7c18fa55e7
* Add benchmarking test suite * Improve amortized time of model relation loads with a large number of rows * Improve performance of loading models with many related models * Improve performance of loading models with many related models to O(N)ish * Fix bug where N model creation with shared related model would build in N^2 time * Lower blocking time for queryset results * Add docstrings and streamline hash code Co-authored-by: haydeec1 <Eric.Haydel@jhuapl.edu>
58 lines
1.5 KiB
Python
58 lines
1.5 KiB
Python
from typing import List
|
|
|
|
import pytest
|
|
|
|
from benchmarks.conftest import Author
|
|
|
|
pytestmark = pytest.mark.asyncio
|
|
|
|
|
|
@pytest.mark.parametrize("num_models", [250, 500, 1000])
|
|
async def test_count(aio_benchmark, num_models: int, authors_in_db: List[Author]):
|
|
@aio_benchmark
|
|
async def count():
|
|
return await Author.objects.count()
|
|
|
|
c = count()
|
|
assert c == len(authors_in_db)
|
|
|
|
|
|
@pytest.mark.parametrize("num_models", [250, 500, 1000])
|
|
async def test_avg(aio_benchmark, num_models: int, authors_in_db: List[Author]):
|
|
@aio_benchmark
|
|
async def avg():
|
|
return await Author.objects.avg("score")
|
|
|
|
average = avg()
|
|
assert 0 <= average <= 100
|
|
|
|
|
|
@pytest.mark.parametrize("num_models", [250, 500, 1000])
|
|
async def test_sum(aio_benchmark, num_models: int, authors_in_db: List[Author]):
|
|
@aio_benchmark
|
|
async def sum_():
|
|
return await Author.objects.sum("score")
|
|
|
|
s = sum_()
|
|
assert 0 <= s <= 100 * num_models
|
|
|
|
|
|
@pytest.mark.parametrize("num_models", [250, 500, 1000])
|
|
async def test_min(aio_benchmark, num_models: int, authors_in_db: List[Author]):
|
|
@aio_benchmark
|
|
async def min_():
|
|
return await Author.objects.min("score")
|
|
|
|
m = min_()
|
|
assert 0 <= m <= 100
|
|
|
|
|
|
@pytest.mark.parametrize("num_models", [250, 500, 1000])
|
|
async def test_max(aio_benchmark, num_models: int, authors_in_db: List[Author]):
|
|
@aio_benchmark
|
|
async def max_():
|
|
return await Author.objects.max("score")
|
|
|
|
m = max_()
|
|
assert 0 <= m <= 100
|