Fix for GUI not using pydantic. Also added feature for custom date co…

[rtomek]

…lumn

[Copilot]

Pull request overview

This pull request refactors the GUI data source handling to use Pydantic's DataSourceConfig model instead of plain dictionaries, and adds support for custom date column configuration. The changes improve type safety and allow users to specify which column should be treated as the date column in CSV/TSV files.

Changes:

• Updated Signal types to use DataSourceConfig instead of dict for type-safe data source emission
• Added date_column field to DataSourceConfig with default value 'date' and alias 'date column'
• Added UI field in CSV/TSV dialog for users to specify the date column name
• Modified data source instantiation in file dialogs to create DataSourceConfig objects

Reviewed changes

Copilot reviewed 5 out of 5 changed files in this pull request and generated 3 comments.

Show a summary per file

File	Description
src/midrc_react/gui/pyside6/jsdview.py	Updated Signal type from dict to DataSourceConfig and added import
src/midrc_react/gui/pyside6/file_open_dialogs.py	Added date_column UI field, updated file dialogs to create DataSourceConfig instances
src/midrc_react/gui/common/jsdview_base.py	Updated Signal type from dict to DataSourceConfig and added import
src/midrc_react/core/jsdconfig.py	Added date_column field with alias support to DataSourceConfig
src/midrc_react/core/excel_layout.py	Added date column handling logic and return type annotation

Comments suppressed due to low confidence (1)

src/midrc_react/core/jsdconfig.py:60

• In Pydantic v2, validate_by_name has been renamed to populate_by_name. Since the setup.py specifies pydantic>=2.7.0, you should use populate_by_name = True instead to follow Pydantic v2 conventions and avoid using deprecated configuration.

    class Config:
        validate_by_name = True

---

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[Copilot]

The FileOptionsDialog class does not have a get_data() method, but it's being called here. This will result in an AttributeError at runtime when opening Excel files. You need to either add a get_data() method to FileOptionsDialog that returns the necessary fields (name, description, remove_column_name_text), or directly access the dialog's line edit fields as was done in the previous implementation.

Suggested change

	data_source_dict = dialog.get_data()
	if hasattr(dialog, "get_data") and callable(getattr(dialog, "get_data", None)):
	data_source_dict = dialog.get_data()
	else:
	# Fallback: construct the data source dict directly from dialog attributes
	data_source_dict = {
	"name": getattr(dialog, "name", ""),
	"description": getattr(dialog, "description", ""),
	"remove_column_name_text": getattr(dialog, "remove_column_name_text", ""),
	}

[Copilot]

If self._date_column is None (which can happen since it's Optional[str] in DataSourceConfig), this will raise a TypeError when checking None not in df.columns. You should add a check to handle the None case, such as defaulting to 'date' or df.columns[0] before the comparison.

Suggested change

	if self._date_column not in df.columns:
	self._date_column = df.columns[0]
	df.rename(columns={self._date_column: 'date'}, inplace=True) # Ensure the date column is named 'date'
	# Determine which column to use as the date column, handling None and missing cases safely.
	if self._date_column is not None and self._date_column in df.columns:
	date_column = self._date_column
	elif 'date' in df.columns:
	# Prefer an existing 'date' column if present.
	date_column = 'date'
	else:
	# Fallback: use the first column in the DataFrame.
	date_column = df.columns[0]
	# Update the stored date column name to the resolved value.
	self._date_column = date_column
	df.rename(columns={date_column: 'date'}, inplace=True) # Ensure the date column is named 'date'

[Copilot]

Import of 'NumericColumnConfig' is not used.

Suggested change

	from midrc_react.core.jsdconfig import DataSourceConfig, NumericColumnConfig
	from midrc_react.core.jsdconfig import DataSourceConfig