Add more tests for /data/ endpoint #90
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t20100
approved these changes
Mar 11, 2024
axelboc
commented
Mar 11, 2024
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| @pytest.mark.parametrize("format_arg", ("json", "bin", "npy", "csv", "tiff")) | ||
| def test_data_on_array_with_format(self, server, format_arg): | ||
| """Test /data/ endpoint on array dataset""" |
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This one now tests all the supported formats without setting the other parameters. This means we no longer need to test flatten: False and dtype: 'origin' in subsequent tests.
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| retrieved_data = decode_array_response( | ||
| response, format_arg, ref_dtype, data.shape | ||
| f"/data/?{urlencode({'file': filename, 'path': tested_h5entity_path, 'format': format_arg, 'dtype': 'safe'})}" |
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Now focusing on testing dtype: 'safe' in this test.
| @@ -108,12 +107,31 @@ def test_data_on_slice(self, server, format_arg, flatten): | |||
| h5file[tested_h5entity_path] = data | |||
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| response = server.get( | |||
| f"/data/?{urlencode({'file': filename, 'path': tested_h5entity_path, 'selection': '100,0', 'format': format_arg, 'flatten': flatten})}" | |||
| f"/data/?{urlencode({'file': filename, 'path': tested_h5entity_path, 'selection': '100,0', 'format': format_arg, 'flatten': True})}" | |||
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Now focusing on testing flatten: True in this test.
| "format_arg", | ||
| ("csv", "npy", "tiff"), | ||
| ) | ||
| def test_422_on_format_incompatible_with_non_numeric_data(self, server, format_arg): |
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To cover the condition that was moved in #89.
| raise ValueError(f"Unsupported format: {format}") | ||
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| def decode_array_response( | ||
| response: Response, | ||
| format: str, | ||
| dtype: str, | ||
| shape: Tuple[int], | ||
| shape: Tuple[int, ...], |
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Matching numpy's internal _Shape type.
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format=tiffandformat=csvwith numeric arrayformat=binwith opaque datasetThis increases the coverage by a couple of percentage points to 94%. I also reorganise the tests a bit to avoid testing the same things twice.