def initialize(self) -> None:
"""
Initializes the DataGrid.
Iterates over all rows and columns, preparing cell structures.
Cells then contain a graph and data queries to leaf processors.
Upon providing data to a leaf, the leaf processor is calculated and propagated up the graph to the cell level.
"""
all_queries: List[DataQueryInfo] = []
entity_cells: List[DataCell] = []
current_row_group = None
# Loop over rows, columns
for row_index, row in enumerate(self.rows):
if isinstance(row, RowSeparator):
current_row_group = row.name
continue
entity: Entity = row.entity
cells: List[DataCell] = []
row_overrides = row.overrides
for column_index, column in enumerate(self.columns):
column_name = column.name
column_processor = column.processor
# Get all the data coordinate overrides and apply the processor override if it exists
data_overrides = _get_overrides(row_overrides, column_name,
column)
# Create the cell
cell: DataCell = DataCell(column_name, column_processor,
entity, data_overrides, column_index,
row_index, current_row_group)
# treat data cells different to entity
if isinstance(column_processor, EntityProcessor):
# store these cells to fetch entity data during poll
entity_cells.append(cell)
if isinstance(column_processor, CoordinateProcessor):
# store these cells to fetch entity data during poll
if len(data_overrides):
# Get the last in the list if more than 1 override is given
cell.processor.children['a'].set_dimensions(
data_overrides[-1].dimensions)
self._coord_processor_cells.append(cell)
else:
# append the required queries to the map
cell.build_cell_graph(all_queries)
cells.append(cell)
self._cells.extend(cells)
self.results.append(cells)
self._data_queries = all_queries
self._entity_cells = entity_cells
self.is_initialized = True
def get_test_datagrid(self):
spx, aapl, amzn = self.get_test_entities()
datagrid = DataGrid('Test DataGrid', rows=[], columns=[DataColumn('Name', None), DataColumn('Value', None)])
results = [
[DataCell('Name', None, None, None, 0, 0), DataCell('Value', None, None, None, 1, 0)],
[DataCell('Name', None, None, None, 0, 1), DataCell('Value', None, None, None, 1, 1)],
[DataCell('Name', None, None, None, 0, 2), DataCell('Value', None, None, None, 1, 2)],
]
results[0][0].value = ProcessorResult(True, spx.name)
results[0][1].value = ProcessorResult(True, np.float64(10))
results[1][0].value = ProcessorResult(True, aapl.name)
results[1][1].value = ProcessorResult(True, np.float64(0))
results[2][0].value = ProcessorResult(True, amzn.name)
results[2][1].value = ProcessorResult(True, np.float64(-10))
datagrid.results = results
return datagrid
def initialize(self) -> None:
"""
Initializes the DataGrid.
Iterates over all rows and columns, preparing cell structures.
Cells then contain a graph and data queries to leaf processors.
Upon providing data to a leaf, the leaf processor is calculated and propagated up the graph to the cell level.
"""
all_queries: List[Union[DataQueryInfo, MeasureQueryInfo]] = []
entity_cells: List[DataCell] = []
current_row_group = None
# Loop over rows, columns
for row_index, row in enumerate(self.rows):
if isinstance(row, RowSeparator):
current_row_group = row.name
continue
entity: Entity = row.entity
if isinstance(entity, Entity):
self.entity_map[entity.get_marquee_id()] = entity
else:
self.entity_map[''] = entity
cells: List[DataCell] = []
row_overrides = row.overrides
for column_index, column in enumerate(self.columns):
column_name = column.name
column_processor = column.processor
# Get all the data coordinate overrides and apply the processor override if it exists
data_overrides, value_override, processor_override = _get_overrides(row_overrides, column_name)
# Create the cell
cell: DataCell = DataCell(column_name,
column_processor,
entity,
data_overrides,
column_index,
row_index,
current_row_group)
if processor_override:
# Check if there is a processor override and apply if so
cell.processor = processor_override
if value_override:
cell.value = ProcessorResult(True, value_override.value)
cell.updated_time = get_utc_now()
elif isinstance(column_processor, EntityProcessor):
# store these cells to fetch entity data during poll
entity_cells.append(cell)
elif isinstance(column_processor, CoordinateProcessor):
# store these cells to fetch entity data during poll
if len(data_overrides):
# Get the last in the list if more than 1 override is given
cell.processor.children['a'].set_dimensions(data_overrides[-1].dimensions)
self._coord_processor_cells.append(cell)
elif column_processor.measure_processor:
all_queries.append(MeasureQueryInfo(attr='', entity=entity, processor=column_processor))
else:
# append the required queries to the map
cell.build_cell_graph(all_queries, self.rdate_entity_map)
cells.append(cell)
self._cells.extend(cells)
self.results.append(cells)
self._data_queries = all_queries
self._entity_cells = entity_cells
self.is_initialized = True