float or [float]
         :returns:
             Tuple of:
                 1. observation
@@ -103,19 +102,19 @@ def step(self, action: ActType) -> Tuple[ObsType, float, bool, bool, dict]:
         """
 
         if hasattr(action, "__len__"):
-            action = action[0]
-        electricity_consumption, electricity_price = self.building_simulation.simulate_one_step(action)
+            action = action[0]  # type: ignore
+        electricity_consumption, electricity_price = self.building_simulation.simulate_one_step(action)  # type: ignore
         reward = Environment.calc_reward(electricity_consumption, electricity_price)
         observation = self.get_observation()
         return observation, reward, self._get_terminated(), False, {'electricity_consumption': electricity_consumption,
                                                                     'electricity_price': electricity_price}
 
-    def _get_terminated(self):
+    def _get_terminated(self) -> bool:
         if self.building_simulation.step_count >= self.max_timesteps:
             return True
         return False
 
-    def get_observation(self):
+    def get_observation(self) -> np.ndarray:
         current_index = self.building_simulation.start_index + self.building_simulation.step_count
         sim = self.building_simulation
         electric_load_forecast = sim.electricity_load_profile[current_index: current_index + self.num_forecasting_steps]
@@ -127,23 +126,23 @@ def get_observation(self):
             solar_gen_forecast = self._randomize_forecast(solar_gen_forecast)
             energy_price_forecast = self._randomize_forecast(energy_price_forecast)
 
-        return np.concatenate(([self.building_simulation.battery.state_of_charge],
+        return np.concatenate(([self.building_simulation.battery.state_of_charge],  # type: ignore
                                electric_load_forecast,
                                solar_gen_forecast,
                                energy_price_forecast),
                               axis=0)
 
     @staticmethod
-    def _randomize_forecast(forecast: MutableSequence,
+    def _randomize_forecast(forecast: np.ndarray,
                             standard_deviation_start: float = 0.2,
-                            standard_deviation_end: float = 1.0) -> MutableSequence:
+                            standard_deviation_end: float = 1.0) -> np.ndarray:
         # gamma can be interpreted as the quantification of the increase of uncertainty per time step.
         gamma = standard_deviation_end - standard_deviation_start
         for i in range(len(forecast)):
             std = standard_deviation_end - gamma ** i
             forecast[i] = forecast[i] + np.random.normal(0, std)
-        return forecast
+        return np.array(forecast)
 
     @staticmethod
-    def calc_reward(electricity_consumption, electricity_price):
+    def calc_reward(electricity_consumption: float, electricity_price: float) -> float:
         return -1 * electricity_consumption * electricity_price

setup.py

@@ -4,7 +4,7 @@
 long_description = (this_directory / "README.md").read_text()
 
 setup(name='building_energy_storage_simulation',
-      version='0.9.0',
+      version='0.9.2',
       description='A simulation of a building to optimize energy storage utilization.',
       long_description=long_description,
       long_description_content_type='text/markdown',
@@ -26,11 +26,12 @@
           "numpy"
       ],
       extras_require={
-          "docs": [
-              "sphinx"
-          ],
-          "tests": [
-              "pytest"
+          "dev": [
+              "sphinx",
+              "pytest",
+              "mypy",
+              "pandas-stubs",
+              "types-setuptools"
           ]
       }
       )