docs: Sort __all__ list guideline instruction (#433)

Closes #370

### Summary of Changes

Sorted the entries in `__all__` list in `__init__.py` files and added an
instruction to the guidelines.

---------

Co-authored-by: megalinter-bot <[email protected]>
Co-authored-by: Lars Reimann <[email protected]>
Co-authored-by: Severin Paul Höfer <[email protected]>

Author: 4 people

docs/development/guidelines.md

@@ -205,6 +205,27 @@ The user should not have to deal with exceptions that are defined in the wrapper
         return pd.read_csv(path) # May raise a pd.ParserError
     ```
 
+### Sort entries in `__all__` lists alphabetically
+The entries in the `__all__` list in `__init__.py` files should be sorted alphabetically. This helps reduce the likelihood of merge conflicts when new entries are introduced on different branches.
+!!! success "**DO** (library code):"
+
+    ```py
+    __all__ = [
+        "ColumnSizeError",
+        "DuplicateColumnNameError",
+        "MissingValuesColumnError"
+    ]
+    ```
+!!! failure "**DON'T** (library code):"
+
+    ```py
+    __all__ = [
+        "MissingValuesColumnError",
+        "ColumnSizeError",
+        "DuplicateColumnNameError"
+    ]
+    ```
+
 ### Group API elements by task
 
 Packages should correspond to a specific task like classification or imputation. This eases discovery and makes it easy to switch between different solutions for the same task.

src/safeds/data/tabular/transformation/__init__.py

@@ -9,12 +9,12 @@
 from ._table_transformer import InvertibleTableTransformer, TableTransformer
 
 __all__ = [
+    "Discretizer",
     "Imputer",
+    "InvertibleTableTransformer",
     "LabelEncoder",
     "OneHotEncoder",
-    "InvertibleTableTransformer",
-    "TableTransformer",
     "RangeScaler",
-    "Discretizer",
     "StandardScaler",
+    "TableTransformer",
 ]

src/safeds/exceptions/__init__.py

@@ -29,19 +29,19 @@
     "ColumnSizeError",
     "DuplicateColumnNameError",
     "IndexOutOfBoundsError",
+    "MissingValuesColumnError",
     "NonNumericColumnError",
     "SchemaMismatchError",
     "TransformerNotFittedError",
     "UnknownColumnNameError",
     "ValueNotPresentWhenFittedError",
     "WrongFileExtensionError",
-    "MissingValuesColumnError",
     # ML exceptions
     "DatasetContainsTargetError",
+    "DatasetMissesDataError",
     "DatasetMissesFeaturesError",
     "LearningError",
     "ModelNotFittedError",
     "PredictionError",
     "UntaggedTableError",
-    "DatasetMissesDataError",
 ]