diff --git a/src/caosadvancedtools/table_json_conversion/xlsx_utils.py b/src/caosadvancedtools/table_json_conversion/xlsx_utils.py
index 5002f3ac7fe4bd78accffe0697cd7ecc7273dc27..3cb2de680e29154c888305b0786ba442f20b4354 100644
--- a/src/caosadvancedtools/table_json_conversion/xlsx_utils.py
+++ b/src/caosadvancedtools/table_json_conversion/xlsx_utils.py
@@ -68,22 +68,22 @@ class RowType(Enum):
def array_schema_from_model_schema(model_schema: dict) -> dict:
"""Convert a *data model* schema to a *data array* schema.
-Practically, this means that the top level properties are converted into lists. In a simplified
-notation, this can be expressed as:
-
-``array_schema = { elem: [elem typed data...] for elem in model_schema }``
-
-Parameters
-----------
-model_schema: dict
- The schema description of the data model. Must be a json schema *object*, with a number of
- *object* typed properties.
-
-Returns
--------
-array_schema: dict
- A corresponding json schema, where the properties are arrays with the types of the input's
- top-level properties.
+ Practically, this means that the top level properties are converted into lists. In a simplified
+ notation, this can be expressed as:
+
+ ``array_schema = { elem: [elem typed data...] for elem in model_schema }``
+
+ Parameters
+ ----------
+ model_schema: dict
+ The schema description of the data model. Must be a json schema *object*, with a number of
+ *object* typed properties.
+
+ Returns
+ -------
+ array_schema: dict
+ A corresponding json schema, where the properties are arrays with the types of the input's
+ top-level properties.
"""
assert model_schema["type"] == "object"
result = deepcopy(model_schema)
@@ -100,30 +100,30 @@ array_schema: dict
def get_defining_paths(workbook: Workbook) -> dict[str, list[list[str]]]:
"""For all sheets in ``workbook``, list the paths which they define.
-A sheet is said to define a path, if it has data columns for properties inside that path. For
-example, consider the following worksheet:
-
-| `COL_TYPE` | `SCALAR` | `SCALAR` | `LIST` | `SCALAR` |
-| `PATH` | `Training` | `Training` | `Training` | `Training` |
-| `PATH` | `url` | `date` | `subjects` | `supervisor` |
-| `PATH` | | | | `email` |
-|------------|----------------|---------------|--------------|--------------------|
-| | example.com/mp | 2024-02-27 | Math;Physics | steve@example.com |
-| | example.com/m | 2024-02-27 | Math | stella@example.com |
-
-This worksheet defines properties for the paths `["Training"]` and `["Training", "supervisor"]`, and
-thus these two path lists would be returned for the key with this sheet's sheetname.
-
-Parameters
-----------
-workbook: Workbook
- The workbook to analyze.
-
-Returns
--------
-out: dict[str, list[list[str]]
- A dict with worksheet names as keys and lists of paths (represented as string lists) as values.
-"""
+ A sheet is said to define a path, if it has data columns for properties inside that path. For
+ example, consider the following worksheet:
+
+ | `COL_TYPE` | `SCALAR` | `SCALAR` | `LIST` | `SCALAR` |
+ | `PATH` | `Training` | `Training` | `Training` | `Training` |
+ | `PATH` | `url` | `date` | `subjects` | `supervisor` |
+ | `PATH` | | | | `email` |
+ |------------|----------------|---------------|--------------|--------------------|
+ | | example.com/mp | 2024-02-27 | Math;Physics | steve@example.com |
+ | | example.com/m | 2024-02-27 | Math | stella@example.com |
+
+ This worksheet defines properties for the paths `["Training"]` and `["Training", "supervisor"]`, and
+ thus these two path lists would be returned for the key with this sheet's sheetname.
+
+ Parameters
+ ----------
+ workbook: Workbook
+ The workbook to analyze.
+
+ Returns
+ -------
+ out: dict[str, list[list[str]]
+ A dict with worksheet names as keys and lists of paths (represented as string lists) as values.
+ """
result: dict[str, list[list[str]]] = {}
for sheet in workbook.worksheets:
paths = []
@@ -140,11 +140,11 @@ out: dict[str, list[list[str]]
def get_data_columns(sheet: Worksheet) -> dict[str, SimpleNamespace]:
"""Return the data paths of the worksheet.
-Returns
--------
-out: dict[str, SimpleNamespace]
- The keys are the stringified paths. The values are SimpleNamespace objects with ``index``,
- ``path`` and ``column`` attributes.
+ Returns
+ -------
+ out: dict[str, SimpleNamespace]
+ The keys are the stringified paths. The values are SimpleNamespace objects with ``index``,
+ ``path`` and ``column`` attributes.
"""
column_types = _get_column_types(sheet)
path_rows = get_path_rows(sheet)
@@ -171,11 +171,11 @@ out: dict[str, SimpleNamespace]
def get_foreign_key_columns(sheet: Worksheet) -> dict[str, SimpleNamespace]:
"""Return the foreign keys of the worksheet.
-Returns
--------
-out: dict[str, SimpleNamespace]
- The keys are the stringified paths. The values are SimpleNamespace objects with ``index``,
- ``path`` and ``column`` attributes.
+ Returns
+ -------
+ out: dict[str, SimpleNamespace]
+ The keys are the stringified paths. The values are SimpleNamespace objects with ``index``,
+ ``path`` and ``column`` attributes.
"""
column_types = _get_column_types(sheet)
path_rows = get_path_rows(sheet)
@@ -198,20 +198,20 @@ out: dict[str, SimpleNamespace]
def get_path_position(sheet: Worksheet) -> tuple[list[str], str]:
"""Return a path which represents the parent element, and the sheet's "proper name".
-For top-level sheets / entries (those without foreign columns), the path is an empty list.
+ For top-level sheets / entries (those without foreign columns), the path is an empty list.
-A sheet's "proper name" is detected from the data column paths: it is the first component after the
-parent components.
+ A sheet's "proper name" is detected from the data column paths: it is the first component after the
+ parent components.
-Returns
--------
-parent: list[str]
- Path to the parent element. Note that there may be list elements on the path which are **not**
- represented in this return value.
+ Returns
+ -------
+ parent: list[str]
+ Path to the parent element. Note that there may be list elements on the path which are **not**
+ represented in this return value.
-proper_name: str
- The "proper name" of this sheet. This defines an array where all the data lives, relative to the
- parent path.
+ proper_name: str
+ The "proper name" of this sheet. This defines an array where all the data lives, relative to the
+ parent path.
"""
# Parent element: longest common path shared among any foreign column and all the data columns
parent: list[str] = []
@@ -285,7 +285,7 @@ def is_exploded_sheet(sheet: Worksheet) -> bool:
"""Return True if this is a an "exploded" sheet.
An exploded sheet is a sheet whose data entries are LIST valued properties of entries in another
- sheet. A sheet is detected as exploded iff it has FOREIGN columns.
+ sheet. A sheet is detected as exploded if it has FOREIGN columns.
"""
column_types = _get_column_types(sheet)
return ColumnType.FOREIGN.name in column_types.values()
@@ -308,22 +308,22 @@ def p2s(path: list[str]) -> str:
def parse_multiple_choice(value: Any) -> bool:
"""Interpret ``value`` as a multiple choice input.
-*Truthy* values are:
-- The boolean ``True``.
-- The number "1".
-- The (case-insensitive) strings ``true``, ``wahr``, ``x``, ``√``, ``yes``, ``ja``, ``y``, ``j``.
-
-*Falsy* values are:
-- The boolean ``False``.
-- ``None``, empty strings, lists, dicts.
-- The number "0".
-- The (case-insensitive) strings ``false``, ``falsch``, ``-``, ``no``, ``nein``, ``n``.
-- Everything else.
-
-Returns
--------
-out: bool
- The interpretation result of ``value``.
+ *Truthy* values are:
+ - The boolean ``True``.
+ - The number "1".
+ - The (case-insensitive) strings ``true``, ``wahr``, ``x``, ``√``, ``yes``, ``ja``, ``y``, ``j``.
+
+ *Falsy* values are:
+ - The boolean ``False``.
+ - ``None``, empty strings, lists, dicts.
+ - The number "0".
+ - The (case-insensitive) strings ``false``, ``falsch``, ``-``, ``no``, ``nein``, ``n``.
+ - Everything else.
+
+ Returns
+ -------
+ out: bool
+ The interpretation result of ``value``.
"""
# Non-string cases first:
# pylint: disable-next=too-many-boolean-expressions
@@ -349,7 +349,7 @@ out: bool
def read_or_dict(data: Union[dict, str, TextIO]) -> dict:
"""If data is a json file name or input stream, read data from there.
-If it is a dict already, just return it."""
+ If it is a dict already, just return it."""
if isinstance(data, dict):
return data