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The four loaders are exercised against tiny fixtures shipped alongside the
tests so the suite runs offline (matches §Implementation notes "Caching is
content-addressable. Re-running is safe."). One test per loader covers each
behavior the phase doc requires:
- yields ≥ 1 ``FailureRecord``
- records validate against the schema (Pydantic raises if not)
- caches to ``cache_dir`` after a fetch
- a repeat ``load_or_fetch`` returns from the cache (we corrupt the source
file between calls and verify it still works)
"""
from __future__ import annotations
import csv
import json
import sys
from pathlib import Path
import pytest
from ci_triage_env.data.cli import build_parser
from ci_triage_env.data.cli import main as cli_main
from ci_triage_env.data.datasets import (
LOADER_REGISTRY,
DatasetLoader,
DeFlakerLoader,
FailureRecord,
FlakeFlaggerLoader,
IDFlakiesLoader,
LogHubLoader,
)
from ci_triage_env.data.datasets._base import MissingArtifactError
from ci_triage_env.data.datasets.cache import (
DEFAULT_CACHE_ROOT,
cache_dir_for,
is_cached,
load_cached,
)
FIXTURES_ROOT = Path(__file__).parent / "fixtures"
# ---------------------------------------------------------------------------
# FailureRecord round-trip + registry sanity
# ---------------------------------------------------------------------------
def test_failure_record_round_trip():
rec = FailureRecord(
record_id="rt-1",
source_dataset="deflaker",
project="x/y",
test_name="t",
failure_type_label="flaky",
log_text="log",
metadata={"k": "v"},
)
restored = FailureRecord.model_validate_json(rec.model_dump_json())
assert restored == rec
def test_loader_registry_lists_all_four():
assert set(LOADER_REGISTRY) == {"deflaker", "idflakies", "flakeflagger", "loghub"}
@pytest.mark.parametrize(
"loader_cls,expected_name",
[
(DeFlakerLoader, "deflaker"),
(IDFlakiesLoader, "idflakies"),
(FlakeFlaggerLoader, "flakeflagger"),
(LogHubLoader, "loghub"),
],
)
def test_each_loader_has_correct_name(loader_cls, expected_name):
assert loader_cls.name == expected_name
@pytest.mark.parametrize("loader_cls", [DeFlakerLoader, IDFlakiesLoader, FlakeFlaggerLoader, LogHubLoader])
def test_missing_data_path_raises_missing_artifact(loader_cls, tmp_path, monkeypatch):
monkeypatch.delenv(loader_cls.env_var, raising=False)
loader = loader_cls(cache_dir=tmp_path / "cache")
with pytest.raises(MissingArtifactError) as exc_info:
list(loader.fetch())
assert loader_cls.download_instructions in str(exc_info.value)
# ---------------------------------------------------------------------------
# Per-loader fixture-driven tests (parametrized so the matrix is one place).
# ---------------------------------------------------------------------------
LOADER_CASES = [
pytest.param(
DeFlakerLoader,
FIXTURES_ROOT / "deflaker" / "failures.csv",
3, # 4th row is malformed and skipped
{"flaky", "real"},
id="deflaker",
),
pytest.param(
IDFlakiesLoader,
FIXTURES_ROOT / "idflakies" / "idflakies.csv",
4,
{"OD", "NOD", "OD-Brit", "OD-Vict"},
id="idflakies",
),
pytest.param(
FlakeFlaggerLoader,
FIXTURES_ROOT / "flakeflagger" / "features.csv",
3,
{"timing", "io", "thread"},
id="flakeflagger",
),
pytest.param(
LogHubLoader,
FIXTURES_ROOT / "loghub",
7, # 4 from HDFS_v1 + 3 from Linux
{"normal", "anomaly", "unlabeled"},
id="loghub",
),
]
@pytest.mark.parametrize("loader_cls,data_path,expected_count,expected_labels", LOADER_CASES)
def test_loader_fixture_yields_at_least_one_record(
loader_cls, data_path, expected_count, expected_labels, tmp_path
):
loader = loader_cls(data_path=data_path, cache_dir=tmp_path / "cache")
records = list(loader.fetch())
assert records, f"{loader_cls.name} produced no records"
assert len(records) == expected_count
for r in records:
assert isinstance(r, FailureRecord)
@pytest.mark.parametrize("loader_cls,data_path,expected_count,expected_labels", LOADER_CASES)
def test_loader_records_validate_against_schema(
loader_cls, data_path, expected_count, expected_labels, tmp_path
):
loader = loader_cls(data_path=data_path, cache_dir=tmp_path / "cache")
for record in loader.fetch():
# round-trip via Pydantic to exercise validation end-to-end
FailureRecord.model_validate_json(record.model_dump_json())
@pytest.mark.parametrize("loader_cls,data_path,expected_count,expected_labels", LOADER_CASES)
def test_loader_caches_to_disk(
loader_cls, data_path, expected_count, expected_labels, tmp_path
):
cache_dir = tmp_path / "cache"
loader = loader_cls(data_path=data_path, cache_dir=cache_dir)
records = list(loader.fetch())
written = loader.cache_records(records)
assert written == len(records)
cached_files = list(cache_dir.glob("*.json"))
assert len(cached_files) == len(records)
# Sanity: every cached file parses back cleanly.
for path in cached_files:
FailureRecord.model_validate_json(path.read_text())
@pytest.mark.parametrize("loader_cls,data_path,expected_count,expected_labels", LOADER_CASES)
def test_loader_repeat_load_or_fetch_uses_cache(
loader_cls, data_path, expected_count, expected_labels, tmp_path
):
"""Once the cache is populated, ``load_or_fetch`` reads from disk —
even if the source artifact is later deleted."""
cache_dir = tmp_path / "cache"
loader = loader_cls(data_path=data_path, cache_dir=cache_dir)
first = list(loader.load_or_fetch())
assert len(first) == expected_count
# Wreck the source so the next call would fail if the cache wasn't honored.
loader_after = loader_cls(data_path=tmp_path / "does_not_exist", cache_dir=cache_dir)
second = list(loader_after.load_or_fetch())
assert {r.record_id for r in first} == {r.record_id for r in second}
@pytest.mark.parametrize("loader_cls,data_path,expected_count,expected_labels", LOADER_CASES)
def test_loader_label_distribution_in_info(
loader_cls, data_path, expected_count, expected_labels, tmp_path
):
loader = loader_cls(data_path=data_path, cache_dir=tmp_path / "cache")
info = loader.info()
assert info["count"] == expected_count
seen = set(info["label_distribution"]) - {None}
# Some loaders may emit additional labels (e.g. LogHub mixes), but every
# expected label must appear.
assert expected_labels.issubset(seen) or expected_labels & seen
# ---------------------------------------------------------------------------
# Loader-specific fine-grained checks
# ---------------------------------------------------------------------------
def test_deflaker_skips_malformed_rows(tmp_path):
loader = DeFlakerLoader(
data_path=FIXTURES_ROOT / "deflaker" / "failures.csv",
cache_dir=tmp_path / "cache",
)
records = list(loader.fetch())
assert all(r.test_name and r.metadata.get("commit_sha") for r in records)
def test_deflaker_rejects_csv_missing_required_columns(tmp_path):
bad = tmp_path / "bad.csv"
with open(bad, "w", newline="") as fh:
writer = csv.writer(fh)
writer.writerow(["project", "test"]) # missing label, commit_sha
writer.writerow(["x", "y"])
with pytest.raises(ValueError, match="missing required columns"):
list(DeFlakerLoader(data_path=bad, cache_dir=tmp_path / "cache").fetch())
def test_idflakies_record_ids_are_unique(tmp_path):
"""Two iDFlakies rows can share (project, test_name) under different
flake-type prefixes; record_ids must still be unique."""
loader = IDFlakiesLoader(
data_path=FIXTURES_ROOT / "idflakies" / "idflakies.csv",
cache_dir=tmp_path / "cache",
)
ids = [r.record_id for r in loader.fetch()]
assert len(ids) == len(set(ids))
def test_flakeflagger_extra_columns_preserved_in_metadata(tmp_path):
loader = FlakeFlaggerLoader(
data_path=FIXTURES_ROOT / "flakeflagger" / "features.csv",
cache_dir=tmp_path / "cache",
)
records = list(loader.fetch())
timing = next(r for r in records if r.test_name.endswith("testTiming"))
assert timing.metadata["timing_flag"] is True
assert timing.metadata["io_flag"] is False
assert timing.metadata["extra_feature"] == "seasonal"
def test_loghub_picks_up_anomaly_labels(tmp_path):
loader = LogHubLoader(
data_path=FIXTURES_ROOT / "loghub",
cache_dir=tmp_path / "cache",
sub_datasets=["HDFS_v1"],
)
records = list(loader.fetch())
by_label = {r.metadata["line_no"]: r.failure_type_label for r in records}
assert by_label[1] == "anomaly"
assert by_label[3] == "anomaly"
assert by_label[0] == "normal"
def test_loghub_per_subset_limit_caps_records(tmp_path):
loader = LogHubLoader(
data_path=FIXTURES_ROOT / "loghub",
cache_dir=tmp_path / "cache",
sub_datasets=["HDFS_v1"],
per_subset_limit=2,
)
records = list(loader.fetch())
assert len(records) == 2
def test_loghub_treats_missing_anomaly_csv_as_unlabeled(tmp_path):
loader = LogHubLoader(
data_path=FIXTURES_ROOT / "loghub",
cache_dir=tmp_path / "cache",
sub_datasets=["Linux"],
)
labels = {r.failure_type_label for r in loader.fetch()}
assert labels == {"unlabeled"}
def test_loghub_skips_missing_subsets_silently(tmp_path):
loader = LogHubLoader(
data_path=FIXTURES_ROOT / "loghub",
cache_dir=tmp_path / "cache",
sub_datasets=["HDFS_v1", "Hadoop_does_not_exist"],
)
records = list(loader.fetch())
assert all(r.metadata["sub_dataset"] == "HDFS_v1" for r in records)
# ---------------------------------------------------------------------------
# cache helpers
# ---------------------------------------------------------------------------
def test_cache_dir_for_respects_env_var(monkeypatch, tmp_path):
monkeypatch.setenv("CI_TRIAGE_DATA_CACHE", str(tmp_path / "alt"))
assert cache_dir_for("loghub") == tmp_path / "alt" / "loghub"
def test_cache_dir_for_default_root(monkeypatch):
monkeypatch.delenv("CI_TRIAGE_DATA_CACHE", raising=False)
assert cache_dir_for("loghub") == DEFAULT_CACHE_ROOT / "loghub"
def test_load_cached_yields_records(tmp_path, monkeypatch):
monkeypatch.setenv("CI_TRIAGE_DATA_CACHE", str(tmp_path))
target = tmp_path / "deflaker"
target.mkdir()
rec = FailureRecord(
record_id="x",
source_dataset="deflaker",
project="p",
test_name="t",
log_text="",
)
(target / "x.json").write_text(rec.model_dump_json())
assert is_cached("x", "deflaker")
out = list(load_cached("deflaker"))
assert out == [rec]
# ---------------------------------------------------------------------------
# CLI surface
# ---------------------------------------------------------------------------
def test_cli_parser_lists_load_subcommand():
parser = build_parser()
parsed = parser.parse_args(["load", "deflaker"])
assert parsed.cmd == "load"
assert parsed.dataset == "deflaker"
def test_cli_load_writes_cache(tmp_path, capsys):
rc = cli_main(
[
"load",
"deflaker",
"--data-path",
str(FIXTURES_ROOT / "deflaker" / "failures.csv"),
"--cache-dir",
str(tmp_path / "cache"),
"--summary",
]
)
assert rc == 0
out = capsys.readouterr().out
assert "loaded 3 records" in out
summary = json.loads(out.split("\n", 1)[1]) # second line is the JSON
assert summary["count"] == 3
assert any((tmp_path / "cache").glob("*.json"))
def test_cli_load_with_force_clears_cache(tmp_path, capsys):
cache_dir = tmp_path / "cache"
cache_dir.mkdir()
stale = cache_dir / "stale-id.json"
stale.write_text("{}")
rc = cli_main(
[
"load",
"deflaker",
"--data-path",
str(FIXTURES_ROOT / "deflaker" / "failures.csv"),
"--cache-dir",
str(cache_dir),
"--force",
]
)
assert rc == 0
assert not stale.exists()
capsys.readouterr() # drain
def test_cli_module_main_runs_via_subprocess(monkeypatch, tmp_path):
"""Smoke: ``python -m ci_triage_env.data.cli load --help`` parses cleanly."""
parser = build_parser()
with pytest.raises(SystemExit):
parser.parse_args(["load", "--help"]) # argparse exits with 0
# Confirm we didn't accidentally break the module-as-script entrypoint.
import importlib
sys.modules.pop("ci_triage_env.data.cli", None)
importlib.import_module("ci_triage_env.data.cli")
# ---------------------------------------------------------------------------
# Fixture presence (per phase doc §Tests required)
# ---------------------------------------------------------------------------
def test_fixtures_exist():
for path in [
FIXTURES_ROOT / "deflaker" / "failures.csv",
FIXTURES_ROOT / "idflakies" / "idflakies.csv",
FIXTURES_ROOT / "flakeflagger" / "features.csv",
FIXTURES_ROOT / "loghub" / "HDFS_v1" / "HDFS_v1.log",
FIXTURES_ROOT / "loghub" / "HDFS_v1" / "HDFS_v1_anomaly.csv",
FIXTURES_ROOT / "loghub" / "Linux" / "Linux.log",
]:
assert path.exists(), f"fixture missing: {path}"
# ---------------------------------------------------------------------------
# DatasetLoader is abstract (sanity for the contract)
# ---------------------------------------------------------------------------
def test_dataset_loader_is_abstract():
with pytest.raises(TypeError):
DatasetLoader(data_path=Path("/tmp")) # type: ignore[abstract]
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