batch error logs

.readthedocs.yaml

@@ -19,6 +19,7 @@ python:
 # Doc builds will fail if there are any warnings
 sphinx:
   fail_on_warning: true
+  configuration: docs/conf.py
 
 formats:
   - pdf

pyproject.toml

@@ -23,5 +23,6 @@ exclude = [
 [[tool.mypy.overrides]]
 module = [
     "scipy.*",
+    "pytest_check",
 ]
 ignore_missing_imports = true

setup.py

@@ -50,6 +50,7 @@
         "tqdm",
         "layered_config_tree>=2.1.0",
         "loguru",
+        "pytest_check",
         # type stubs
         "pandas-stubs",
         "types-PyYAML",

tests/integration/release/test_release.py

@@ -5,6 +5,7 @@
 import pandas as pd
 import pytest
 from _pytest.fixtures import FixtureRequest
+from pytest_check import check
 from vivarium_testing_utils import FuzzyChecker
 
 from pseudopeople.dataset import Dataset

tests/integration/release/test_runner.py

@@ -19,7 +19,7 @@
 )
 def test_release_tests(pytest_args: list[str]) -> None:
     os.chdir(Path(__file__).parent)  # need this to access cli options from conftest.py
-    base_cmd = ["pytest", "--release", "test_release.py"]
+    base_cmd = ["pytest", "--release", "test_release.py", "--check-max-tb=1000"]
     cmd = base_cmd + pytest_args
     result = subprocess.run(cmd, capture_output=True, text=True)
     assert result.returncode == 0

tests/utilities.py

@@ -8,6 +8,7 @@
 import numpy as np
 import numpy.typing as npt
 import pandas as pd
+from pytest_check import check
 from vivarium_testing_utils import FuzzyChecker
 
 from pseudopeople.configuration import Keys, get_configuration
@@ -34,7 +35,8 @@ def run_column_noising_tests(
 
         # Check that originally missing data remained missing
         originally_missing_idx = check_original.index[check_original[col.name].isna()]
-        assert check_noised.loc[originally_missing_idx, col.name].isna().all()
+        with check:
+            assert check_noised.loc[originally_missing_idx, col.name].isna().all()
 
         # Check for noising where applicable
         to_compare_idx = shared_idx.difference(originally_missing_idx)
@@ -43,7 +45,8 @@ def run_column_noising_tests(
                 check_original.loc[to_compare_idx, col.name].values
                 != check_noised.loc[to_compare_idx, col.name].values
             )
-            assert different_check.any()
+            with check:
+                assert different_check.any()
 
             noise_level = different_check.sum()
 
@@ -64,7 +67,8 @@ def run_column_noising_tests(
                 == check_noised.loc[to_compare_idx, col.name].values
             )
 
-            assert same_check.all()
+            with check:
+                assert same_check.all()
 
 
 def run_omit_row_or_do_not_respond_tests(
@@ -87,15 +91,20 @@ def run_omit_row_or_do_not_respond_tests(
     ]:
         # Census and household surveys have do_not_respond and omit_row.
         # For all other datasets they are mutually exclusive
-        assert len(noise_types) == 2
+        with check:
+            assert len(noise_types) == 2
     else:
-        assert len(noise_types) < 2
+        with check:
+            assert len(noise_types) < 2
     if not noise_types:  # Check that there are no missing indexes
-        assert noised_data.index.symmetric_difference(original_data.index).empty
+        with check:
+            assert noised_data.index.symmetric_difference(original_data.index).empty
     else:  # Check that there are some omissions
         # TODO: assert levels are as expected
-        assert noised_data.index.difference(original_data.index).empty
-        assert not original_data.index.difference(noised_data.index).empty
+        with check:
+            assert noised_data.index.difference(original_data.index).empty
+        with check:
+            assert not original_data.index.difference(noised_data.index).empty
 
 
 def validate_column_noise_level(
@@ -158,7 +167,8 @@ def validate_column_noise_level(
                     [1 - p for p in token_probability]
                 )
             else:
-                assert isinstance(tokens_per_string, pd.Series)
+                with check:
+                    assert isinstance(tokens_per_string, pd.Series)
                 avg_probability_any_token_noised = (
                     1 - (1 - token_probability) ** tokens_per_string
                 ).mean()