Benchmarks

Performance Benchmarks

Side-by-side pytest-benchmark suite comparing coodie against cqlengine. Benchmarks live in the benchmarks/ directory at the repository root.

When to Use This Skill

• Running performance benchmarks (coodie vs cqlengine)
• Adding a new benchmark for a coodie feature
• Investigating performance regressions or bottlenecks
• Debugging benchmark CI failures
• Comparing benchmark results over time

Prerequisites

• Docker must be running — most benchmarks spin up a ScyllaDB container via testcontainers.
• Python ≥ 3.10
• scylla-driver (or cassandra-driver) and pytest-benchmark must be installed.

Setup

See setup-environment.md for the shared environment setup (dev dependencies, pre-commit hooks, commit/push checklist).

Then install the scylla driver extra if not already present:

uv pip install -e ".[scylla]"

Running Benchmarks

Benchmarks are disabled by default (--benchmark-disable in pyproject.toml addopts). Pass --benchmark-enable to activate them.

# Run all benchmarks (requires Docker)
uv run pytest benchmarks/ -v --benchmark-enable --benchmark-sort=mean

# Run a specific benchmark file
uv run pytest benchmarks/bench_insert.py -v --benchmark-enable

# Compare coodie vs cqlengine side by side (grouped)
uv run pytest benchmarks/ -v --benchmark-enable --benchmark-group-by=group

# Serialization benchmarks only — no Docker needed
uv run pytest benchmarks/bench_serialization.py -v --benchmark-enable

Running with Different Drivers

Use --driver-type to choose which driver coodie uses for benchmarks. The cqlengine side always uses cassandra-driver / scylla-driver.

# Default — coodie uses CassandraDriver backed by scylla-driver
uv run pytest benchmarks/ -v --benchmark-enable --driver-type=scylla

# coodie uses AcsyllaDriver (async-native)
uv pip install -e ".[acsylla]"
uv run pytest benchmarks/ -v --benchmark-enable --driver-type=acsylla

Saving and Comparing Results

# Save results as a named baseline
uv run pytest benchmarks/ --benchmark-enable --benchmark-save=baseline

# Compare against a saved baseline
uv run pytest benchmarks/ --benchmark-enable --benchmark-compare=0001_baseline

# Generate an HTML histogram report
uv run pytest benchmarks/ --benchmark-enable --benchmark-histogram=bench_results

Benchmark Directory Layout

benchmarks/
├── conftest.py              # Session fixtures: ScyllaDB container, cqlengine + coodie setup
├── models_cqlengine.py      # cqlengine model definitions (Product, Review, Event)
├── models_coodie.py         # coodie model definitions (identical schema)
├── bench_insert.py          # INSERT benchmarks
├── bench_read.py            # SELECT / query benchmarks
├── bench_update.py          # UPDATE benchmarks
├── bench_delete.py          # DELETE benchmarks
├── bench_batch.py           # Batch operation benchmarks
├── bench_schema.py          # DDL / sync_table benchmarks
├── bench_collections.py     # Collection type read/write benchmarks
├── bench_serialization.py   # Model instantiation + serialization (no DB)
└── README.md                # Full documentation

Writing a New Benchmark

Each benchmark file contains paired functions — one for cqlengine, one for coodie — grouped by @pytest.mark.benchmark(group="<name>").

Template

"""<Feature> benchmarks — coodie vs cqlengine."""

from __future__ import annotations

from uuid import uuid4
import pytest


@pytest.mark.benchmark(group="my-feature")
def test_cqlengine_my_feature(benchmark, bench_env):
    from benchmarks.models_cqlengine import CqlProduct

    def _op():
        CqlProduct.create(id=uuid4(), name="Bench")

    benchmark(_op)


@pytest.mark.benchmark(group="my-feature")
def test_coodie_my_feature(benchmark, bench_env):
    from benchmarks.models_coodie import CoodieProduct

    def _op():
        CoodieProduct(id=uuid4(), name="Bench").save()

    benchmark(_op)

Key Conventions

• Use the bench_env fixture for tests that need the database (ensures both cqlengine and coodie are initialised with a ScyllaDB container).
• Omit bench_env for pure-Python benchmarks (e.g. serialization).
• Name functions test_cqlengine_<feature> and test_coodie_<feature>.
• Use the same group= value so results are displayed side by side.

Fixture Reference

Performance Targets

Pydantic validation adds overhead versus cqlengine's metaclass approach. These targets accept that trade-off in exchange for type safety and FastAPI integration.

Bottleneck Investigation

When a benchmark shows coodie is slower than cqlengine:

1. Flame graph — py-spy record -o profile.svg -- python -m pytest benchmarks/bench_insert.py -v
2. Python vs C time — scalene --- -m pytest benchmarks/bench_insert.py -v
3. Memory — memray run -o output.bin -m pytest benchmarks/bench_insert.py -v && memray flamegraph output.bin
4. Isolate the layer — run the same CQL via raw driver.execute() to check if overhead is in the ORM layer or the driver
5. Serialization — compare model_dump() vs cqlengine's internal serialization separately (see bench_serialization.py)
6. Prepared-statement cache — verify cache hits (a miss = extra round-trip)

CI Integration

The .github/workflows/benchmark.yml workflow runs benchmarks:

• On every push to main
• On a weekly schedule (Monday 06:00 UTC)
• On pull requests when the benchmark label is added

Results are exported as a benchmark-results.json artifact (retained 90 days).

To trigger benchmarks on a PR, add the benchmark label.