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refactor: improve naming consistency in DataCombiner component (#5471)

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* refactor: improve naming consistency in DataCombiner component

- Rename MergeOperation to DataOperation
- Rename component to DataCombinerComponent
- Convert operation enum values to uppercase
- Update method names for consistency

* [autofix.ci] apply automated fixes

* fix: resolved linting errors in __init__.py

* [autofix.ci] apply automated fixes

* Changed operation names to capitalize only first letter

* refactor: rename DataCombinerComponent to MergeDataComponent for better clarity and backwards compatibility

* [autofix.ci] apply automated fixes

* fix: Translate Portuguese text to English in merge_data.py

* feat: add required to data_inputs in MergeDataComponent

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: Edwin Jose <edwin.jose@datastax.com>
This commit is contained in:
Raphael Valdetaro 2025-01-16 15:37:18 -03:00 • committed by GitHub
commit b55c9f1698
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1 changed files with 23 additions and 25 deletions
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48
src/backend/base/langflow/components/processing/merge_data.py
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@ -8,50 +8,48 @@ from langflow.io import DataInput, DropdownInput, Output
from langflow.schema import DataFrame
class MergeOperation(str, Enum):
CONCATENATE = "concatenate"
APPEND = "append"
MERGE = "merge"
JOIN = "join"
class DataOperation(str, Enum):
CONCATENATE = "Concatenate"
APPEND = "Append"
MERGE = "Merge"
JOIN = "Join"
class MergeDataComponent(Component):
display_name = "Merge Data"
description = "Combines data using merge operations"
display_name = "Data Combiner"
description = "Combines data using different operations"
icon = "merge"
MIN_INPUTS_REQUIRED = 2
inputs = [
DataInput(name="data_inputs", display_name="Data Inputs", info="Dados para combinar", is_list=True),
DataInput(name="data_inputs", display_name="Data Inputs", info="Data to combine", is_list=True, required=True),
DropdownInput(
name="operation",
display_name="Merge Operation",
options=[op.value for op in MergeOperation],
value=MergeOperation.CONCATENATE.value,
display_name="Operation Type",
options=[op.value for op in DataOperation],
value=DataOperation.CONCATENATE.value,
),
]
outputs = [Output(display_name="DataFrame", name="combined_data", method="combine_data")]
outputs = [Output(display_name="DataFrame", name="merged_data", method="merge_data")]
def merge_data(self) -> DataFrame:
def combine_data(self) -> DataFrame:
if not self.data_inputs or len(self.data_inputs) < self.MIN_INPUTS_REQUIRED:
empty_dataframe = DataFrame()
self.status = empty_dataframe
return empty_dataframe
operation = MergeOperation(self.operation)
operation = DataOperation(self.operation)
try:
merged_dataframe = self._process_operation(operation)
self.status = merged_dataframe
combined_dataframe = self._process_operation(operation)
self.status = combined_dataframe
except Exception as e:
logger.error(f"Erro durante operação {operation}: {e!s}")
logger.error(f"Error during operation {operation}: {e!s}")
raise
else:
return merged_dataframe
return combined_dataframe
def _process_operation(self, operation: MergeOperation) -> DataFrame:
if operation == MergeOperation.CONCATENATE:
def _process_operation(self, operation: DataOperation) -> DataFrame:
if operation == DataOperation.CONCATENATE:
combined_data: dict[str, str | object] = {}
for data_input in self.data_inputs:
for key, value in data_input.data.items():
@ -64,11 +62,11 @@ class MergeDataComponent(Component):
combined_data[key] = value
return DataFrame([combined_data])
if operation == MergeOperation.APPEND:
if operation == DataOperation.APPEND:
rows = [data_input.data for data_input in self.data_inputs]
return DataFrame(rows)
if operation == MergeOperation.MERGE:
if operation == DataOperation.MERGE:
result_data: dict[str, str | list[str] | object] = {}
for data_input in self.data_inputs:
for key, value in data_input.data.items():
@ -81,7 +79,7 @@ class MergeDataComponent(Component):
result_data[key] = value
return DataFrame([result_data])
if operation == MergeOperation.JOIN:
if operation == DataOperation.JOIN:
combined_data = {}
for idx, data_input in enumerate(self.data_inputs, 1):
for key, value in data_input.data.items():