[FEATURE] Provide ability for DataAssistant to return its effective underlying BaseRuleBasedProfiler configuration #5359
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…4/GREAT-999/alexsherstinsky/rule_based_profiler/data_assistant/data_assistant_result/move_getting_expectation_suite_to_expectation_suite_class-2022_06_15-170
…/alexsherstinsky/rule_based_profiler/remove_json_serialize_directive_and_add_raw_parameter_builder_computation_results_to_json_serialized_results-2022_06_15-170
…/alexsherstinsky/rule_based_profiler/remove_json_serialize_directive_and_add_raw_parameter_builder_computation_results_to_json_serialized_results-2022_06_15-170
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…ror-changelog' into maintenance/GREAT-467/GREAT-464/GREAT-999/alexsherstinsky/rule_based_profiler/remove_json_serialize_directive_and_add_raw_parameter_builder_computation_results_to_json_serialized_results-2022_06_15-170
…ky/rule_based_profiler/remove_json_serialize_directive_and_add_raw_parameter_builder_computation_results_to_json_serialized_results-2022_06_15-170' into pre_pr-prototype/maintenance/GREAT-467/GREAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
…exsherstinsky/rule_based_profiler/enable_numeric_metric_range_multibatch_parameter_builder_to_use_evaluation_dependencies-2022_06_16-171
…EAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
…rule_based_profiler/enable_numeric_metric_range_multibatch_parameter_builder_to_use_evaluation_dependencies-2022_06_16-171' into pre_pr-prototype/maintenance/GREAT-467/GREAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
…/maintenance/GREAT-467/GREAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
…lder throughout the codebase.
…lder throughout the codebase.
…EAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
…EAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
added 13 commits
June 16, 2022 17:16
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…EAT-464/GREAT-1000/alexsherstinsky/rule_based_profiler/data_assistant/onboarding_data_assistant/performance_improvements-2022_06_15-171
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| rules: name/(configuration-dictionary) to modify using "runtime_environment" | ||
| kwargs: additional/override directives supplied at runtime | ||
| batch_request: Explicit batch_request used to supply data at runtime | ||
| kwargs: additional/override directives supplied at runtime (using "runtime_environment") | ||
| "kwargs" directives structure: |
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Very helpful to include this. Thank you Alex
| CARDINALITY_LIMIT_MODE = "cardinality_limit_mode" | ||
| MAX_UNIQUE_VALUES = "max_unique_values" |
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Not sure if I missed this, but I was wondering if these values were actually used in this PR.
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@Shinnnyshinshin this is for runtime_environment (the kwargs into DataAssistant.run(). Thanks!
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cdkini,
anthonyburdi and
donaldheppner
…based_profiler/data_assistant/provide_ability_to_obtain_defined_effective_underlying_rule_based_profiler_configuration-2022_06_21-178
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…-context-logict-abstract * develop: [MAINTENANCE] Move `_apply_global_config_overrides()` to AbstractDataContext (#5285) chore: update linter thresholds (#5367) [MAINTENANCE] Reduce output amount in Jupyter notebooks when displaying DataAssistantResult (#5362) [RELEASE] 0.15.11 (#5361) chore: update gh action (#5363) [MAINTENANCE] Include only essential public methods in DataAssistantResult class (and its descendants) (#5360) [FEATURE] Provide ability for DataAssistant to return its effective underlying BaseRuleBasedProfiler configuration (#5359) [FEATURE] Update `add_datasource` to leverage the `DatasourceStore` (#5334)
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Scope
By returning
JSONconfiguration of its underlying Rule-Based Profiler by aDataAssistant, it becomes possible to introspect thisJSONstructure and determineruntime-environmentoverrides programmatically.Usage Example:
By default ,
JSON-formatted structure is returned. Other available formats are as perConfigOutputModesingreat_expectations/core/config_peer.py.Please annotate your PR title to describe what the PR does, then give a brief bulleted description of your PR below. PR titles should begin with [BUGFIX], [FEATURE], [DOCS], or [MAINTENANCE]. If a new feature introduces breaking changes for the Great Expectations API or configuration files, please also add [BREAKING]. You can read about the tags in our contributor checklist.
Changes proposed in this pull request:
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