From 4cbff6df3ecaceae213f462cb3a4442cdbcd497c Mon Sep 17 00:00:00 2001
From: Daniel <d.hornung@indiscale.com>
Date: Tue, 5 Sep 2023 10:49:04 +0200
Subject: [PATCH] TEST: Additional column type conversion checks.
---
unittests/test_table_importer.py | 24 ++++++++++++++++++------
1 file changed, 18 insertions(+), 6 deletions(-)
diff --git a/unittests/test_table_importer.py b/unittests/test_table_importer.py
index 72650d61..599ea535 100644
--- a/unittests/test_table_importer.py
+++ b/unittests/test_table_importer.py
@@ -44,7 +44,7 @@ from test_utils import BaseMockUpTest
# For testing the table importer
IMPORTER_KWARGS = dict(
converters={'c': float, 'd': yes_no_converter, 'x': float}, # x does not exist
- datatypes={'a': str, 'b': int, 'x': int}, # x does not exist
+ datatypes={'a': str, 'b': int, 'float': float, 'x': int}, # x does not exist
obligatory_columns=['a', 'b'], unique_keys=[('a', 'b')],
existing_columns=['e'],
)
@@ -192,17 +192,29 @@ class TableImporterTest(unittest.TestCase):
def test_wrong_datatype(self):
importer = TableImporter(**self.importer_kwargs)
- df = pd.DataFrame([[None, 0, 2.0, 'yes'],
- [5, 1, 2.0, 'yes']],
- columns=['a', 'b', 'c', 'd'])
+ df = pd.DataFrame([[1234, 0, 2.0, 3, 'yes'],
+ [5678, 1, 2.0, 3, 'yes']],
+ columns=['a', 'b', 'c', 'float', 'd'])
+ # wrong datatypes before
+ assert df["a"].dtype == int
+ assert df["float"].dtype == int
# strict = False by default, so this shouldn't raise an error
importer.check_datatype(df)
+ # The types should be correct now.
+ assert df["a"].dtype == pd.StringDtype
+ assert df["float"].dtype == float
- # Reset since check_datatype changes datatypes
+ # Resetting `df` since check_datatype may change datatypes
df = pd.DataFrame([[None, 0, 2.0, 'yes'],
[5, 1, 2.0, 'yes']],
columns=['a', 'b', 'c', 'd'])
- # strict=True, so int in str column raises an error
+ # strict=True, so number in str column raises an error
+ self.assertRaises(DataInconsistencyError, importer.check_datatype, df, None, True)
+
+ df = pd.DataFrame([[0],
+ [1]],
+ columns=['float'])
+ # strict=True, so int in float column raises an error
self.assertRaises(DataInconsistencyError, importer.check_datatype, df, None, True)
# This is always wrong (float in int column)
--
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