215 lines
8.6 KiB
Python
215 lines
8.6 KiB
Python
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import logging
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import timeit
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from typing import Literal
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from odoo import Command
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from odoo.models import BaseModel
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from odoo.tests.common import TransactionCase
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_logger = logging.getLogger(__name__)
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class TestPerformanceTimeit(TransactionCase):
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@classmethod
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def setUpClass(cls):
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super().setUpClass()
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cls.Model = cls.env['test_performance.simple.minded'].with_context(active_test=False)
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def create_parent(size):
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return cls.Model.create({
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'name': f'parent_{size}_children',
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'child_ids': [
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Command.create({
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'name': f'{size}_child_{i}',
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'active': (i % 4) != 0,
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})
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for i in range(size)
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],
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})
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cls.parent_0_child = create_parent(0)
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cls.parent_1_child = create_parent(1)
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cls.parent_10_children = create_parent(10)
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cls.parent_100_children = create_parent(100)
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cls.parent_1000_children = create_parent(1_000)
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cls.parent_10000_children = create_parent(10_000)
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cls.example_domains = [
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[('id', '<', 100)],
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[('id', '<', 100), ('name', '=like', 'par')],
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[('active', '=', False)],
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[('parent_id.name', 'like', "100")],
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[('parent_id', 'like', "100")],
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]
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@classmethod
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def get_parents(cls):
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return [
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cls.parent_1_child,
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cls.parent_10_children,
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cls.parent_100_children,
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cls.parent_1000_children,
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cls.parent_10000_children,
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]
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@classmethod
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def get_test_children(cls, *, max_size=10**6):
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"""Get records for testing, give the max size of the recordset"""
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all_records = [p.child_ids for p in cls.get_parents()]
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result = [recs for recs in all_records if len(recs) < max_size]
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# find the next bigger and trucate it to max size
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if bigger := next((recs for recs in all_records if len(recs) > max_size), None):
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result.append(bigger[:max_size])
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return result
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def setUp(self):
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super().setUp()
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# Warm up the cache of all data
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self.Model.with_context(active_test=False).search([]).mapped('name')
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def launch_perf(
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self, code: str, records: BaseModel, *,
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relative_size: int = 1, # relative size of the batch (for comparisons)
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number: int = 100, # number of runs in each iteration
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repeat: int = 3, # number of repeated runs
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ctx: dict = {}, # additional local variables
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) -> float:
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"""Run a performance test.
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Returns the best execution run time in microseconds.
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The number of runs is `number * repeat`.
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"""
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assert repeat > 1, "repeat at least twice as the first result is often slower"
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assert number > 0, "number of runs must be positive"
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times = timeit.repeat(code, globals={**ctx, 'records': records}, repeat=repeat, number=number)
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best_mean = min(times) / number * 1_000_000
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if relative_size != 1:
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_logger.info(" `%s` takes %.3fµs (%.3fµs/%d)", code, best_mean / relative_size, best_mean, relative_size)
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else:
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_logger.info(" `%s` takes %.3fµs", code, best_mean)
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return best_mean
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def launch_perf_set(
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self,
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code: str, *,
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record_list: list[BaseModel] | None = None,
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relative_size: list[int] | None = None,
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check_type: Literal['linear', 'maybe-linear', None] = 'linear',
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number: int = 4,
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repeat: int = 3,
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**kw,
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):
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# initialize the record list with the children records
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if not record_list:
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record_list = self.get_test_children()
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# relative sizes are initialized to 1, 10, 100, ...
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relative_sizes = relative_size or [10 ** i for i in range(len(record_list))]
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assert len(relative_sizes) == len(record_list)
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results = [
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self.launch_perf(code, records=records, relative_size=relative_size, repeat=repeat, number=number, **kw)
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for records, relative_size in zip(record_list, relative_sizes)
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]
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# checks
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if len(results) <= 3:
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check_type = None
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if check_type in ('linear', 'maybe-linear'):
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# approximative check that the resulting runs are behaving linearly
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# skip the first result as it is very small and not comparable
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check_results = [r / s for r, s in zip(results, relative_sizes)][1:]
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min_time = check_results[0] # take the time for the first check result as a comparison point
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max_time = max(check_results)
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# just check that the biggest difference of timings per record
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# compared to minimum run time is not greater than the max_tolerance
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max_tolerance = 2.5
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if check_type == 'linear':
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self.assertLess(max_time / min_time, max_tolerance, f"Non-linear behaviour detected, relative results: {check_results}")
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else:
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_logger.info("Linear behaviour result is %s for %s", max_time / min_time < max_tolerance, check_results)
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else:
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self.assertFalse(check_type, "Unsupported check_type")
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return results
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def test_perf_field_get(self):
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self.launch_perf("records.name", self.parent_0_child)
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def test_perf_field_getitem(self):
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self.launch_perf("records['name']", self.parent_0_child)
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def test_perf_field_set(self):
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self.launch_perf("records.name = 'ok'", self.parent_0_child)
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self.launch_perf_set("records.name = records[0].name")
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def test_perf_field_set_flush(self):
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self.launch_perf("records.flush_recordset()", self.parent_0_child)
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self.launch_perf("records.write({'name': 'ok'}); records.flush_recordset()", self.parent_0_child)
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def test_perf_filtered_by_field(self):
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self.launch_perf_set("records.filtered('active')")
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def test_perf_mapped(self):
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self.launch_perf_set("records.mapped('name')")
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def test_perf_sorted(self):
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self.launch_perf_set("records.sorted('name')")
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def test_perf_access_one2many_active_test(self):
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record_list = [
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p.with_context(active_test=True)
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for p in self.get_parents()
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]
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self.launch_perf_set("records.child_ids", record_list=record_list)
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def test_perf_access_iter(self):
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self.launch_perf_set("list(records)")
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def test_perf_as_query(self):
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self.launch_perf_set("records._as_query()", number=100)
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def test_perf_exists(self):
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self.launch_perf_set("records.exists()")
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def test_perf_search_query(self):
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self.launch_perf("records._search([])", self.Model)
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self.launch_perf("records._search([], limit=10)", self.Model)
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self.launch_perf("records._search([], order='id')", self.Model)
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self.launch_perf("records._search([], order='name')", self.Model)
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self.launch_perf("records._search([], order='parent_id, id desc')", self.Model)
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def test_perf_domain_search(self):
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for domain in self.example_domains:
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self.launch_perf(f"records._search({domain!r})", self.Model)
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def test_perf_domain_filtered(self):
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for domain in self.example_domains:
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self.launch_perf_set(f"records.filtered_domain({domain!r})", repeat=2)
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def test_perf_xxlarge_domain(self):
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def large_domain(records):
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N = len(records)
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return ['|'] * (N - 1) + [('name', '=', 'admin')] * N
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ctx = {'dom': large_domain}
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# _search()
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self.launch_perf_set("records._search(dom(records))",
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ctx=ctx, repeat=2, number=3, check_type='maybe-linear')
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# search() with result, minimal run times, just to check if we can handle the query execution
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self.launch_perf_set("records.search(dom(records))",
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# max is set to 9.5k because for 10k we get an out of memory error
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record_list=self.get_test_children(max_size=9500),
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ctx=ctx, repeat=2, number=1, check_type='maybe-linear')
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# filtered_domain() is non-linear and may time-out!
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self.launch_perf_set("records.filtered_domain(dom(records))",
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record_list=self.get_test_children(max_size=400),
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ctx=ctx, repeat=2, number=2, check_type=None)
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def test_perf_xxlarge_domain_unique(self):
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def large_domain_uniq(records):
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N = len(records)
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return ['|'] * (N - 1) + [('name', '=', str(i)) for i in range(N)]
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ctx = {'dom': large_domain_uniq}
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self.launch_perf_set("records._search(dom(records))",
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ctx=ctx, repeat=2, number=3, check_type='maybe-linear')
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