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# Copyright (C) 2023 The Qt Company Ltd.
# SPDX-License-Identifier: LicenseRef-Qt-Commercial OR LGPL-3.0-only OR GPL-2.0-only OR GPL-3.0-only
import datetime
import logging
from typing import Any, Dict, List, Optional, Union
import influxdb_client # type: ignore
import urllib3
from influxdb_client.client.influxdb_client_async import InfluxDBClientAsync # type: ignore
import common
import coordinator
import host
import qt
import storage
class UploadTimedOut(common.Error):
pass
class Mode(storage.Mode):
"""
A storage mode in which the runner uploads results to a database.
It includes database credentials.
"""
def __init__(self, server_url: str, username: str, password: str, database_name: str) -> None:
self.server_url = server_url
self.username = username
self.password = password
self.database_name = database_name
def create_environment(self) -> "Environment":
return Environment(self)
class Environment(storage.Environment):
"""
Uploads results to a database.
"""
def __init__(self, mode: Mode) -> None:
self.database_name = mode.database_name
self.client = InfluxDBClientAsync(
url=mode.server_url, token=f"{mode.username}:{mode.password}", org="-"
)
async def __aenter__(self) -> "Environment":
await self.client.__aenter__()
return self
async def __aexit__(self, exception_type: Any, exception_value: Any, traceback: Any) -> bool:
await self.client.__aexit__(exception_type, exception_value, traceback)
return False
async def store(
self,
results: List[qt.TestFileResult],
issues: List[qt.TestFileIssue],
work_item: coordinator.WorkItem,
host_info: host.Info,
logger: Optional[logging.Logger],
) -> Optional[common.Error]:
if logger is not None:
logger.debug("Preparing results for upload")
data_points = self.prepare_data(
results=results,
issues=issues,
work_item=work_item,
host_info=host_info,
logger=logger,
)
match data_points:
case common.Error() as error:
return error
if logger is not None:
logger.info("Uploading results")
try:
await self.client.write_api().write(
bucket=f"{self.database_name}/autogen", record=data_points
)
except urllib3.exceptions.TimeoutError as exception:
return UploadTimedOut(f"Upload timed out: {repr(exception)}")
except Exception as exception:
return common.Error(f"InfluxDB exception: {repr(exception)}")
return None
def prepare_data(
self,
results: List[qt.TestFileResult],
issues: List[qt.TestFileIssue],
work_item: coordinator.WorkItem,
host_info: host.Info,
logger: Optional[logging.Logger],
) -> Union[List[influxdb_client.Point], common.Error]:
"""
Prepare data for upload.
Data points are created for several measurements. Integration timestamp is used as time.
"""
benchmark_run = [
self.prepare_benchmark_run(
timestamp=work_item.integration_timestamp,
host_info=host_info,
work_item=work_item,
)
]
test_file_issues = self.prepare_test_file_issues(
timestamp=work_item.integration_timestamp,
issues=issues,
branch=work_item.branch,
host_info=host_info,
)
benchmark_results = self.prepare_benchmark_results(
timestamp=work_item.integration_timestamp,
branch=work_item.branch,
results=results,
host_info=host_info,
logger=logger,
)
if not benchmark_results:
return common.Error("No data points in test results")
else:
return benchmark_run + test_file_issues + benchmark_results
def prepare_benchmark_run(
self,
timestamp: datetime.datetime,
host_info: host.Info,
work_item: coordinator.WorkItem,
) -> influxdb_client.Point:
"""
Create a data point for the benchmark run measurement.
"""
point = influxdb_client.Point("benchmark_runs")
point.time(timestamp)
point.tag("host", host_info.name)
point.tag("branch", work_item.branch)
point.field("integration_id", work_item.integration_id)
point.field("sha", work_item.revision)
return point
def prepare_test_file_issues(
self,
timestamp: datetime.datetime,
host_info: host.Info,
branch: str,
issues: List[qt.TestFileIssue],
) -> List[influxdb_client.Point]:
"""
Create data points for the test file issue measurement.
"""
points = []
for issue in issues:
point = influxdb_client.Point("test_file_issues")
point.time(timestamp)
point.tag("host", host_info.name)
point.tag("branch", branch)
point.tag("test_file", issue.test_file.relative_path)
point.field("description", issue.description)
points.append(point)
return points
def prepare_benchmark_results(
self,
timestamp: datetime.datetime,
branch: str,
results: List[qt.TestFileResult],
host_info: host.Info,
logger: Optional[logging.Logger],
) -> List[influxdb_client.Point]:
"""
Create data points for the benchmark result measurement.
"""
points = []
for test_file_result in results:
if logger is not None:
logger.debug(f"Preparing results from test file {test_file_result.test_file.name}")
for test_function_result in test_file_result.test_case_result.test_function_results:
if logger is not None:
logger.debug(
f"Preparing results from test function {test_function_result.name}"
)
# Group everything by data tag.
benchmark_results_by_tag: Dict[Optional[str], List[qt.BenchmarkResult]] = {}
for benchmark_result in test_function_result.benchmark_results:
benchmark_results_by_tag.setdefault(benchmark_result.data_tag, []).append(
benchmark_result
)
incidents_by_tag: Dict[Optional[str], List[qt.Incident]] = {}
for incident in test_function_result.incidents:
incidents_by_tag.setdefault(incident.data_tag, []).append(incident)
messages_by_tag: Dict[Optional[str], List[qt.Message]] = {}
for message in test_function_result.messages:
messages_by_tag.setdefault(message.data_tag, []).append(message)
for tag, benchmark_results in benchmark_results_by_tag.items():
incidents = incidents_by_tag.get(benchmark_result.data_tag, [])
if len(benchmark_results) > 1:
if logger is not None:
logger.debug(
"Dropping benchmark result data from "
f"test file {test_file_result.test_file.name}, "
f"test function {test_function_result.name}, "
f'and data tag "{tag}": duplicate data tags'
)
elif not incidents:
if logger is not None:
logger.debug(
"Dropping benchmark result data from "
f"test file {test_file_result.test_file.name}, "
f"test function {test_function_result.name}, "
f'and data tag "{tag}": no pass/fail information'
)
else:
benchmark_result = benchmark_results[0]
incident = incidents[0]
point = influxdb_client.Point("benchmark_results")
point.time(timestamp)
point.tag("host", host_info.name)
point.tag("branch", branch)
point.tag("test_file", test_file_result.test_file.relative_path)
point.tag("test_case", test_file_result.test_case_result.name)
point.tag("test_function", test_function_result.name)
point.tag("data_tag", benchmark_result.data_tag)
point.field("value", benchmark_result.value)
points.append(point)
return points
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