Files
dbt-core/core/dbt/task/test.py

407 lines
14 KiB
Python

import agate
import daff
import io
import json
import re
from dataclasses import dataclass
from dbt.utils import _coerce_decimal, strtobool
from dbt_common.events.format import pluralize
from dbt_common.dataclass_schema import dbtClassMixin
import threading
from typing import Dict, Any, Optional, Union, List
from .compile import CompileRunner
from .run import RunTask
from dbt.contracts.graph.nodes import TestNode, UnitTestDefinition, UnitTestNode
from dbt.contracts.graph.manifest import Manifest
from dbt.artifacts.schemas.results import TestStatus
from dbt.artifacts.schemas.run import RunResult
from dbt.artifacts.schemas.catalog import PrimitiveDict
from dbt.context.providers import generate_runtime_model_context
from dbt.clients.jinja import MacroGenerator
from dbt_common.events.functions import fire_event
from dbt.events.types import (
LogTestResult,
LogStartLine,
)
from dbt.exceptions import DbtInternalError, BooleanError
from dbt_common.exceptions import DbtBaseException, DbtRuntimeError
from dbt.adapters.exceptions import MissingMaterializationError
from dbt.graph import (
ResourceTypeSelector,
)
from dbt.node_types import NodeType
from dbt.parser.unit_tests import UnitTestManifestLoader
from dbt.flags import get_flags
from dbt_common.ui import green, red
@dataclass
class UnitTestDiff(dbtClassMixin):
actual: List[Dict[str, Any]]
expected: List[Dict[str, Any]]
rendered: str
@dataclass
class TestResultData(dbtClassMixin):
failures: int
should_warn: bool
should_error: bool
adapter_response: Dict[str, Any]
@classmethod
def validate(cls, data):
data["should_warn"] = cls.convert_bool_type(data["should_warn"])
data["should_error"] = cls.convert_bool_type(data["should_error"])
super().validate(data)
def convert_bool_type(field) -> bool:
# if it's type string let python decide if it's a valid value to convert to bool
if isinstance(field, str):
try:
return bool(strtobool(field)) # type: ignore
except ValueError:
raise BooleanError(field, "get_test_sql")
# need this so we catch both true bools and 0/1
return bool(field)
@dataclass
class UnitTestResultData(dbtClassMixin):
should_error: bool
adapter_response: Dict[str, Any]
diff: Optional[UnitTestDiff] = None
class TestRunner(CompileRunner):
_ANSI_ESCAPE = re.compile(r"\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])")
def describe_node_name(self):
if self.node.resource_type == NodeType.Unit:
name = f"{self.node.model}::{self.node.versioned_name}"
return name
else:
return self.node.name
def describe_node(self):
return f"{self.node.resource_type} {self.describe_node_name()}"
def print_result_line(self, result):
model = result.node
fire_event(
LogTestResult(
name=self.describe_node_name(),
status=str(result.status),
index=self.node_index,
num_models=self.num_nodes,
execution_time=result.execution_time,
node_info=model.node_info,
num_failures=result.failures,
),
level=LogTestResult.status_to_level(str(result.status)),
)
def print_start_line(self):
fire_event(
LogStartLine(
description=self.describe_node(),
index=self.node_index,
total=self.num_nodes,
node_info=self.node.node_info,
)
)
def before_execute(self):
self.print_start_line()
def execute_data_test(self, data_test: TestNode, manifest: Manifest) -> TestResultData:
context = generate_runtime_model_context(data_test, self.config, manifest)
materialization_macro = manifest.find_materialization_macro_by_name(
self.config.project_name, data_test.get_materialization(), self.adapter.type()
)
if materialization_macro is None:
raise MissingMaterializationError(
materialization=data_test.get_materialization(), adapter_type=self.adapter.type()
)
if "config" not in context:
raise DbtInternalError(
"Invalid materialization context generated, missing config: {}".format(context)
)
# generate materialization macro
macro_func = MacroGenerator(materialization_macro, context)
# execute materialization macro
macro_func()
# load results from context
# could eventually be returned directly by materialization
result = context["load_result"]("main")
table = result["table"]
num_rows = len(table.rows)
if num_rows != 1:
raise DbtInternalError(
f"dbt internally failed to execute {data_test.unique_id}: "
f"Returned {num_rows} rows, but expected "
f"1 row"
)
num_cols = len(table.columns)
if num_cols != 3:
raise DbtInternalError(
f"dbt internally failed to execute {data_test.unique_id}: "
f"Returned {num_cols} columns, but expected "
f"3 columns"
)
test_result_dct: PrimitiveDict = dict(
zip(
[column_name.lower() for column_name in table.column_names],
map(_coerce_decimal, table.rows[0]),
)
)
test_result_dct["adapter_response"] = result["response"].to_dict(omit_none=True)
TestResultData.validate(test_result_dct)
return TestResultData.from_dict(test_result_dct)
def build_unit_test_manifest_from_test(
self, unit_test_def: UnitTestDefinition, manifest: Manifest
) -> Manifest:
# build a unit test manifest with only the test from this UnitTestDefinition
loader = UnitTestManifestLoader(manifest, self.config, {unit_test_def.unique_id})
return loader.load()
def execute_unit_test(
self, unit_test_def: UnitTestDefinition, manifest: Manifest
) -> UnitTestResultData:
unit_test_manifest = self.build_unit_test_manifest_from_test(unit_test_def, manifest)
# The unit test node and definition have the same unique_id
unit_test_node = unit_test_manifest.nodes[unit_test_def.unique_id]
assert isinstance(unit_test_node, UnitTestNode)
# Compile the node
unit_test_node = self.compiler.compile_node(unit_test_node, unit_test_manifest, {})
# generate_runtime_unit_test_context not strictly needed - this is to run the 'unit'
# materialization, not compile the node.compiled_code
context = generate_runtime_model_context(unit_test_node, self.config, unit_test_manifest)
materialization_macro = unit_test_manifest.find_materialization_macro_by_name(
self.config.project_name, unit_test_node.get_materialization(), self.adapter.type()
)
if materialization_macro is None:
raise MissingMaterializationError(
materialization=unit_test_node.get_materialization(),
adapter_type=self.adapter.type(),
)
if "config" not in context:
raise DbtInternalError(
"Invalid materialization context generated, missing config: {}".format(context)
)
# generate materialization macro
macro_func = MacroGenerator(materialization_macro, context)
# execute materialization macro
try:
macro_func()
except DbtBaseException as e:
raise DbtRuntimeError(
f"An error occurred during execution of unit test '{unit_test_def.name}'. "
f"There may be an error in the unit test definition: check the data types.\n {e}"
)
# load results from context
# could eventually be returned directly by materialization
result = context["load_result"]("main")
adapter_response = result["response"].to_dict(omit_none=True)
table = result["table"]
actual = self._get_unit_test_agate_table(table, "actual")
expected = self._get_unit_test_agate_table(table, "expected")
# generate diff, if exists
should_error, diff = False, None
daff_diff = self._get_daff_diff(expected, actual)
if daff_diff.hasDifference():
should_error = True
rendered = self._render_daff_diff(daff_diff)
rendered = f"\n\n{green('actual')} differs from {red('expected')}:\n\n{rendered}\n"
diff = UnitTestDiff(
actual=json_rows_from_table(actual),
expected=json_rows_from_table(expected),
rendered=rendered,
)
return UnitTestResultData(
diff=diff,
should_error=should_error,
adapter_response=adapter_response,
)
def execute(self, test: Union[TestNode, UnitTestDefinition], manifest: Manifest):
if isinstance(test, UnitTestDefinition):
unit_test_result = self.execute_unit_test(test, manifest)
return self.build_unit_test_run_result(test, unit_test_result)
else:
# Note: manifest here is a normal manifest
test_result = self.execute_data_test(test, manifest)
return self.build_test_run_result(test, test_result)
def build_test_run_result(self, test: TestNode, result: TestResultData) -> RunResult:
severity = test.config.severity.upper()
thread_id = threading.current_thread().name
num_errors = pluralize(result.failures, "result")
status = None
message = None
failures = 0
if severity == "ERROR" and result.should_error:
status = TestStatus.Fail
message = f"Got {num_errors}, configured to fail if {test.config.error_if}"
failures = result.failures
elif result.should_warn:
if get_flags().WARN_ERROR:
status = TestStatus.Fail
message = f"Got {num_errors}, configured to fail if {test.config.warn_if}"
else:
status = TestStatus.Warn
message = f"Got {num_errors}, configured to warn if {test.config.warn_if}"
failures = result.failures
else:
status = TestStatus.Pass
run_result = RunResult(
node=test,
status=status,
timing=[],
thread_id=thread_id,
execution_time=0,
message=message,
adapter_response=result.adapter_response,
failures=failures,
)
return run_result
def build_unit_test_run_result(
self, test: UnitTestDefinition, result: UnitTestResultData
) -> RunResult:
thread_id = threading.current_thread().name
status = TestStatus.Pass
message = None
failures = 0
if result.should_error:
status = TestStatus.Fail
message = result.diff.rendered if result.diff else None
failures = 1
return RunResult(
node=test, # type: ignore
status=status,
timing=[],
thread_id=thread_id,
execution_time=0,
message=message,
adapter_response=result.adapter_response,
failures=failures,
)
def after_execute(self, result):
self.print_result_line(result)
def _get_unit_test_agate_table(self, result_table, actual_or_expected: str):
unit_test_table = result_table.where(
lambda row: row["actual_or_expected"] == actual_or_expected
)
columns = list(unit_test_table.columns.keys())
columns.remove("actual_or_expected")
return unit_test_table.select(columns)
def _get_daff_diff(
self, expected: agate.Table, actual: agate.Table, ordered: bool = False
) -> daff.TableDiff:
expected_daff_table = daff.PythonTableView(list_rows_from_table(expected))
actual_daff_table = daff.PythonTableView(list_rows_from_table(actual))
alignment = daff.Coopy.compareTables(expected_daff_table, actual_daff_table).align()
result = daff.PythonTableView([])
flags = daff.CompareFlags()
flags.ordered = ordered
diff = daff.TableDiff(alignment, flags)
diff.hilite(result)
return diff
def _render_daff_diff(self, daff_diff: daff.TableDiff) -> str:
result = daff.PythonTableView([])
daff_diff.hilite(result)
rendered = daff.TerminalDiffRender().render(result)
# strip colors if necessary
if not self.config.args.use_colors:
rendered = self._ANSI_ESCAPE.sub("", rendered)
return rendered
class TestSelector(ResourceTypeSelector):
def __init__(self, graph, manifest, previous_state) -> None:
super().__init__(
graph=graph,
manifest=manifest,
previous_state=previous_state,
resource_types=[NodeType.Test, NodeType.Unit],
)
class TestTask(RunTask):
"""
Testing:
Read schema files + custom data tests and validate that
constraints are satisfied.
"""
__test__ = False
def raise_on_first_error(self):
return False
def get_node_selector(self) -> TestSelector:
if self.manifest is None or self.graph is None:
raise DbtInternalError("manifest and graph must be set to get perform node selection")
return TestSelector(
graph=self.graph,
manifest=self.manifest,
previous_state=self.previous_state,
)
def get_runner_type(self, _):
return TestRunner
# This was originally in agate_helper, but that was moved out into dbt_common
def json_rows_from_table(table: agate.Table) -> List[Dict[str, Any]]:
"Convert a table to a list of row dict objects"
output = io.StringIO()
table.to_json(path=output) # type: ignore
return json.loads(output.getvalue())
# This was originally in agate_helper, but that was moved out into dbt_common
def list_rows_from_table(table: agate.Table) -> List[Any]:
"Convert a table to a list of lists, where the first element represents the header"
rows = [[col.name for col in table.columns]]
for row in table.rows:
rows.append(list(row.values()))
return rows