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updated insight names
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src/datapilot/core/platforms/dbt/insights/checks/check_column_desc_are_same.py

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class CheckColumnDescAreSame(ChecksInsight):
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NAME = "Column descriptions consistent for same column names"
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NAME = "column_desc_mismatch"
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ALIAS = "column_descriptions_are_same"
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DESCRIPTION = "Column description for the same column name should be same "
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REASON_TO_FLAG = (

src/datapilot/core/platforms/dbt/insights/checks/check_column_name_contract.py

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class CheckColumnNameContract(ChecksInsight):
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NAME = "Column name follows contract pattern"
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NAME = "column_name_contract"
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ALIAS = "column_name_contract"
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DESCRIPTION = "Column names should adhere to the contract pattern defined for the data type. "
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REASON_TO_FLAG = (

src/datapilot/core/platforms/dbt/insights/checks/check_macro_args_have_desc.py

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class CheckMacroArgsHaveDesc(ChecksInsight):
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NAME = "Check macro arguments has description"
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NAME = "macro_arg_no_desc"
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ALIAS = "check_macro_args_have_desc"
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DESCRIPTION = "Macro arguments should have a description. "
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REASON_TO_FLAG = "Clear descriptions for macro arguments are crucial as they prevent misunderstandings, enhance user comprehension, and simplify maintenance. This leads to more accurate data analysis and efficient workflows."

src/datapilot/core/platforms/dbt/insights/checks/check_macro_has_desc.py

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class CheckMacroHasDesc(ChecksInsight):
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NAME = "Macro has documentation"
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NAME = "macro_no_docs"
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ALIAS = "check_macro_has_desc"
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DESCRIPTION = "Macros should be documented."
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REASON_TO_FLAG = "Undocumented macros can cause misunderstandings and inefficiencies in data modeling and analysis, as they make it difficult to understand their purpose and usage. Clear descriptions are vital for accuracy and streamlined workflow."

src/datapilot/core/platforms/dbt/insights/checks/check_model_has_all_columns.py

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class CheckModelHasAllColumns(ChecksInsight):
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NAME = "Model has all columns as per catalog"
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NAME = "model_column_mismatch"
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ALIAS = "check_model_has_all_columns"
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DESCRIPTION = "Models should have all the columns as per the catalog."
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REASON_TO_FLAG = (

src/datapilot/core/platforms/dbt/insights/checks/check_model_has_meta_keys.py

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class CheckModelHasMetaKeys(ChecksInsight):
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NAME = "Model has all valid keys in metadata"
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NAME = "model_invalid_meta_keys"
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ALIAS = "check_model_has_valid_meta_keys"
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DESCRIPTION = "Model always has a list of valid metadata keys."
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REASON_TO_FLAG = (

src/datapilot/core/platforms/dbt/insights/checks/check_model_has_properties_file.py

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class CheckModelHasPropertiesFile(ChecksInsight):
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NAME = "Model has properties file"
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NAME = "model_no_properties_file"
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ALIAS = "check_model_has_properties_file"
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DESCRIPTION = "Models should have a properties/schema file (.yml) defined."
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REASON_TO_FLAG = (

src/datapilot/core/platforms/dbt/insights/checks/check_model_has_tests_by_group.py

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class CheckModelHasTestsByGroup(ChecksInsight):
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NAME = "Model has tests by group"
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NAME = "model_tests_by_group"
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ALIAS = "check_model_has_tests_by_group"
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DESCRIPTION = "Check if models have a number of tests for specific test groups."
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REASON_TO_FLAG = "Models should have tests with specific groups for proper validation."

src/datapilot/core/platforms/dbt/insights/checks/check_model_has_tests_by_name.py

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class CheckModelHasTestsByName(ChecksInsight):
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NAME = "Model has tests by name"
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NAME = "model_tests_by_name"
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ALIAS = "check_model_has_tests_by_name"
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DESCRIPTION = "Checks that the model has tests with specific names."
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REASON_TO_FLAG = "Models should have tests with specific names for proper validation."

src/datapilot/core/platforms/dbt/insights/checks/check_model_has_tests_by_type.py

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class CheckModelHasTestsByType(ChecksInsight):
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NAME = "Model has tests by type"
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NAME = "model_tests_by_type"
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ALIAS = "check_model_has_tests_by_type"
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DESCRIPTION = "Checks that the model has tests with specific types."
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REASON_TO_FLAG = "Models should have tests with specific types for proper validation."

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