Files
cleveragents-core/scripts/run_behave_parallel.py

333 lines
11 KiB
Python

"""In-process parallel behave runner.
Replaces the old subprocess-per-feature model with direct use of
behave's ``Runner`` API. Step definitions and environment hooks are
loaded once per process; feature files are parsed and executed without
Python interpreter startup overhead.
Parallelism modes
-----------------
* **Sequential** (``--processes 1`` or ``BEHAVE_PARALLEL_COVERAGE=1``):
All features run in a single ``Runner.run()`` call.
* **Parallel** (``--processes N``, N > 1, no coverage):
Features are split into *N* equal-size chunks. A
``multiprocessing.Pool`` with the ``fork`` start method dispatches
each chunk to a worker that creates its own ``Runner`` (hooks and
step definitions are re-loaded cheaply because all heavy modules are
already in memory from the parent).
"""
from __future__ import annotations
import argparse
import io
import multiprocessing
import os
import sys
import time
from contextlib import redirect_stderr, redirect_stdout, suppress
from pathlib import Path
from typing import Any
DEFAULT_FEATURE_ROOT = "features/"
# Type alias for summary dictionaries
Summary = dict[str, Any]
# ---------------------------------------------------------------------------
# Summary helpers
# ---------------------------------------------------------------------------
def _empty_summary() -> Summary:
return {
"features": {"passed": 0, "failed": 0, "errors": 0, "skipped": 0},
"scenarios": {"passed": 0, "failed": 0, "errors": 0, "skipped": 0},
"steps": {"passed": 0, "failed": 0, "errors": 0, "skipped": 0},
"duration": 0.0,
}
def _extract_summary(runner: Any) -> Summary:
"""Build a summary dict from a completed behave Runner."""
summary = _empty_summary()
for feature in runner.features:
status_name = feature.status.name
if status_name == "passed":
summary["features"]["passed"] += 1
elif status_name == "skipped":
summary["features"]["skipped"] += 1
else:
summary["features"]["failed"] += 1
summary["duration"] += feature.duration or 0.0
for scenario in feature.walk_scenarios():
sname = scenario.status.name
if sname == "passed":
summary["scenarios"]["passed"] += 1
elif sname == "skipped":
summary["scenarios"]["skipped"] += 1
elif sname == "failed":
summary["scenarios"]["failed"] += 1
else:
summary["scenarios"]["errors"] += 1
for step in scenario.steps:
stname = step.status.name
if stname == "passed":
summary["steps"]["passed"] += 1
elif stname == "skipped":
summary["steps"]["skipped"] += 1
elif stname == "failed":
summary["steps"]["failed"] += 1
else:
summary["steps"]["errors"] += 1
return summary
def _merge_summaries(summaries: list[Summary]) -> Summary:
total = _empty_summary()
for s in summaries:
for bucket in ("features", "scenarios", "steps"):
for field in ("passed", "failed", "errors", "skipped"):
total[bucket][field] += s.get(bucket, {}).get(field, 0)
total["duration"] += float(s.get("duration", 0.0))
return total
def _format_duration(seconds: float) -> str:
minutes = int(seconds // 60)
remainder = seconds % 60
if minutes:
return f"{minutes}m {remainder:.3f}s"
return f"{remainder:.3f}s"
def _print_overall_summary(
total: Summary,
wall_seconds: float | None = None,
) -> None:
print("\nOverall summary:")
for bucket in ("features", "scenarios", "steps"):
b = total[bucket]
print(
f"{b['passed']} {bucket} passed, {b['failed']} failed, "
f"{b['errors']} errored, {b['skipped']} skipped"
)
if total["duration"]:
print(f"Took {_format_duration(float(total['duration']))}")
if wall_seconds is not None:
print(f"Wall time: {_format_duration(wall_seconds)}")
def _has_failures(total: Summary) -> bool:
return (
total["features"]["failed"] > 0
or total["features"]["errors"] > 0
or total["scenarios"]["failed"] > 0
or total["scenarios"]["errors"] > 0
)
def _no_scenarios_ran(total: Summary) -> bool:
"""Return True when no scenario reached a terminal state.
This catches runner-level crashes (e.g. ``before_all`` failure) that
prevent any scenario from executing. Without this guard the summary
would contain all-zero counters, ``_has_failures()`` would return
``False``, and CI would silently pass a broken suite.
"""
s = total["scenarios"]
return s["passed"] + s["failed"] + s["errors"] + s["skipped"] == 0
# ---------------------------------------------------------------------------
# Feature discovery
# ---------------------------------------------------------------------------
def _iter_features(paths: list[str]) -> list[str]:
collected = []
for path in paths:
p = Path(path)
if p.is_dir():
collected.extend(sorted(str(fp) for fp in p.rglob("*.feature")))
else:
collected.append(str(p))
return collected
def _extract_features_and_args(argv: list[str]) -> tuple[list[str], list[str]]:
positional = []
options = []
for arg in argv:
if arg.startswith("-"):
options.append(arg)
else:
positional.append(arg)
if positional:
return positional, options
return [DEFAULT_FEATURE_ROOT], options
# ---------------------------------------------------------------------------
# In-process behave execution
# ---------------------------------------------------------------------------
def _make_runner(feature_paths: list[str], behave_args: list[str]) -> Any:
"""Create a behave Runner with proper configuration defaults.
Mirrors the format-defaulting logic from ``behave.__main__.run_behave``
so that ``-q`` and bare invocations get a sensible formatter instead
of crashing on ``config.format is None``.
"""
from behave.configuration import Configuration
from behave.runner import Runner
from behave.runner_util import reset_runtime
reset_runtime()
args = list(behave_args) + [str(p) for p in feature_paths]
config = Configuration(command_args=args)
if not config.format:
config.format = [config.default_format]
return Runner(config)
def _run_features_inprocess(
feature_paths: list[str], behave_args: list[str]
) -> tuple[bool, Summary]:
"""Run *all* feature_paths in a single behave Runner invocation.
Returns ``(failed: bool, summary: dict)``.
"""
runner = _make_runner(feature_paths, behave_args)
failed = runner.run()
summary = _extract_summary(runner)
return failed, summary
def _worker_run_features(
payload: tuple[list[str], list[str]],
) -> tuple[bool, str, str, Summary]:
"""Entry point for multiprocessing workers.
Runs a chunk of feature files in a forked child process. Heavy
Python modules (cleveragents, behave, SQLAlchemy, ...) are already
loaded in the parent and shared via copy-on-write after ``fork``.
``load_step_definitions()`` and ``load_hooks()`` still execute
inside each worker (they ``exec()`` the step .py files and
environment.py), but every ``import`` they trigger is a cache hit.
"""
feature_paths, behave_args = payload
stdout_buf = io.StringIO()
stderr_buf = io.StringIO()
runner = _make_runner(feature_paths, behave_args)
with redirect_stdout(stdout_buf), redirect_stderr(stderr_buf):
failed = runner.run()
summary = _extract_summary(runner)
return failed, stdout_buf.getvalue(), stderr_buf.getvalue(), summary
# ---------------------------------------------------------------------------
# CLI entry point
# ---------------------------------------------------------------------------
def main(argv: list[str] | None = None) -> None:
argv = list(sys.argv[1:] if argv is None else argv)
parser = argparse.ArgumentParser(add_help=False)
parser.add_argument("--processes", "-j", type=int, default=None)
known, remaining = parser.parse_known_args(argv)
processes = known.processes or os.cpu_count() or 1
feature_args, other_args = _extract_features_and_args(remaining)
# Pass-through --help / --version to behave
if any(flag in remaining for flag in ("-h", "--help", "--version")):
import subprocess
code = subprocess.run(
[sys.executable, "-m", "behave", *other_args, *feature_args]
).returncode
sys.exit(code)
feature_paths = _iter_features(feature_args)
if not feature_paths:
print("No feature files found", file=sys.stderr)
sys.exit(0)
coverage_mode = bool(os.environ.get("BEHAVE_PARALLEL_COVERAGE"))
start = time.monotonic()
if processes <= 1 or coverage_mode or len(feature_paths) == 1:
# ---- sequential in-process mode ----
_, total = _run_features_inprocess(feature_paths, other_args)
else:
# ---- parallel in-process mode (multiprocessing fork) ----
# Pre-import heavy modules so forked children get them for free.
with suppress(ImportError):
import cleveragents # noqa: F401
with suppress(ImportError):
import behave # noqa: F401
# Split features into roughly equal chunks.
chunk_size = max(1, (len(feature_paths) + processes - 1) // processes)
chunks = [
feature_paths[i : i + chunk_size]
for i in range(0, len(feature_paths), chunk_size)
]
ctx = multiprocessing.get_context("fork")
with ctx.Pool(processes=min(processes, len(chunks))) as pool:
results = pool.map(
_worker_run_features,
[(chunk, other_args) for chunk in chunks],
)
summaries = []
for _worker_failed, stdout, stderr, summary in results:
if stdout:
print(stdout, end="")
if stderr:
print(stderr, end="", file=sys.stderr)
summaries.append(summary)
total = _merge_summaries(summaries)
wall = time.monotonic() - start
_print_overall_summary(total, wall_seconds=wall)
# Use the summary-based check rather than the raw runner ``failed``
# boolean. The ``@tdd_expected_fail`` handler in environment.py
# inverts scenario statuses for TDD issue-capture tests, but behave's
# ``runner.run()`` tracks step failures in a local variable that
# cannot be updated by after_scenario hooks. Relying solely on the
# summary (which reflects the corrected scenario statuses) ensures
# that TDD-inverted scenarios do not cause a spurious exit-code 1.
if _has_failures(total):
sys.exit(1)
# Safety net: if features were requested but zero scenarios ran, the
# runner crashed before executing any scenario (e.g. ``before_all``
# failure). Treat this as a failure so CI does not silently pass.
if feature_paths and _no_scenarios_ran(total):
print(
"ERROR: features were requested but no scenarios ran — "
"possible runner-level crash.",
file=sys.stderr,
)
sys.exit(1)
if __name__ == "__main__":
main()