ENH: XLSXConverter now checks the paths in the given workbook for validity:

- New method XLSXConverter._check_path_validity() called in __init__
- New test with test data containing various incorrect paths
- Updated tests and test data to reflect new behaviour

CHANGELOG.md

@@ -33,6 +33,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed ###
 
 - Yaml data model parser adds data types of properties of record types and other attributes which fixes https://gitlab.indiscale.com/caosdb/customers/f-fit/management/-/issues/58
+- `XLSXConverter` now checks path validity before parsing the worksheet.
 
 ### Security ###
 

src/caosadvancedtools/table_json_conversion/convert.py

@@ -182,16 +182,107 @@ class XLSXConverter:
         self._workbook = load_workbook(xlsx)
         self._schema = read_or_dict(schema)
         self._defining_path_index = xlsx_utils.get_defining_paths(self._workbook)
-        try:
+        self._check_path_validity()
         self._check_columns(fail_fast=strict)
-        except KeyError as e:
-            raise jsonschema.ValidationError(f"Malformed metadata: Cannot parse paths. "
-                                             f"Unknown path: '{e.args[1]}' in sheet '{e.args[0]}'."
-                                             ) from e
         self._handled_sheets: set[str] = set()
         self._result: dict = {}
         self._errors: dict = {}
 
+    def _check_path_validity(self):
+        """
+        Method to check the workbook paths for completeness and correctness,
+        and raises a jsonschema.ValidationError containing information on all
+        faulty paths if any are found.
+
+        If this method does not raise an error, this does not mean the workbook
+        is formatted correctly, only that the contained paths are complete and
+        can be found in the schema.
+        """
+        # Setup
+        error_message = ["There were errors during path validation:"]
+        only_warnings = True
+        for sheetname in self._workbook.sheetnames:
+            sheet = self._workbook[sheetname]
+            error_message.append(f"\nIn sheet {sheetname}:")
+
+            # Collect path information and filter out information column
+            row_i_col_type = xlsx_utils.get_column_type_row_index(sheet)
+            path_rows = xlsx_utils.get_path_rows(sheet)
+            paths = []
+            for col_i, col in enumerate(sheet.iter_cols()):
+                col_type = col[row_i_col_type].value
+                path = [col[row_i].value for row_i in path_rows
+                        if col[row_i].value not in [None, '']]
+                if col_type == 'COL_TYPE':
+                    continue
+                paths.append((col_type, path, col_i, col))
+
+            # Check paths
+            for col_type, path, col_i, col in paths:
+                # No column type set
+                if col_type in [None, '']:
+                    if len(path) == 0:              # Likely a comment column
+                        # Check whether the column has any visible content
+                        content_in_column = False
+                        for cell in col:
+                            visible_content = ''.join(str(cell.value)).split()
+                            if cell.value is not None and visible_content != '':
+                                content_in_column = True
+                        # If yes - might be an error but is not forbidden, so warn
+                        if content_in_column:
+                            m = (f"Warning:\tIn column {_column_id_to_chars(col_i)} "
+                                 f"there is no column metadata set. This column "
+                                 f"will be ignored during parsing.")
+                            error_message.append(m)
+                        continue
+                    else:                    # Path is set but no column type
+                        only_warnings = False
+                        m = (f"ERROR:\t\tIn column {_column_id_to_chars(col_i)} "
+                             f"the column type is missing.")
+                        error_message.append(m)
+                        # No continue - even if column type is missing, we can check path
+                if len(path) == 0:           # Column type is set but no path
+                    only_warnings = False
+                    m = (f"ERROR:\t\tIn column {_column_id_to_chars(col_i)} "
+                         f"the path is missing.")
+                    error_message.append(m)
+                    continue
+                # Check path is in schema
+                try:
+                    subschema = xlsx_utils.get_subschema(path, self._schema)
+                    schema_type = subschema.get('type', None)
+                    if schema_type is None and 'enum' in subschema:
+                        schema_type = 'enum'
+                    if schema_type is None and 'anyOf' in subschema:
+                        schema_type = 'anyOf'
+                    if schema_type == 'array':      # Check item type instead
+                        schema_type = subschema.get('items', {}).get('type', None)
+                    if schema_type in ['object', 'array', None]:
+                        m = (f"Warning:\tIn column {_column_id_to_chars(col_i)} "
+                             f"the path may be incomplete.")
+                        error_message.append(m)
+                except KeyError as e:
+                    only_warnings = False
+                    m = (f"ERROR:\t\tIn column {_column_id_to_chars(col_i)} "
+                         f"parsing of the path '{'.'.join(path)}' fails "
+                         f"on the path component {str(e)}.\n\t\t\t"
+                         f"This likely means the path is incomplete or not "
+                         f"present in the schema.")
+                    error_message.append(m)
+
+            # Cleanup if no errors were found
+            if error_message[-1] == f"\nIn sheet {sheetname}:":
+                error_message.pop(-1)
+
+        # Determine whether error / warning / nothing should be raised
+        if error_message == ["There were errors during path validation:"]:
+            return
+        error_message = '\n'.join(error_message)
+        if only_warnings:
+            warn(error_message)
+        else:
+            raise jsonschema.ValidationError(error_message)
+
     def to_dict(self, validate: bool = False, collect_errors: bool = True) -> dict:
         """Convert the xlsx contents to a dict.
 
@@ -375,13 +466,6 @@ class XLSXConverter:
                             value = self._validate_and_convert(value, path)
                             _set_in_nested(mydict=data, path=path, value=value, prefix=parent, skip=1)
                         continue
-                    elif sheet.cell(col_type_row+1, col_idx+1).value is None:
-                        mess = (f"\nNo metadata configured for column "
-                                f"'{_column_id_to_chars(col_idx)}' in worksheet "
-                                f"'{sheet.title}'.\n")
-                        if mess not in warns:
-                            print(mess, file=sys.stderr)
-                            warns.append(mess)  # Prevent multiple instances of same warning
                 except (ValueError, KeyError, jsonschema.ValidationError) as e:
                     # Append error for entire column only once
                     if isinstance(e, KeyError) and 'column' in str(e):
@@ -460,10 +544,7 @@ class XLSXConverter:
         """
         if value is None:
             return value
-        try:
         subschema = self._get_subschema(path)
-        except KeyError as e:
-            raise KeyError("There is no entry in the schema that corresponds to this column.") from e
         # Array handling only if schema says it's an array.
         if subschema.get("type") == "array":
             array_type = subschema["items"]["type"]

unittests/table_json_conversion/test_read_xlsx.py

@@ -105,7 +105,8 @@ def test_missing_columns():
     with pytest.warns(UserWarning) as caught:
         convert.to_dict(xlsx=rfp("data/simple_data_missing.xlsx"),
                         schema=rfp("data/simple_schema.json"))
-    assert str(caught.pop().message) == "Missing column: Training.coach.given_name"
+    messages = {str(w.message) for w in caught}
+    assert "Missing column: Training.coach.given_name" in messages
     with pytest.warns(UserWarning) as caught:
         convert.to_dict(xlsx=rfp("data/multiple_choice_data_missing.xlsx"),
                         schema=rfp("data/multiple_choice_schema.json"))
@@ -122,12 +123,10 @@ def test_error_table():
         convert.to_dict(xlsx=rfp("data/simple_data_broken.xlsx"),
                         schema=rfp("data/simple_schema.json"))
     # Correct Errors
-    assert "Malformed metadata: Cannot parse paths in worksheet 'Person'." in str(caught.value)
     assert "'Not a num' is not of type 'number'" in str(caught.value)
     assert "'Yes a number?' is not of type 'number'" in str(caught.value)
     assert "1.5 is not of type 'integer'" in str(caught.value)
     assert "1.2345 is not of type 'integer'" in str(caught.value)
-    assert "'There is no entry in the schema" in str(caught.value)
     assert "'Not an enum' is not one of [" in str(caught.value)
     # Correct Locations
     matches = set()
@@ -144,9 +143,6 @@ def test_error_table():
         if "1.2345 is not of type 'integer'" in line:
             assert "K8" in line
             matches.add("K8")
-        if "'There is no entry in the schema" in line:
-            assert "Column M" in line
-            matches.add("Col M")
         if "'Not an enum' is not one of [" in line:
             assert "G8" in line
             matches.add("K8")
@@ -157,33 +153,62 @@ def test_error_table():
         if "'=NOT(TRUE())' is not of type 'boolean'" in line:
             assert "L10" in line
             matches.add("L10")
-    assert matches == {"J7", "J8", "K7", "K8", "Col M", "K8", "L9", "L10"}
+    assert matches == {"J7", "J8", "K7", "K8", "K8", "L9", "L10"}
 
     # No additional errors
-    assert str(caught.value).count("Malformed metadata: Cannot parse paths in worksheet") == 1
-    assert str(caught.value).count("There is no entry in the schema") == 1
     assert str(caught.value).count("is not one of") == 1
     assert str(caught.value).count("is not of type") == 6
-    # Check correct error message for completely unknown path
-    with pytest.raises(jsonschema.ValidationError) as caught:
-        convert.to_dict(xlsx=rfp("data/simple_data_broken_paths.xlsx"),
-                        schema=rfp("data/simple_schema.json"))
-    assert ("Malformed metadata: Cannot parse paths. Unknown path: 'There' in sheet 'Person'."
-            == str(caught.value))
 
 
-def test_additional_column():
+def test_malformed_paths():
     with pytest.raises(jsonschema.ValidationError) as caught:
+        convert.to_dict(xlsx=rfp("data/simple_data_broken_paths_2.xlsx"),
+                        schema=rfp("data/simple_schema.json"))
+    message_lines = str(caught.value).lower().split('\n')
+    expected_errors = {
+        'person': {'c': "column type is missing",
+                   'd': "parsing of the path",
+                   'e': "path may be incomplete"},
+        'training': {'c': "path is missing",
+                     'd': "column type is missing",
+                     'e': "path may be incomplete",
+                     'f': "parsing of the path",
+                     'g': "path may be incomplete",
+                     'h': "parsing of the path",
+                     'i': "parsing of the path"},
+        'training.coach': {'f': "no column metadata set"}}
+    current_sheet = None
+    for line in message_lines:
+        if 'in sheet' in line:
+            current_sheet = line.replace('in sheet ', '').replace(':', '')
+            continue
+        if 'in column' in line:
+            for column, expected_error in expected_errors[current_sheet].items():
+                if f'in column {column}' in line:
+                    assert expected_error in line
+                    expected_errors[current_sheet].pop(column)
+                    break
+    for _, errors_left in expected_errors.items():
+        assert len(errors_left) == 0
+
+
+def test_empty_columns():
+    with pytest.warns(UserWarning) as caught:
+        try:
             convert.to_dict(xlsx=rfp("data/simple_data_broken.xlsx"),
                             schema=rfp("data/simple_schema.json"))
-    # Correct Error
-    assert "no entry in the schema that corresponds to this column" in str(caught.value)
-    # Correct Location
-    for line in str(caught.value).split('\n'):
-        if "no entry in the schema that corresponds to this column" in line:
-            assert " M " in line
-    # No additional column errors
-    assert str(caught.value).count("no entry in the schema that corresponds to this column") == 1
+        except jsonschema.ValidationError:
+            pass                  # Errors are checked in test_error_table
+    messages = {str(w.message).lower() for w in caught}
+    expected_warnings = {"column h": "no column metadata"}
+    for message in messages:
+        for column, warning in list(expected_warnings.items()):
+            if column in message:
+                assert warning in message
+                expected_warnings.pop(column)
+            else:
+                assert warning not in message
+    assert len(expected_warnings) == 0
 
 
 def test_faulty_foreign():