Fix type errors not TypeError

cognite/client/_api/data_modeling/instances.py

@@ -858,7 +858,7 @@ def histogram(
 
         for histogram in histogram_seq:
             if not isinstance(histogram, Histogram):
-                raise ValueError(f"Not a histogram: {histogram}")
+                raise TypeError(f"Not a histogram: {histogram}")
 
         body["aggregates"] = [histogram.dump(camel_case=True) for histogram in histogram_seq]
         if filter:

cognite/client/_api/raw.py

@@ -501,7 +501,7 @@ def _make_columns_param(self, columns: list[str] | None) -> str | None:
         if columns is None:
             return None
         if not isinstance(columns, list):
-            raise ValueError("Expected a list for argument columns")
+            raise TypeError("Expected a list for argument columns")
         if len(columns) == 0:
             return ","
         else:

cognite/client/_api/sequences.py

@@ -922,7 +922,7 @@ def insert(
         elif isinstance(rows, SequenceType) and (len(rows) == 0 or isinstance(rows[0], tuple)):
             all_rows = [{"rowNumber": k, "values": v} for k, v in rows]
         else:
-            raise ValueError("Invalid format for 'rows', expected a list of tuples, list of dict or dict")
+            raise TypeError("Invalid format for 'rows', expected a list of tuples, list of dict or dict")
 
         base_obj = Identifier.of_either(id, external_id).as_dict()
         base_obj.update(self._process_columns(column_external_ids))

cognite/client/data_classes/data_modeling/ids.py

@@ -40,7 +40,7 @@ def load(cls: type[T_DataModelingId], data: dict | T_DataModelingId | tuple[str,
             return cls(*data)
         elif isinstance(data, dict):
             return cls(**convert_all_keys_to_snake_case(rename_and_exclude_keys(data, exclude={"type"})))
-        raise ValueError(f"Cannot load {data} into {cls}, invalid type={type(data)}")
+        raise TypeError(f"Cannot load {data} into {cls}, invalid type={type(data)}")
 
 
 T_DataModelingId = TypeVar("T_DataModelingId", bound=DataModelingId)
@@ -73,7 +73,7 @@ def load(
             return cls(*data)
         elif isinstance(data, dict):
             return cls(**convert_all_keys_to_snake_case(rename_and_exclude_keys(data, exclude={"type"})))
-        raise ValueError(f"Cannot load {data} into {cls}, invalid type={type(data)}")
+        raise TypeError(f"Cannot load {data} into {cls}, invalid type={type(data)}")
 
 
 T_Versioned_DataModeling_Id = TypeVar("T_Versioned_DataModeling_Id", bound=VersionedDataModelingId)

cognite/client/data_classes/time_series.py

@@ -96,13 +96,13 @@ def count(self) -> int:
             int: The number of datapoints in this time series.
 
         Raises:
-            ValueError: If the time series is string as count aggregate is only supported for numeric data
+            RuntimeError: If the time series is string, as count aggregate is only supported for numeric data
 
         Returns:
             int: The total number of datapoints
         """
         if self.is_string:
-            raise ValueError("String time series does not support count aggregate.")
+            raise RuntimeError("String time series does not support count aggregate.")
 
         identifier = Identifier.load(self.id, self.external_id).as_dict()
         dps = self._cognite_client.time_series.data.retrieve(

cognite/client/utils/_auxiliary.py

@@ -233,7 +233,7 @@ def split_into_chunks(collection: list | dict, chunk_size: int) -> list[list] |
         collection = list(collection.items())
         return [dict(collection[i : i + chunk_size]) for i in range(0, len(collection), chunk_size)]
 
-    raise ValueError(f"Can only split list or dict, not {type(collection)}")
+    raise TypeError(f"Can only split list or dict, not {type(collection)}")
 
 
 def convert_true_match(true_match: dict | list | tuple[int | str, int | str]) -> dict:

tests/tests_integration/test_api/test_time_series.py

@@ -294,7 +294,7 @@ def test_get_count__numeric(self, test_tss, ts_idx, exp_count):
 
     def test_get_count__string_fails(self, test_ts_string):
         assert test_ts_string.is_string is True
-        with pytest.raises(ValueError, match="String time series does not support count aggregate."):
+        with pytest.raises(RuntimeError, match="String time series does not support count aggregate."):
             test_ts_string.count()
 
     def test_get_latest(self, test_ts_numeric, test_ts_string):

tests/tests_unit/test_api/test_raw.py

@@ -238,7 +238,7 @@ def test_list_cols_empty(self, cognite_client, mock_raw_row_response):
         assert "columns=%2C&" in mock_raw_row_response.calls[0].request.path_url + "&"
 
     def test_list_cols_str_not_supported(self, cognite_client, mock_raw_row_response):
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             cognite_client.raw.rows.list(db_name="db1", table_name="table1", columns="a,b")
 
     def test_iter_single(self, cognite_client, mock_raw_row_response):
@@ -287,7 +287,7 @@ def test_iter_cols_empty(self, cognite_client, mock_raw_row_response):
         assert "columns=%2C&" in mock_raw_row_response.calls[0].request.path_url + "&"
 
     def test_iter_cols_str_not_supported(self, cognite_client, mock_raw_row_response):
-        with pytest.raises(ValueError):
+        with pytest.raises(TypeError):
             cognite_client.raw.rows(db_name="db1", table_name="table1", columns="a,b")
 
 

tests/tests_unit/test_data_classes/test_time_series.py

@@ -103,7 +103,7 @@ def mock_get_first_dp_in_ts(mock_ts_by_ids_response, cognite_client):
 
 class TestTimeSeries:
     def test_get_count__string_raises(self, cognite_client, mock_ts_by_ids_response):
-        with pytest.raises(ValueError, match="String time series does not support count aggregate"):
+        with pytest.raises(RuntimeError, match="String time series does not support count aggregate"):
             cognite_client.time_series.retrieve(id=1).count()
 
     def test_get_latest(self, cognite_client, mock_get_latest_dp_in_ts):