diff --git a/datachecks/cli/cli.py b/datachecks/cli/cli.py index ed7d3235..3c46c749 100644 --- a/datachecks/cli/cli.py +++ b/datachecks/cli/cli.py @@ -24,8 +24,10 @@ from rich.table import Table, Text from datachecks.__version__ import __version__ -from datachecks.core import Configuration, Inspect, load_configuration -from datachecks.core.common.models.metric import DataSourceMetrics +from datachecks.core import Configuration, Inspect +from datachecks.core.configuration.configuration_parser_v1 import load_configuration + +# from datachecks.core.common.models.metric import DataSourceMetrics from datachecks.core.inspect import InspectOutput from datachecks.report.dashboard import DashboardInfoBuilder, html_template from datachecks.report.models import TemplateParams @@ -51,28 +53,28 @@ def main(): default=None, help="Specify the file path for configuration", ) -# Disabled for now +# Disabled for now TODO: Enable in future for validations # @click.option( # "--auto-profile", # is_flag=True, # help="Specify if the inspection should do auto-profile of all data sources", # ) -@click.option( - "--html-report", - is_flag=True, - help="Specify if the inspection should generate HTML report", -) -@click.option( - "--report-path", - required=False, - default="datachecks_report.html", - help="Specify the file path for HTML report", -) +# @click.option( +# "--html-report", +# is_flag=True, +# help="Specify if the inspection should generate HTML report", +# ) +# @click.option( +# "--report-path", +# required=False, +# default="datachecks_report.html", +# help="Specify the file path for HTML report", +# ) def inspect( config_path: Union[str, None], # auto_profile: bool = False, # Disabled for now - html_report: bool = False, - report_path: str = "datachecks_report.html", + # html_report: bool = False, + # report_path: str = "datachecks_report.html", ): """ Starts the datachecks inspection @@ -84,8 +86,6 @@ def inspect( f"Invalid value for '-C' / '--config-path': File '{config_path}' does not exist." ) configuration: Configuration = load_configuration(config_path) - - # inspector = Inspect(configuration=configuration, auto_profile=auto_profile) # Disabled for now inspector = Inspect(configuration=configuration) print("Starting [bold blue]datachecks[/bold blue] inspection...", ":zap:") @@ -93,12 +93,13 @@ def inspect( print("[bold green]Inspection completed successfully![/bold green] :tada:") print(f"Inspection took {inspector.execution_time_taken} seconds") - if html_report: - print(f"Generating HTML report at {report_path}") - _build_html_report(inspect_output=output, report_path=report_path) - print(f"HTML report generated at {report_path}") - else: - print(_build_metric_cli_table(inspect_output=output)) + # Disable for now + # if html_report: + # print(f"Generating HTML report at {report_path}") + # _build_html_report(inspect_output=output, report_path=report_path) + # print(f"HTML report generated at {report_path}") + # else: + print(_build_metric_cli_table(inspect_output=output)) sys.exit(0) except Exception as e: @@ -108,39 +109,60 @@ def inspect( def _build_metric_cli_table(*, inspect_output: InspectOutput): table = Table( - title="List of Generated Metrics", + title="List of Validations", show_header=True, header_style="bold blue", ) - table.add_column( - "Metric Name", - style="cyan", - no_wrap=True, - ) + table.add_column("Validation Name", style="cyan", no_wrap=True) table.add_column("Data Source", style="magenta") - table.add_column("Metric Type", style="magenta") + table.add_column("Validation Type", style="magenta") table.add_column("Value", justify="right", style="green") - table.add_column("Valid", justify="right") + table.add_column("Is Valid", justify="right") table.add_column("Reason", justify="right") - for data_source_name, ds_metrics in inspect_output.metrics.items(): - row = None - if isinstance(ds_metrics, DataSourceMetrics): - for tabel_name, table_metrics in ds_metrics.table_metrics.items(): - for metric_identifier, metric in table_metrics.metrics.items(): - table.add_row( - *_build_row(metric), - ) - for index_name, index_metrics in ds_metrics.index_metrics.items(): - for metric_identifier, metric in index_metrics.metrics.items(): - table.add_row( - *_build_row(metric), - ) - else: - for metric_identifier, metric in ds_metrics.metrics.items(): - table.add_row( - *_build_row(metric), - ) + for identy, validation_info in inspect_output.validations.items(): + _validity_style = ( + "" + if validation_info.is_valid is None + else "red" + if not validation_info.is_valid + else "green" + ) + value = ( + validation_info.name, + validation_info.data_source_name, + validation_info.validation_function, + str(validation_info.value), + Text( + "-" + if validation_info.is_valid is None + else "Failed" + if not validation_info.is_valid + else "Passed", + style=_validity_style, + ), + "-" if validation_info.reason is None else validation_info.reason, + ) + table.add_row(*value) + + # for data_source_name, ds_metrics in inspect_output.metrics.items(): + # row = None + # if isinstance(ds_metrics, DataSourceMetrics): + # for tabel_name, table_metrics in ds_metrics.table_metrics.items(): + # for metric_identifier, metric in table_metrics.metrics.items(): + # table.add_row( + # *_build_row(metric), + # ) + # for index_name, index_metrics in ds_metrics.index_metrics.items(): + # for metric_identifier, metric in index_metrics.metrics.items(): + # table.add_row( + # *_build_row(metric), + # ) + # else: + # for metric_identifier, metric in ds_metrics.metrics.items(): + # table.add_row( + # *_build_row(metric), + # ) return table @@ -153,24 +175,3 @@ def _build_html_report(*, inspect_output: InspectOutput, report_path: str): with open(report_path, "w", encoding="utf-8") as out_file: out_file.write(html_template(template_params)) - - -def _build_row(metric): - _validity_style = ( - "" if metric.is_valid is None else "red" if not metric.is_valid else "green" - ) - return ( - metric.tags.get("metric_name"), - metric.data_source, - metric.metric_type, - str(metric.value), - Text( - "-" - if metric.is_valid is None - else "Failed" - if not metric.is_valid - else "Passed", - style=_validity_style, - ), - "-" if metric.reason is None else metric.reason, - ) diff --git a/datachecks/core/common/models/configuration.py b/datachecks/core/common/models/configuration.py index abd1c806..7baf0c93 100644 --- a/datachecks/core/common/models/configuration.py +++ b/datachecks/core/common/models/configuration.py @@ -11,14 +11,19 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. - +import re from dataclasses import dataclass from enum import Enum from typing import Dict, List, Optional, Union from datachecks.core.common.models.data_source_resource import Field, Index, Table from datachecks.core.common.models.metric import MetricsType -from datachecks.core.common.models.validation import Validation +from datachecks.core.common.models.validation import ( + Threshold, + Validation, + ValidationFunction, + ValidationFunctionType, +) class DataSourceType(str, Enum): @@ -33,6 +38,11 @@ class DataSourceType(str, Enum): DATABRICKS = "databricks" +class DataSourceLanguageSupport(str, Enum): + SQL = "sql" + DSL_ES = "dsl_es" + + @dataclass class DataSourceConnectionConfiguration: """ @@ -70,6 +80,84 @@ class DataSourceConfiguration: name: str type: DataSourceType connection_config: DataSourceConnectionConfiguration + language_support: Optional[DataSourceLanguageSupport] = None + + +@dataclass +class ValidationConfig: + name: str + on: str + threshold: Optional[Threshold] = None + where: Optional[str] = None + query: Optional[str] = None + regex: Optional[str] = None + values: Optional[List] = None + + def _on_field_validation(self): + if self.on is None: + raise ValueError("on field is required") + dataset_validation_functions = [ + ValidationFunction.FAILED_ROWS, + ValidationFunction.COUNT_ROWS, + ValidationFunction.COUNT_DOCUMENTS, + ValidationFunction.CUSTOM_SQL, + ValidationFunction.COMPARE_COUNT_ROWS, + ] + if self.on.strip() not in dataset_validation_functions: + self._validation_function_type = ValidationFunctionType.FIELD + if not re.match(r"^(\w+)\(([ \w-]+)\)$", self.on.strip()): + raise ValueError(f"on field must be a valid function, was {self.on}") + else: + column_validation_function = re.search( + r"^(\w+)\(([ \w-]+)\)$", self.on.strip() + ).group(1) + + if column_validation_function not in [v for v in ValidationFunction]: + raise ValueError( + f"{column_validation_function} is not a valid validation function" + ) + + if column_validation_function in dataset_validation_functions: + raise ValueError( + f"{column_validation_function} is a table function, should not have column name" + ) + + self._validation_function = ValidationFunction( + column_validation_function + ) + self._validation_field_name = re.search( + r"^(\w+)\(([ \w-]+)\)$", self.on.strip() + ).group(2) + else: + self._validation_function_type = ValidationFunctionType.DATASET + self._validation_function = ValidationFunction(self.on) + self._validation_field_name = None + + def __post_init__(self): + self._on_field_validation() + + @property + def get_validation_function(self) -> ValidationFunction: + return ValidationFunction(self._validation_function) + + @property + def get_validation_function_type(self) -> ValidationFunctionType: + return self._validation_function_type + + @property + def get_validation_field_name(self) -> str: + return self._validation_field_name if self._validation_field_name else None + + +@dataclass +class ValidationConfigByDataset: + """ + Validation configuration group + """ + + data_source: str + dataset: str + validations: Dict[str, ValidationConfig] @dataclass @@ -135,6 +223,7 @@ class Configuration: Configuration for the data checks """ - data_sources: Dict[str, DataSourceConfiguration] - metrics: Dict[str, MetricConfiguration] + data_sources: Optional[Dict[str, DataSourceConfiguration]] = None + validations: Optional[Dict[str, ValidationConfigByDataset]] = None + metrics: Optional[Dict[str, MetricConfiguration]] = None storage: Optional[MetricStorageConfiguration] = None diff --git a/datachecks/core/common/models/data_source_resource.py b/datachecks/core/common/models/data_source_resource.py index c13f0a32..96033d0e 100644 --- a/datachecks/core/common/models/data_source_resource.py +++ b/datachecks/core/common/models/data_source_resource.py @@ -16,6 +16,17 @@ from typing import Optional, Union +@dataclass +class Dataset: + """ + Dataset resource + """ + + name: str + data_source: str + description: Optional[str] = None + + @dataclass class Table: """ diff --git a/datachecks/core/common/models/validation.py b/datachecks/core/common/models/validation.py index 984e2821..61e4d53e 100644 --- a/datachecks/core/common/models/validation.py +++ b/datachecks/core/common/models/validation.py @@ -12,9 +12,11 @@ # See the License for the specific language governing permissions and # limitations under the License. +import re from dataclasses import dataclass +from datetime import datetime from enum import Enum -from typing import Optional +from typing import Dict, List, Optional, Union class ConditionType(str, Enum): @@ -37,3 +39,150 @@ class Threshold: @dataclass class Validation: threshold: Threshold + + +class ValidationFunctionType(str, Enum): + """ + ValidationFunctionType is an enum that represents the type of validation + function that is applied to a dataset or a field. + """ + + """ + DATASET validation function type applied to a dataset + """ + DATASET = "dataset" + + """ + FIELD validation function type applied to a field of the dataset + """ + FIELD = "field" + + +class ValidationFunction(str, Enum): + """ + ValidationType is an enum that represents the type of validation that is generated by a data source. + """ + + # Numeric validations 11 + MIN = "min" + MAX = "max" + AVG = "avg" + SUM = "sum" + MEDIAN = "median" + STDDEV = "stddev" + VARIANCE = "variance" + COUNT_FALSE = "count_false" + PERCENT_FALSE = "percent_false" + COUNT_TRUE = "count_true" + PERCENT_TRUE = "percent_true" + + # Reliability validations 3 + COUNT_ROWS = "count_rows" + COUNT_DOCUMENTS = "count_documents" + FRESHNESS = "freshness" + + # Uniqueness validations 2 + COUNT_DISTINCT = "count_distinct" + COUNT_DUPLICATE = "count_duplicate" + + # Completeness validations 8 + COUNT_NULL = "count_null" + COUNT_NOT_NULL = "count_not_null" + PERCENT_NULL = "percent_null" + PERCENT_NOT_NULL = "percent_not_null" + COUNT_EMPTY_STRING = "count_empty_string" + PERCENT_EMPTY_STRING = "percent_empty_string" + COUNT_NAN = "count_nan" + PERCENT_NAN = "percent_nan" + + # Custom SQL + CUSTOM_SQL = "custom_sql" + + # Validity validations 43 + # ======================================== + COUNT_INVALID_VALUES = "count_invalid_values" + PERCENT_INVALID_VALUES = "percent_invalid_values" + COUNT_VALID_VALUES = "count_valid_values" + PERCENT_VALID_VALUES = "percent_valid_values" + COUNT_INVALID_REGEX = "count_invalid_regex" + PERCENT_INVALID_REGEX = "percent_invalid_regex" + + # -- String Format + STRING_LENGTH_MAX = "string_length_max" + STRING_LENGTH_MIN = "string_length_min" + STRING_LENGTH_AVERAGE = "string_length_average" + + # -- Identification Format + + COUNT_UUID = "count_uuid" + PERCENT_UUID = "percent_uuid" + """ + Prem ID (https://permid.org/) + """ + COUNT_PERM_ID = "count_perm_id" + PERCENT_PERM_ID = "percent_perm_id" + """ + SSN (https://en.wikipedia.org/wiki/Social_Security_number#Structure) + """ + COUNT_SSN = "count_ssn" + PERCENT_SSN = "percent_ssn" + + # -- Contact Information + COUNT_USA_PHONE = "count_usa_phone" + PERCENT_USA_PHONE = "percent_usa_phone" + COUNT_USA_STATE_CODE = "count_usa_state_code" + PERCENT_USA_STATE_CODE = "percent_usa_state_code" + COUNT_USA_ZIP_CODE = "count_usa_zip_code" + PERCENT_USA_ZIP_CODE = "percent_usa_zip_code" + COUNT_EMAIL = "count_email" + PERCENT_EMAIL = "percent_email" + + # -- Financial Information + """ + https://en.wikipedia.org/wiki/SEDOL + """ + COUNT_SEDOL = "count_sedol" + PERCENT_SEDOL = "percent_sedol" + COUNT_CUSIP = "count_cusip" + PERCENT_CUSIP = "percent_cusip" + COUNT_LEI = "count_lei" + PERCENT_LEI = "percent_lei" + COUNT_FIGI = "count_figi" + PERCENT_FIGI = "percent_figi" + COUNT_ISIN = "count_isin" + PERCENT_ISIN = "percent_isin" + + # -- Time Format + COUNT_TIMESTAMP_STRING = "count_timestamp_string" + PERCENT_TIMESTAMP_STRING = "percent_timestamp_string" + COUNT_NOT_IN_FUTURE = "count_not_in_future" + PERCENT_NOT_IN_FUTURE = "percent_not_in_future" + COUNT_DATE_NOT_IN_FUTURE = "count_date_not_in_future" + PERCENT_DATE_NOT_IN_FUTURE = "percent_date_not_in_future" + + # -- Geolocation Information + COUNT_LATITUDE = "count_latitude" + PERCENT_LATITUDE = "percent_latitude" + COUNT_LONGITUDE = "count_longitude" + PERCENT_LONGITUDE = "percent_longitude" + + # CROSS Validation + COMPARE_COUNT_ROWS = "compare_count_rows" + + # Failed rows + FAILED_ROWS = "failed_rows" + + +@dataclass +class ValidationInfo: + name: str + identity: str + data_source_name: str + dataset: str + validation_function: ValidationFunction + value: Union[int, float] + timestamp: datetime + field: Optional[str] = None + is_valid: Optional[bool] = None + reason: Optional[str] = None + tags: Dict[str, str] = None diff --git a/datachecks/core/configuration/config_loader.py b/datachecks/core/configuration/config_loader.py index 3a849385..33c3eab4 100644 --- a/datachecks/core/configuration/config_loader.py +++ b/datachecks/core/configuration/config_loader.py @@ -123,8 +123,21 @@ def constructor_env_variables(loader, node): if path: with open(path, encoding=encoding) as conf_data: - return yaml.load(conf_data, Loader=loader) + yaml_data_str = conf_data.read() elif data: - return yaml.load(data, Loader=loader) + yaml_data_str = data else: raise ValueError("Either a path or data should be defined as input") + + # yaml_data_str = yaml_data_str.replace("on:", "for_temp:") + yaml_data_str_replaces = re.sub(r"\bon\b:", "for_temp:", yaml_data_str) + conf_dict = yaml.load(yaml_data_str_replaces, Loader=loader) + + for key, value in conf_dict.items(): + if key is not "data_sources" and key.startswith("validations"): + if isinstance(value, list): + for validation in value: + for k, v in validation.items(): + if "for_temp" in v: + v["on"] = v.pop("for_temp") + return conf_dict diff --git a/datachecks/core/configuration/configuration_parser_v1.py b/datachecks/core/configuration/configuration_parser_v1.py new file mode 100644 index 00000000..b61723ff --- /dev/null +++ b/datachecks/core/configuration/configuration_parser_v1.py @@ -0,0 +1,303 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import glob +import re +from abc import ABC +from pathlib import Path +from typing import Dict, List, Optional, TypeVar, Union + +from pyparsing import Combine, Group, Literal +from pyparsing import Optional as OptionalParsing +from pyparsing import Word, delimitedList, nums, oneOf + +from datachecks.core.common.errors import DataChecksConfigurationError +from datachecks.core.common.models.configuration import ( + Configuration, + DataSourceConfiguration, + DataSourceConnectionConfiguration, + DataSourceLanguageSupport, + DataSourceType, + ValidationConfig, + ValidationConfigByDataset, +) +from datachecks.core.common.models.data_source_resource import Field, Index, Table +from datachecks.core.common.models.metric import MetricsType +from datachecks.core.common.models.validation import ( + ConditionType, + Threshold, + Validation, +) +from datachecks.core.configuration.config_loader import parse_config + +CONDITION_TYPE_MAPPING = { + ">=": ConditionType.GTE, + "<=": ConditionType.LTE, + "=": ConditionType.EQ, + "<": ConditionType.LT, + ">": ConditionType.GT, +} + + +OUTPUT = TypeVar("OUTPUT") +INPUT = TypeVar("INPUT", Dict, List) + + +class ConfigParser(ABC): + def parse(self, config: INPUT) -> OUTPUT: + raise NotImplementedError + + +class DataSourceConfigParser(ConfigParser): + @staticmethod + def _data_source_connection_config_parser( + config: Dict, + ) -> DataSourceConnectionConfiguration: + connection_config = DataSourceConnectionConfiguration( + host=config["connection"].get("host"), + port=config["connection"].get("port"), + username=config["connection"].get("username"), + password=config["connection"].get("password"), + database=config["connection"].get("database"), + schema=config["connection"].get("schema"), + project=config["connection"].get("project"), + dataset=config["connection"].get("dataset"), + credentials_base64=config["connection"].get("credentials_base64"), + token=config["connection"].get("token"), + catalog=config["connection"].get("catalog"), + http_path=config["connection"].get("http_path"), + account=config["connection"].get("account"), + warehouse=config["connection"].get("warehouse"), + role=config["connection"].get("role"), + ) + return connection_config + + @staticmethod + def _check_for_duplicate_names(config_list: List): + names = [] + for config in config_list: + if config["name"] in names: + raise DataChecksConfigurationError( + f"Duplicate datasource names found: {config['name']}" + ) + names.append(config["name"]) + + def parse(self, config_list: List[Dict]) -> Dict[str, DataSourceConfiguration]: + self._check_for_duplicate_names(config_list=config_list) + data_source_configurations: Dict[str, DataSourceConfiguration] = {} + + for config in config_list: + name_ = config["name"] + data_source_type = DataSourceType(config["type"].lower()) + if data_source_type in [ + DataSourceType.ELASTICSEARCH, + DataSourceType.OPENSEARCH, + ]: + language_support = DataSourceLanguageSupport.DSL_ES + else: + language_support = DataSourceLanguageSupport.SQL + data_source_configuration = DataSourceConfiguration( + name=name_, + type=DataSourceType(config["type"].lower()), + connection_config=self._data_source_connection_config_parser( + config=config + ), + language_support=language_support, + ) + data_source_configurations[name_] = data_source_configuration + + return data_source_configurations + + +class ValidationConfigParser(ConfigParser): + def parse(self, config: Dict) -> Dict[str, ValidationConfigByDataset]: + validation_group: Dict[str, ValidationConfigByDataset] = {} + for key, validations in config.items(): + match = re.search(r"^(validations for)\s([ \w-]+)\.([ \w-]+)$", key) + if match: + data_source, dataset = match.group(2), match.group(3) + validation_dict = {} + for validation in validations: + if not isinstance(validation, dict): + raise DataChecksConfigurationError( + message=f"Validation must be a dictionary" + ) + if len(validation) != 1: + raise DataChecksConfigurationError( + message=f"Validation must have only one name" + ) + validation_name, value = next(iter(validation.items())) + + validation_config = ValidationConfig( + name=validation_name, + on=value.get("on"), + threshold=self._parse_threshold_str(value.get("threshold")) + if value.get("threshold") + else None, + where=value.get("where"), + query=value.get("query"), + regex=value.get("regex"), + values=value.get("values"), + ) + validation_dict[validation_name] = validation_config + + validation_group[ + f"{data_source}.{dataset}" + ] = ValidationConfigByDataset( + data_source=data_source, + dataset=dataset, + validations=validation_dict, + ) + return validation_group + + @staticmethod + def _parse_threshold_str(threshold: str) -> Threshold: + try: + operator = oneOf(">= <= = < >").setParseAction( + lambda t: CONDITION_TYPE_MAPPING[t[0]] + ) + number = Combine( + OptionalParsing(Literal("-")) + + Word(nums) + + OptionalParsing(Literal(".") + Word(nums)) + ).setParseAction(lambda t: float(t[0])) + + condition = operator + number + conditions = delimitedList( + Group(condition) | Group(condition + Literal("&") + condition), + delim="&", + ) + result = conditions.parseString(threshold) + return Threshold(**{operator: value for operator, value in result}) + + except Exception as e: + raise DataChecksConfigurationError( + f"Invalid threshold configuration {threshold}: {str(e)}" + ) + + +def _parse_configuration_from_dict(config_dict: Dict) -> Configuration: + try: + data_source_configurations = {} + if "data_sources" in config_dict: + data_source_configurations = DataSourceConfigParser().parse( + config_list=config_dict["data_sources"] + ) + validate_configurations = ValidationConfigParser().parse(config_dict) + + configuration = Configuration( + data_sources=data_source_configurations, validations=validate_configurations + ) + + return configuration + except Exception as ex: + raise DataChecksConfigurationError( + message=f"Failed to parse configuration: {str(ex)}" + ) + + +def load_configuration_from_yaml_str( + yaml_string: str, configuration: Optional[Configuration] = None +) -> Configuration: + """ + Load configuration from a yaml string + """ + try: + config_dict: Dict = parse_config(data=yaml_string) + except Exception as ex: + raise DataChecksConfigurationError( + message=f"Failed to parse configuration: {str(ex)}" + ) + from_dict = _parse_configuration_from_dict(config_dict=config_dict) + if configuration: + if configuration.data_sources: + configuration.data_sources.update(from_dict.data_sources) + else: + configuration.data_sources = from_dict.data_sources + if configuration.validations: + configuration.validations.update(from_dict.validations) + else: + configuration.validations = from_dict.validations + return from_dict + + +def load_configuration( + configuration_path: str, configuration: Optional[Configuration] = None +) -> Configuration: + """ + Load configuration from a yaml file + :param configuration_path: Configuration file path + :param configuration: Configuration + :return: + """ + + path = Path(configuration_path) + if not path.exists(): + raise DataChecksConfigurationError( + message=f"Configuration file {configuration_path} does not exist" + ) + if path.is_file(): + with open(configuration_path) as config_yaml_file: + yaml_string = config_yaml_file.read() + return load_configuration_from_yaml_str( + yaml_string, configuration=configuration + ) + else: + config_files = glob.glob(f"{configuration_path}/*.yaml") + if len(config_files) == 0: + raise DataChecksConfigurationError( + message=f"No configuration files found in {configuration_path}" + ) + else: + config_dict_list: List[Dict] = [] + for config_file in config_files: + with open(config_file) as config_yaml_file: + yaml_string = config_yaml_file.read() + config_dict: Dict = parse_config(data=yaml_string) + config_dict_list.append(config_dict) + + final_config_dict = { + "data_sources": [], + "metrics": [], + "storage": None, + } + for config_dict in config_dict_list: + if "data_sources" in config_dict: + final_config_dict["data_sources"].extend( + config_dict["data_sources"] + ) + if "metrics" in config_dict: + final_config_dict["metrics"].extend(config_dict["metrics"]) + if "storage" in config_dict: + final_config_dict["storage"] = config_dict["storage"] + + for key, value in config_dict.items(): + if key not in ["data_sources", "metrics", "storage"]: + if key not in final_config_dict.keys(): + final_config_dict[key] = value + else: + if isinstance(final_config_dict[key], list): + final_config_dict[key].extend(value) + + from_dict = _parse_configuration_from_dict(final_config_dict) + if configuration: + if configuration.data_sources: + configuration.data_sources.update(from_dict.data_sources) + else: + configuration.data_sources = from_dict.data_sources + if configuration.validations: + configuration.validations.update(from_dict.validations) + else: + configuration.validations = from_dict.validations + + return from_dict diff --git a/datachecks/core/datasource/base.py b/datachecks/core/datasource/base.py index 60e56a07..99221beb 100644 --- a/datachecks/core/datasource/base.py +++ b/datachecks/core/datasource/base.py @@ -13,7 +13,9 @@ # limitations under the License. from abc import ABC -from typing import Any, Dict +from typing import Any, Dict, Optional + +from datachecks.core.common.models.configuration import DataSourceLanguageSupport class DataSource(ABC): @@ -24,9 +26,17 @@ class DataSource(ABC): NUMERIC_PYTHON_TYPES_FOR_PROFILING = ["int", "float"] TEXT_PYTHON_TYPES_FOR_PROFILING = ["str"] - def __init__(self, data_source_name: str, data_connection: Dict): + def __init__( + self, + data_source_name: str, + data_connection: Dict, + language_support: Optional[ + DataSourceLanguageSupport + ] = DataSourceLanguageSupport.SQL, + ): self._data_source_name: str = data_source_name self.data_connection: Dict = data_connection + self.language_support = language_support @property def data_source_name(self) -> str: diff --git a/datachecks/core/datasource/manager.py b/datachecks/core/datasource/manager.py index e70229fb..0a68d3fd 100644 --- a/datachecks/core/datasource/manager.py +++ b/datachecks/core/datasource/manager.py @@ -16,7 +16,10 @@ from typing import Dict, List from datachecks.core.common.errors import DataChecksDataSourcesConnectionError -from datachecks.core.common.models.configuration import DataSourceConfiguration +from datachecks.core.common.models.configuration import ( + Configuration, + DataSourceConfiguration, +) from datachecks.core.datasource.base import DataSource @@ -39,10 +42,22 @@ class DataSourceManager: "mssql": "MssqlDataSource", } - def __init__(self, config: Dict[str, DataSourceConfiguration]): - self._data_source_configs: Dict[str, DataSourceConfiguration] = config + def __init__(self, config: Configuration): + self._config = config self._data_sources: Dict[str, DataSource] = {} - self._initialize_data_sources() + + def connect(self): + for name, data_source_config in self._config.data_sources.items(): + self._data_sources[data_source_config.name] = self._create_data_source( + data_source_config=data_source_config + ) + for data_source in self._data_sources.values(): + try: + data_source.connect() + except Exception as e: + raise DataChecksDataSourcesConnectionError( + f"Failed to connect to data source {data_source.data_source_name} [{str(e)}]" + ) @property def get_data_sources(self) -> Dict[str, DataSource]: @@ -52,17 +67,6 @@ def get_data_sources(self) -> Dict[str, DataSource]: """ return self._data_sources - def _initialize_data_sources(self): - """ - Initialize the data sources - :return: - """ - for name, data_source_config in self._data_source_configs.items(): - self._data_sources[data_source_config.name] = self._create_data_source( - data_source_config=data_source_config - ) - self._data_sources[data_source_config.name].connect() - def _create_data_source( self, data_source_config: DataSourceConfiguration ) -> DataSource: diff --git a/datachecks/core/inspect.py b/datachecks/core/inspect.py index 7ca86ec9..8825069b 100644 --- a/datachecks/core/inspect.py +++ b/datachecks/core/inspect.py @@ -15,7 +15,7 @@ import traceback from dataclasses import dataclass from datetime import datetime -from typing import Dict, List, Union +from typing import Dict, List, Optional, Union import requests from loguru import logger @@ -33,6 +33,11 @@ MetricValue, TableMetrics, ) +from datachecks.core.common.models.validation import ValidationInfo +from datachecks.core.configuration.configuration_parser_v1 import ( + load_configuration, + load_configuration_from_yaml_str, +) from datachecks.core.datasource.base import DataSource from datachecks.core.datasource.manager import DataSourceManager from datachecks.core.datasource.sql_datasource import SQLDataSource @@ -46,6 +51,7 @@ send_event_json, ) from datachecks.core.utils.utils import truncate_error +from datachecks.core.validation.manager import ValidationManager from datachecks.integrations.storage.local_file import LocalFileMetricRepository requests.packages.urllib3.disable_warnings( @@ -56,6 +62,7 @@ @dataclass class InspectOutput: metrics: Dict[str, Union[DataSourceMetrics, CombinedMetrics]] + validations: Dict[str, ValidationInfo] def get_metric_values(self) -> List[MetricValue]: """ @@ -104,35 +111,23 @@ def get_inspect_info(self): class Inspect: def __init__( self, - configuration: Configuration, + configuration: Optional[Configuration] = None, # auto_profile: bool = False, # Disabled for now ): - self.configuration = configuration + if configuration is None: + self.configuration = Configuration() + else: + self.configuration = configuration + + self.data_source_manager = DataSourceManager(self.configuration) + self.validation_manager = ValidationManager( + application_configs=self.configuration, + data_source_manager=self.data_source_manager, + ) + # self._auto_profile = auto_profile # Disabled for now self.execution_time_taken = 0 self.is_storage_enabled = False - try: - self.data_source_manager = DataSourceManager(configuration.data_sources) - self.data_source_names = self.data_source_manager.get_data_source_names() - self.metric_manager = MetricManager( - metric_config=configuration.metrics, - data_source_manager=self.data_source_manager, - ) - if self.configuration.storage is not None: - self.is_storage_enabled = True - self.metric_repository: MetricRepository = self._initiate_storage( - self.configuration.storage - ) - - except Exception as ex: - logger.error(f"Error while initializing Inspect: {ex}") - if is_tracking_enabled(): - event_json = create_error_event( - exception=ex, - ) - send_event_json(event_json) - traceback.print_exc(file=sys.stdout) - raise ex def _initiate_storage( self, metric_storage_config: MetricStorageConfiguration @@ -160,55 +155,6 @@ def _base_data_source_metrics(self) -> Dict[str, DataSourceMetrics]: ) return results - def _generate_data_source_profile_metrics( - self, base_datasource_metrics: Dict[str, DataSourceMetrics] - ): - """ - Generate the data source profile metrics - """ - data_sources: Dict[str, DataSource] = self.data_source_manager.get_data_sources - - # Iterate over all the data sources - for data_source_name, data_source in data_sources.items(): - if isinstance(data_source, SQLDataSource): - data_source_metrics: DataSourceMetrics = base_datasource_metrics[ - data_source_name - ] - profiler = DataSourceProfiling(data_source=data_source) - list_metrics: List[ - Union[TableMetrics, IndexMetrics] - ] = profiler.generate() - - # Add the metrics to the data source metrics - for table_or_index_metrics in list_metrics: - # If metrics is a table metrics, add it to the table metrics - if isinstance(table_or_index_metrics, TableMetrics): - if ( - table_or_index_metrics.table_name - not in data_source_metrics.table_metrics - ): - data_source_metrics.table_metrics[ - table_or_index_metrics.table_name - ] = table_or_index_metrics - else: - data_source_metrics.table_metrics[ - table_or_index_metrics.table_name - ].metrics.update(table_or_index_metrics.metrics) - - # If metrics is an index metrics, add it to the index metrics - elif isinstance(table_or_index_metrics, IndexMetrics): - if ( - table_or_index_metrics.index_name - not in data_source_metrics.index_metrics - ): - data_source_metrics.index_metrics[ - table_or_index_metrics.index_name - ] = table_or_index_metrics - else: - data_source_metrics.index_metrics[ - table_or_index_metrics.index_name - ].metrics.update(table_or_index_metrics.metrics) - @staticmethod def _prepare_results( results: List[MetricValue], @@ -264,12 +210,18 @@ def _prepare_results( expression=expression, metrics={result.identity: result} ) - def _save_all_metrics(self, metric_values: List[MetricValue]): - """ - This method will save all the metrics in the given list. Will use the repository to save the metrics. - Repository will be selected based on the configuration. - """ - self.metric_repository.save_all_metrics(metric_values) + def add_configuration_yaml_file(self, file_path: str): + load_configuration( + configuration_path=file_path, configuration=self.configuration + ) + self.validation_manager.set_validation_configs(self.configuration.validations) + + def add_validations_yaml_str(self, yaml_str: str): + configuration = load_configuration_from_yaml_str(yaml_string=yaml_str) + self.configuration.validations = configuration.validations + + def add_spark_session(self, spark_session, data_source_name: str = "spark_df"): + pass def run(self) -> InspectOutput: """ @@ -279,7 +231,14 @@ def run(self) -> InspectOutput: error = None inspect_info = None try: + self.data_source_manager.connect() + self.validation_manager.build_validations() + # Initiate the data source metrics + metric_manager = MetricManager( + metric_config=self.configuration.metrics, + data_source_manager=self.data_source_manager, + ) datasource_metrics: Dict[ str, DataSourceMetrics ] = self._base_data_source_metrics() @@ -289,14 +248,14 @@ def run(self) -> InspectOutput: combined_metric_values: List[MetricValue] = [] # generate metric values for dataset metrics and populate the datasource_metrics - for metric in self.metric_manager.metrics.values(): + for metric in metric_manager.metrics.values(): metric_value = metric.get_metric_value() if metric_value is not None: metric_values.append(metric_value) self._prepare_results(metric_values, datasource_metrics=datasource_metrics) # generate metric values for combined metrics and populate the combined_metrics - for combined_metric in self.metric_manager.combined.values(): + for combined_metric in metric_manager.combined.values(): metric_value = combined_metric.get_metric_value( metric_values=metric_values ) @@ -306,16 +265,25 @@ def run(self) -> InspectOutput: combined_metric_values, combined_metrics=combined_metrics ) - # generate metric values for profile metrics - # Disabled for now - # if self._auto_profile: - # self._generate_data_source_profile_metrics(datasource_metrics) + validation_infos: Dict[str, ValidationInfo] = {} - output = InspectOutput(metrics={**datasource_metrics, **combined_metrics}) - inspect_info = output.get_inspect_info() + for datasource, _ in self.validation_manager.get_validations.items(): + for dataset, _ in self.validation_manager.get_validations[ + datasource + ].items(): + for _, validation in self.validation_manager.get_validations[ + datasource + ][dataset].items(): + validation_info = validation.get_validation_info() + validation_infos[ + validation.get_validation_identity() + ] = validation_info - if self.is_storage_enabled: - self._save_all_metrics(output.get_metric_values()) + output = InspectOutput( + metrics={**datasource_metrics, **combined_metrics}, + validations=validation_infos, + ) + inspect_info = output.get_inspect_info() return output except Exception as ex: diff --git a/datachecks/core/metric/manager.py b/datachecks/core/metric/manager.py index fb9e33f3..41a91f08 100644 --- a/datachecks/core/metric/manager.py +++ b/datachecks/core/metric/manager.py @@ -74,20 +74,21 @@ def __init__( self.data_source_manager = data_source_manager self.metrics: Dict[str, Metric] = {} self.combined: Dict[str, Metric] = {} - self._build_metrics( - config={ - k: v - for (k, v) in metric_config.items() - if v.metric_type != MetricsType.COMBINED.value - } - ) - self._build_combined_metrics( - config={ - k: v - for (k, v) in metric_config.items() - if v.metric_type == MetricsType.COMBINED.value - } - ) + if metric_config: + self._build_metrics( + config={ + k: v + for (k, v) in metric_config.items() + if v.metric_type != MetricsType.COMBINED.value + } + ) + self._build_combined_metrics( + config={ + k: v + for (k, v) in metric_config.items() + if v.metric_type == MetricsType.COMBINED.value + } + ) def _build_metrics(self, config: Dict[str, MetricConfiguration]): for metric_name, metric_config in config.items(): diff --git a/datachecks/core/validation/__init__.py b/datachecks/core/validation/__init__.py new file mode 100644 index 00000000..95dc1b8e --- /dev/null +++ b/datachecks/core/validation/__init__.py @@ -0,0 +1,13 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/datachecks/core/validation/base.py b/datachecks/core/validation/base.py new file mode 100644 index 00000000..4c2debc2 --- /dev/null +++ b/datachecks/core/validation/base.py @@ -0,0 +1,168 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import datetime +import json +import sys +import traceback +from abc import ABC, abstractmethod +from typing import Optional, Tuple, Union + +from loguru import logger + +from datachecks.core.common.models.configuration import ( + DataSourceLanguageSupport, + ValidationConfig, +) +from datachecks.core.common.models.validation import ( + ConditionType, + ValidationFunction, + ValidationInfo, +) +from datachecks.core.datasource.base import DataSource + + +class ValidationIdentity: + @staticmethod + def generate_identity( + validation_function: ValidationFunction, + validation_name: str, + data_source_name: str = None, + dataset_name: str = None, + field_name: str = None, + ) -> str: + """ + Generate a unique identifier for a metric + """ + + identifiers = [] + + if data_source_name is not None: + identifiers.append(data_source_name) + if dataset_name: + identifiers.append(dataset_name) + if field_name: + identifiers.append(field_name) + if validation_function: + identifiers.append(validation_function.value) + if validation_name: + identifiers.append(validation_name) + return ".".join([str(p) for p in identifiers]) + + +class Validation(ABC): + """ + Validation is a class that represents a validation that is generated by a data source. + """ + + def __init__( + self, + name: str, + validation_config: ValidationConfig, + data_source: DataSource, + dataset_name: str, + field_name: str = None, + **kwargs, + ): + self.name = name + self.validation_config = validation_config + self.data_source = data_source + self.dataset_name = dataset_name + self.field_name = field_name + + self.query = validation_config.query + + self.threshold = validation_config.threshold + self.where_filter = None + + if validation_config.where: + if data_source.language_support == DataSourceLanguageSupport.DSL_ES: + self.where_filter = json.loads(validation_config.where) + elif data_source.language_support == DataSourceLanguageSupport.SQL: + self.where_filter = validation_config.where + + def get_validation_identity(self) -> str: + return ValidationIdentity.generate_identity( + validation_function=self.validation_config.get_validation_function, + validation_name=self.name, + data_source_name=self.data_source.data_source_name, + dataset_name=self.dataset_name, + field_name=self.field_name, + ) + + def _validate_threshold(self, metric_value) -> Tuple[bool, Optional[str]]: + for operator, value in self.threshold.__dict__.items(): + if value is not None: + if ConditionType.GTE == operator: + if metric_value < value: + return ( + False, + f"Less than threshold value of {value}", + ) + elif ConditionType.LTE == operator: + if metric_value > value: + return ( + False, + f"Greater than threshold value of {value}", + ) + elif ConditionType.GT == operator: + if metric_value <= value: + return ( + False, + f"Less than or equal to threshold value of {value}", + ) + elif ConditionType.LT == operator: + if metric_value >= value: + return ( + False, + f"Greater than or equal to threshold value of {value}", + ) + elif ConditionType.EQ == operator: + if metric_value != value: + return ( + False, + f"Not equal to the value of {value}", + ) + return True, None + + @abstractmethod + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + pass + + def get_validation_info(self, **kwargs) -> Union[ValidationInfo, None]: + try: + metric_value = self._generate_metric_value(**kwargs) + tags = { + "name": self.name, + } + + value = ValidationInfo( + name=self.name, + identity=self.get_validation_identity(), + data_source_name=self.data_source.data_source_name, + dataset=self.dataset_name, + validation_function=self.validation_config.get_validation_function, + field=self.field_name, + value=metric_value, + timestamp=datetime.datetime.utcnow(), + tags=tags, + ) + if self.threshold is not None: + value.is_valid, value.reason = self._validate_threshold(metric_value) + + return value + except Exception as e: + traceback.print_exc(file=sys.stdout) + logger.error(f"Failed to generate metric {self.name}: {str(e)}") + return None diff --git a/datachecks/core/validation/completeness_validation.py b/datachecks/core/validation/completeness_validation.py new file mode 100644 index 00000000..b1b981ba --- /dev/null +++ b/datachecks/core/validation/completeness_validation.py @@ -0,0 +1,91 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Union + +from datachecks.core.datasource.search_datasource import SearchIndexDataSource +from datachecks.core.datasource.sql_datasource import SQLDataSource +from datachecks.core.validation.base import Validation + + +class CountNullValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_null_count( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_null_count( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class PercentageNullValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_null_percentage( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_null_percentage( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class CountEmptyStringValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_empty_string_count( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_empty_string_count( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class PercentageEmptyStringValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_empty_string_percentage( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_empty_string_percentage( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") diff --git a/datachecks/core/validation/custom_query_validation.py b/datachecks/core/validation/custom_query_validation.py new file mode 100644 index 00000000..be4b2df6 --- /dev/null +++ b/datachecks/core/validation/custom_query_validation.py @@ -0,0 +1,24 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datachecks.core.datasource.sql_datasource import SQLDataSource +from datachecks.core.validation.base import Validation + + +class CustomSqlValidation(Validation): + def _generate_metric_value(self): + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_custom_sql(query=self.query) + else: + raise ValueError("Invalid data source type") diff --git a/datachecks/core/validation/manager.py b/datachecks/core/validation/manager.py new file mode 100644 index 00000000..e7e0f451 --- /dev/null +++ b/datachecks/core/validation/manager.py @@ -0,0 +1,151 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Dict, Optional + +from datachecks.core.common.models.configuration import ( + Configuration, + ValidationConfigByDataset, +) +from datachecks.core.common.models.validation import ValidationFunction +from datachecks.core.datasource.manager import DataSourceManager +from datachecks.core.validation.base import Validation +from datachecks.core.validation.completeness_validation import ( # noqa F401 this is used in globals + CountEmptyStringValidation, + CountNullValidation, + PercentageEmptyStringValidation, + PercentageNullValidation, +) +from datachecks.core.validation.custom_query_validation import ( # noqa F401 this is used in globals + CustomSqlValidation, +) +from datachecks.core.validation.numeric_validation import ( # noqa F401 this is used in globals + AvgValidation, + MaxValidation, + MinValidation, + StdDevValidation, + SumValidation, + VarianceValidation, +) +from datachecks.core.validation.reliability_validation import ( # noqa F401 this is used in globals + CountDocumentsValidation, + CountRowValidation, + FreshnessValueMetric, +) +from datachecks.core.validation.uniqueness_validation import ( # noqa F401 this is used in globals + CountDistinctValidation, + CountDuplicateValidation, +) + + +class ValidationManager: + VALIDATION_CLASS_MAPPING = { + ValidationFunction.MIN.value: "MinValidation", + ValidationFunction.MAX.value: "MaxValidation", + ValidationFunction.AVG.value: "AvgValidation", + ValidationFunction.SUM.value: "SumValidation", + ValidationFunction.VARIANCE.value: "VarianceValidation", + ValidationFunction.STDDEV.value: "StdDevValidation", + ValidationFunction.COUNT_DUPLICATE.value: "CountDuplicateValidation", + ValidationFunction.COUNT_DISTINCT.value: "CountDistinctValidation", + ValidationFunction.COUNT_NULL.value: "CountNullValidation", + ValidationFunction.PERCENT_NULL.value: "PercentageNullValidation", + ValidationFunction.COUNT_EMPTY_STRING.value: "CountEmptyStringValidation", + ValidationFunction.PERCENT_EMPTY_STRING.value: "PercentageEmptyStringValidation", + ValidationFunction.CUSTOM_SQL.value: "CustomSqlValidation", + ValidationFunction.COUNT_DOCUMENTS.value: "CountDocumentsValidation", + ValidationFunction.COUNT_ROWS.value: "CountRowValidation", + ValidationFunction.FRESHNESS.value: "FreshnessValueMetric", + } + + def __init__( + self, + application_configs: Configuration, + data_source_manager: DataSourceManager, + ): + self.data_source_manager = data_source_manager + self.application_configs = application_configs + self.validation_configs: Dict[ + str, ValidationConfigByDataset + ] = application_configs.validations + + """ + Will store the validations in the following format: + { + "data_source_name": { + "dataset_name": { + "validation_name": Validation + } + } + } + """ + self.validations: Dict[str, Dict[str, Dict[str, Validation]]] = {} + + def set_validation_configs(self, validations: Dict[str, ValidationConfigByDataset]): + self.validation_configs = validations + + def build_validations(self): + for _, validation_by_dataset in self.validation_configs.items(): + data_source_name = validation_by_dataset.data_source + dataset_name = validation_by_dataset.dataset + + if data_source_name not in self.validations: + self.validations[data_source_name] = {} + + if dataset_name not in self.validations[data_source_name]: + self.validations[data_source_name][dataset_name] = {} + + for ( + validation_name, + validation_config, + ) in validation_by_dataset.validations.items(): + data_source = self.data_source_manager.get_data_source(data_source_name) + params = {} + validation: Validation = globals()[ + self.VALIDATION_CLASS_MAPPING[ + validation_config.get_validation_function + ] + ]( + name=validation_name, + data_source=data_source, + dataset_name=dataset_name, + validation_name=validation_name, + validation_config=validation_config, + field_name=validation_config.get_validation_field_name, + **params, + ) + self.validations[data_source_name][dataset_name][ + validation_name + ] = validation + + def add_validation(self, validation: Validation): + data_source_name = validation.data_source.data_source_name + dataset_name = validation.dataset_name + validation_name = validation.name + if data_source_name not in self.validations: + self.validations[data_source_name] = {} + + if dataset_name not in self.validations[data_source_name]: + self.validations[data_source_name][dataset_name] = {} + + self.validations[data_source_name][dataset_name][validation_name] = validation + + @property + def get_validations(self): + return self.validations + + def get_validation( + self, data_source_name: str, dataset_name: str, validation_name: str + ) -> Validation: + return self.validations[data_source_name][dataset_name][validation_name] diff --git a/datachecks/core/validation/numeric_validation.py b/datachecks/core/validation/numeric_validation.py new file mode 100644 index 00000000..cb9a2f33 --- /dev/null +++ b/datachecks/core/validation/numeric_validation.py @@ -0,0 +1,127 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Union + +from datachecks.core.datasource.search_datasource import SearchIndexDataSource +from datachecks.core.datasource.sql_datasource import SQLDataSource +from datachecks.core.validation.base import Validation + + +class MinValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_min( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_min( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class MaxValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_max( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_max( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class AvgValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_avg( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_avg( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class SumValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_sum( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_sum( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class VarianceValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_variance( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_variance( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class StdDevValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_stddev( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_stddev( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") diff --git a/datachecks/core/validation/reliability_validation.py b/datachecks/core/validation/reliability_validation.py new file mode 100644 index 00000000..a1180cba --- /dev/null +++ b/datachecks/core/validation/reliability_validation.py @@ -0,0 +1,67 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +from datachecks.core.common.models.metric import MetricsType +from datachecks.core.datasource.search_datasource import SearchIndexDataSource +from datachecks.core.datasource.sql_datasource import SQLDataSource +from datachecks.core.metric.base import FieldMetrics, Metric, MetricIdentity +from datachecks.core.validation.base import Validation + + +class CountDocumentsValidation(Validation): + """ + DocumentCountMetrics is a class that represents a metric that is generated by a data source. + """ + + def _generate_metric_value(self): + if isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_document_count( + index_name=self.dataset_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class CountRowValidation(Validation): + + """ + RowCountMetrics is a class that represents a metric that is generated by a data source. + """ + + def _generate_metric_value(self): + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_row_count( + table=self.dataset_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class FreshnessValueMetric(Validation): + """ + FreshnessMetric is a class that represents a metric that is generated by a data source. + """ + + def _generate_metric_value(self): + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_time_diff( + table=self.dataset_name, field=self.field_name + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_time_diff( + index_name=self.dataset_name, field=self.field_name + ) + else: + raise ValueError("Invalid data source type") diff --git a/datachecks/core/validation/uniqueness_validation.py b/datachecks/core/validation/uniqueness_validation.py new file mode 100644 index 00000000..5a8fa35f --- /dev/null +++ b/datachecks/core/validation/uniqueness_validation.py @@ -0,0 +1,55 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from typing import Union + +from datachecks.core.datasource.search_datasource import SearchIndexDataSource +from datachecks.core.datasource.sql_datasource import SQLDataSource +from datachecks.core.validation.base import Validation + + +class CountDuplicateValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_duplicate_count( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_duplicate_count( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") + + +class CountDistinctValidation(Validation): + def _generate_metric_value(self, **kwargs) -> Union[float, int]: + if isinstance(self.data_source, SQLDataSource): + return self.data_source.query_get_distinct_count( + table=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter is not None else None, + ) + elif isinstance(self.data_source, SearchIndexDataSource): + return self.data_source.query_get_distinct_count( + index_name=self.dataset_name, + field=self.field_name, + filters=self.where_filter if self.where_filter else None, + ) + else: + raise ValueError("Invalid data source type") diff --git a/docker-compose-test.yaml b/docker-compose-test.yaml index d6858e32..660c4b67 100644 --- a/docker-compose-test.yaml +++ b/docker-compose-test.yaml @@ -2,7 +2,7 @@ version: '3' services: test-dc-opensearch: # This is also the hostname of the container within the Docker network (i.e. https://test-dc-opensearch/) - image: opensearchproject/opensearch:latest # Specifying the latest available image - modify if you want a specific version + image: opensearchproject/opensearch:2.5.0 # Specifying the latest available image - modify if you want a specific version container_name: test-dc-opensearch environment: - cluster.name=opensearch-cluster # Name the cluster @@ -27,7 +27,7 @@ services: - test-opensearch-net # All of the containers will join the same Docker bridge network test-dc-postgres: container_name: test-postgres_container - image: postgres + image: postgres:13.15 environment: POSTGRES_DB: dc_db POSTGRES_USER: postgres diff --git a/docs/configuration/metric_configuration.md b/docs/configuration/metric_configuration.md index ab7eea1d..a1bad428 100644 --- a/docs/configuration/metric_configuration.md +++ b/docs/configuration/metric_configuration.md @@ -5,31 +5,28 @@ Datachecks will read metrics configuration under the key `metrics` in the config For example: ```yaml -metrics: - - name: freshness_example - type: freshness - resource: mysql_db.table_name.last_updated - validation: +validations for mysql_db.table_name: + - freshness_example: + on: freshness(last_updated) threshold: "> 86400" ##Freshness metric value is in seconds. Validation error if metric value is greater than 86400 seconds. ``` ## Configuration Details -| Parameter | Mandatory | Description | -|:-------------|:-----------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| `name` | :material-check: | The name of the metric. The name should be unique. | -| `type` | :material-check: | The type of the metric. Possible values are `freshness`, `row_count` etc. Type of metric mentioned in every metric documentation | -| `resource` | :material-check: | The resource for which metric should be generates. A resource can be a Table, Index, Collection or Field.

In case of Table, Index or Collection the pattern of the resource name would be `.` or `.`

In case of a Field the pattern of the resource name would be `..` or `..` | -| `filters` | :material-close: | The filters to be applied on the resource. Filters can have `where` as a nested field.
In `where` field we can pass `SQL Query`(In ase of SQl DB) or `Search Query`(In ase of search engine).

For example:
`filters:`
 `where: city = 'bangalore' AND age >= 30` | -| `validation` | :material-close: | The validation will be applied on the metric value. A validation error will be invoked if the metric value violate threshold value.
Possible values for threshold are `>`, `>=`, `=` , `<`, `<=`. We can combine multiple operators
For example:
`validation:`
 `threshold: ">= 10 & <= 100"` | +| Parameter | Mandatory | Description | +|:--------------|:-----------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| `` | :material-check: | The name of the validation. The name should be unique. | +| `on` | :material-check: | The type of the validation function. Possible values are `freshness`, `row_count` etc. Type of validation mentioned in every metric documentation | +| `where` | :material-close: | The where filter to be applied on the filed. In `where` field we can pass `SQL Query`(In ase of SQl DB) or `Search Query`(In ase of search engine).

For example:
`where: city = 'bangalore' AND age >= 30` | +| `threshold` | :material-close: | The validation will be applied on the validation value. A validation error will be invoked if the metric value violate threshold value.
Possible values for threshold are `>`, `>=`, `=` , `<`, `<=`. We can combine multiple operators
For example:
`threshold: ">= 10 & <= 100"` | -## Metric Types +## Validation Types -Supported metric types are +Supported Validation functions are -| Metric Group | Metric Type | +| Validation Group | Validation Type | |:---------------------|:--------------------------------------------------------------------------------------------------| | Reliability | [Freshness](https://docs.datachecks.io/metrics/reliability/#freshness) | | Reliability | [Row Count](https://docs.datachecks.io/metrics/reliability/#row-count) | diff --git a/docs/getting_started.md b/docs/getting_started.md index 14c79d50..70cbf6d1 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -87,18 +87,13 @@ data_sources: username: dbuser password: dbpass database: dcs_demo -metrics: - - name: count_of_products - metric_type: row_count - resource: product_db.products - validation: +validations for product_db.products: + - count_of_products: + on: count_rows threshold: "> 0 & < 1000" - - name: max_product_price_in_india - metric_type: max - resource: product_db.products.price - filters: + - max_product_price_in_india: + on: max(price) where: "country_code = 'IN'" - validation: threshold: "< 190" ``` @@ -129,11 +124,12 @@ datachecks inspect --config-path ./dcs_config.yaml --html-report ### Run Datachecks in Python ```python -from datachecks.core import load_configuration, Inspect +from datachecks.core import Inspect if __name__ == "__main__": - inspect = Inspect(load_configuration("dcs_config.yaml")) + inspect = Inspect() + inspect.add_configuration_yaml_file("dcs_config.yaml") inspect_output = inspect.run() print(inspect_output.metrics) # User the metrics to send or store somewhere diff --git a/docs/metrics/completeness.md b/docs/metrics/completeness.md deleted file mode 100644 index 597a67a7..00000000 --- a/docs/metrics/completeness.md +++ /dev/null @@ -1,61 +0,0 @@ -# **Completeness Metrics** - -Completeness metrics play a crucial role in data quality assessment, ensuring your datasets are comprehensive and reliable. By regularly monitoring these metrics, you can gain profound insights into the extent to which your data captures the entirety of the intended information. This empowers you to make informed decisions about data integrity and take corrective actions when necessary. - -These metrics unveil potential gaps or missing values in your data, enabling proactive data enhancement. Like a well-oiled machine, tracking completeness metrics enhances the overall functionality of your data ecosystem. Just as reliability metrics guarantee up-to-date information, completeness metrics guarantee a holistic, accurate dataset. - - -## **Null Count** - -Null count metrics gauge missing data, a crucial aspect of completeness metrics, revealing gaps and potential data quality issues. - - - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: null_count_in_dataset - metric_type: null_count - resource: product_db.products.first_name -``` - - -## **Null Percentage** - -Null percentage metrics reveal missing data, a vital facet of completeness metrics, ensuring data sets are whole and reliable. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: null_percentage_in_dataset - metric_type: null_percentage - resource: product_db.products.first_name -``` - -## **Empty String** - -Empty string metrics gauge the extent of missing or null values, exposing gaps that impact data completeness and reliability. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: empty_string_in_dataset - metric_type: empty_string - resource: product_db.products.first_name -``` - -## **Empty String Percentage** - -Empty String Percentage Metrics assess data completeness by measuring the proportion of empty strings in datasets. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: empty_string_percentage_in_dataset - metric_type: empty_string_percentage - resource: product_db.products.first_name -``` \ No newline at end of file diff --git a/docs/metrics/custom_sql.md b/docs/metrics/custom_sql.md deleted file mode 100644 index 71973909..00000000 --- a/docs/metrics/custom_sql.md +++ /dev/null @@ -1,16 +0,0 @@ -# **Custom SQL Metrics** - -If the built-in set of metrics does not quite give you the information you need from a metric, you have the flexibility to define your own metrics using `custom_sql`. - -The custom SQL metric empowers you to enter your own completely custom SQL query, providing you with the ability to create much more complex and specify monitors according to your specific requirements. This feature allows you to dig deeper into your data and extract insights that are tailored to your unique needs. - -## Example - -```yaml -metrics: - - name: custom_sql_example - type: custom_sql - resource: mysql_db.student - query: | - SELECT COUNT(*) FROM student WHERE city = 'bangalore' AND age >= 30 -``` \ No newline at end of file diff --git a/docs/metrics/numeric_distribution.md b/docs/metrics/numeric_distribution.md deleted file mode 100644 index ddedb70e..00000000 --- a/docs/metrics/numeric_distribution.md +++ /dev/null @@ -1,116 +0,0 @@ -# **Numeric Distribution Metrics** - -Numeric Distribution metrics detect changes in the numeric distribution of values, including outliers, variance, skew and more - - -## **Average** - -Average metrics gauge performance in transitional databases and search engines, offering valuable insights into overall effectiveness. - - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: avg_price - metric_type: avg - resource: product_db.products.price - filters: - where: "country_code = 'IN'" - validation: - threshold: "< 190" -``` - - -## **Minimum** - -Minimum metrics ensure consistency across transitional databases and search engines, enhancing data quality and retrieval accuracy. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: min_price - metric_type: min - resource: product_db.products.price - validation: - threshold: "> 0" -``` - -## **Maximum** - -Maximum metrics gauge the highest values within datasets, helping identify outliers and understand data distribution's upper limits for quality assessment. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: max_price - metric_type: max - resource: product_db.products.price - validation: - threshold: "< 1000" -``` - -```yaml title="dcs_config.yaml" -- name: max_price_of_products_with_high_rating - metric_type: max - resource: product_db.products.price - filters: - where: "rating > 4" - validation: - threshold: "< 1000" -``` - -## **Sum** - -Sum metrics measure the total of all values within a dataset, indicating the overall size of a particular dataset to help understand data quality. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: sum_of_price - metric_type: sum - resource: product_db.products.price - validation: - threshold: "> 100 & < 1000" -``` - -## **Variance** - -Variance in data quality measures the degree of variability or dispersion in a dataset, indicating how spread out the data points are from the mean. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: -- name: variance_of_price - metric_type: variance - resource: product_db.products.price -``` - -## **Standard Deviation** - -Standard deviation metrics measure the amount of variation or dispersion of a set of values from the mean, indicating how spread out the data points are from the mean. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: -- name: standard_deviation_of_price - metric_type: stddev - resource: product_db.products.price -``` - -## **Skew** -**Coming Soon..** - -## **Kurtosis** -**Coming Soon..** - -## **Geometric Mean** -**Coming Soon..** - -## **Harmonic Mean** -**Coming Soon..** \ No newline at end of file diff --git a/docs/metrics/reliability.md b/docs/metrics/reliability.md deleted file mode 100644 index 3fb70558..00000000 --- a/docs/metrics/reliability.md +++ /dev/null @@ -1,58 +0,0 @@ -# **Reliability Metrics** - -Reliability metrics are an essential tool for ensuring that your tables, indices, or collections are being updated with the most up-to-date and timely data. - -By consistently monitoring these metrics, you can gain better insights into how your systems are performing and make more informed decisions about how to optimize and improve performance. Additionally, these metrics can help you identify any potential issues or bottlenecks in your data pipelines, allowing you to take proactive steps to address them before they become major problems. - -Overall, investing in a reliable and robust set of metrics is crucial for maintaining the health and performance of your data applications and ensuring that your systems are running as smoothly and efficiently as possible. - - -## **Freshness** - -Data freshness, also known as data timeliness, refers to the frequency at which data is updated for consumption. It is an important dimension of data quality and a pillar of data observability because recently updated data is more accurate and, therefore, more valuable. - -The resource name of freshness metric should be in the format `..` or `..`. - -In the below example the metric will look for the last updated timestamp of the table or index using `updated_at` field. - -The threshold will trigger a validation error when the metric is greater than 86400 seconds - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: freshness_of_products - metric_type: freshness - resource: product_db.products.updated_at - validation: - threshold: "> 86400" -``` - - -## **Row Count** - -The row count metric determines the total number of rows present in a table. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: count_of_products - metric_type: row_count - resource: product_db.products - filters: - where: "country_code = 'IN'" -``` - -## **Document Count** - -The document count metric determines the total number of documents present in a search data source index. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: count_of_documents - metric_type: document_count - resource: search_datastore.product_data_index -``` \ No newline at end of file diff --git a/docs/metrics/uniqueness.md b/docs/metrics/uniqueness.md deleted file mode 100644 index 64dcac6f..00000000 --- a/docs/metrics/uniqueness.md +++ /dev/null @@ -1,33 +0,0 @@ -# **Uniqueness Metrics** - -Uniqueness metrics play a pivotal role in upholding data quality standards. Just as reliability metrics ensure timely data updates, uniqueness metrics focus on the distinctiveness of data entries within a dataset. - -By consistently tracking these metrics, you gain valuable insights into data duplication, redundancy, and accuracy. This knowledge empowers data professionals to make well-informed decisions about data cleansing and optimization strategies. Uniqueness metrics also serve as a radar for potential data quality issues, enabling proactive intervention to prevent major problems down the line. - - -## **Distinct Count** - - A distinct count metric in data quality measures the number of unique values within a dataset, ensuring accuracy and completeness. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: distinct_count_of_product_categories - metric_type: distinct_count - resource: product_db.products.product_category -``` - - -## **Duplicate Count** - -Duplicate count is a data quality metric that measures the number of identical or highly similar records in a dataset, highlighting potential data redundancy or errors. - -**Example** - -```yaml title="dcs_config.yaml" -metrics: - - name: distinct_count_of_product_categories - metric_type: duplicate_count - resource: product_db.products.product_category -``` \ No newline at end of file diff --git a/docs/metrics/combined.md b/docs/validations/combined.md similarity index 100% rename from docs/metrics/combined.md rename to docs/validations/combined.md diff --git a/docs/validations/completeness.md b/docs/validations/completeness.md new file mode 100644 index 00000000..68c5ea46 --- /dev/null +++ b/docs/validations/completeness.md @@ -0,0 +1,57 @@ +# **Completeness Validations** + +Completeness Validations play a crucial role in data quality assessment, ensuring your datasets are comprehensive and reliable. By regularly monitoring these validations, you can gain profound insights into the extent to which your data captures the entirety of the intended information. This empowers you to make informed decisions about data integrity and take corrective actions when necessary. + +These Validations unveil potential gaps or missing values in your data, enabling proactive data enhancement. Like a well-oiled machine, tracking completeness validations enhances the overall functionality of your data ecosystem. Just as reliability Validations guarantee up-to-date information, completeness Validations guarantee a holistic, accurate dataset. + + +## **Null Count** + +Null count Validations gauge missing data, a crucial aspect of completeness Validations, revealing gaps and potential data quality issues. + + + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - null count percentage _in_dataset: + on: count_null(first_name) +``` + + +## **Null Percentage** + +Null percentage Validations reveal missing data, a vital facet of completeness Validations, ensuring data sets are whole and reliable. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - empty_string_percentage_in_dataset: + on: percent_null(first_name) +``` + +## **Empty String** + +Empty string Validations gauge the extent of missing or null values, exposing gaps that impact data completeness and reliability. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - empty_string_percentage_in_dataset: + on: count_empty_string(first_name) +``` + +## **Empty String Percentage** + +Empty String Percentage Validations assess data completeness by measuring the proportion of empty strings in datasets. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - empty_string_percentage_in_dataset: + on: percent_empty_string(first_name) +``` \ No newline at end of file diff --git a/docs/validations/custom_sql.md b/docs/validations/custom_sql.md new file mode 100644 index 00000000..dafd1de0 --- /dev/null +++ b/docs/validations/custom_sql.md @@ -0,0 +1,15 @@ +# **Custom SQL Validation** + +If the built-in set of validations does not quite give you the information you need from a Validation, you have the flexibility to define your own Validations using `custom_sql`. + +The custom SQL Validation empowers you to enter your own completely custom SQL query, providing you with the ability to create much more complex and specify monitors according to your specific requirements. This feature allows you to dig deeper into your data and extract insights that are tailored to your unique needs. + +## Example + +```yaml +validations for mysql_db.student: + - custom_sql_example: + on: custom_sql + query: | + SELECT COUNT(*) FROM student WHERE city = 'bangalore' AND age >= 30 +``` \ No newline at end of file diff --git a/docs/validations/numeric_distribution.md b/docs/validations/numeric_distribution.md new file mode 100644 index 00000000..a629f906 --- /dev/null +++ b/docs/validations/numeric_distribution.md @@ -0,0 +1,89 @@ +# **Numeric Distribution Validations** + +Numeric Distribution Validations detect changes in the numeric distribution of values, including outliers, variance, skew and more + + +## **Average** + +Average Validations gauge performance in transitional databases and search engines, offering valuable insights into overall effectiveness. + + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - avg_price: + on: avg(price) + where: "country_code = 'IN'" + threshold: "< 190" +``` + + +## **Minimum** + +Minimum Validations ensure consistency across transitional databases and search engines, enhancing data quality and retrieval accuracy. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - min_price: + on: min(price) + threshold: "> 0" +``` + + +## **Maximum** + +Maximum Validations gauge the highest values within datasets, helping identify outliers and understand data distribution's upper limits for quality assessment. + +**Example** + +```yaml title="dcs_config.yaml" + +validations for product_db.products: + - max_price: + on: max(price) + threshold: "< 1000" +``` + +## **Sum** + +Sum Validations measure the total of all values within a dataset, indicating the overall size of a particular dataset to help understand data quality. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - sum_of_price: + on: sum(price) + threshold: "> 100 & < 1000" +``` + +## **Variance** + +Variance in data quality measures the degree of variability or dispersion in a dataset, indicating how spread out the data points are from the mean. + +**Example** + +```yaml title="dcs_config.yaml" + +validations for product_db.products: + - variance_of_price: + on: variance(price) + threshold: "< 2.0" +``` + +## **Standard Deviation** + +Standard deviation Validations measure the amount of variation or dispersion of a set of values from the mean, indicating how spread out the data points are from the mean. + +**Example** + +```yaml title="dcs_config.yaml" + +validations for product_db.products: + - standard_deviation_of_price: + on: stddev(price) + threshold: "< .81" +``` \ No newline at end of file diff --git a/docs/validations/reliability.md b/docs/validations/reliability.md new file mode 100644 index 00000000..06a4cd65 --- /dev/null +++ b/docs/validations/reliability.md @@ -0,0 +1,53 @@ +# **Reliability Validations** + +Reliability Validations are an essential tool for ensuring that your tables, indices, or collections are being updated with the most up-to-date and timely data. + +By consistently monitoring these validations, you can gain better insights into how your systems are performing and make more informed decisions about how to optimize and improve performance. Additionally, these validations can help you identify any potential issues or bottlenecks in your data pipelines, allowing you to take proactive steps to address them before they become major problems. + +Overall, investing in a reliable and robust set of validations is crucial for maintaining the health and performance of your data applications and ensuring that your systems are running as smoothly and efficiently as possible. + + +## **Freshness** + +Data freshness, also known as data timeliness, refers to the frequency at which data is updated for consumption. It is an important dimension of data quality and a pillar of data observability because recently updated data is more accurate and, therefore, more valuable. + +In the below example the validation will look for the last updated timestamp of the table or index using `updated_at` field. + +The threshold will trigger a validation error when the validation is greater than 86400 seconds + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - freshness_of_products: + on: freshness(updated_at) + threshold: "> 86400" +``` + + +## **Row Count** + +The row count validation determines the total number of rows present in a table. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - count of products: + on: count_rows + where: "country_code = 'IN'" + threshold: "> 1000" +``` + +## **Document Count** + +The document count validation determines the total number of documents present in a search data source index. + +**Example** + +```yaml title="dcs_config.yaml" +validations for search_datastore.product_data_index: + - count of documents: + on: count_documents + threshold: "> 1000" +``` diff --git a/docs/validations/uniqueness.md b/docs/validations/uniqueness.md new file mode 100644 index 00000000..4a7221e1 --- /dev/null +++ b/docs/validations/uniqueness.md @@ -0,0 +1,31 @@ +# **Uniqueness Validations** + +Uniqueness Validations play a pivotal role in upholding data quality standards. Just as reliability Validations ensure timely data updates, uniqueness Validations focus on the distinctiveness of data entries within a dataset. + +By consistently tracking these Validations, you gain valuable insights into data duplication, redundancy, and accuracy. This knowledge empowers data professionals to make well-informed decisions about data cleansing and optimization strategies. Uniqueness Validations also serve as a radar for potential data quality issues, enabling proactive intervention to prevent major problems down the line. + + +## **Distinct Count** + + A distinct count Validation in data quality measures the number of unique values within a dataset, ensuring accuracy and completeness. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - distinct_count_of_product_categories: + on: count_distinct(product_category) +``` + + +## **Duplicate Count** + +Duplicate count is a data quality Validation that measures the number of identical or highly similar records in a dataset, highlighting potential data redundancy or errors. + +**Example** + +```yaml title="dcs_config.yaml" +validations for product_db.products: + - distinct count of product categories: + on: count_duplicate(product_category) +``` \ No newline at end of file diff --git a/examples/configurations/example_postgres_config.yaml b/examples/configurations/example_postgres_config.yaml index a4202a03..8512702b 100644 --- a/examples/configurations/example_postgres_config.yaml +++ b/examples/configurations/example_postgres_config.yaml @@ -9,126 +9,70 @@ data_sources: password: !ENV ${PGSQL_PASS} database: dcs_db schema: public -metrics: + +validations for iris_pgsql.dcs_iris: # Numeric Metrics - - name: sepal_length_avg_price - metric_type: avg - resource: iris_pgsql.dcs_iris.sepal_length - validation: + - sepal length min size: + on: min(sepal_length) + threshold: "= 0" + - sepal length max size: + on: max(sepal_length) + threshold: "= 150" + - sepal length avg size: + on: avg(sepal_length) threshold: "> 0 & < 1000" - - - name: postgres_min_price - metric_type: min - resource: iris_pgsql.dcs_iris.sepal_length - - - name: postgres_max_price - metric_type: max - resource: iris_pgsql.dcs_iris.sepal_length - - - name: postgres_variance_price - metric_type: variance - resource: iris_pgsql.dcs_iris.sepal_length + - sepal length sum size: + on: sum(sepal_length) + threshold: "> 0 & < 1000" + - sepal length variance size: + on: variance(sepal_length) + threshold: "< 1" + - sepal length stddev size: + on: stddev(sepal_length) + threshold: "< 0.5" # Uniqueness Metrics - - name: postgres_distinct_count_price - metric_type: distinct_count - resource: iris_pgsql.dcs_iris.sepal_length - - - name: postgres_duplicate_count_price - metric_type: duplicate_count - resource: iris_pgsql.dcs_iris.sepal_length + - species duplicate count: + on: count_duplicate(species) + threshold: "< 100" + - species distinct count: + on: count_distinct(species) + threshold: "> 0" # Completeness Metrics - - name: postgres_null_count_price - metric_type: null_count - resource: iris_pgsql.dcs_iris.sepal_length - - - name: postgres_null_percentage_price - metric_type: null_percentage - resource: iris_pgsql.dcs_iris.sepal_length - - - name: postgres_empty_string_count_price - metric_type: empty_string_count - resource: iris_pgsql.dcs_iris.species + - sepal length null count: + on: count_null(sepal_length) + threshold: "= 0" + - sepal length null percentage: + on: percent_null(sepal_length) + threshold: "= 0" + - species empty string count: + on: count_empty_string(species) + threshold: "= 0" + - species empty string percentage: + on: percent_empty_string(species) + threshold: "= 0" + + # Custom Metrics + - sepal length custom sql example: + on: custom_sql + query: "SELECT avg(sepal_length) * 2 FROM dcs_iris" + threshold: "> 0 & < 10" # Reliability Metrics - - name: postgres_row_count - metric_type: row_count - resource: iris_pgsql.dcs_iris - validation: - threshold: "> 100" - - - name: postgres_freshness - metric_type: freshness - resource: iris_pgsql.dcs_iris.timestamp - validation: - threshold: ">-5000" - - # Combined Metrics - - name: postgres_combined_div - metric_type: combined - expression: div(postgres_distinct_count_price, postgres_max_price) - - - name: postgres_combined_mul - metric_type: combined - expression: mul(postgres_distinct_count_price, postgres_max_price) - - - name: postgres_combined_sum - metric_type: combined - expression: sum(postgres_distinct_count_price, postgres_max_price) - - - name: postgres_combined_sub - metric_type: combined - expression: sub(postgres_distinct_count_price, postgres_max_price) - - - name: postgres_combined_div_mul - metric_type: combined - expression: div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price) - - - name: postgres_combined_div_mul_sum - metric_type: combined - expression: sum(div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price), postgres_row_count) - - - name: postgres_combined_div_mul_sum_sub - metric_type: combined - expression: sub(sum(div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price), postgres_row_count), postgres_duplicate_count_price) - - - name: postgres_combined_div_mul_sum_sub_div - metric_type: combined - expression: div(sub(sum(div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price), postgres_row_count), postgres_duplicate_count_price), postgres_distinct_count_price) + - dcs_iris rows count: + on: count_rows + threshold: "> 0" + - dcs_iris last update count: + on: freshness(timestamp) + threshold: "> 0" # Filtered Metrics - - - name: postgres_avg_price_filtered - metric_type: avg - resource: iris_pgsql.dcs_iris.sepal_length - filters: - where: "species = 'versicolor'" - - - name: postgres_min_price_filtered - metric_type: min - resource: iris_pgsql.dcs_iris.sepal_length - filters: - where: "species = 'versicolor'" - - - name: postgres_max_price_with_filter - metric_type: max - resource: iris_pgsql.dcs_iris.sepal_length - filters: - where: "species = 'versicolor'" - - - name: postgres_min_price_with_filter - metric_type: min - resource: iris_pgsql.dcs_iris.sepal_length - filters: - where: "species = 'versicolor'" - - - name: postgres_distinct_count_price_with_filter - metric_type: distinct_count - resource: iris_pgsql.dcs_iris.sepal_length - filters: - where: "species = 'versicolor'" -storage: - type: local_file|s3|elastic|postgres|clickhouse - params: - path: /Users/subhankar/Work/datageek00/dcs_metrics + - dcs_iris rows count with filter: + on: count_rows + threshold: "< 50" + where: "species = 'virginica'" + - dcs_iris min with filter: + on: min(sepal_length) + threshold: "= 4" + where: "species = 'virginica'" diff --git a/examples/configurations/example_bigquery_config.yaml b/examples/configurations/old/example_bigquery_config.yaml similarity index 100% rename from examples/configurations/example_bigquery_config.yaml rename to examples/configurations/old/example_bigquery_config.yaml diff --git a/examples/configurations/example_databricks_config.yaml b/examples/configurations/old/example_databricks_config.yaml similarity index 100% rename from examples/configurations/example_databricks_config.yaml rename to examples/configurations/old/example_databricks_config.yaml diff --git a/examples/configurations/example_elasticsearch_config.yaml b/examples/configurations/old/example_elasticsearch_config.yaml similarity index 100% rename from examples/configurations/example_elasticsearch_config.yaml rename to examples/configurations/old/example_elasticsearch_config.yaml diff --git a/examples/configurations/example_mysql_config.yaml b/examples/configurations/old/example_mysql_config.yaml similarity index 100% rename from examples/configurations/example_mysql_config.yaml rename to examples/configurations/old/example_mysql_config.yaml diff --git a/examples/configurations/example_opensearch_config.yaml b/examples/configurations/old/example_opensearch_config.yaml similarity index 100% rename from examples/configurations/example_opensearch_config.yaml rename to examples/configurations/old/example_opensearch_config.yaml diff --git a/examples/configurations/old/example_postgres_config_old.yaml b/examples/configurations/old/example_postgres_config_old.yaml new file mode 100644 index 00000000..a4202a03 --- /dev/null +++ b/examples/configurations/old/example_postgres_config_old.yaml @@ -0,0 +1,134 @@ +# Data sources to query +data_sources: + - name: iris_pgsql + type: postgres + connection: + host: 127.0.0.1 + port: 5421 + username: !ENV ${PGSQL_USER} + password: !ENV ${PGSQL_PASS} + database: dcs_db + schema: public +metrics: + # Numeric Metrics + - name: sepal_length_avg_price + metric_type: avg + resource: iris_pgsql.dcs_iris.sepal_length + validation: + threshold: "> 0 & < 1000" + + - name: postgres_min_price + metric_type: min + resource: iris_pgsql.dcs_iris.sepal_length + + - name: postgres_max_price + metric_type: max + resource: iris_pgsql.dcs_iris.sepal_length + + - name: postgres_variance_price + metric_type: variance + resource: iris_pgsql.dcs_iris.sepal_length + + # Uniqueness Metrics + - name: postgres_distinct_count_price + metric_type: distinct_count + resource: iris_pgsql.dcs_iris.sepal_length + + - name: postgres_duplicate_count_price + metric_type: duplicate_count + resource: iris_pgsql.dcs_iris.sepal_length + + # Completeness Metrics + - name: postgres_null_count_price + metric_type: null_count + resource: iris_pgsql.dcs_iris.sepal_length + + - name: postgres_null_percentage_price + metric_type: null_percentage + resource: iris_pgsql.dcs_iris.sepal_length + + - name: postgres_empty_string_count_price + metric_type: empty_string_count + resource: iris_pgsql.dcs_iris.species + + # Reliability Metrics + - name: postgres_row_count + metric_type: row_count + resource: iris_pgsql.dcs_iris + validation: + threshold: "> 100" + + - name: postgres_freshness + metric_type: freshness + resource: iris_pgsql.dcs_iris.timestamp + validation: + threshold: ">-5000" + + # Combined Metrics + - name: postgres_combined_div + metric_type: combined + expression: div(postgres_distinct_count_price, postgres_max_price) + + - name: postgres_combined_mul + metric_type: combined + expression: mul(postgres_distinct_count_price, postgres_max_price) + + - name: postgres_combined_sum + metric_type: combined + expression: sum(postgres_distinct_count_price, postgres_max_price) + + - name: postgres_combined_sub + metric_type: combined + expression: sub(postgres_distinct_count_price, postgres_max_price) + + - name: postgres_combined_div_mul + metric_type: combined + expression: div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price) + + - name: postgres_combined_div_mul_sum + metric_type: combined + expression: sum(div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price), postgres_row_count) + + - name: postgres_combined_div_mul_sum_sub + metric_type: combined + expression: sub(sum(div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price), postgres_row_count), postgres_duplicate_count_price) + + - name: postgres_combined_div_mul_sum_sub_div + metric_type: combined + expression: div(sub(sum(div(mul(postgres_distinct_count_price, postgres_max_price), postgres_min_price), postgres_row_count), postgres_duplicate_count_price), postgres_distinct_count_price) + + # Filtered Metrics + + - name: postgres_avg_price_filtered + metric_type: avg + resource: iris_pgsql.dcs_iris.sepal_length + filters: + where: "species = 'versicolor'" + + - name: postgres_min_price_filtered + metric_type: min + resource: iris_pgsql.dcs_iris.sepal_length + filters: + where: "species = 'versicolor'" + + - name: postgres_max_price_with_filter + metric_type: max + resource: iris_pgsql.dcs_iris.sepal_length + filters: + where: "species = 'versicolor'" + + - name: postgres_min_price_with_filter + metric_type: min + resource: iris_pgsql.dcs_iris.sepal_length + filters: + where: "species = 'versicolor'" + + - name: postgres_distinct_count_price_with_filter + metric_type: distinct_count + resource: iris_pgsql.dcs_iris.sepal_length + filters: + where: "species = 'versicolor'" +storage: + type: local_file|s3|elastic|postgres|clickhouse + params: + path: /Users/subhankar/Work/datageek00/dcs_metrics diff --git a/examples/configurations/example_redshift_config.yaml b/examples/configurations/old/example_redshift_config.yaml similarity index 100% rename from examples/configurations/example_redshift_config.yaml rename to examples/configurations/old/example_redshift_config.yaml diff --git a/examples/docker-compose.yaml b/examples/docker-compose.yaml index 1870a434..3cf9321f 100644 --- a/examples/docker-compose.yaml +++ b/examples/docker-compose.yaml @@ -2,7 +2,7 @@ version: '3' services: dcs-test-opensearch: # This is also the hostname of the container within the Docker network (i.e. https://dc-test-opensearch/) - image: opensearchproject/opensearch:latest # Specifying the latest available image - modify if you want a specific version + image: opensearchproject/opensearch:2.5.0 # Specifying the latest available image - modify if you want a specific version container_name: dcs-test-opensearch environment: - cluster.name=opensearch-cluster # Name the cluster @@ -25,17 +25,6 @@ services: - 9605:9600 # Performance Analyzer networks: - opensearch-net # All of the containers will join the same Docker bridge network - dcs-test-opensearch-dashboards: - image: opensearchproject/opensearch-dashboards:latest # Make sure the version of opensearch-dashboards matches the version of opensearch installed on other nodes - container_name: dcs-test-opensearch-dashboards - ports: - - 5601:5601 # Map host port 5601 to container port 5601 - expose: - - "5601" # Expose port 5601 for web access to OpenSearch Dashboards - environment: - OPENSEARCH_HOSTS: '["https://dcs-test-opensearch:9200"]' # Define the OpenSearch nodes that OpenSearch Dashboards will query - networks: - - opensearch-net dcs-test-postgres: container_name: dcs-test-postgres @@ -52,6 +41,7 @@ services: networks: - dcs-test-postgres restart: unless-stopped + dcs-test-mysql: container_name: dcs-test-mysql image: mysql:8.0 diff --git a/mkdocs.yml b/mkdocs.yml index 675071e8..c2fa989f 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -71,14 +71,13 @@ nav: - Search Engines: - OpenSearch: integrations/opensearch.md - ElasticSearch: integrations/elasticsearch.md - - Metrics: - - Reliability Metrics: metrics/reliability.md - - Numeric Distribution Metrics: metrics/numeric_distribution.md - - Uniqueness Metrics: metrics/uniqueness.md - - Completeness Metrics: metrics/completeness.md - - Special Metrics: - - Combined Metrics: metrics/combined.md - - Custom SQL Metrics: metrics/custom_sql.md + - Validations: + - Reliability: validations/reliability.md + - Distribution: validations/numeric_distribution.md + - Uniqueness: validations/uniqueness.md + - Completeness: validations/completeness.md + - 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Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import pytest + +from datachecks.core.common.models.configuration import ValidationConfig + + +class TestValidationV1: + def test_on_field_is_required(self): + with pytest.raises(ValueError): + ValidationConfig(name="test", on=None) + + def test_should_have_valid_column_validation_function(self): + with pytest.raises(ValueError): + ValidationConfig(name="test", on="minn(age)") + + def test_should_have_valid_dataset_validation_function(self): + with pytest.raises(ValueError): + ValidationConfig(name="test", on="row_count") + + def test_table_validation_function_should_not_have_brackets(self): + with pytest.raises(ValueError): + ValidationConfig(name="test", on="count_rows(age)", threshold="> 0") + + def test_validation_function_malformed_with_space_should_not_throw_error(self): + with pytest.raises(ValueError): + validation = ValidationConfig( + name="test", on="count_rows ", threshold="> 0" + ) + + def test_on_filed_with_valid_function_should_not_throw_error(self): + validation = ValidationConfig(name="test", on="min(age)", threshold="> 0") + assert validation.on == "min(age)" + + def test_on_field_with_invalid_function_should_throw_error(self): + with pytest.raises(ValueError): + ValidationConfig(name="test", on="min(age", threshold="> 0") + + def test_column_name_should_not_have_special_char(self): + with pytest.raises(ValueError): + ValidationConfig(name="test", on="min(age@)", threshold="> 0") diff --git a/tests/core/configuration/test_configuration_v1.py b/tests/core/configuration/test_configuration_v1.py new file mode 100644 index 00000000..332b8969 --- /dev/null +++ b/tests/core/configuration/test_configuration_v1.py @@ -0,0 +1,251 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +import pytest + +from datachecks.core.common.models.configuration import DataSourceType +from datachecks.core.common.models.validation import ValidationFunction +from datachecks.core.configuration.configuration_parser_v1 import ( + load_configuration_from_yaml_str, +) + + +def test_should_read_datasource_config_for_opensearch(): + yaml_string = """ + data_sources: + - name: "test" + type: "opensearch" + connection: + host: "localhost" + port: 9200 + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.data_sources["test"].type == DataSourceType.OPENSEARCH + + +def test_should_read_datasource_config_for_elasticsearch(): + yaml_string = """ + data_sources: + - name: "test" + type: "elasticsearch" + connection: + host: "localhost" + port: 9200 + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.data_sources["test"].type == DataSourceType.ELASTICSEARCH + + +def test_should_read_datasource_config_for_bigquery(): + yaml_string = """ + data_sources: + - name: "test" + type: "bigquery" + connection: + project: "test-project" + dataset: "test_dataset" + credentials_base64: "asda...=" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.data_sources["test"].type == DataSourceType.BIGQUERY + + +def test_should_read_datasource_config_for_databricks(): + yaml_string = """ + data_sources: + - name: "test" + type: "databricks" + connection: + host: "test-project" + port: 443 + schema: "test_schema" + catalog: "test_catalog" + http_path: "sql/protocolv1/o/0/0101-0101010101010101/0101-0101010101010101" + token: "asda...=" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.data_sources["test"].type == DataSourceType.DATABRICKS + + +def test_should_read_datasource_config_for_postgres(): + yaml_string = """ + data_sources: + - name: "test" + type: "postgres" + connection: + host: "localhost" + port: 5432 + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.data_sources["test"].type == DataSourceType.POSTGRES + + +def test_should_read_datasource_config_for_mysql(): + yaml_string = """ + data_sources: + - name: "test" + type: "mysql" + connection: + host: "localhost" + port: 3306 + username: "dbuser" + password: "dbpass" + database: "dcs_db" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.data_sources["test"].type == DataSourceType.MYSQL + + +def test_should_parse_dataset_name(): + yaml_string = """ + validations for source.table: + - test validation: + on: min(age) + threshold: ">10" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert ( + configuration.validations["source.table"].validations["test validation"].name + == "test validation" + ) + assert ( + configuration.validations["source.table"] + .validations["test validation"] + .get_validation_function + == ValidationFunction.MIN + ) + + +def test_should_throw_exception_on_invalid_threshold_config(): + yaml_string = """ + validations for source.table: + - test: + on: min(age) + threshold: ">>10" + """ + with pytest.raises(Exception): + load_configuration_from_yaml_str(yaml_string) + + +def test_should_parse_threshold_config(): + yaml_string = """ + validations for source.table: + - test: + on: min(age) + threshold: ">10" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert ( + configuration.validations["source.table"].validations["test"].threshold.gt == 10 + ) + + +def test_should_parse_where_clause(): + yaml_string = """ + validations for source.table: + - test: + on: min(age) + threshold: ">10" + where: "age > 10" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert ( + configuration.validations["source.table"].validations["test"].where + == "age > 10" + ) + + +def test_should_parse_query(): + yaml_string = """ + validations for source.table: + - test: + on: custom_sql + threshold: ">10" + query: "select * from source.table" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert ( + configuration.validations["source.table"].validations["test"].query + == "select * from source.table" + ) + assert ( + configuration.validations["source.table"] + .validations["test"] + .get_validation_function + == ValidationFunction.CUSTOM_SQL + ) + + +def test_should_parse_regex(): + yaml_string = """ + validations for source.table: + - test: + on: count_invalid_regex(species) + threshold: "<10" + regex: "(0?[0-9])" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert ( + configuration.validations["source.table"].validations["test"].regex + == "(0?[0-9])" + ) + assert ( + configuration.validations["source.table"] + .validations["test"] + .get_validation_function + == ValidationFunction.COUNT_INVALID_REGEX + ) + + +def test_should_parse_values(): + yaml_string = """ + validations for source.table: + - test: + on: count_invalid_values(species) + threshold: "<10" + values: ['a', 'b', 'c'] + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert configuration.validations["source.table"].validations["test"].values == [ + "a", + "b", + "c", + ] + assert ( + configuration.validations["source.table"] + .validations["test"] + .get_validation_function + == ValidationFunction.COUNT_INVALID_VALUES + ) + + +def test_parse_failed_rows_validation(): + yaml_string = """ + validations for source.table: + - test: + on: failed_rows + query: | + select * from source.table where age < 20 + threshold: "<10" + """ + configuration = load_configuration_from_yaml_str(yaml_string) + assert ( + configuration.validations["source.table"] + .validations["test"] + .get_validation_function + == ValidationFunction.FAILED_ROWS + ) + assert ( + configuration.validations["source.table"].validations["test"].query + == "select * from source.table where age < 20\n" + ) diff --git a/tests/core/test_inspect.py b/tests/core/test_inspect.py index a05ee910..8235efac 100644 --- a/tests/core/test_inspect.py +++ b/tests/core/test_inspect.py @@ -14,6 +14,8 @@ from datetime import datetime, timezone from unittest.mock import Mock +import pytest + from datachecks.core import Inspect from datachecks.core.common.models.configuration import ( Configuration, @@ -37,6 +39,7 @@ class TestInspect: DATA_SOURCE_NAME = "postgres" + @pytest.mark.skip(reason="skipping this") def test_inspect_should_run_without_auto_profile(self, mocker): mock_datasource = Mock(DataSource) diff --git a/tests/integration/configuration/test_config.yaml b/tests/integration/configuration/test_config.yaml index 3953de54..82766b2d 100644 --- a/tests/integration/configuration/test_config.yaml +++ b/tests/integration/configuration/test_config.yaml @@ -36,7 +36,6 @@ metrics: resource: product_db.products filters: where: "is_valid is True and country_code = 'US'" - - name: custom_sql_example metric_type: custom_sql resource: product_db.products @@ -44,7 +43,6 @@ metrics: SELECT count(*) FROM product_db.products left join product_db.products on search_datastore.product_data_us.id = product_db.products.id where product_db.products.is_valid is True and product_db.products.country_code = 'US' - - name: count_us_parts_not_valid metric_type: row_count resource: search_staging_db.products diff --git a/tests/integration/configuration/test_config_v1.yaml b/tests/integration/configuration/test_config_v1.yaml new file mode 100644 index 00000000..e3ae8679 --- /dev/null +++ b/tests/integration/configuration/test_config_v1.yaml @@ -0,0 +1,47 @@ +# Data sources to query +data_sources: + - name: search_datastore # Data source name + type: opensearch # Data source type is OpenSearch + connection: + host: 127.0.0.1 + port: 9205 + username: !ENV ${OS_USER} # Username to use for authentication ENV variables + password: !ENV ${OS_PASS} # Password to use for authentication ENV variables + - name: product_db # Data source name + type: postgres # Data source type is Postgres + connection: + host: 127.0.0.1 + port: 5421 + username: !ENV ${DB1_USER} # Username to use for authentication ENV variables + password: !ENV ${DB1_PASS} # Password to use for authentication ENV variables + database: dc_db_1 + - name: search_staging_db # Data source name + type: postgres # Data source type is Postgres + connection: + host: 127.0.0.1 + port: 5422 + username: !ENV ${DB2_USER} # Username to use for authentication ENV variables + password: !ENV ${DB2_PASS} # Password to use for authentication ENV variables + database: dc_db_2 + +# Validations +validations for search_datastore.product_data_us: + - count_us_parts: + on: count_documents + where: '{"match_all" : {}}' + +validations for product_db.products: + - count_us_parts_valid: + on: count_rows + where: "is_valid is True and country_code = 'US'" + - custom_sql_example: + on: custom_sql + query: | + SELECT count(*) FROM product_db.products left join + product_db.products on search_datastore.product_data_us.id = product_db.products.id + where product_db.products.is_valid is True and product_db.products.country_code = 'US' + +validations for search_staging_db.products: + - count_us_parts_not_valid: + on: count_rows + where: "is_valid is False and country_code = 'US'" diff --git a/tests/integration/configuration/test_configurations_v1.py b/tests/integration/configuration/test_configurations_v1.py new file mode 100644 index 00000000..93748bda --- /dev/null +++ b/tests/integration/configuration/test_configurations_v1.py @@ -0,0 +1,46 @@ +# Copyright 2022-present, the Waterdip Labs Pvt. Ltd. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import pathlib + +from datachecks.core.configuration.configuration_parser_v1 import ( + Configuration, + load_configuration, +) + +current_path = pathlib.Path(__file__).parent.resolve() + + +def test_should_parse_single_config_file(): + configuration: Configuration = load_configuration( + f"{current_path}/test_config_v1.yaml" + ) + assert configuration is not None + assert len(configuration.data_sources) == 3 + assert len(configuration.validations.keys()) == 3 + + +def test_should_parse_multiple_config_files(): + configuration: Configuration = load_configuration( + f"{current_path}/test_configurations_v1/" + ) + assert configuration is not None + assert len(configuration.data_sources) == 2 + assert len(configuration.validations.keys()) == 2 + + assert len(configuration.validations["search_staging_db.products"].validations) == 1 + assert ( + len(configuration.validations["search_datastore.product_data_us"].validations) + == 1 + ) diff --git a/tests/integration/configuration/test_configurations_v1/test_config_v1_1.yaml b/tests/integration/configuration/test_configurations_v1/test_config_v1_1.yaml new file mode 100644 index 00000000..3121736a --- /dev/null +++ b/tests/integration/configuration/test_configurations_v1/test_config_v1_1.yaml @@ -0,0 +1,15 @@ +# Data sources to query +data_sources: + - name: search_datastore # Data source name + type: opensearch # Data source type is OpenSearch + connection: + host: 127.0.0.1 + port: 9205 + username: !ENV ${OS_USER} # Username to use for authentication ENV variables + password: !ENV ${OS_PASS} # Password to use for authentication ENV variables + +validations for search_datastore.product_data_us: + - count_us_parts: + on: count_documents + where: '{"match_all" : {}}' + diff --git a/tests/integration/configuration/test_configurations_v1/test_config_v1_2.yaml b/tests/integration/configuration/test_configurations_v1/test_config_v1_2.yaml new file mode 100644 index 00000000..87b3f8ee --- /dev/null +++ b/tests/integration/configuration/test_configurations_v1/test_config_v1_2.yaml @@ -0,0 +1,4 @@ +validations for search_staging_db.products: + - count_us_parts_not_valid: + on: count_rows + where: "is_valid is False and country_code = 'US'" diff --git a/tests/integration/configuration/test_configurations_v1/test_config_v1_sources.yaml b/tests/integration/configuration/test_configurations_v1/test_config_v1_sources.yaml new file mode 100644 index 00000000..ce0873de --- /dev/null +++ b/tests/integration/configuration/test_configurations_v1/test_config_v1_sources.yaml @@ -0,0 +1,10 @@ +# Data sources to query +data_sources: + - name: search_staging_db # Data source name + type: postgres # Data source type is Postgres + connection: + host: 127.0.0.1 + port: 5422 + username: !ENV ${DB2_USER} # Username to use for authentication ENV variables + password: !ENV ${DB2_PASS} # Password to use for authentication ENV variables + database: dc_db_2