random sampling issue

[SimonMolinsky]

TypeError                                 Traceback (most recent call last)
Cell In[45], line 3
      1 get_ipython().run_line_magic('scrun', '')
      2 for _r in recs:
----> 3     output = model.recommend(
      4         _r
      5     )

File ~/miniforge3/envs/wsknn/lib/python3.12/site-packages/wsknn/model/wsknn.py:276, in WSKNN.recommend(self, event_stream, settings)
    273 if settings is not None:
    274     self.set_model_params(**settings)
--> 276 recommendations = self._predict(event_stream)
    278 return recommendations

File ~/miniforge3/envs/wsknn/lib/python3.12/site-packages/wsknn/model/wsknn.py:388, in WSKNN._predict(self, session)
    387 def _predict(self, session):
--> 388     neighbors = self._nearest_neighbors(session)
    390     if len(neighbors) == 0:
    391         if self.recommend_any:

File ~/miniforge3/envs/wsknn/lib/python3.12/site-packages/wsknn/model/wsknn.py:629, in WSKNN._nearest_neighbors(self, session)
    608 def _nearest_neighbors(self, session: List) -> List:
    609     """Method searches for nearest neighbors for a given session.
    610 
    611     Parameters
   (...)
    627         smaller than number of the closest sessions.
    628     """
--> 629     possible_neighbor_sessions = self._possible_neighbors(session)
    630     items_sequence = session[0]
    631     rank = self._calculate_similarity(items_sequence, possible_neighbor_sessions)

File ~/miniforge3/envs/wsknn/lib/python3.12/site-packages/wsknn/model/wsknn.py:668, in WSKNN._possible_neighbors(self, session)
    665 if self.required_sampling_event is not None:
    666     common_sessions = self._get_sessions_with_event(common_sessions)
--> 668 sample_subset = self._sample_possible_neighbors(common_sessions, session)
    669 return sample_subset

File ~/miniforge3/envs/wsknn/lib/python3.12/site-packages/wsknn/model/wsknn.py:815, in WSKNN._sample_possible_neighbors(self, all_sessions, session)
    798 """Method samples possible neighbors.
    799 
    800 Parameters
   (...)
    811     The subset of possible neighbors
    812 """
    814 if self.sampling_strategy == 'random':
--> 815     return self._sampling_random(all_sessions)
    816 elif self.sampling_strategy == 'recent':
    817     return self._sampling_recent(all_sessions)

File ~/miniforge3/envs/wsknn/lib/python3.12/site-packages/wsknn/model/wsknn.py:842, in WSKNN._sampling_random(self, sessions)
    828 """Get random sessions from the sessions space. This method is good to estimate model performance.
    829 
    830 Parameters
   (...)
    838     Random sample of ``self.possible_neighbors_sample_size`` sessions.
    839 """
    841 sample_size = min(self.possible_neighbors_sample_size, len(sessions))
--> 842 sample = random.sample(sessions, sample_size)
    844 return sample

File ~/miniforge3/envs/wsknn/lib/python3.12/random.py:413, in Random.sample(self, population, k, counts)
    389 # Sampling without replacement entails tracking either potential
    390 # selections (the pool) in a list or previous selections in a set.
    391 
   (...)
    409 # too many calls to _randbelow(), making them slower and
    410 # causing them to eat more entropy than necessary.
    412 if not isinstance(population, _Sequence):
--> 413     raise TypeError("Population must be a sequence.  "
    414                     "For dicts or sets, use sorted(d).")
    415 n = len(population)
    416 if counts is not None:

TypeError: Population must be a sequence.  For dicts or sets, use sorted(d).