diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 3f3d3337..32cb6fed 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -186,6 +186,8 @@ This package uses [Great Expectations](https://greatexpectations.io/) to validat - You can prevent Great Expectations from running for a dataset by setting `gx_enabled: false` in the configuration for the dataset. 1. Test data processing by running `adt test_config.yaml --upload` and ensure that HTML reports with all expectations are generated and uploaded to the proper folder in Synapse. +**Note:** If you are adding a new expectation and you want to allow for "fuzzy validation" (e.g. you expect X% of the values in a column to match the expectation, but the remaining Y% are allowed to not match), you will need to make use of the `mostly` [parameter](https://docs.greatexpectations.io/docs/0.18/reference/learn/expectations/standard_arguments/#mostly). This package is set up to surface "warnings" for instances where the `mostly` parameter is used to show users which expectations have some failed values although the overall validation still passes. + #### Custom Expectations This repository is currently home to three custom expectations that were created for use on `agora-data-tools` datasets: diff --git a/Pipfile.lock b/Pipfile.lock index fa9404a2..5c2e1713 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -38,11 +38,19 @@ }, "anyio": { "hashes": [ - "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94", - "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7" + "sha256:2f834749c602966b7d456a7567cafcb309f96482b5081d14ac93ccd457f9dd48", + "sha256:ea60c3723ab42ba6fff7e8ccb0488c898ec538ff4df1f1d5e642c3601d07e352" ], - "markers": "python_version >= '3.8'", - "version": "==4.4.0" + "markers": "python_version >= '3.9'", + "version": "==4.7.0" + }, + "appnope": { + "hashes": [ + "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee", + "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c" + ], + "markers": "platform_system == 'Darwin'", + "version": "==0.1.4" }, "argon2-cffi": { "hashes": [ @@ -89,10 +97,11 @@ }, "asttokens": { "hashes": [ - "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24", - "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0" + "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7", + "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2" ], - "version": "==2.4.1" + "markers": "python_version >= '3.8'", + "version": "==3.0.0" }, "async-lru": { "hashes": [ @@ -102,21 +111,29 @@ "markers": "python_version >= '3.8'", "version": "==2.0.4" }, + "asyncio-atexit": { + "hashes": [ + "sha256:1d0c71544b8ee2c484d322844ee72c0875dde6f250c0ed5b6993592ab9f7d436", + "sha256:d93d5f7d5633a534abd521ce2896ed0fbe8de170bb1e65ec871d1c20eac9d376" + ], + "markers": "python_version >= '3.6'", + "version": "==1.0.1" + }, "attrs": { "hashes": [ - "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30", - "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1" + "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346", + "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2" ], "markers": "python_version >= '3.7'", - "version": "==23.2.0" + "version": "==24.2.0" }, "babel": { "hashes": [ - "sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb", - "sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413" + "sha256:368b5b98b37c06b7daf6696391c3240c938b37767d4584413e8438c5c435fa8b", + "sha256:d1f3554ca26605fe173f3de0c65f750f5a42f924499bf134de6423582298e316" ], "markers": "python_version >= '3.8'", - "version": "==2.15.0" + "version": "==2.16.0" }, "backoff": { "hashes": [ @@ -136,188 +153,203 @@ }, "bleach": { "hashes": [ - "sha256:0a31f1837963c41d46bbf1331b8778e1308ea0791db03cc4e7357b97cf42a8fe", - "sha256:3225f354cfc436b9789c66c4ee030194bee0568fbf9cbdad3bc8b5c26c5f12b6" + "sha256:117d9c6097a7c3d22fd578fcd8d35ff1e125df6736f554da4e432fdd63f31e5e", + "sha256:123e894118b8a599fd80d3ec1a6d4cc7ce4e5882b1317a7e1ba69b56e95f991f" ], - "markers": "python_version >= '3.8'", - "version": "==6.1.0" + "markers": "python_version >= '3.9'", + "version": "==6.2.0" }, "certifi": { "hashes": [ - "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516", - "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56" + "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8", + "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9" ], "markers": "python_version >= '3.6'", - "version": "==2024.6.2" + "version": "==2024.8.30" }, "cffi": { "hashes": [ - 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- "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19", - "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c" + "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4", + "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931" ], - "markers": "python_version >= '3.8'", - "version": "==3.19.2" + "markers": "python_version >= '3.9'", + "version": "==3.21.0" } } } diff --git a/gx_suite_definitions/gene_info.ipynb b/gx_suite_definitions/gene_info.ipynb index 1f0ece5b..64b8c083 100644 --- a/gx_suite_definitions/gene_info.ipynb +++ b/gx_suite_definitions/gene_info.ipynb @@ -236,7 +236,7 @@ "validator.expect_column_values_to_be_of_type(\"median_expression\", \"str\")\n", "with open(\"../src/agoradatatools/great_expectations/gx/json_schemas/gene_info/median_expression.json\", \"r\") as file:\n", " median_expression_schema = json.load(file)\n", - "validator.expect_column_values_to_match_json_schema(\"median_expression\", json_schema=median_expression_schema)" + "validator.expect_column_values_to_match_json_schema(\"median_expression\", json_schema=median_expression_schema, mostly=0.95)" ] }, { @@ -271,7 +271,7 @@ "source": [ "# biodomains\n", "validator.expect_column_values_to_be_of_type(\"biodomains\", \"list\")\n", - "validator.expect_column_values_to_have_list_members_of_type(column=\"biodomains\", member_type=\"str\")\n", + "validator.expect_column_values_to_have_list_members_of_type(column=\"biodomains\", member_type=\"str\", mostly=0.95)\n", "validator.expect_column_values_to_have_list_members(column=\"biodomains\", list_members={\n", " 'Apoptosis',\n", " 'Vasculature',\n", @@ -350,7 +350,7 @@ "outputs": [], "source": [ "# uniprotkb_accessions\n", - "validator.expect_column_values_to_be_of_type(\"uniprotkb_accessions\", \"list\")\n", + "validator.expect_column_values_to_be_of_type(\"uniprotkb_accessions\", \"list\", mostly=0.95)\n", "validator.expect_column_values_to_have_list_members_of_type(column=\"uniprotkb_accessions\", member_type=\"str\")" ] }, diff --git a/setup.cfg b/setup.cfg index 86a94bba..56e163cf 100644 --- a/setup.cfg +++ b/setup.cfg @@ -36,7 +36,7 @@ install_requires = pandas~=2.0.0 numpy~=1.21 setuptools~=70.0.0 - synapseclient~=4.0.0 + synapseclient==4.4.1 PyYAML~=6.0 pyarrow~=14.0.1 typer~=0.7.0 diff --git a/src/agoradatatools/great_expectations/gx/expectations/gene_info.json b/src/agoradatatools/great_expectations/gx/expectations/gene_info.json index 231acf9b..54b5362b 100644 --- a/src/agoradatatools/great_expectations/gx/expectations/gene_info.json +++ b/src/agoradatatools/great_expectations/gx/expectations/gene_info.json @@ -411,7 +411,8 @@ "array", "null" ] - } + }, + "mostly": 0.95 }, "meta": {} }, @@ -494,7 +495,8 @@ "expectation_type": "expect_column_values_to_have_list_members_of_type", "kwargs": { "column": "biodomains", - "member_type": "str" + "member_type": "str", + "mostly": 0.95 }, "meta": {} }, @@ -503,25 +505,25 @@ "kwargs": { "column": "biodomains", "list_members": [ - "Oxidative Stress", + "Myelination", + "Vasculature", "Synapse", - "Metal Binding and Homeostasis", + "Immune Response", + "DNA Repair", "Autophagy", - "RNA Spliceosome", - "APP Metabolism", - "Apoptosis", "Endolysosome", - "Vasculature", - "DNA Repair", - "Immune Response", + "Proteostasis", + "Mitochondrial Metabolism", + "Cell Cycle", + "Epigenetic", "Lipid Metabolism", + "Metal Binding and Homeostasis", + "RNA Spliceosome", "Tau Homeostasis", - "Myelination", - "Epigenetic", - "Mitochondrial Metabolism", - "Proteostasis", - "Structural Stabilization", - "Cell Cycle" + "Apoptosis", + "Oxidative Stress", + "APP Metabolism", + "Structural Stabilization" ] }, "meta": {} @@ -629,6 +631,7 @@ "expectation_type": "expect_column_values_to_be_of_type", "kwargs": { "column": "uniprotkb_accessions", + "mostly": 0.95, "type_": "list" }, "meta": {} diff --git a/src/agoradatatools/gx.py b/src/agoradatatools/gx.py index 9f9ab6bc..1d4ae9ec 100644 --- a/src/agoradatatools/gx.py +++ b/src/agoradatatools/gx.py @@ -17,10 +17,22 @@ class GreatExpectationsRunner: - """Class to run great expectations on a dataset and upload the HTML report to Synapse""" + """Class to run great expectations on a dataset and upload the HTML report to Synapse + + Attributes: + failures (bool): Whether or not the GX run had any failed expectations. + failure_message (str): Message of the GX run if any expectations failed. + warnings (bool): Whether or not the GX run had any warnings. + warning_message (str): Summary message for the GX run if any expectations had warnings. + report_file (str): Synapse ID of the GX report file. + report_version (int): Version number of the GX report file. + report_link (str): URL of the specific version of the GX report file. + """ failures: bool = False failure_message: Optional[str] = None + warnings: bool = False + warning_message: Optional[str] = None report_file: Optional[str] = None report_version: Optional[int] = None report_link: Optional[str] = None @@ -67,7 +79,7 @@ def _get_data_context_location(self) -> str: gx_directory = os.path.join(script_dir, "great_expectations") return gx_directory - def _check_if_expectation_suite_exists(self) -> bool: + def check_if_expectation_suite_exists(self) -> bool: """Checks if the expectation suite exists in the great_expectations workspace""" exists = ( self.expectation_suite_name in self.context.list_expectation_suite_names() @@ -78,7 +90,7 @@ def _check_if_expectation_suite_exists(self) -> bool: ) return exists - def _get_results_path(self, checkpoint_result: CheckpointResult) -> str: + def get_results_path(self, checkpoint_result: CheckpointResult) -> str: """Gets the path to the most recent HTML report for a checkpoint, copies it to a Synapse-API friendly name, and returns the new path @@ -106,7 +118,7 @@ def _get_results_path(self, checkpoint_result: CheckpointResult) -> str: shutil.copy(original_results_path, new_results_path) return new_results_path - def _upload_results_file_to_synapse(self, results_path: str) -> None: + def upload_results_file_to_synapse(self, results_path: str) -> None: """Uploads a results file to Synapse. Assigns class attributes associated with the report file. @@ -148,43 +160,61 @@ def convert_nested_columns_to_json( df[column] = df[column].apply(json.dumps) return df - def get_failed_expectations(self, checkpoint_result: CheckpointResult) -> str: - """Gets the failed expectations from a CheckpointResult and returns them as a formatted string + def set_warnings_and_failures(self, checkpoint_result: CheckpointResult) -> None: + """Sets class attributes for warnings and failures given a CheckpointResult Args: checkpoint_result (CheckpointResult): CheckpointResult object - - Returns: - fail_message (str): String with information on which fields and expectations failed """ + warning_dict = {self.expectation_suite_name: {}} fail_dict = {self.expectation_suite_name: {}} expectation_results = checkpoint_result.list_validation_results()[0]["results"] + for result in expectation_results: - if not result["success"]: - column = result["expectation_config"]["kwargs"]["column"] - failed_expectation = result["expectation_config"]["expectation_type"] - if not fail_dict[self.expectation_suite_name].get(column, None): - fail_dict[self.expectation_suite_name][column] = [] - fail_dict[self.expectation_suite_name][column].append( - failed_expectation + column = result["expectation_config"]["kwargs"].get( + "column", + "/".join(result["expectation_config"]["kwargs"].get("column_list", [])), + ) + expectation = result["expectation_config"]["expectation_type"] + if result["success"]: + if result["result"].get("partial_unexpected_list", None): + warning_dict[self.expectation_suite_name].setdefault( + column, [] + ).append(expectation) + else: + fail_dict[self.expectation_suite_name].setdefault(column, []).append( + expectation ) + + self.warning_message, self.warnings = self._generate_message( + warning_dict, "warnings" + ) + self.failure_message, self.failures = self._generate_message( + fail_dict, "failures" + ) + + def _generate_message( + self, result_dict: dict, message_type: str + ) -> typing.Tuple[str, bool]: + """Generate message and status for warnings or failures.""" messages = [] - for _, fields_dict in fail_dict.items(): - for field, failed_expectations in fields_dict.items(): + for suite_name, fields_dict in result_dict.items(): + for field, expectations in fields_dict.items(): messages.append( - f"{field} has failed expectations {', '.join(failed_expectations)}" + f"In the {suite_name} dataset, '{field}' has failed values for expectations {', '.join(expectations)}" ) - - fail_message = ("Great Expectations data validation has failed: ") + "; ".join( - messages + message = ( + (f"Great Expectations data validation has the following {message_type}: ") + + "; ".join(messages) + if messages + else None ) - - return fail_message + return message, bool(message) def run(self) -> None: """Run great expectations on a dataset and upload the results to Synapse.""" - if not self._check_if_expectation_suite_exists(): + if not self.check_if_expectation_suite_exists(): return logger.info(f"Running data validation on {self.expectation_suite_name}") @@ -209,11 +239,9 @@ def run(self) -> None: logger.info( f"Data validation complete for {self.expectation_suite_name}. Uploading results to Synapse." ) - latest_reults_path = self._get_results_path(checkpoint_result) + latest_reults_path = self.get_results_path(checkpoint_result) - if self.upload_folder: - self._upload_results_file_to_synapse(latest_reults_path) + self.set_warnings_and_failures(checkpoint_result) - if not checkpoint_result.success: - self.failures = True - self.failure_message = self.get_failed_expectations(checkpoint_result) + if self.upload_folder: + self.upload_results_file_to_synapse(latest_reults_path) diff --git a/src/agoradatatools/process.py b/src/agoradatatools/process.py index 39a60e9a..3fd7951a 100644 --- a/src/agoradatatools/process.py +++ b/src/agoradatatools/process.py @@ -160,6 +160,8 @@ def process_dataset( ), gx_failures=gx_runner.failures, gx_failure_message=gx_runner.failure_message, + gx_warnings=gx_runner.warnings, + gx_warning_message=gx_runner.warning_message, ) if upload and not gx_runner.failures: diff --git a/src/agoradatatools/reporter.py b/src/agoradatatools/reporter.py index fd321650..bdea3602 100644 --- a/src/agoradatatools/reporter.py +++ b/src/agoradatatools/reporter.py @@ -22,6 +22,8 @@ class DatasetReport: gx_report_link: URL of the specific version of the GX report file. gx_failures: Whether or not the GX run had any failed expectations. gx_failure_message: Message of the GX run if any expectations failed. + gx_warnings: Whether or not the GX run had any warnings. + gx_warning_message: Summary message for the GX run if any expectations had warnings. adt_output_file: Synapse ID of the ADT output file. adt_output_version: Version number of the ADT output file. adt_output_link: URL of the specific version of the ADT output file. @@ -39,6 +41,8 @@ class DatasetReport: gx_report_link: Optional[str] = field(default=None) gx_failures: Optional[bool] = field(default=False) gx_failure_message: Optional[str] = field(default=None) + gx_warnings: Optional[bool] = field(default=False) + gx_warning_message: Optional[str] = field(default=None) adt_output_file: Optional[str] = field(default=None) adt_output_version: Optional[int] = field(default=None) adt_output_link: Optional[str] = field(default=None) diff --git a/tests/test_assets/gx/checkpoint_result_fail.json b/tests/test_assets/gx/checkpoint_result_fail.json index 968ffb61..bde673b4 100644 --- a/tests/test_assets/gx/checkpoint_result_fail.json +++ b/tests/test_assets/gx/checkpoint_result_fail.json @@ -64,7 +64,7 @@ } }, { - "success": false, + "success": true, "expectation_config": { "expectation_type": "expect_column_value_lengths_to_equal", "kwargs": { diff --git a/tests/test_assets/gx/checkpoint_result_pass.json b/tests/test_assets/gx/checkpoint_result_pass.json index 0059b5ae..2666be77 100644 --- a/tests/test_assets/gx/checkpoint_result_pass.json +++ b/tests/test_assets/gx/checkpoint_result_pass.json @@ -76,11 +76,9 @@ }, "result": { "element_count": 15991, - "unexpected_count": 1, - "unexpected_percent": 0.006253517603652055, - "partial_unexpected_list": [ - "ENSG00" - ], + "unexpected_count": 0, + "unexpected_percent": 0.0, + "partial_unexpected_list": [], "missing_count": 0, "missing_percent": 0.0, "unexpected_percent_total": 0.006253517603652055, @@ -115,11 +113,9 @@ }, "result": { "element_count": 15991, - "unexpected_count": 1, - "unexpected_percent": 0.006253517603652055, - "partial_unexpected_list": [ - "ENSG00" - ], + "unexpected_count": 0, + "unexpected_percent": 0.0, + "partial_unexpected_list": [], "missing_count": 0, "missing_percent": 0.0, "unexpected_percent_total": 0.006253517603652055, diff --git a/tests/test_gx.py b/tests/test_gx.py index ba2e335e..bf4bc290 100644 --- a/tests/test_gx.py +++ b/tests/test_gx.py @@ -47,6 +47,8 @@ def setup_method(self, syn): def test_that_an_initialized_runner_has_the_attributes_it_should(self, syn): assert self.good_runner.failures is False assert self.good_runner.failure_message is None + assert self.good_runner.warnings is False + assert self.good_runner.warning_message is None assert self.good_runner.report_file is None assert self.good_runner.report_version is None assert self.good_runner.report_link is None @@ -79,12 +81,12 @@ def test_that_get_data_context_location_returns_the_path_to_the_gx_directory( def test_check_if_expectation_suite_exists_returns_false_when_the_expectation_suite_does_not_exist( self, ): - assert self.bad_runner._check_if_expectation_suite_exists() is False + assert self.bad_runner.check_if_expectation_suite_exists() is False def test_check_if_expectation_suite_exists_returns_true_when_the_expectation_suite_exists( self, ): - assert self.good_runner._check_if_expectation_suite_exists() is True + assert self.good_runner.check_if_expectation_suite_exists() is True def test_get_results_path(self): expected = ( @@ -109,7 +111,7 @@ def test_get_results_path(self): ) as patch_list_validation_result_identifiers, patch.object( shutil, "copy" ) as patch_copy: - result = self.good_runner._get_results_path(mocked_checkpoint_result) + result = self.good_runner.get_results_path(mocked_checkpoint_result) patch_list_validation_result_identifiers.assert_called_once() patch_copy.assert_called_once_with( self.good_runner.validations_path + "/test/path/to/file.html", @@ -124,7 +126,7 @@ def test_upload_results_file_to_synapse(self): "store", return_value=File(parent="syn456", id="syn123", versionNumber=1), ) as patch_syn_store: - self.good_runner._upload_results_file_to_synapse("test_path") + self.good_runner.upload_results_file_to_synapse("test_path") patch_syn_store.assert_called_once_with( File(path="test_path", parent=self.good_runner.upload_folder), activity=Activity( @@ -153,22 +155,76 @@ def test_that_convert_nested_columns_to_json_does_nothing_if_no_nested_columns( result = self.good_runner.convert_nested_columns_to_json(df, []) pd.testing.assert_frame_equal(result, df) - def test_get_failed_expectations_with_failed_checkpoint_result(self): - expected = ( - "Great Expectations data validation has failed: " - "ensembl_gene_id has failed expectations expect_column_value_lengths_to_equal, " - "expect_column_values_to_match_regex" + def test_generate_message_returns_formatted_strings_as_expected(self): + result_dict = { + "test_suite": {"test_column": ["expect_column_values_to_be_unique"]} + } + test_warn_message, test_warn_status = self.good_runner._generate_message( + result_dict, "warnings" + ) + assert ( + test_warn_message + == "Great Expectations data validation has the following warnings: " + "In the test_suite dataset, 'test_column' has failed values for " + "expectations expect_column_values_to_be_unique" + ) + assert test_warn_status is True + + test_fail_message, test_fail_status = self.good_runner._generate_message( + result_dict, "failures" + ) + assert ( + test_fail_message + == "Great Expectations data validation has the following failures: " + "In the test_suite dataset, 'test_column' has failed values for " + "expectations expect_column_values_to_be_unique" + ) + assert test_fail_status is True + + def test_generate_message_returns_none_if_no_messages(self): + result_dict = {} + test_warn_message, test_warn_status = self.good_runner._generate_message( + result_dict, "warnings" ) - fail_message = self.good_runner.get_failed_expectations( - self.failed_checkpoint_result + assert test_warn_message is None + assert test_warn_status is False + + test_fail_message, test_fail_status = self.good_runner._generate_message( + result_dict, "failures" + ) + assert test_fail_message is None + assert test_fail_status is False + + def test_set_warnings_and_failures_changes_no_attributes_if_everything_passes(self): + self.good_runner.set_warnings_and_failures(self.passed_checkpoint_result) + assert self.good_runner.warnings is False + assert self.good_runner.warning_message is None + assert self.good_runner.failures is False + assert self.good_runner.failure_message is None + + def test_set_warnings_and_failures_changes_attributes_if_there_are_warnings_and_failures( + self, + ): + self.good_runner.set_warnings_and_failures(self.failed_checkpoint_result) + assert self.good_runner.warnings is True + assert ( + self.good_runner.warning_message + == "Great Expectations data validation has the following warnings: " + "In the metabolomics dataset, 'ensembl_gene_id' has failed values for " + "expectations expect_column_value_lengths_to_equal" + ) + assert self.good_runner.failures is True + assert self.good_runner.failure_message == ( + "Great Expectations data validation has the following failures: " + "In the metabolomics dataset, 'ensembl_gene_id' has failed values for " + "expectations expect_column_values_to_match_regex" ) - assert fail_message == expected def test_run_when_expectation_suite_exists_and_nested_columns( self, ): with patch.object( - self.good_runner, "_check_if_expectation_suite_exists", return_value=True + self.good_runner, "check_if_expectation_suite_exists", return_value=True ) as patch_check_if_expectation_suite_exists, patch.object( pd, "read_json", return_value=pd.DataFrame() ) as patch_read_json, patch.object( @@ -176,16 +232,16 @@ def test_run_when_expectation_suite_exists_and_nested_columns( "convert_nested_columns_to_json", return_value=pd.DataFrame(), ) as patch_convert_nested_columns_to_json, patch.object( - self.good_runner, "_get_results_path", return_value="test_path" + self.good_runner, "get_results_path", return_value="test_path" ) as patch_get_results_path, patch.object( - self.good_runner, "_upload_results_file_to_synapse", return_value=None + self.good_runner, "upload_results_file_to_synapse", return_value=None ) as patch_upload_results_file_to_synapse, patch.object( Checkpoint, "run", return_value=self.passed_checkpoint_result, ) as patch_checkpoint_run, patch.object( - self.good_runner, "get_failed_expectations", return_value="test" - ) as patch_get_failed_expectations: + self.good_runner, "set_warnings_and_failures" + ) as patch_set_warnings_and_failures: self.good_runner.nested_columns = ["a"] self.good_runner.run() patch_check_if_expectation_suite_exists.assert_called_once() @@ -196,15 +252,15 @@ def test_run_when_expectation_suite_exists_and_nested_columns( patch_checkpoint_run.assert_called_once() patch_get_results_path.assert_called_once() patch_upload_results_file_to_synapse.assert_called_once_with("test_path") - patch_get_failed_expectations.assert_not_called() - assert self.good_runner.failures is False - assert self.good_runner.failure_message is None + patch_set_warnings_and_failures.assert_called_once_with( + patch_checkpoint_run.return_value + ) def test_run_when_expectation_suite_exists_and_no_nested_columns( self, ): with patch.object( - self.good_runner, "_check_if_expectation_suite_exists", return_value=True + self.good_runner, "check_if_expectation_suite_exists", return_value=True ) as patch_check_if_expectation_suite_exists, patch.object( pd, "read_json", return_value=pd.DataFrame() ) as patch_read_json, patch.object( @@ -212,16 +268,16 @@ def test_run_when_expectation_suite_exists_and_no_nested_columns( "convert_nested_columns_to_json", return_value=pd.DataFrame(), ) as patch_convert_nested_columns_to_json, patch.object( - self.good_runner, "_get_results_path", return_value="test_path" + self.good_runner, "get_results_path", return_value="test_path" ) as patch_get_results_path, patch.object( - self.good_runner, "_upload_results_file_to_synapse", return_value=None + self.good_runner, "upload_results_file_to_synapse", return_value=None ) as patch_upload_results_file_to_synapse, patch.object( Checkpoint, "run", return_value=self.passed_checkpoint_result, ) as patch_checkpoint_run, patch.object( - self.good_runner, "get_failed_expectations", return_value="test" - ) as patch_get_failed_expectations: + self.good_runner, "set_warnings_and_failures" + ) as patch_set_warnings_and_failures: self.good_runner.run() patch_check_if_expectation_suite_exists.assert_called_once() patch_read_json.assert_called_once_with( @@ -231,15 +287,15 @@ def test_run_when_expectation_suite_exists_and_no_nested_columns( patch_checkpoint_run.assert_called_once() patch_get_results_path.assert_called_once() patch_upload_results_file_to_synapse.assert_called_once_with("test_path") - patch_get_failed_expectations.assert_not_called() - assert self.good_runner.failures is False - assert self.good_runner.failure_message is None + patch_set_warnings_and_failures.assert_called_once_with( + self.passed_checkpoint_result + ) def test_that_run_does_not_complete_when_check_if_expectation_suite_exists_is_false( self, ): with patch.object( - self.good_runner, "_check_if_expectation_suite_exists", return_value=False + self.good_runner, "check_if_expectation_suite_exists", return_value=False ) as patch_check_if_expectation_suite_exists, patch.object( pd, "read_json", return_value=pd.DataFrame() ) as patch_read_json, patch.object( @@ -247,15 +303,15 @@ def test_that_run_does_not_complete_when_check_if_expectation_suite_exists_is_fa "convert_nested_columns_to_json", return_value=pd.DataFrame(), ) as patch_convert_nested_columns_to_json, patch.object( - self.good_runner, "_get_results_path", return_value="test_path" + self.good_runner, "get_results_path", return_value="test_path" ) as patch_get_results_path, patch.object( - self.good_runner, "_upload_results_file_to_synapse", return_value=None + self.good_runner, "upload_results_file_to_synapse", return_value=None ) as patch_upload_results_file_to_synapse, patch.object( Checkpoint, "run", ) as patch_checkpoint_run, patch.object( - self.good_runner, "get_failed_expectations", return_value="test" - ) as patch_get_failed_expectations: + self.good_runner, "set_warnings_and_failures" + ) as patch_set_warnings_and_failures: self.good_runner.run() patch_check_if_expectation_suite_exists.assert_called_once() patch_read_json.assert_not_called() @@ -263,15 +319,13 @@ def test_that_run_does_not_complete_when_check_if_expectation_suite_exists_is_fa patch_checkpoint_run.assert_not_called() patch_get_results_path.assert_not_called() patch_upload_results_file_to_synapse.assert_not_called() - patch_get_failed_expectations.assert_not_called() - assert self.good_runner.failures is False - assert self.good_runner.failure_message is None + patch_set_warnings_and_failures.assert_not_called() - def test_run_when_validation_fails( + def test_run_when_validation_fails_and_has_warnings( self, ): with patch.object( - self.good_runner, "_check_if_expectation_suite_exists", return_value=True + self.good_runner, "check_if_expectation_suite_exists", return_value=True ) as patch_check_if_expectation_suite_exists, patch.object( pd, "read_json", return_value=pd.DataFrame() ) as patch_read_json, patch.object( @@ -279,16 +333,16 @@ def test_run_when_validation_fails( "convert_nested_columns_to_json", return_value=pd.DataFrame(), ) as patch_convert_nested_columns_to_json, patch.object( - self.good_runner, "_get_results_path", return_value="test_path" + self.good_runner, "get_results_path", return_value="test_path" ) as patch_get_results_path, patch.object( - self.good_runner, "_upload_results_file_to_synapse", return_value=None + self.good_runner, "upload_results_file_to_synapse", return_value=None ) as patch_upload_results_file_to_synapse, patch.object( Checkpoint, "run", return_value=self.failed_checkpoint_result, ) as patch_checkpoint_run, patch.object( - self.good_runner, "get_failed_expectations", return_value="test" - ) as patch_get_failed_expectations: + self.good_runner, "set_warnings_and_failures" + ) as patch_set_warnings_and_failures: self.good_runner.run() patch_check_if_expectation_suite_exists.assert_called_once() patch_read_json.assert_called_once_with(self.good_runner.dataset_path) @@ -296,17 +350,15 @@ def test_run_when_validation_fails( patch_checkpoint_run.assert_called_once() patch_get_results_path.assert_called_once() patch_upload_results_file_to_synapse.assert_called_once_with("test_path") - patch_get_failed_expectations.assert_called_once_with( + patch_set_warnings_and_failures.assert_called_once_with( patch_checkpoint_run.return_value ) - assert self.good_runner.failures is True - assert self.good_runner.failure_message == "test" def test_that_that_files_are_not_uploaded_when_upload_folder_is_none( self, ): with patch.object( - self.good_runner, "_check_if_expectation_suite_exists", return_value=True + self.good_runner, "check_if_expectation_suite_exists", return_value=True ) as patch_check_if_expectation_suite_exists, patch.object( pd, "read_json", return_value=pd.DataFrame() ) as patch_read_json, patch.object( @@ -314,16 +366,16 @@ def test_that_that_files_are_not_uploaded_when_upload_folder_is_none( "convert_nested_columns_to_json", return_value=pd.DataFrame(), ) as patch_convert_nested_columns_to_json, patch.object( - self.good_runner, "_get_results_path", return_value="test_path" + self.good_runner, "get_results_path", return_value="test_path" ) as patch_get_results_path, patch.object( - self.good_runner, "_upload_results_file_to_synapse", return_value=None + self.good_runner, "upload_results_file_to_synapse", return_value=None ) as patch_upload_results_file_to_synapse, patch.object( Checkpoint, "run", return_value=self.passed_checkpoint_result, ) as patch_checkpoint_run, patch.object( - self.good_runner, "get_failed_expectations", return_value="test" - ) as patch_get_failed_expectations: + self.good_runner, "set_warnings_and_failures" + ) as patch_set_warnings_and_failures: self.good_runner.upload_folder = None self.good_runner.run() patch_check_if_expectation_suite_exists.assert_called_once() @@ -332,6 +384,6 @@ def test_that_that_files_are_not_uploaded_when_upload_folder_is_none( patch_checkpoint_run.assert_called_once() patch_get_results_path.assert_called_once() patch_upload_results_file_to_synapse.assert_not_called() - patch_get_failed_expectations.assert_not_called() - assert self.good_runner.failures is False - assert self.good_runner.failure_message is None + patch_set_warnings_and_failures.assert_called_once_with( + self.passed_checkpoint_result + )