upgrade pytest to 7.0.1, remove mock and updgrade pytest-mock to 3.6.1

erroranalysis/requirements-dev.txt

@@ -1,6 +1,6 @@
-pytest==5.0.1
+pytest==7.0.1
 pytest-cov
-pytest-mock==3.1.1
+pytest-mock==3.6.1
 requests==2.25.1
 
 requirements-parser==0.2.0

rai_core_flask/requirements-dev.txt

@@ -1,6 +1,6 @@
-pytest==5.0.1
+pytest==7.0.1
 pytest-cov
-pytest-mock==3.1.1
+pytest-mock==3.6.1
 requests==2.25.1
 
 requirements-parser==0.2.0

raiutils/requirements-dev.txt

@@ -1,6 +1,6 @@
-pytest==5.0.1
+pytest==7.0.1
 pytest-cov
-pytest-mock==3.1.1
+pytest-mock==3.6.1
 requests==2.25.1
 
 requirements-parser==0.2.0

raiwidgets/requirements-dev.txt

@@ -1,9 +1,8 @@
 # Requirements for raiwidgets development
 
-pytest==5.0.1
-mock==4.0.1
+pytest==7.0.1
 pytest-cov
-pytest-mock==3.1.1
+pytest-mock==3.6.1
 requests==2.25.1
 
 requirements-parser==0.2.0

raiwidgets/tests/test_fairness_calculations.py

@@ -3,6 +3,7 @@
 
 import numpy as np
 import pytest
+from pytest import approx
 
 from raiwidgets.fairness_metric_calculation import (compute_wilson_bounds,
                                                     false_negative_rate_wilson,
@@ -58,23 +59,23 @@ def test_false_negative_rate_wilson(sample_binary_data):
 
 def test_mse_standard_normal_binary(sample_binary_data):
     y_true, y_pred = sample_binary_data
-    assert pytest.approx(mse_standard_normal(y_true, y_pred), (0.0160, 0.5840))
+    mse = mse_standard_normal(y_true, y_pred)
+    assert mse == approx((0.0160, 0.5840), rel=1e-3, abs=1e-3)
 
 
 def test_mae_standard_normal_binary(sample_binary_data):
     y_true, y_pred = sample_binary_data
-    assert pytest.approx(mae_standard_normal(y_true, y_pred), (0.0160, 0.5840))
+    mae = mae_standard_normal(y_true, y_pred)
+    assert mae == approx((0.0160, 0.5840), rel=1e-3, abs=1e-3)
 
 
 def test_mse_standard_normal_continuous(sample_continuous_data):
     y_true, y_pred = sample_continuous_data
-    assert pytest.approx(
-        mse_standard_normal(y_true, y_pred), (57.7926, 637.2074)
-    )
+    mse = mse_standard_normal(y_true, y_pred)
+    assert mse == approx((57.7926, 637.2074), rel=1e-3, abs=1e-3)
 
 
 def test_mae_standard_normal_continuous(sample_continuous_data):
     y_true, y_pred = sample_continuous_data
-    assert pytest.approx(
-        mae_standard_normal(y_true, y_pred), (9.4708, 21.9292)
-    )
+    mae = mae_standard_normal(y_true, y_pred)
+    assert mae == approx((9.4708, 21.9292), rel=1e-3, abs=1e-3)

raiwidgets/tests/test_no_fairlearn.py

@@ -1,15 +1,16 @@
 # Copyright (c) Microsoft Corporation
 # Licensed under the MIT License.
 
-import mock
+from unittest.mock import patch
+
 import pytest
 
 from raiwidgets import FairnessDashboard
 from raiwidgets.fairness_metric_calculation import \
     MODULE_NOT_INSTALLED_ERROR_MESSAGE
 
 
-@mock.patch("importlib.import_module")
+@patch("importlib.import_module")
 def test_no_fairlearn(importlib_mock):
     importlib_mock.side_effect = \
         ModuleNotFoundError("No module named 'fairlearn.metrics'")

raiwidgets/tests/test_responsibleai_dashboard_input.py

@@ -1,7 +1,7 @@
 # Copyright (c) Microsoft Corporation
 # Licensed under the MIT License.
 
-import mock
+from unittest.mock import patch
 
 from raiwidgets.responsibleai_dashboard_input import \
     ResponsibleAIDashboardInput
@@ -15,7 +15,7 @@ def test_model_analysis_adult(
         test_data = ri.test
 
         dashboard_input = ResponsibleAIDashboardInput(ri)
-        with mock.patch.object(knn, "predict_proba") as predict_mock:
+        with patch.object(knn, "predict_proba") as predict_mock:
             test_pred_data = test_data.head(1).drop("Income", axis=1).values
             dashboard_input.on_predict(
                 test_pred_data)

responsibleai/requirements-dev.txt

@@ -1,9 +1,8 @@
 # Requirements for responsibleai development
 
-pytest==5.0.1
+pytest==7.0.1
 pytest-cov
-mock==4.0.1
-pytest-mock==3.1.1
+pytest-mock==3.6.1
 
 # Required for responsibleai package tests
 deptree~=0.0.10