fixing some issue from sonarcloud

grid2op/Reward/baseReward.py

@@ -12,7 +12,6 @@
 import grid2op
 from grid2op.dtypes import dt_float
 from grid2op.Action import BaseAction
-# from grid2op.Environment import BaseEnv
 
 
 class BaseReward(ABC):

grid2op/gym_compat/box_gym_actspace.py

@@ -630,6 +630,10 @@ def from_gym(self, gym_act: np.ndarray) -> BaseAction:
         return res
 
     def close(self) -> None:
+        """If you override this class, this function is called when the GymEnv is deleted.
+        
+        You can use it to free some memory if needed, but there is nothing to do in the general case.
+        """
         pass
 
     def normalize_attr(self, attr_nm: POSSIBLE_KEYS)-> None:

grid2op/gym_compat/discrete_gym_actspace.py

@@ -341,6 +341,10 @@ def from_gym(self, gym_act: int) -> BaseAction:
         return res
 
     def close(self) -> None:
+        """If you override this class, this function is called when the GymEnv is deleted.
+        
+        You can use it to free some memory if needed, but there is nothing to do in the general case.
+        """
         pass
 
 

grid2op/gym_compat/gymenv.py

@@ -29,6 +29,7 @@ def decorator(func):
         return NotImplementedError()  # anything that is not a callbe anyway
     return decorator
 
+_TIME_SERIE_ID = "time serie id"
 RESET_INFO_GYM_TYPING = Dict[Literal["time serie id", "seed", "grid2op_env_seed", "underlying_env_seeds"], Any]
 
 class __AuxGymEnv(Generic[ObsType, ActType]):
@@ -155,7 +156,7 @@ def _aux_reset(self,
 
         if return_info:
             chron_id = self.init_env.chronics_handler.get_id()
-            info = {"time serie id": chron_id}
+            info = {_TIME_SERIE_ID: chron_id}
             if seed is not None:
                 info["seed"] = seed
                 info["grid2op_env_seed"] = next_seed
@@ -170,7 +171,7 @@ def _aux_reset_new(self,
         # used for gym > 0.26
         if (self._shuffle_chronics and 
             isinstance(self.init_env.chronics_handler.real_data, Multifolder) and 
-            (options is not None and "time serie id" not in options)):
+            (options is not None and _TIME_SERIE_ID not in options)):
             self.init_env.chronics_handler.sample_next_chronics()
 
         super().reset(seed=seed)  # seed gymnasium env
@@ -184,7 +185,7 @@ def _aux_reset_new(self,
         gym_obs = self.observation_space.to_gym(g2op_obs)
 
         chron_id = self.init_env.chronics_handler.get_id()
-        info = {"time serie id": chron_id}
+        info = {_TIME_SERIE_ID: chron_id}
         if seed is not None:
             info["seed"] = seed
             info["grid2op_env_seed"] = next_seed

grid2op/gym_compat/multidiscrete_gym_actspace.py

@@ -270,74 +270,77 @@ def __init__(self,
                 None,
                 act_sp.n_sub,
                 type(self).ATTR_NEEDBUILD,
-            ),  # dimension will be computed on the fly, if the stuff is used
+            ),  # dimension will be computed on the fly, if the kwarg is used
             "sub_change_bus": (
                 None,
                 act_sp.n_sub,
                 type(self).ATTR_NEEDBUILD,
-            ),  # dimension will be computed on the fly, if the stuff is used
+            ),  # dimension will be computed on the fly, if the kwarg is used
             "one_sub_set": (
                 None,
                 1,
                 type(self).ATTR_NEEDBUILD,
-            ),  # dimension will be computed on the fly, if the stuff is used
+            ),  # dimension will be computed on the fly, if the kwarg is used
             "one_sub_change": (
                 None,
                 1,
                 type(self).ATTR_NEEDBUILD,
-            ),  # dimension will be computed on the fly, if the stuff is used
+            ),  # dimension will be computed on the fly, if the kwarg is used
             "one_line_set": (
                 None,
                 1,
                 type(self).ATTR_NEEDBUILD,
-            ),  # dimension will be computed on the fly, if the stuff is used
+            ),  # dimension will be computed on the fly, if the kwarg is used
             "one_line_change": (
                 None,
                 1,
                 type(self).ATTR_NEEDBUILD,
-            ),  # dimension will be computed on the fly, if the stuff is used
+            ),  # dimension will be computed on the fly, if the kwarg is used
         }
         self._nb_bins = nb_bins
         for el in ["redispatch", "set_storage", "curtail", "curtail_mw"]:
-            if el in attr_to_keep:
-                if el not in nb_bins:
-                    raise RuntimeError(
-                        f'The attribute you want to keep "{el}" is not present in the '
-                        f'"nb_bins". This attribute is continuous, you have to specify in how '
-                        f"how to convert it to a discrete space. See the documentation "
-                        f"for more information."
-                    )
-                nb_redispatch = act_sp.gen_redispatchable.sum()
-                nb_renew = act_sp.gen_renewable.sum()
-                if el == "redispatch":
-                    self.dict_properties[el] = (
-                        [nb_bins[el] for _ in range(nb_redispatch)],
-                        nb_redispatch,
-                        self.ATTR_NEEDBINARIZED,
-                    )
-                elif el == "curtail" or el == "curtail_mw":
-                    self.dict_properties[el] = (
-                        [nb_bins[el] for _ in range(nb_renew)],
-                        nb_renew,
-                        self.ATTR_NEEDBINARIZED,
-                    )
-                elif el == "set_storage":
-                    self.dict_properties[el] = (
-                        [nb_bins[el] for _ in range(act_sp.n_storage)],
-                        act_sp.n_storage,
-                        self.ATTR_NEEDBINARIZED,
-                    )
-                else:
-                    raise Grid2OpException(f'Unknown attribute "{el}"')
-
+            self._aux_check_continuous_elements(el, attr_to_keep, nb_bins, act_sp)
+
         self._dims = None
         self._functs = None  # final functions that is applied to the gym action to map it to a grid2Op action
-        self._binarizers = None  # contains all the stuff to binarize the data
+        self._binarizers = None  # contains all the kwarg to binarize the data
         self._types = None
         nvec = self._get_info()
         # initialize the base container
         type(self)._MultiDiscreteType.__init__(self, nvec=nvec)
 
+    def _aux_check_continuous_elements(self, el, attr_to_keep, nb_bins, act_sp):
+        if el in attr_to_keep:
+            if el not in nb_bins:
+                raise RuntimeError(
+                    f'The attribute you want to keep "{el}" is not present in the '
+                    f'"nb_bins". This attribute is continuous, you have to specify in how '
+                    f"how to convert it to a discrete space. See the documentation "
+                    f"for more information."
+                )
+            nb_redispatch = act_sp.gen_redispatchable.sum()
+            nb_renew = act_sp.gen_renewable.sum()
+            if el == "redispatch":
+                self.dict_properties[el] = (
+                    [nb_bins[el] for _ in range(nb_redispatch)],
+                    nb_redispatch,
+                    self.ATTR_NEEDBINARIZED,
+                )
+            elif el == "curtail" or el == "curtail_mw":
+                self.dict_properties[el] = (
+                    [nb_bins[el] for _ in range(nb_renew)],
+                    nb_renew,
+                    self.ATTR_NEEDBINARIZED,
+                )
+            elif el == "set_storage":
+                self.dict_properties[el] = (
+                    [nb_bins[el] for _ in range(act_sp.n_storage)],
+                    act_sp.n_storage,
+                    self.ATTR_NEEDBINARIZED,
+                )
+            else:
+                raise Grid2OpException(f'Unknown attribute "{el}"')
+
     @staticmethod
     def _funct_set(vect):
         # gym encodes: