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add pytest-benchmarks:ubuntu-22.04,psql_dos benchmark result for 6316099
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github-action-benchmark committed Jun 28, 2024
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185 changes: 184 additions & 1 deletion dev/bench/ubuntu-22.04/psql_dos/data.js
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window.BENCHMARK_DATA = {
"lastUpdate": 1719217931630,
"lastUpdate": 1719563519190,
"repoUrl": "https://github.com/aiidateam/aiida-core",
"xAxis": "id",
"oneChartGroups": [],
Expand Down Expand Up @@ -49231,6 +49231,189 @@ window.BENCHMARK_DATA = {
"extra": "mean: 22.266 msec\nrounds: 100"
}
]
},
{
"cpu": {
"speed": "3.24",
"cores": 4,
"physicalCores": 2,
"processors": 1
},
"extra": {
"pythonVersion": "3.10.14",
"metadata": "postgres:12.14, rabbitmq:3.8.14-management"
},
"commit": {
"id": "63160995d6078051f0f5e524b6fab9aabb2747ed",
"message": "CLI: Remove the RabbitMQ options from `verdi profile setup` (#6480)\n\nFor the vast majority of use cases, users will have a default setup for\r\nRabbitMQ and so the default configuration will be adequate and so they\r\nwill not need the options in the command. On the flipside, showing the\r\noptions by default can makes the command harder to use as users will\r\ntake pause to think what value to pass.\r\n\r\nSince there is the `verdi profile configure-rabbitmq` command now that\r\nallows to configure or reconfigure the RabbitMQ connection parameters\r\nfor an existing profile, it is fine to remove these options from the\r\nprofile setup. Advanced users that need to customize the connection\r\nparameters can resort to that separate command.",
"timestamp": "2024-06-28T10:24:28+02:00",
"url": "https://github.com/aiidateam/aiida-core/commit/63160995d6078051f0f5e524b6fab9aabb2747ed",
"distinct": true,
"tree_id": "6bed041b71901fe5c655fca0ddeea2f3bb6b14eb"
},
"date": 1719563514567,
"benches": [
{
"name": "tests/benchmark/test_archive.py::test_export[no-objects]",
"value": 3.157310601976752,
"unit": "iter/sec",
"range": "stddev: 0.058003",
"group": "import-export",
"extra": "mean: 316.73 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_archive.py::test_export[with-objects]",
"value": 3.069987049671511,
"unit": "iter/sec",
"range": "stddev: 0.060018",
"group": "import-export",
"extra": "mean: 325.73 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_archive.py::test_import[no-objects]",
"value": 4.45635708743272,
"unit": "iter/sec",
"range": "stddev: 0.0049008",
"group": "import-export",
"extra": "mean: 224.40 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_archive.py::test_import[with-objects]",
"value": 4.328511732814025,
"unit": "iter/sec",
"range": "stddev: 0.0037267",
"group": "import-export",
"extra": "mean: 231.03 msec\nrounds: 12"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[basic-loop]",
"value": 3.7457152533790414,
"unit": "iter/sec",
"range": "stddev: 0.0079910",
"group": "engine",
"extra": "mean: 266.97 msec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[serial-wc-loop]",
"value": 0.8102939855531748,
"unit": "iter/sec",
"range": "stddev: 0.086805",
"group": "engine",
"extra": "mean: 1.2341 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[threaded-wc-loop]",
"value": 0.8919307090032151,
"unit": "iter/sec",
"range": "stddev: 0.079698",
"group": "engine",
"extra": "mean: 1.1212 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[serial-calcjob-loop]",
"value": 0.21388756922902563,
"unit": "iter/sec",
"range": "stddev: 0.12862",
"group": "engine",
"extra": "mean: 4.6754 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_local[threaded-calcjob-loop]",
"value": 0.235817292932101,
"unit": "iter/sec",
"range": "stddev: 0.15853",
"group": "engine",
"extra": "mean: 4.2406 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[basic-loop]",
"value": 2.6299448733388098,
"unit": "iter/sec",
"range": "stddev: 0.010308",
"group": "engine",
"extra": "mean: 380.24 msec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[serial-wc-loop]",
"value": 0.542992789490042,
"unit": "iter/sec",
"range": "stddev: 0.040660",
"group": "engine",
"extra": "mean: 1.8416 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[threaded-wc-loop]",
"value": 0.6169507325180636,
"unit": "iter/sec",
"range": "stddev: 0.030029",
"group": "engine",
"extra": "mean: 1.6209 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[serial-calcjob-loop]",
"value": 0.16299274447396617,
"unit": "iter/sec",
"range": "stddev: 0.13486",
"group": "engine",
"extra": "mean: 6.1352 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_engine.py::test_workchain_daemon[threaded-calcjob-loop]",
"value": 0.18360929308279444,
"unit": "iter/sec",
"range": "stddev: 0.072438",
"group": "engine",
"extra": "mean: 5.4463 sec\nrounds: 10"
},
{
"name": "tests/benchmark/test_nodes.py::test_store_backend",
"value": 494.30249376209434,
"unit": "iter/sec",
"range": "stddev: 0.00010395",
"group": "node",
"extra": "mean: 2.0231 msec\nrounds: 294"
},
{
"name": "tests/benchmark/test_nodes.py::test_store",
"value": 79.53288858404802,
"unit": "iter/sec",
"range": "stddev: 0.00019724",
"group": "node",
"extra": "mean: 12.573 msec\nrounds: 100"
},
{
"name": "tests/benchmark/test_nodes.py::test_store_with_object",
"value": 54.478899981248226,
"unit": "iter/sec",
"range": "stddev: 0.00047515",
"group": "node",
"extra": "mean: 18.356 msec\nrounds: 100"
},
{
"name": "tests/benchmark/test_nodes.py::test_delete_backend",
"value": 295.3974958065447,
"unit": "iter/sec",
"range": "stddev: 0.00028811",
"group": "node",
"extra": "mean: 3.3853 msec\nrounds: 100"
},
{
"name": "tests/benchmark/test_nodes.py::test_delete",
"value": 46.788664153267206,
"unit": "iter/sec",
"range": "stddev: 0.00051531",
"group": "node",
"extra": "mean: 21.373 msec\nrounds: 100"
},
{
"name": "tests/benchmark/test_nodes.py::test_delete_with_object",
"value": 45.54062860707013,
"unit": "iter/sec",
"range": "stddev: 0.00082634",
"group": "node",
"extra": "mean: 21.958 msec\nrounds: 100"
}
]
}
]
}
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