code: def test_perceptron_accuracy(container):
      data = container(X)
      clf = Perceptron(max_iter=100, tol=None, shuffle=False)
      clf.fit(data, y)
      score = clf.score(data, y)
      assert score > 0.7
  
file_path: scikit-learn/sklearn/linear_model/tests/test_perceptron.py
imports: import numpy
  import pytest
  from sklearn.datasets import load_iris
  from sklearn.linear_model import Perceptron
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 1 for calling a global function with example usage: test_perceptron_accuracy(container) without return types