KNN RandomizedSearchCV typerror

Question

While trying to study a binary classification problem with KNN and trying to tune the parameters of the model I'm getting a typerror that I quite don't understand. Is a parameter missing or something?

TypeError: init() takes exactly 1 positional argument (0 given)

Here is my code:

import pandas as pd
import numpy as np
from sklearn import model_selection
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import RandomizedSearchCV

# generate example data
X = pd.DataFrame({
    'a': np.linspace(0, 10, 500),
    'b': np.random.randint(0, 10, size=500),
})
y = np.random.randint(0, 2, size=500)

# set search parameters
n_neighbors = [int(x) for x in np.linspace(start = 1, stop = 100, num = 50)]   
weights = ['uniform','distance']
metric = ['euclidean','manhattan','chebyshev','seuclidean','minkowski'] 
random_grid = {
    'n_neighbors': n_neighbors,
    'weights': weights,
    'metric': metric,
}

# run search
knn = KNeighborsClassifier() 
knn_random = RandomizedSearchCV(estimator = knn, random_state = 42,n_jobs = -1,param_distributions = random_grid,n_iter = 100, cv=3,verbose = 2)
knn_random.fit(X,y)
knn_random.best_params_

Full error:

_RemoteTraceback                          Traceback (most recent call last)
_RemoteTraceback: 
"""
Traceback (most recent call last):
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\externals\joblib\externals\loky\process_executor.py", line 418, in _process_worker
    r = call_item()
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\externals\joblib\externals\loky\process_executor.py", line 272, in __call__
    return self.fn(*self.args, **self.kwargs)
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\externals\joblib\_parallel_backends.py", line 567, in __call__
    return self.func(*args, **kwargs)
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\externals\joblib\parallel.py", line 225, in __call__
    for func, args, kwargs in self.items]
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\externals\joblib\parallel.py", line 225, in <listcomp>
    for func, args, kwargs in self.items]
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\model_selection\_validation.py", line 528, in _fit_and_score
    estimator.fit(X_train, y_train, **fit_params)
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\neighbors\base.py", line 916, in fit
    return self._fit(X)
  File "C:\Users\dungeon\Anaconda3\lib\site-packages\sklearn\neighbors\base.py", line 254, in _fit
    **self.effective_metric_params_)
  File "sklearn\neighbors\binary_tree.pxi", line 1071, in sklearn.neighbors.ball_tree.BinaryTree.__init__
  File "sklearn\neighbors\dist_metrics.pyx", line 286, in sklearn.neighbors.dist_metrics.DistanceMetric.get_metric
  File "sklearn\neighbors\dist_metrics.pyx", line 443, in sklearn.neighbors.dist_metrics.SEuclideanDistance.__init__
TypeError: __init__() takes exactly 1 positional argument (0 given)
"""

The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)
<ipython-input-2-b5a9f7ea82d0> in <module>
     29 knn_random = RandomizedSearchCV(estimator = knn, random_state = 42,n_jobs = -1,param_distributions = random_grid,n_iter = 100, cv=3,verbose = 2)
     30 
---> 31 knn_random.fit(X,y)
     32 knn_random.best_params_

~\Anaconda3\lib\site-packages\sklearn\model_selection\_search.py in fit(self, X, y, groups, **fit_params)
    720                 return results_container[0]
    721 
--> 722             self._run_search(evaluate_candidates)
    723 
    724         results = results_container[0]

~\Anaconda3\lib\site-packages\sklearn\model_selection\_search.py in _run_search(self, evaluate_candidates)
   1513         evaluate_candidates(ParameterSampler(
   1514             self.param_distributions, self.n_iter,
-> 1515             random_state=self.random_state))

~\Anaconda3\lib\site-packages\sklearn\model_selection\_search.py in evaluate_candidates(candidate_params)
    709                                for parameters, (train, test)
    710                                in product(candidate_params,
--> 711                                           cv.split(X, y, groups)))
    712 
    713                 all_candidate_params.extend(candidate_params)

~\Anaconda3\lib\site-packages\sklearn\externals\joblib\parallel.py in __call__(self, iterable)
    928 
    929             with self._backend.retrieval_context():
--> 930                 self.retrieve()
    931             # Make sure that we get a last message telling us we are done
    932             elapsed_time = time.time() - self._start_time

~\Anaconda3\lib\site-packages\sklearn\externals\joblib\parallel.py in retrieve(self)
    831             try:
    832                 if getattr(self._backend, 'supports_timeout', False):
--> 833                     self._output.extend(job.get(timeout=self.timeout))
    834                 else:
    835                     self._output.extend(job.get())

~\Anaconda3\lib\site-packages\sklearn\externals\joblib\_parallel_backends.py in wrap_future_result(future, timeout)
    519         AsyncResults.get from multiprocessing."""
    520         try:
--> 521             return future.result(timeout=timeout)
    522         except LokyTimeoutError:
    523             raise TimeoutError()

~\Anaconda3\lib\concurrent\futures\_base.py in result(self, timeout)
    430                 raise CancelledError()
    431             elif self._state == FINISHED:
--> 432                 return self.__get_result()
    433             else:
    434                 raise TimeoutError()

~\Anaconda3\lib\concurrent\futures\_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

TypeError: __init__() takes exactly 1 positional argument (0 given)