addressing eneko's comments

docs/advanced_usage.rst

@@ -7,10 +7,10 @@ Running models one (or more) step(s) at a time
 ----------------------------------------------
 
 Coupling different models requires the exchange of certain variables between them. This is only possible if a stepping mechanism is available, which allows for running any number of steps with certain boundary conditions that evolve along time.
-In this section, we show how the teacup model may be run in a for loop using the :py:meth:`.step` function (rather than the :py:meth:`.run` function) and update the value of a model variable before each step::
+In this section, we show how the teacup model may be run in a for loop using the :py:meth:`pysd.py_backend.model.Model.step` function (rather than the :py:meth:`pysd.py_backend.model.Model.run` function) and update the value of a model variable before each step::
 
    from pysd.py_backend.output import ModelOutput
-   
+
    # instantiate ModelOutput object
    output = ModelOutput()
 

pysd/py_backend/model.py

@@ -1312,7 +1312,6 @@ def __init__(self, py_model_file, data_files, initialize, missing_values):
         self.missing_values = missing_values
         self.progress = None
         self.output = None
-        self._stepper_mode = False
 
         if initialize:
             self.initialize()
@@ -1420,6 +1419,8 @@ def run(self, params=None, return_columns=None, return_timestamps=None,
         pysd.set_initial_condition : handles setting initial conditions
 
         """
+        self._stepper_mode = False
+
         if reload:
             self.reload()
 
@@ -1440,7 +1441,6 @@ def set_stepper(self, output_obj, params=None, step_vars=[],
                     return_columns=None, return_timestamps=None,
                     initial_condition='original', final_time=None,
                     time_step=None, saveper=None, cache_output=True):
-
         """
         Configure the model stepping behavior.
 
@@ -1460,7 +1460,7 @@ def set_stepper(self, output_obj, params=None, step_vars=[],
             List of variable or parameter names whose values might be updated
             after one or more simulation steps.
 
-        return_columns:list, 'step' or None (optional)
+        return_columns: list, 'step' or None (optional)
             List of string model component names, returned dataframe
             will have corresponding columns. If 'step' only variables with
             cache step will be returned. If None, variables with cache step
@@ -1564,7 +1564,7 @@ def _config_simulation(self, params, return_columns, return_timestamps,
 
         if self._stepper_mode:
             for step_var in kwargs["step_vars"]:
-                self.dependencies[step_var]["time"] = 1
+                self._dependencies[step_var]["time"] = 1
 
         # update cache types after setting params
         self._assign_cache_type()