Add benchmarking test suite and greatly improve performance in a few cases (#948)

* 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>

benchmarks/test_benchmark_aggregate.py

@@ -0,0 +1,57 @@
+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