F fix strict values in table columns

Summary

For https://gitlab.indiscale.com/caosdb/customers/geomar/management/-/issues/152. The TableImporter.check_datatype function is now less strict (by default) with numeric values in columns that are expected to have string values.

Focus

There had been already a strict option but it was only used for float columns containing integer values. This was extended.

Test Environment

No manual testing is needed, unit tests should be sufficient.

If you still want to test it manually, run the Geomar server-profile with this branch and use, e.g., an integer in the "Storage ID" column of the sample upload.

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src/caosadvancedtools/table_importer.py

@@ -322,7 +322,7 @@ class TableImporter():
         .. note::
 
           If columns are integer, but should be float, this method converts the respective columns
-          in place.
+          in place. The same for columns that should have string value but have numeric value.
 
         Parameters
         ----------
@@ -338,9 +338,11 @@ class TableImporter():
             # float, because CaosDB does not have different sizes anyway.
             col_dtype = df.dtypes[key]
             if not strict and not np.issubdtype(col_dtype, datatype):
-                issub = np.issubdtype
                 #  These special cases should be fine.
-                if issub(col_dtype, np.integer) and issub(datatype, np.floating):
+                if ((datatype == str)
+                        or (np.issubdtype(col_dtype, np.integer)
+                            and np.issubdtype(datatype, np.floating))
+                    ):  # NOQA
                     df[key] = df[key].astype(datatype)
 
             # Now check each element

[Florian Spreckelsen]

That's all. The strict option had been there already and the problem with ints and floats in the original issue was in fact the other way round (float value where int was expected), so irrelevant here.

[Daniel Hornung]

Changed the code a bit. Looks ok?