Use tempfile for unit test

scripts/tests/test_train.py

@@ -16,6 +16,7 @@
 import math
 import os
 import sys
+import tempfile
 import typing
 import unittest
 
@@ -73,11 +74,10 @@ def test_cmdargs_full(self) -> None:
 
 
 class TestPreprocess(unittest.TestCase):
-  ENTRIES_FILE_PATH = os.path.abspath(
-      os.path.join(os.path.dirname(__file__), 'entries_test.txt'))
 
   def test_standard_setup(self) -> None:
-    with open(self.ENTRIES_FILE_PATH, 'w') as f:
+    entries_file_path = tempfile.NamedTemporaryFile().name
+    with open(entries_file_path, 'w') as f:
       f.write(('1\tfoo\tbar\n'
                '-1\tfoo\n'
                '1\tfoo\tbar\tbaz\n'
@@ -90,30 +90,29 @@ def test_standard_setup(self) -> None:
     # 1      1   1   1
     # 1      1   1   0
     # -1     0   0   1
-    rows, cols, Y, features = train.preprocess(self.ENTRIES_FILE_PATH, 1)
+    rows, cols, Y, features = train.preprocess(entries_file_path, 1)
     self.assertEqual(features, ['foo', 'bar', 'baz'])
     self.assertEqual(Y.tolist(), [True, False, True, True, False])
     self.assertEqual(rows.tolist(), [0, 0, 1, 2, 2, 2, 3, 3, 4])
     self.assertEqual(cols.tolist(), [0, 1, 0, 0, 1, 2, 1, 0, 2])
+    os.remove(entries_file_path)
 
   def test_skip_invalid_rows(self) -> None:
-    with open(self.ENTRIES_FILE_PATH, 'w') as f:
+    entries_file_path = tempfile.NamedTemporaryFile().name
+    with open(entries_file_path, 'w') as f:
       f.write(('\n1\tfoo\tbar\n'
                '-1\n\n'
                '-1\tfoo\n\n'))
     # The input matrix X and the target vector Y should look like below now:
     # Y    X(foo bar)
     # 1      1   1
     # -1     1   0
-    rows, cols, Y, features = train.preprocess(self.ENTRIES_FILE_PATH, 0)
+    rows, cols, Y, features = train.preprocess(entries_file_path, 0)
     self.assertEqual(features, ['foo', 'bar'])
     self.assertEqual(Y.tolist(), [True, False])
     self.assertEqual(rows.tolist(), [0, 0, 1])
     self.assertEqual(cols.tolist(), [0, 1, 0])
-
-  def tearDown(self) -> None:
-    if (os.path.exists(self.ENTRIES_FILE_PATH)):
-      os.remove(self.ENTRIES_FILE_PATH)
+    os.remove(entries_file_path)
 
 
 class TestSplitData(unittest.TestCase):
@@ -205,12 +204,10 @@ def test_standard_setup1(self) -> None:
 
 
 class TestFit(unittest.TestCase):
-  WEIGHTS_FILE_PATH = os.path.abspath(
-      os.path.join(os.path.dirname(__file__), 'weights_test.txt'))
-  LOG_FILE_PATH = os.path.abspath(
-      os.path.join(os.path.dirname(__file__), 'train_test.log'))
 
   def test_fit(self) -> None:
+    weights_file_path = tempfile.NamedTemporaryFile().name
+    log_file_path = tempfile.NamedTemporaryFile().name
     # Prepare a dataset that the 2nd feature (= the 2nd col in X) perfectly
     # correlates with Y in a negative way.
     X = np.array([
@@ -225,8 +222,8 @@ def test_fit(self) -> None:
     iters = 5
     out_span = 2
     scores = train.fit(rows, cols, rows, cols, Y, Y, features, iters,
-                       self.WEIGHTS_FILE_PATH, self.LOG_FILE_PATH, out_span)
-    with open(self.WEIGHTS_FILE_PATH) as f:
+                       weights_file_path, log_file_path, out_span)
+    with open(weights_file_path) as f:
       weights = [
           line.split('\t') for line in f.read().splitlines() if line.strip()
       ]
@@ -238,7 +235,7 @@ def test_fit(self) -> None:
         iters,
         msg='The number of lines should equal to the iteration count.')
 
-    with open(self.LOG_FILE_PATH) as f:
+    with open(log_file_path) as f:
       log = [line.split('\t') for line in f.read().splitlines() if line.strip()]
     self.assertEqual(
         len(log),
@@ -257,10 +254,8 @@ def test_fit(self) -> None:
     self.assertEqual(scores.shape[0], len(features))
     loaded_scores = [model.get(feature, 0) for feature in features]
     self.assertTrue(np.all(np.isclose(scores, loaded_scores)))
-
-  def tearDown(self) -> None:
-    os.remove(self.WEIGHTS_FILE_PATH)
-    os.remove(self.LOG_FILE_PATH)
+    os.remove(weights_file_path)
+    os.remove(log_file_path)
 
 
 if __name__ == '__main__':