mirror of
https://github.com/NVIDIA-NeMo/DataDesigner
synced 2026-05-24 09:48:29 +00:00
f8c201e085
* update script * update headers * refactor a bit and add test script * update headers * update for edge case * update headers * add step to get file creation date * use git history to get copyright year * generation type is printed with inference parameters * fix unit test
63 lines
2.4 KiB
Python
63 lines
2.4 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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import pandas as pd
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import pytest
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from pydantic import ValidationError
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from data_designer.config.column_configs import SamplerColumnConfig
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from data_designer.config.column_types import DataDesignerColumnType
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from data_designer.config.sampler_params import SamplerType
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from data_designer.engine.analysis.column_profilers.base import (
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ColumnConfigWithDataFrame,
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ColumnProfilerMetadata,
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)
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def test_column_config_with_dataframe_valid_column_config_with_dataframe():
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df = pd.DataFrame({"test_column": [1, 2, 3]})
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column_config = SamplerColumnConfig(
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name="test_column", sampler_type=SamplerType.CATEGORY, params={"values": [1, 2, 3]}
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)
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config_with_df = ColumnConfigWithDataFrame(column_config=column_config, df=df)
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assert config_with_df.column_config.name == "test_column"
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assert "test_column" in config_with_df.df.columns
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assert config_with_df.df["test_column"].tolist() == [1, 2, 3]
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def test_column_config_with_dataframe_column_not_found_validation_error():
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df = pd.DataFrame({"other_column": [1, 2, 3]})
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column_config = SamplerColumnConfig(
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name="test_column", sampler_type=SamplerType.CATEGORY, params={"values": [1, 2, 3]}
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)
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with pytest.raises(ValidationError, match="Column 'test_column' not found in DataFrame"):
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ColumnConfigWithDataFrame(column_config=column_config, df=df)
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def test_column_config_with_dataframe_as_tuple_method():
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df = pd.DataFrame({"test_column": [1, 2, 3]})
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column_config = SamplerColumnConfig(
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name="test_column", sampler_type=SamplerType.CATEGORY, params={"values": [1, 2, 3]}
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)
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config_with_df = ColumnConfigWithDataFrame(column_config=column_config, df=df)
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column_config_result, df_result = config_with_df.as_tuple()
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assert column_config_result == column_config
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assert df_result["test_column"].tolist() == df["test_column"].tolist()
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def test_column_profiler_metadata_creation():
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metadata = ColumnProfilerMetadata(
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name="test_profiler",
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description="Test profiler",
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applicable_column_types=[DataDesignerColumnType.SAMPLER, DataDesignerColumnType.LLM_TEXT],
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)
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assert metadata.name == "test_profiler"
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assert metadata.description == "Test profiler"
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assert metadata.applicable_column_types == [DataDesignerColumnType.SAMPLER, DataDesignerColumnType.LLM_TEXT]
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