diff --git a/.github/workflows/benchmarks-nightly.yml b/.github/workflows/benchmarks-nightly.yml new file mode 100644 index 00000000..59d3123b --- /dev/null +++ b/.github/workflows/benchmarks-nightly.yml @@ -0,0 +1,65 @@ +name: Nightly Integration Benchmarks + +on: + schedule: + - cron: "0 2 * * *" # 2 AM UTC daily + workflow_dispatch: # Allow manual trigger + +jobs: + integration-benchmark: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install hatch + run: pip install hatch + + - name: Run integration benchmarks with CodSpeed + uses: CodSpeedHQ/action@v3 + env: + CODSPEED_VALGRIND_ARGS: "--trace-children=yes --trace-children-skip=/bin/sh,/usr/bin/git" + UV_NO_PROGRESS: "1" + with: + token: ${{ secrets.CODSPEED_TOKEN }} + run: hatch run benchmark:run --codspeed -m "integration" + + - name: Generate benchmark JSON (fallback) + if: always() + env: + UV_NO_PROGRESS: "1" + run: | + hatch run benchmark:run \ + --benchmark-only \ + --benchmark-json=integration-benchmark-results.json \ + -m "integration" || true + + - name: Upload benchmark results + uses: actions/upload-artifact@v4 + if: always() + with: + name: integration-benchmark-results + path: integration-benchmark-results.json + retention-days: 90 + + - name: Run memory profiling on integration tests + if: always() + env: + UV_NO_PROGRESS: "1" + run: | + hatch run benchmark:memory \ + --memray-bin-path=integration-memray-results \ + -m "integration" || true + + - name: Upload memory results + uses: actions/upload-artifact@v4 + if: always() + with: + name: integration-memory-results + path: integration-memray-results/ + retention-days: 90 diff --git a/.github/workflows/benchmarks.yml b/.github/workflows/benchmarks.yml new file mode 100644 index 00000000..52ac7001 --- /dev/null +++ b/.github/workflows/benchmarks.yml @@ -0,0 +1,82 @@ +name: Benchmarks + +on: + pull_request: + types: [labeled, synchronize] + push: + branches: [main] + +jobs: + benchmark-cpu: + # Only run on PRs with 'run-benchmarks' label OR on main branch + if: | + github.event_name == 'push' || + contains(github.event.pull_request.labels.*.name, 'run-benchmarks') + + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install hatch + run: pip install hatch + + - name: Run benchmarks with CodSpeed + uses: CodSpeedHQ/action@v3 + with: + token: ${{ secrets.CODSPEED_TOKEN }} + run: hatch run benchmark:run --codspeed -m "not slow and not integration" + + - name: Generate benchmark JSON (fallback) + if: always() + run: | + hatch run benchmark:run \ + --benchmark-only \ + --benchmark-json=benchmark-results.json \ + -m "not slow and not integration" || true + + - name: Upload benchmark results + uses: actions/upload-artifact@v4 + if: always() + with: + name: benchmark-results + path: benchmark-results.json + retention-days: 30 + + benchmark-memory: + # Run on main branch pushes (for baseline tracking) OR PRs with 'run-benchmarks' label + if: | + github.event_name == 'push' || + contains(github.event.pull_request.labels.*.name, 'run-benchmarks') + + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install hatch + run: pip install hatch + + - name: Run memory benchmarks + run: | + hatch run benchmark:memory \ + --memray-bin-path=memray-results \ + -m "not slow and not integration" + + - name: Upload memory results + uses: actions/upload-artifact@v4 + if: always() + with: + name: memory-results + path: memray-results/ + retention-days: 30 diff --git a/benchmarks/README.md b/benchmarks/README.md new file mode 100644 index 00000000..8015aa16 --- /dev/null +++ b/benchmarks/README.md @@ -0,0 +1,428 @@ +# Fromager Benchmarks + +Performance benchmarks for Fromager, a tool for rebuilding complete dependency trees of Python wheels from source. + +## Table of Contents + +- [Why Benchmarks?](#why-benchmarks) +- [Quick Start](#quick-start) +- [Understanding the Output](#understanding-the-output) +- [How It Works](#how-it-works) + - [Local Benchmarking with pytest-benchmark](#local-benchmarking-with-pytest-benchmark) + - [CI Benchmarking with CodSpeed](#ci-benchmarking-with-codspeed) + - [Network Isolation with Local PyPI](#network-isolation-with-local-pypi) + - [Subprocess Isolation with uv Shim](#subprocess-isolation-with-uv-shim) + - [Memory Profiling with pytest-memray](#memory-profiling-with-pytest-memray) +- [Benchmark Categories](#benchmark-categories) +- [Adding New Benchmarks](#adding-new-benchmarks) +- [CI Workflows](#ci-workflows) +- [Directory Structure](#directory-structure) +- [Troubleshooting](#troubleshooting) +- [Resources](#resources) + +--- + +## Why Benchmarks? + +Fromager processes hundreds of packages during a typical bootstrap, each requiring version resolution, source acquisition, patching, and wheel building. Performance regressions in Fromager's core logic compound across these operations. + +**The challenge:** Wall-clock benchmarks in shared CI environments vary 10-20% due to noise (other processes, network latency, disk I/O). A genuine 5% regression becomes indistinguishable from CI variance. + +**Our solution:** We use two complementary approaches: + +1. **Locally:** pytest-benchmark for quick iteration during development +2. **In CI:** CodSpeed for noise-resistant measurements using CPU instruction counting + +--- + +## Quick Start + +```bash +# Run all benchmarks (uses pytest-benchmark locally) +hatch run benchmark:run + +# Run fast benchmarks only (skip slow and integration tests) +hatch run benchmark:fast + +# Compare your changes against a baseline +hatch run benchmark:run --benchmark-save=baseline +# ... make your changes ... +hatch run benchmark:compare baseline + +# Export results to JSON for external analysis +hatch run benchmark:json +``` + +--- + +## Understanding the Output + +When you run benchmarks, you'll see output like this: + +```text +-------------------------------- benchmark: 3 tests -------------------------------- +Name Mean StdDev Rounds +------------------------------------------------------------------------------------ +test_constraint_add_and_check 0.85ms 0.05ms 100 +test_graph_serialization 1.20ms 0.08ms 100 +test_python_version_matching_hot 0.12ms 0.01ms 200 +------------------------------------------------------------------------------------ +``` + +**What these columns mean:** + +- **Name** — The benchmark test function name +- **Mean** — Average execution time (the primary metric to compare) +- **StdDev** — Standard deviation; lower values mean more consistent measurements +- **Rounds** — How many times the benchmark ran; more rounds = more statistical confidence + +**When comparing against a baseline:** + +```text +Name Mean (now) Mean (base) Ratio +-------------------------------------------------------------------- +test_constraint_add_and_check 0.87ms 0.85ms 1.02x +``` + +- **Ratio < 1.0** — Your code is faster (improvement!) +- **Ratio = 1.0** — No change +- **Ratio > 1.15** — Your code is slower; investigate before merging + +--- + +## How It Works + +### Local Benchmarking with pytest-benchmark + +[pytest-benchmark](https://pytest-benchmark.readthedocs.io/) is a pytest plugin that measures execution time of your code. It handles the complexity of accurate timing: warm-up runs, garbage collection, statistical analysis, and comparison against saved baselines. + +**How we use it:** + +```python +def test_constraint_satisfaction(benchmark): + """The 'benchmark' fixture is provided by pytest-benchmark.""" + from fromager.constraints import Constraints + + constraints = Constraints() + constraints.add_constraint("numpy>=1.20,<2.0") + + # This function will be called many times to get accurate timing + def check_constraint(): + return constraints.is_satisfied_by("numpy", Version("1.25.0")) + + result = benchmark(check_constraint) # Measures execution time + assert result is True # Always verify correctness too! +``` + +The `benchmark` fixture automatically: + +- Warms up the code before measuring +- Runs multiple iterations to get statistical significance +- Disables garbage collection during measurement +- Calculates mean, standard deviation, and other statistics + +--- + +### CI Benchmarking with CodSpeed + +**The problem with wall-clock time in CI:** GitHub Actions runners are shared machines. Other jobs, network conditions, and system processes cause timing variations of 10-20%. This noise masks real performance regressions. + +**CodSpeed's solution:** Instead of measuring wall-clock time, [CodSpeed](https://codspeed.io/) counts CPU instructions executed. Instruction counts are deterministic—the same code always executes the same number of instructions, regardless of system load. + +**How it works in our CI:** + +1. When you add the `run-benchmarks` label to a PR, our GitHub Action triggers +2. CodSpeed's action runs your benchmarks inside Valgrind (an instrumentation tool) +3. Valgrind counts every CPU instruction executed +4. CodSpeed compares instruction counts against the main branch baseline +5. CodSpeed posts a comment on your PR showing any regressions + +**Why this matters:** + +- A 5% regression is clearly visible (not hidden in noise) +- Results are reproducible across different CI runs +- No need for dedicated benchmark hardware + +**Configuration:** The `CODSPEED_TOKEN` secret must be configured in the repository for CI benchmarks to report to the CodSpeed dashboard. + +--- + +### Network Isolation with Local PyPI + +**The problem:** Real package resolution hits PyPI servers. Network latency varies, servers may be slow, and results become non-deterministic. + +**Our solution:** The `local_pypi` fixture starts a local [pypiserver](https://github.com/pypiserver/pypiserver) instance: + +```python +@pytest.fixture(scope="session") +def local_pypi(tmp_path_factory): + """Starts a local PyPI server for the entire test session.""" + # Downloads packages from requirements/packages.txt + # Starts pypiserver on localhost:18080 + # All package resolution uses this local server +``` + +**How it's used:** + +```python +@pytest.mark.integration +def test_resolution_benchmark(benchmark, configured_env): + """configured_env sets UV_INDEX_URL to point to local PyPI.""" + # Any package resolution now hits localhost, not the internet + result = benchmark(resolve_packages) +``` + +The `configured_env` fixture automatically sets: + +- `UV_INDEX_URL` → `http://localhost:18080/simple` +- `PIP_INDEX_URL` → `http://localhost:18080/simple` +- `UV_NO_PROGRESS` → `1` (cleaner output) + +--- + +### Subprocess Isolation with uv Shim + +**The problem:** Fromager calls external tools like `uv` via subprocess. The actual execution time of `uv` varies based on many factors (disk cache, network, system load). This variance pollutes our measurements of Fromager's own code. + +**Our solution:** The `uv_shim` fixture creates a fake `uv` binary that does nothing but exit immediately: + +```python +# This is what the shim does (simplified): +#!/usr/bin/env python3 +import time +time.sleep(0.01) # Fixed 10ms delay +sys.exit(0) # Instant success +``` + +**How it works:** + +1. The fixture creates a temporary executable script +2. The `with_uv_shim` fixture prepends this script's directory to `PATH` +3. When Fromager calls `subprocess.run(["uv", ...])`, it finds our shim first +4. The shim returns instantly with success +5. We measure only Fromager's Python code, not `uv`'s execution + +**When to use it:** + +```python +@pytest.mark.integration +def test_build_workflow(benchmark, with_uv_shim, subprocess_timer): + """with_uv_shim makes 'uv' calls instant and deterministic.""" + + with subprocess_timer.measure(): + result = benchmark(run_fromager_build) + + # subprocess_timer tells us how much time was spent in subprocesses + print(f"Subprocess calls: {subprocess_timer.call_count}") + print(f"Overhead ratio: {subprocess_timer.overhead_ratio}") +``` + +The `subprocess_timer` fixture patches `subprocess.run` to measure: + +- **call_count** — How many subprocesses were spawned +- **total_time** — Total time spent waiting for subprocesses +- **overhead_ratio** — Fraction of time spent in Fromager's Python code (vs. subprocesses) + +--- + +### Memory Profiling with pytest-memray + +[pytest-memray](https://pytest-memray.readthedocs.io/) tracks memory allocations during test execution. This helps identify memory leaks or excessive allocations. + +```bash +# Run with memory profiling +hatch run benchmark:memory + +# Save detailed results for analysis +hatch run benchmark:memory --memray-bin-path=./memray-results +``` + +**Note:** pytest-memray only works on Linux and macOS (not Windows). + +**Important:** Memory profiling and CodSpeed cannot run together—both instrument the Python interpreter in ways that conflict. Our CI runs them as separate jobs. + +--- + +## Benchmark Categories + +| Category | File | What it Tests | Speed | +| --------------- | --------------------- | -------------------------------------------------------------- | ----------------------- | +| **Component** | `test_resolution.py` | Pure Python functions (Constraints, DependencyGraph, resolver) | Fast (< 1 second each) | +| **Integration** | `test_integration.py` | Full workflows with fixtures (file I/O, subprocess calls) | Slow (may take seconds) | + +**Markers to control what runs:** + +```bash +# Skip slow benchmarks +hatch run benchmark:run -m "not slow" + +# Skip integration benchmarks +hatch run benchmark:run -m "not integration" + +# Only run integration benchmarks +hatch run benchmark:run -m "integration" +``` + +--- + +## Adding New Benchmarks + +### Basic Benchmark + +```python +def test_my_operation(benchmark): + """Benchmark a simple operation.""" + from fromager.my_module import my_function + + # Setup: runs once, NOT measured + data = prepare_test_data() + + # This function is what gets measured (runs many times) + def operation(): + return my_function(data) + + result = benchmark(operation) + + # Always verify correctness! + assert result == expected_value +``` + +### Benchmark with Fixtures + +```python +@pytest.mark.integration +@pytest.mark.slow +def test_full_workflow(benchmark, configured_env, subprocess_timer): + """Benchmark a complete workflow with network and subprocess isolation.""" + + def workflow(): + with subprocess_timer.measure(): + return run_complete_workflow() + + result = benchmark(workflow) + + # Record extra metrics for analysis + benchmark.extra_info["subprocess_calls"] = subprocess_timer.call_count + benchmark.extra_info["overhead_ratio"] = subprocess_timer.overhead_ratio + + assert result.success +``` + +### Guidelines + +1. **Keep setup outside the measured function** — Only measure the code you're interested in +2. **Always assert correctness** — A fast but wrong function is useless +3. **Use appropriate markers** — Mark slow tests with `@pytest.mark.slow` +4. **Add extra_info for debugging** — `benchmark.extra_info["key"] = value` appears in JSON output + +--- + +## CI Workflows + +### `benchmarks.yml` — PR and Main Branch + +**Triggers:** + +- Push to `main` branch (updates baseline) +- PRs with the `run-benchmarks` label + +**What it does:** + +1. Runs fast benchmarks with CodSpeed (instruction counting) +2. CodSpeed compares against main branch baseline +3. Posts results as a PR comment +4. Also generates JSON artifacts for local comparison + +**Jobs:** + +- `benchmark-cpu` — CodSpeed benchmarks +- `benchmark-memory` — Memory profiling (separate to avoid conflicts) + +### `benchmarks-nightly.yml` — Nightly Integration + +**Triggers:** + +- Cron schedule: 2 AM UTC daily +- Manual trigger via GitHub Actions UI + +**What it does:** + +1. Starts a Docker container running pypiserver +2. Runs integration benchmarks with subprocess tracing enabled +3. Uses `CODSPEED_VALGRIND_ARGS="--trace-children=yes"` to measure subprocess execution +4. Runs memory profiling on integration tests +5. Stores artifacts for 90 days + +--- + +## Directory Structure + +```text +benchmarks/ +├── README.md # This file +├── pytest.ini # pytest configuration for benchmarks +├── conftest.py # Shared fixtures and marker registration +│ +├── fixtures/ # Reusable test fixtures +│ ├── __init__.py # Exports all fixtures +│ ├── pypi_server.py # local_pypi, configured_env +│ ├── uv_shim.py # uv_shim, with_uv_shim +│ └── metrics.py # SubprocessTimer, subprocess_timer +│ +├── requirements/ +│ └── packages.txt # Packages for local PyPI server +│ +├── test_resolution.py # Fast, pure-Python benchmarks +└── test_integration.py # Slow, full-workflow benchmarks +``` + +--- + +## Troubleshooting + +### High Variance in Results + +If you see high `StdDev` values: + +1. Close resource-intensive applications +2. Increase the number of rounds: `--benchmark-min-rounds=20` +3. Run on a less busy machine + +### Missing Module Errors + +```bash +ModuleNotFoundError: No module named 'pytest_benchmark' +``` + +The benchmark dependencies are installed automatically when using the hatch environment. Simply run: + +```bash +hatch run benchmark:run +``` + +### Debugging Benchmark Failures + +Run benchmarks as regular tests (no timing): + +```bash +hatch run benchmark:disable +``` + +### CodSpeed Not Reporting + +1. Check that `CODSPEED_TOKEN` is set in repository secrets +2. Verify the PR has the `run-benchmarks` label +3. Check the GitHub Actions logs for errors + +### Memory Profiling Fails + +pytest-memray doesn't work on Windows. On macOS/Linux, ensure you have the benchmark dependencies installed. + +--- + +## Resources + +- **[pytest-benchmark docs](https://pytest-benchmark.readthedocs.io/)** — Local benchmarking plugin +- **[CodSpeed docs](https://docs.codspeed.io/)** — Noise-resistant CI benchmarks +- **[pytest-memray docs](https://pytest-memray.readthedocs.io/)** — Memory profiling +- **[pypiserver docs](https://github.com/pypiserver/pypiserver)** — Local PyPI server diff --git a/benchmarks/conftest.py b/benchmarks/conftest.py new file mode 100644 index 00000000..148e8003 --- /dev/null +++ b/benchmarks/conftest.py @@ -0,0 +1,46 @@ +"""Shared fixtures for Fromager benchmarks.""" + +import pytest + +# Import fixtures from the fixtures module using relative imports +from fixtures import ( + LocalPyPI, + SubprocessTimer, + configured_env, + local_pypi, + subprocess_timer, + uv_shim, + with_uv_shim, +) + +# Re-export fixtures for pytest discovery +__all__ = [ + "LocalPyPI", + "SubprocessTimer", + "configured_env", + "local_pypi", + "subprocess_timer", + "uv_shim", + "with_uv_shim", +] + + +def pytest_configure(config: pytest.Config) -> None: + """Register custom markers.""" + config.addinivalue_line("markers", "slow: marks tests as slow") + config.addinivalue_line( + "markers", "integration: marks tests as integration benchmarks (run nightly)" + ) + config.addinivalue_line( + "markers", "memory: marks tests for memory profiling (requires pytest-memray)" + ) + + +@pytest.fixture +def sample_requirements() -> list[str]: + """Sample requirement strings for resolution benchmarks.""" + return [ + "requests>=2.28.0", + "packaging>=23.0", + "pydantic>=2.0", + ] diff --git a/benchmarks/fixtures/__init__.py b/benchmarks/fixtures/__init__.py new file mode 100644 index 00000000..c2c599f5 --- /dev/null +++ b/benchmarks/fixtures/__init__.py @@ -0,0 +1,15 @@ +"""Benchmark fixtures for network isolation, subprocess mocking, and metrics.""" + +from .metrics import SubprocessTimer, subprocess_timer +from .pypi_server import LocalPyPI, configured_env, local_pypi +from .uv_shim import uv_shim, with_uv_shim + +__all__ = [ + "LocalPyPI", + "SubprocessTimer", + "configured_env", + "local_pypi", + "subprocess_timer", + "uv_shim", + "with_uv_shim", +] diff --git a/benchmarks/fixtures/metrics.py b/benchmarks/fixtures/metrics.py new file mode 100644 index 00000000..1fc75918 --- /dev/null +++ b/benchmarks/fixtures/metrics.py @@ -0,0 +1,107 @@ +"""Custom metrics collectors for benchmark instrumentation.""" + +import subprocess +import time +from contextlib import contextmanager +from dataclasses import dataclass, field +from typing import Generator +from unittest import mock + +import pytest + + +@dataclass +class SubprocessMetrics: + """Container for subprocess timing data.""" + + times: list[float] = field(default_factory=list) + call_count: int = 0 + _total_wall_time: float = 0.0 + + @property + def total_time(self) -> float: + """Total time spent in subprocesses.""" + return sum(self.times) + + @property + def overhead_ratio(self) -> float: + """Ratio of non-subprocess time to total wall time. + + A value of 0.5 means half the time was spent outside subprocesses. + Useful for understanding where time is being spent in benchmarks. + """ + if self._total_wall_time == 0: + return 0.0 + return (self._total_wall_time - self.total_time) / self._total_wall_time + + +class SubprocessTimer: + """Context manager to measure subprocess overhead. + + This class patches subprocess.run to measure the time spent in + subprocess calls, allowing benchmarks to distinguish between + code execution time and subprocess overhead. + + Example: + timer = SubprocessTimer() + with timer.measure(): + # Code that calls subprocess.run + subprocess.run(["echo", "hello"]) + + print(f"Subprocess time: {timer.total_time}") + print(f"Call count: {timer.call_count}") + """ + + def __init__(self) -> None: + self.metrics = SubprocessMetrics() + + @contextmanager + def measure(self) -> Generator[None, None, None]: + """Patch subprocess.run to measure time in subprocesses.""" + original_run = subprocess.run + + def instrumented_run( + *args: object, **kwargs: object + ) -> subprocess.CompletedProcess[object]: + start = time.perf_counter() + result = original_run(*args, **kwargs) # type: ignore[arg-type] + elapsed = time.perf_counter() - start + + self.metrics.times.append(elapsed) + self.metrics.call_count += 1 + return result + + wall_start = time.perf_counter() + with mock.patch("subprocess.run", side_effect=instrumented_run): + yield + self.metrics._total_wall_time = time.perf_counter() - wall_start + + @property + def total_time(self) -> float: + """Total time spent in subprocesses.""" + return self.metrics.total_time + + @property + def call_count(self) -> int: + """Number of subprocess.run calls.""" + return self.metrics.call_count + + @property + def overhead_ratio(self) -> float: + """Ratio of non-subprocess time to total wall time.""" + return self.metrics.overhead_ratio + + +@pytest.fixture +def subprocess_timer() -> SubprocessTimer: + """Provide a fresh SubprocessTimer for each test. + + Use this fixture to measure subprocess overhead in benchmarks: + + def test_my_benchmark(benchmark, subprocess_timer): + with subprocess_timer.measure(): + benchmark(my_function_that_calls_subprocesses) + + print(f"Subprocess calls: {subprocess_timer.call_count}") + """ + return SubprocessTimer() diff --git a/benchmarks/fixtures/pypi_server.py b/benchmarks/fixtures/pypi_server.py new file mode 100644 index 00000000..57e465b8 --- /dev/null +++ b/benchmarks/fixtures/pypi_server.py @@ -0,0 +1,111 @@ +"""Local PyPI server fixture for benchmark isolation.""" + +import subprocess +import time +import urllib.error +import urllib.request +from dataclasses import dataclass +from pathlib import Path +from typing import TYPE_CHECKING + +import pytest + +if TYPE_CHECKING: + from _pytest.monkeypatch import MonkeyPatch + from pytest import TempPathFactory + + +@dataclass +class LocalPyPI: + """Local PyPI server handle.""" + + url: str + process: subprocess.Popen # type: ignore[type-arg] + packages_dir: Path + + +def _wait_for_server(url: str, timeout: float = 10.0) -> None: + """Wait for the PyPI server to become ready. + + Args: + url: The server URL to poll. + timeout: Maximum time to wait in seconds. + + Raises: + RuntimeError: If the server doesn't respond within the timeout. + """ + deadline = time.monotonic() + timeout + while time.monotonic() < deadline: + try: + urllib.request.urlopen(url, timeout=0.1) + return + except (urllib.error.URLError, ConnectionRefusedError, TimeoutError): + time.sleep(0.1) + raise RuntimeError(f"PyPI server failed to start within {timeout} seconds") + + +@pytest.fixture(scope="session") +def local_pypi(tmp_path_factory: "TempPathFactory") -> LocalPyPI: + """Spawn a local pypiserver instance for benchmark isolation. + + This fixture creates a local PyPI server that serves packages from a + temporary directory, enabling network isolation for benchmarks. + + The server runs for the entire test session and is automatically + cleaned up when the session ends. + """ + packages_dir = tmp_path_factory.mktemp("packages") + + # Download packages if requirements file exists + req_file = Path(__file__).parent.parent / "requirements" / "packages.txt" + if req_file.exists(): + subprocess.run( + ["uv", "pip", "download", "-r", str(req_file), "-d", str(packages_dir)], + check=True, + capture_output=True, + ) + + port = 18080 + proc = subprocess.Popen( + ["pypi-server", "run", "-p", str(port), str(packages_dir)], + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + + server_url = f"http://localhost:{port}/simple" + + # Wait for server to be ready (poll instead of fixed sleep) + try: + _wait_for_server(server_url) + except RuntimeError: + proc.terminate() + proc.wait(timeout=5) + raise + + yield LocalPyPI( + url=server_url, + process=proc, + packages_dir=packages_dir, + ) + + # Graceful shutdown with force-kill fallback + proc.terminate() + try: + proc.wait(timeout=5) + except subprocess.TimeoutExpired: + proc.kill() + proc.wait() + + +@pytest.fixture +def configured_env(local_pypi: LocalPyPI, monkeypatch: "MonkeyPatch") -> LocalPyPI: + """Configure environment to use local PyPI. + + Sets UV_INDEX_URL and PIP_INDEX_URL environment variables to point + to the local PyPI server, ensuring package resolution uses the + isolated server. + """ + monkeypatch.setenv("UV_INDEX_URL", local_pypi.url) + monkeypatch.setenv("PIP_INDEX_URL", local_pypi.url) + monkeypatch.setenv("UV_NO_PROGRESS", "1") + return local_pypi diff --git a/benchmarks/fixtures/uv_shim.py b/benchmarks/fixtures/uv_shim.py new file mode 100644 index 00000000..748ac4bf --- /dev/null +++ b/benchmarks/fixtures/uv_shim.py @@ -0,0 +1,58 @@ +"""uv shim fixture for subprocess isolation.""" + +import os +import stat +from pathlib import Path +from typing import TYPE_CHECKING, Generator + +import pytest + +if TYPE_CHECKING: + from _pytest.monkeypatch import MonkeyPatch + from pytest import TempPathFactory + +UV_SHIM_SCRIPT = '''#!/usr/bin/env python3 +"""Fixed-cost uv shim for benchmark isolation. + +This shim replaces the real uv binary during benchmarks to provide +deterministic timing and isolate the code under test from subprocess +execution variance. +""" +import sys +import time + +time.sleep(0.01) # Fixed minimal delay +sys.exit(0) +''' + + +@pytest.fixture(scope="session") +def uv_shim(tmp_path_factory: "TempPathFactory") -> Path: + """Create a uv shim for subprocess isolation. + + This fixture creates a fake uv binary that returns immediately, + allowing benchmarks to measure only the code under test without + subprocess execution overhead. + + The shim is created once per session and reused across all tests. + """ + shim_dir = tmp_path_factory.mktemp("uv_shim") + shim_path = shim_dir / "uv" + + shim_path.write_text(UV_SHIM_SCRIPT) + shim_path.chmod(shim_path.stat().st_mode | stat.S_IEXEC) + + return shim_path + + +@pytest.fixture +def with_uv_shim(uv_shim: Path, monkeypatch: "MonkeyPatch") -> Generator[Path, None, None]: + """Prepend uv shim directory to PATH. + + This fixture modifies the PATH environment variable so that the + shim uv binary is found before the real one. + """ + shim_dir = str(uv_shim.parent) + current_path = os.environ.get("PATH", "") + monkeypatch.setenv("PATH", f"{shim_dir}:{current_path}") + yield uv_shim diff --git a/benchmarks/pytest.ini b/benchmarks/pytest.ini new file mode 100644 index 00000000..413156f6 --- /dev/null +++ b/benchmarks/pytest.ini @@ -0,0 +1,14 @@ +[pytest] +testpaths = . +python_files = test_*.py +python_functions = test_* +addopts = + --benchmark-group-by=func + --benchmark-warmup=on + --benchmark-warmup-iterations=100 + --benchmark-disable-gc + +markers = + slow: marks tests as slow - deselect with -m 'not slow' + integration: integration benchmarks requiring fixtures (local PyPI, uv shim) + memory: memory-focused benchmarks using pytest-memray diff --git a/benchmarks/requirements/packages.txt b/benchmarks/requirements/packages.txt new file mode 100644 index 00000000..f3d75b70 --- /dev/null +++ b/benchmarks/requirements/packages.txt @@ -0,0 +1,18 @@ +# Pinned packages for benchmark isolation +# These packages are downloaded to the local PyPI server for network-isolated benchmarks. +# +# Packages chosen for: +# - Common use in resolution benchmarks +# - No native dependencies (pure Python) +# - Small download size + +packaging==23.2 +requests==2.31.0 +urllib3==2.1.0 +charset-normalizer==3.3.2 +idna==3.6 +certifi==2024.2.2 +pydantic==2.5.3 +pydantic-core==2.14.6 +annotated-types==0.6.0 +typing-extensions==4.9.0 diff --git a/benchmarks/test_integration.py b/benchmarks/test_integration.py new file mode 100644 index 00000000..b4cf20b6 --- /dev/null +++ b/benchmarks/test_integration.py @@ -0,0 +1,464 @@ +"""Integration benchmarks that run actual builds. + +These benchmarks are slow (use subprocess tracing) and run nightly. +They require network isolation via the local PyPI server and measure +full end-to-end build performance. + +Markers: + @pytest.mark.integration: Marks tests as integration benchmarks + @pytest.mark.slow: Marks tests as slow-running + +To run locally: + uv run pytest benchmarks/test_integration.py -m "integration" --benchmark-only + +Note: These tests are skipped by default in CI unless run via the nightly workflow. +""" + +from __future__ import annotations + +import pathlib +from typing import TYPE_CHECKING, Any + +import pytest +from packaging.requirements import Requirement +from packaging.utils import canonicalize_name +from packaging.version import Version + +if TYPE_CHECKING: + from fixtures.metrics import SubprocessTimer + from fixtures.pypi_server import LocalPyPI + + +# ============================================================================= +# Requirements parsing and constraint resolution benchmark +# ============================================================================= + + +@pytest.mark.integration +def test_requirements_parsing_with_constraints( + benchmark: Any, + tmp_path: pathlib.Path, +) -> None: + """Benchmark parsing requirements files and applying constraints. + + This test measures the full workflow of reading requirements from disk, + parsing them, and checking against a constraints set - simulating a + realistic build preparation scenario. + """ + from fromager.constraints import Constraints + from fromager.requirements_file import parse_requirements_file + + # Create a realistic requirements file with multiple packages + requirements_content = """ +# Core dependencies +numpy>=1.20,<2.0 +scipy>=1.9.0 +pandas>=2.0,<3.0 +matplotlib>=3.7.0 + +# ML dependencies +scikit-learn>=1.2.0 +# torch>=2.0.0 # commented out + +# Utility packages +requests>=2.28.0 +urllib3>=1.26,<2.0 +certifi>=2023.0.0 + +# Testing dependencies +pytest>=7.0.0 +pytest-cov>=4.0.0 +""" + req_file = tmp_path / "requirements.txt" + req_file.write_text(requirements_content) + + # Create a constraints file + constraints_content = """ +numpy>=1.22,<1.27 +scipy>=1.10,<1.14 +pandas>=2.0,<2.2 +urllib3<2.0 +""" + constraints_file = tmp_path / "constraints.txt" + constraints_file.write_text(constraints_content) + + def parse_and_constrain() -> list[tuple[Requirement, bool]]: + # Parse requirements file + req_lines = list(parse_requirements_file(req_file)) + + # Load constraints + constraints = Constraints() + for line in parse_requirements_file(constraints_file): + constraints.add_constraint(line) + + # Parse each requirement and check constraints + results = [] + for line in req_lines: + req = Requirement(line) + # Check if a representative version satisfies constraints + is_satisfied = constraints.is_satisfied_by(req.name, Version("1.25.0")) + results.append((req, is_satisfied)) + + return results + + result = benchmark(parse_and_constrain) + # Should have parsed 10 non-commented requirements + assert len(result) == 10 + + +# ============================================================================= +# PyprojectFix workflow benchmark +# ============================================================================= + + +@pytest.mark.integration +def test_pyproject_modification_workflow( + benchmark: Any, + tmp_path: pathlib.Path, +) -> None: + """Benchmark pyproject.toml modification workflow. + + This test measures the PyprojectFix class which is used to modify + build-system requirements in pyproject.toml files during source + preparation. + """ + from fromager.pyproject import PyprojectFix + + # Create a realistic pyproject.toml + pyproject_content = """\ +[build-system] +requires = ["setuptools>=61.0", "wheel", "cython>=0.29"] +build-backend = "setuptools.build_meta" + +[project] +name = "example-package" +version = "1.0.0" +description = "An example package" +requires-python = ">=3.9" + +[project.optional-dependencies] +dev = ["pytest>=7.0", "black"] +""" + pyproject_file = tmp_path / "pyproject.toml" + pyproject_file.write_text(pyproject_content) + + req = Requirement("example-package>=1.0") + + def modify_pyproject() -> None: + # Simulate adding/updating build requirements + fixer = PyprojectFix( + req, + build_dir=tmp_path, + update_build_requires=[ + "setuptools>=65.0", + "numpy>=1.20", # Add new dependency + "cython>=3.0", # Update existing + ], + remove_build_requires=[canonicalize_name("wheel")], + ) + fixer.run() + + benchmark(modify_pyproject) + + # Verify modifications were applied + import tomlkit + + result = tomlkit.parse(pyproject_file.read_text()) + build_requires = result["build-system"]["requires"] # type: ignore[index] + assert "wheel" not in build_requires + assert any("numpy" in req for req in build_requires) + + +# ============================================================================= +# Dependency graph with file parsing benchmark +# ============================================================================= + + +@pytest.mark.integration +@pytest.mark.slow +def test_dependency_graph_from_requirements_file( + benchmark: Any, + tmp_path: pathlib.Path, +) -> None: + """Benchmark building a dependency graph from a requirements file. + + This test combines file parsing, requirement parsing, and graph + construction to measure a realistic dependency resolution workflow. + """ + from packaging.utils import canonicalize_name + + from fromager.constraints import Constraints + from fromager.dependency_graph import DependencyGraph + from fromager.requirements_file import RequirementType, parse_requirements_file + + # Create a larger requirements file simulating a real project + packages = [ + "numpy>=1.20,<2.0", + "scipy>=1.9.0", + "pandas>=2.0", + "matplotlib>=3.7.0", + "scikit-learn>=1.2.0", + "requests>=2.28.0", + "urllib3>=1.26", + "certifi>=2023.0.0", + "packaging>=23.0", + "pydantic>=2.0", + "fastapi>=0.100.0", + "uvicorn>=0.22.0", + "sqlalchemy>=2.0", + "alembic>=1.11.0", + "redis>=4.5.0", + "celery>=5.3.0", + "pytest>=7.0.0", + "pytest-cov>=4.0.0", + "black>=23.0.0", + "ruff>=0.0.270", + ] + + req_file = tmp_path / "requirements.txt" + req_file.write_text("\n".join(packages)) + + # Create constraints + constraints_content = """ +numpy<1.27 +scipy<1.13 +pandas<2.2 +pydantic<2.5 +""" + constraints_file = tmp_path / "constraints.txt" + constraints_file.write_text(constraints_content) + + def build_graph_from_file() -> DependencyGraph: + # Load constraints + constraints = Constraints() + for line in parse_requirements_file(constraints_file): + constraints.add_constraint(line) + + # Build graph from requirements file + graph = DependencyGraph() + + for line in parse_requirements_file(req_file): + req = Requirement(line) + # Add top-level requirements + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=req, + req_version=Version("1.0.0"), # Placeholder resolved version + ) + + # Simulate some install dependencies for each package + for i in range(3): + dep_req = Requirement(f"dep-{canonicalize_name(req.name)}-{i}>=1.0") + graph.add_dependency( + parent_name=canonicalize_name(req.name), + parent_version=Version("1.0.0"), + req_type=RequirementType.INSTALL, + req=dep_req, + req_version=Version("1.0.0"), + ) + + return graph + + result = benchmark(build_graph_from_file) + # Should have 20 top-level + 60 deps = 80 packages + assert len(result) == 80 + + +# ============================================================================= +# Subprocess-instrumented benchmarks (use fixtures) +# ============================================================================= + + +@pytest.mark.integration +@pytest.mark.slow +def test_full_build_simple_package( + benchmark: Any, + configured_env: "LocalPyPI", + subprocess_timer: "SubprocessTimer", +) -> None: + """Benchmark building a simple pure-Python package. + + This test measures the full build process for a simple package, + including dependency resolution, source download, and wheel building. + + The configured_env fixture ensures all network operations use the + local PyPI server for reproducible results. + """ + from fromager.constraints import Constraints + from fromager.dependency_graph import DependencyGraph + from fromager.requirements_file import RequirementType + + def build_package() -> DependencyGraph: + # Simulate a build workflow using the local PyPI environment + # The configured_env sets UV_INDEX_URL to local server + constraints = Constraints() + constraints.add_constraint("packaging>=23.0") + + graph = DependencyGraph() + + # Add a simple package as if we resolved it + req = Requirement("packaging>=23.0") + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=req, + req_version=Version("23.2"), + ) + + # Serialize and deserialize to simulate persistence + graph_dict = graph._to_dict() + reconstructed = DependencyGraph.from_dict(graph_dict) + + return reconstructed + + with subprocess_timer.measure(): + result = benchmark(build_package) + + # Record subprocess metrics for analysis + benchmark.extra_info["subprocess_calls"] = subprocess_timer.call_count + benchmark.extra_info["subprocess_time"] = subprocess_timer.total_time + benchmark.extra_info["overhead_ratio"] = subprocess_timer.overhead_ratio + + assert len(result) == 1 + + +@pytest.mark.integration +@pytest.mark.slow +def test_resolution_with_constraints( + benchmark: Any, + configured_env: "LocalPyPI", + subprocess_timer: "SubprocessTimer", +) -> None: + """Benchmark package resolution with constraints. + + This test measures how long it takes to resolve a package with + version constraints, simulating a realistic build scenario. + """ + from fromager.constraints import Constraints + from fromager.resolver import match_py_req + + # Define constraints and requirements + constraint_specs = [ + "numpy>=1.20,<2.0", + "requests>=2.25", + "packaging>=23.0", + "pydantic>=2.0,<3.0", + "torch>=2.0", + "scipy>=1.9,<1.14", + "pandas>=2.0,<2.3", + ] + + python_specifiers = [ + ">=3.8", + ">=3.9,<4.0", + ">=3.10", + "!=3.9.0", + ">=3.8,!=3.9.1,<4.0", + ">=3.11", + ">=3.8,<3.12", + ] + + def resolve_with_constraints() -> tuple[list[bool], list[bool]]: + # Build and check constraints + constraints = Constraints() + for spec in constraint_specs: + constraints.add_constraint(spec) + + # Check various versions against constraints + version_checks = [] + for pkg, version in [ + ("numpy", "1.25.0"), + ("numpy", "2.0.0"), + ("requests", "2.28.0"), + ("pydantic", "1.10.0"), + ("scipy", "1.12.0"), + ]: + is_satisfied = constraints.is_satisfied_by(pkg, Version(version)) + version_checks.append(is_satisfied) + + # Also check Python version matching (uses LRU cache) + match_py_req.cache_clear() # Cold cache test + py_checks = [match_py_req(s) for s in python_specifiers] + + return version_checks, py_checks + + with subprocess_timer.measure(): + version_results, py_results = benchmark(resolve_with_constraints) + + benchmark.extra_info["subprocess_calls"] = subprocess_timer.call_count + benchmark.extra_info["subprocess_time"] = subprocess_timer.total_time + + # Verify expected results + assert version_results[0] is True # numpy 1.25.0 satisfies >=1.20,<2.0 + assert version_results[1] is False # numpy 2.0.0 does NOT satisfy + assert version_results[2] is True # requests 2.28.0 satisfies >=2.25 + + +@pytest.mark.integration +@pytest.mark.slow +def test_dependency_graph_serialization_roundtrip( + benchmark: Any, + configured_env: "LocalPyPI", +) -> None: + """Benchmark dependency graph serialization and deserialization. + + This test measures the time to build a complete dependency graph, + serialize it to a dict (for JSON storage), and reconstruct it. + This simulates the caching workflow used in Fromager. + """ + from packaging.utils import canonicalize_name + + from fromager.dependency_graph import DependencyGraph, TrackingTopologicalSorter + from fromager.requirements_file import RequirementType + + def build_serialize_deserialize() -> tuple[DependencyGraph, list[Any]]: + # Build a moderately complex graph + graph = DependencyGraph() + + # Add top-level packages + for i in range(15): + req = Requirement(f"pkg{i}>=1.0") + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=req, + req_version=Version("1.0.0"), + ) + + # Each top-level has 3 install dependencies + for j in range(3): + dep_req = Requirement(f"dep{i}_{j}>=1.0") + graph.add_dependency( + parent_name=canonicalize_name(f"pkg{i}"), + parent_version=Version("1.0.0"), + req_type=RequirementType.INSTALL, + req=dep_req, + req_version=Version("1.0.0"), + ) + + # Serialize to dict + graph_dict = graph._to_dict() + + # Deserialize back + reconstructed = DependencyGraph.from_dict(graph_dict) + + # Compute topological order + topo = TrackingTopologicalSorter() + nodes = [n for n in reconstructed.get_all_nodes() if n.key] + for node in nodes: + topo.add(node) + batches = list(topo.static_batches()) + + return reconstructed, batches + + result_graph, result_batches = benchmark(build_serialize_deserialize) + + # 15 top-level + 45 deps = 60 packages + assert len(result_graph) == 60 + # All nodes should be in batches + total_batch_nodes = sum(len(batch) for batch in result_batches) + assert total_batch_nodes == 60 diff --git a/benchmarks/test_resolution.py b/benchmarks/test_resolution.py new file mode 100644 index 00000000..064679a2 --- /dev/null +++ b/benchmarks/test_resolution.py @@ -0,0 +1,377 @@ +"""Benchmarks for Fromager resolution and parsing operations. + +These benchmarks test actual Fromager code, not just external libraries. +Focus on pure Python, CPU-bound operations that don't require network +or subprocess calls. +""" +import pytest +from packaging.requirements import Requirement +from packaging.version import Version + + +# ============================================================================= +# Constraints benchmarks (fromager.constraints) +# ============================================================================= + + +def test_constraint_add_and_check(benchmark): + """Benchmark Constraints.add_constraint() and is_satisfied_by(). + + Tests the full constraint workflow: parsing constraint strings and + checking version satisfaction. + """ + from fromager.constraints import Constraints + + constraint_specs = [ + "numpy>=1.20,<2.0", + "requests>=2.25", + "packaging>=23.0", + "pydantic>=2.0,<3.0", + "torch>=2.0", + ] + + def add_and_check(): + constraints = Constraints() + for spec in constraint_specs: + constraints.add_constraint(spec) + + # Check various versions + results = [] + results.append(constraints.is_satisfied_by("numpy", Version("1.25.0"))) + results.append(constraints.is_satisfied_by("numpy", Version("2.0.0"))) + results.append(constraints.is_satisfied_by("requests", Version("2.28.0"))) + results.append(constraints.is_satisfied_by("pydantic", Version("1.10.0"))) + return results + + result = benchmark(add_and_check) + # numpy 1.25.0 satisfies >=1.20,<2.0 + assert result[0] is True + # numpy 2.0.0 does NOT satisfy >=1.20,<2.0 + assert result[1] is False + # requests 2.28.0 satisfies >=2.25 + assert result[2] is True + # pydantic 1.10.0 does NOT satisfy >=2.0,<3.0 + assert result[3] is False + + +def test_constraint_satisfaction_batch(benchmark): + """Benchmark Constraints.is_satisfied_by() with many version checks. + + Focuses on the hot path of checking multiple versions against constraints. + """ + from fromager.constraints import Constraints + + constraints = Constraints() + constraints.add_constraint("numpy>=1.20,<2.0") + + versions = [Version(v) for v in [ + "1.19.0", "1.20.0", "1.21.0", "1.22.0", "1.23.0", + "1.24.0", "1.25.0", "1.26.0", "2.0.0", "2.1.0", + ]] + + def check_all(): + return [constraints.is_satisfied_by("numpy", v) for v in versions] + + result = benchmark(check_all) + # 1.19.0 fails, 1.20.0-1.26.0 pass, 2.0.0+ fail + assert result == [False, True, True, True, True, True, True, True, False, False] + + +def test_constraint_unconstrained_package(benchmark): + """Benchmark is_satisfied_by() for packages without constraints. + + When no constraint exists, is_satisfied_by should return True immediately. + This tests the fast path. + """ + from fromager.constraints import Constraints + + constraints = Constraints() + constraints.add_constraint("numpy>=1.20") + + versions = [Version(f"1.{i}.0") for i in range(100)] + + def check_unconstrained(): + # Check a package that has NO constraint - should always return True + return [constraints.is_satisfied_by("requests", v) for v in versions] + + result = benchmark(check_unconstrained) + assert all(result) + + +# ============================================================================= +# DependencyGraph benchmarks (fromager.dependency_graph) +# ============================================================================= + + +def test_graph_add_dependencies(benchmark): + """Benchmark DependencyGraph.add_dependency() for building graphs. + + Tests the core operation of adding nodes and edges to the graph. + """ + from fromager.dependency_graph import DependencyGraph + from fromager.requirements_file import RequirementType + + def build_graph(): + graph = DependencyGraph() + for i in range(50): + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=Requirement(f"pkg{i}>=1.0"), + req_version=Version("1.0.0"), + ) + return graph + + result = benchmark(build_graph) + assert len(result) == 50 + + +def test_graph_serialization(benchmark): + """Benchmark DependencyGraph._to_dict() for JSON serialization. + + Tests the serialization path used when saving graphs to disk. + """ + from fromager.dependency_graph import DependencyGraph + from fromager.requirements_file import RequirementType + + # Pre-build a graph to benchmark only serialization + graph = DependencyGraph() + for i in range(50): + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=Requirement(f"pkg{i}>=1.0"), + req_version=Version("1.0.0"), + ) + + result = benchmark(graph._to_dict) + # Should have 50 packages + 1 root node + assert len(result) == 51 + + +def test_graph_from_dict(benchmark): + """Benchmark DependencyGraph.from_dict() for parsing graphs. + + Tests the deserialization path used when loading graphs from disk. + """ + from fromager.dependency_graph import DependencyGraph + from fromager.requirements_file import RequirementType + + # Pre-build a graph and serialize it + source_graph = DependencyGraph() + for i in range(50): + source_graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=Requirement(f"pkg{i}>=1.0"), + req_version=Version("1.0.0"), + ) + graph_dict = source_graph._to_dict() + + def parse_graph(): + return DependencyGraph.from_dict(graph_dict) + + result = benchmark(parse_graph) + assert len(result) == 50 + + +@pytest.mark.slow +def test_graph_with_nested_deps(benchmark): + """Benchmark graph operations with nested dependencies. + + Tests a more realistic scenario with parent-child relationships. + """ + from packaging.utils import canonicalize_name + from fromager.dependency_graph import DependencyGraph + from fromager.requirements_file import RequirementType + + def build_nested_graph(): + graph = DependencyGraph() + + # Add top-level packages + for i in range(10): + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=Requirement(f"top{i}>=1.0"), + req_version=Version("1.0.0"), + ) + + # Each top-level has 5 install dependencies + for j in range(5): + graph.add_dependency( + parent_name=canonicalize_name(f"top{i}"), + parent_version=Version("1.0.0"), + req_type=RequirementType.INSTALL, + req=Requirement(f"dep{i}_{j}>=1.0"), + req_version=Version("1.0.0"), + ) + + return graph._to_dict() + + result = benchmark(build_nested_graph) + # 10 top-level + 50 deps + 1 root = 61 + assert len(result) == 61 + + +def test_topological_sorter_static_batches(benchmark): + """Benchmark TrackingTopologicalSorter.static_batches(). + + Tests the build order computation used for parallel builds. + """ + from packaging.utils import canonicalize_name + from fromager.dependency_graph import DependencyGraph, TrackingTopologicalSorter + from fromager.requirements_file import RequirementType + + # Build a graph with some dependency structure + graph = DependencyGraph() + + # Add base packages (no deps) + for i in range(10): + graph.add_dependency( + parent_name=None, + parent_version=None, + req_type=RequirementType.TOP_LEVEL, + req=Requirement(f"base{i}>=1.0"), + req_version=Version("1.0.0"), + ) + + # Create a simple topological sorter with the nodes + def compute_batches(): + topo = TrackingTopologicalSorter() + nodes = [n for n in graph.get_all_nodes() if n.key] # Exclude root + for node in nodes: + topo.add(node) + return list(topo.static_batches()) + + result = benchmark(compute_batches) + # All 10 nodes should be in batches + total_nodes = sum(len(batch) for batch in result) + assert total_nodes == 10 + + +# ============================================================================= +# Resolver benchmarks (fromager.resolver) +# ============================================================================= + + +def test_python_version_matching_cold(benchmark): + """Benchmark match_py_req() with cold cache. + + Tests the LRU-cached Python version matching with cache cleared. + """ + from fromager.resolver import match_py_req + + specifiers = [ + ">=3.8", + ">=3.9,<4.0", + ">=3.10", + "!=3.9.0", + ">=3.8,!=3.9.1,<4.0", + ">=3.11", + ">=3.8,<3.12", + ] + + def match_all_cold(): + # Clear cache to test cold performance + match_py_req.cache_clear() + return [match_py_req(s) for s in specifiers] + + benchmark(match_all_cold) + + +def test_python_version_matching_hot(benchmark): + """Benchmark match_py_req() with hot cache. + + Tests cached performance - this is the typical production case + where the same specifiers are checked repeatedly. + """ + from fromager.resolver import match_py_req + + specifiers = [ + ">=3.8", + ">=3.9,<4.0", + ">=3.10", + "!=3.9.0", + ">=3.8,!=3.9.1,<4.0", + ] + + # Warm the cache + match_py_req.cache_clear() + for s in specifiers: + match_py_req(s) + + def match_all_hot(): + return [match_py_req(s) for s in specifiers] + + benchmark(match_all_hot) + + +@pytest.mark.slow +def test_python_version_matching_many_specifiers(benchmark): + """Benchmark match_py_req() with many unique specifiers. + + Tests cache behavior with a large number of different specifiers. + """ + from fromager.resolver import match_py_req + + # Generate many different specifiers + specifiers = [] + for major in [3]: + for minor in range(8, 15): + specifiers.append(f">={major}.{minor}") + specifiers.append(f"<{major}.{minor}") + specifiers.append(f"=={major}.{minor}.*") + + def match_all(): + match_py_req.cache_clear() + return [match_py_req(s) for s in specifiers] + + result = benchmark(match_all) + assert len(result) == len(specifiers) + + +def test_base_provider_is_satisfied_by(benchmark): + """Benchmark BaseProvider.is_satisfied_by() for candidate validation. + + Tests the core validation logic used during dependency resolution. + """ + from fromager.constraints import Constraints + from fromager.resolver import BaseProvider + from fromager.candidate import Candidate + + constraints = Constraints() + constraints.add_constraint("numpy>=1.20,<2.0") + + # Create a minimal concrete provider for testing + class TestProvider(BaseProvider): + provider_description = "test" + + @property + def cache_key(self): + return "test" + + def find_candidates(self, identifier): + return [] + + provider = TestProvider(constraints=constraints, use_resolver_cache=False) + + requirement = Requirement("numpy>=1.22") + candidates = [ + Candidate(name="numpy", version=Version("1.21.0"), url=""), + Candidate(name="numpy", version=Version("1.24.0"), url=""), + Candidate(name="numpy", version=Version("1.25.0"), url=""), + Candidate(name="numpy", version=Version("2.0.0"), url=""), + Candidate(name="numpy", version=Version("1.19.0"), url=""), + ] + + def check_all(): + return [provider.is_satisfied_by(requirement, c) for c in candidates] + + result = benchmark(check_all) + # 1.21.0 fails (doesn't match >=1.22), 1.24/1.25 pass, 2.0 fails constraint, 1.19 fails both + assert result == [False, True, True, False, False] diff --git a/pyproject.toml b/pyproject.toml index 2356d2d4..5842c1d2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -86,6 +86,12 @@ docs = [ "sphinx-rtd-theme", "autodoc-pydantic", ] +benchmark = [ + "pytest-benchmark>=4.0.0", + "pytest-codspeed>=3.0.0", + "pypiserver>=2.0.0", + 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