"""Conformance gate: diagnostic conformance rows vs an explicit expected-failures list.

Semantics (strict xfail, schema 2):

- every expected-failure entry names its failing legs AND an error pattern per

  leg (``re.fullmatch`` against that leg's detail; legacy v1 scenarios use the

  pseudo-leg ``behaviour`` matched against the row's ``failure``). A listed

  behaviour fails as expected only when the failing-leg set is identical and

  every detail matches its pattern. Any other failure - a new leg, a changed

  error (EEXIST -> ``extra=['../../etc/evil']``, a rejection -> a panic) - is

  a REGRESSION;

- a listed behaviour that passes on a profile the entry applies to is FIXED:

  not a regression, but publish_gate refuses until the list is updated;

- entries may be scoped to filesystem profiles (``fs_profiles``); on other

  profiles they do not apply, so a pass there is just a pass (never FIXED) and

  a failure there is a regression;

- ``outcome: refused`` marks typed policy refusals (a product decision, e.g.

  control characters in names) and is reported separately from bugs;

- coverage: for a recorded profile, any skip not in its ``expected_skips`` is

  a coverage loss (UNMEASURED) - a behaviour that used to pass or xfail must

  not silently turn into a skip. On an unrecorded profile only behaviours that

  need a known filesystem-dependent capability (case/normalization/non-UTF-8)

  or are gated may skip; a row without ``fs_profile`` and a run with zero

  measured behaviours are UNMEASURED. publish_gate additionally requires a

  recorded profile;

- harness errors, reader-unmeasured legs and required behaviours with no row

  make the result UNMEASURED.

Only the gated subject (Oak) is judged; Git rows are the reference arm.

"""

from __future__ import annotations

import json

from pathlib import Path

import re

ROOT = Path(__file__).resolve().parents[2]

EXPECTED_FAILURES = ROOT / "config" / "conformance_expected_failures.json"

SCHEMA_VERSION = 2

TICKET = re.compile(r"^fb-\d+$")

OUTCOMES = ("bug", "refused")

CAPABILITY_SKIP_PREFIXES = ("filesystem capability unavailable", "gated:", "gated behaviour")

# Capabilities that legitimately differ between ordinary hosts (macOS APFS vs

# Linux ext4). On an unrecorded profile only behaviours needing one of these,

# or gated behaviours, may skip; any other skip means a broken probe or host

# and the result is UNMEASURED.

KNOWN_FS_DEPENDENT = frozenset({"case_insensitive_fs", "case_sensitive_fs", "normalization_sensitive_fs",

                                "non_utf8_names"})

def fs_dependent_skip_allowed(behaviour: str) -> bool:

    from oakbench.conformance_matrix import BY_ID

    spec = BY_ID.get(behaviour)

    return spec is not None and (spec.gated or bool(spec.requires & KNOWN_FS_DEPENDENT))

def load_expected(path: Path = EXPECTED_FAILURES) -> dict:

    data = json.loads(Path(path).read_text())

    if data.get("schema_version") != SCHEMA_VERSION or not isinstance(data.get("entries"), list):

        raise ValueError("conformance expected-failures: unsupported schema")

    entries = {}

    for entry in data["entries"]:

        behaviour = entry.get("behaviour")

        if not behaviour or behaviour in entries:

            raise ValueError(f"conformance expected-failures: bad or duplicate behaviour {behaviour!r}")

        if not TICKET.match(str(entry.get("ticket", ""))):

            raise ValueError(f"conformance expected-failures: {behaviour} needs a filed ticket (fb-N)")

        if entry.get("outcome", "bug") not in OUTCOMES:

            raise ValueError(f"conformance expected-failures: {behaviour} outcome must be one of {OUTCOMES}")

        legs = entry.get("failed_legs")

        if not isinstance(legs, dict) or not legs:

            raise ValueError(f"conformance expected-failures: {behaviour} needs failed_legs {{leg: pattern}}")

        compiled = {}

        for leg, pattern in legs.items():

            if not isinstance(pattern, str) or not pattern:

                raise ValueError(f"conformance expected-failures: {behaviour}/{leg} needs an error pattern")

            compiled[leg] = re.compile(pattern, re.S)

        profiles = entry.get("fs_profiles")

        if profiles is not None and (not isinstance(profiles, list) or not profiles):

            raise ValueError(f"conformance expected-failures: {behaviour} fs_profiles must be a non-empty list")

        entries[behaviour] = {**entry, "outcome": entry.get("outcome", "bug"), "patterns": compiled}

    coverage = data.get("coverage") or {}

    if not isinstance(coverage, dict):

        raise ValueError("conformance expected-failures: coverage must map profile -> {expected_skips}")

    return {"subject": data.get("subject", "oak"), "entries": entries, "coverage": coverage}

def row_failed_legs(row: dict) -> dict:

    """{failed leg: detail} for a failing row (legacy rows: {'behaviour': failure})."""

    legs = row.get("legs")

    if isinstance(legs, dict):

        return {name: str(leg.get("detail") or "") for name, leg in legs.items()

                if leg.get("status") in ("fail", "error")}

    return {"behaviour": str(row.get("failure") or "")} if row.get("returncode") == 1 else {}

def entry_applies(entry: dict, profile: str | None) -> bool:

    profiles = entry.get("fs_profiles")

    return profiles is None or profile in profiles

def mismatch(entry: dict, failed: dict) -> str | None:

    """Why a failing row does not match its expected failure, or None."""

    expected = set(entry["patterns"])

    if set(failed) != expected:

        return f"expected legs {sorted(expected)}, observed {sorted(failed)}"

    for leg, pattern in entry["patterns"].items():

        if not pattern.fullmatch(failed[leg]):

            return f"leg {leg} error changed: {failed[leg][:200]!r} does not match {pattern.pattern!r}"

    return None

def evaluate(rows: list, expected: dict, required=None) -> dict:

    subject = expected["subject"]

    entries = expected["entries"]

    result = {"subject": subject, "passed": [], "expected_failures": [], "refused": [], "fixed": [],

              "regressions": [], "unmeasured": [], "skipped": [], "git_reference_failures": [],

              "differential_differs": [], "profiles": [], "notes": []}

    seen = set()

    subject_rows = [row for row in rows if row.get("evidence_class") == "diagnostic_conformance"]

    profiles = sorted({str(row.get("fs_profile")) for row in subject_rows

                       if row.get("subject") == subject and row.get("fs_profile")})

    result["profiles"] = profiles

    if len(profiles) > 1:

        result["unmeasured"].append(f"rows mix filesystem profiles {profiles}; gate one host at a time")

        result["verdict"] = "UNMEASURED"

        return result

    profile = profiles[0] if len(profiles) == 1 else None

    missing_profile = sorted(str(row.get("scenario")) for row in subject_rows

                             if row.get("subject") == subject and not row.get("fs_profile"))

    if missing_profile:

        result["unmeasured"].append(f"rows without fs_profile cannot be judged: {missing_profile[:5]}")

    recorded = expected["coverage"].get(profile) if profile else None

    result["profile_recorded"] = recorded is not None

    if profile and recorded is None:

        result["notes"].append(f"filesystem profile {profile} has no recorded coverage; only known "

                               f"filesystem-dependent ({sorted(KNOWN_FS_DEPENDENT)}) and gated skips accepted")

    expected_skips = set((recorded or {}).get("expected_skips", []))

    for row in subject_rows:

        behaviour = row.get("scenario")

        code = row.get("returncode")

        if row.get("subject") != subject:

            if row.get("subject") == "git" and code == 1:

                result["git_reference_failures"].append(f"{behaviour}: {row.get('failure')}")

            continue

        seen.add(behaviour)

        entry = entries.get(behaviour)

        if entry is not None and not entry_applies(entry, profile):

            entry = None

        differential = str(row.get("git_differential") or "")

        if differential.startswith("differs"):

            result["differential_differs"].append(f"{behaviour}: {differential}")

        if code == 0:

            if entry:

                result["fixed"].append(f"{behaviour}: now passes; remove {entry['ticket']} from the expected-failures list")

            else:

                result["passed"].append(behaviour)

        elif code == 1:

            failed = row_failed_legs(row)

            if entry is None:

                result["regressions"].append(f"{behaviour}: {row.get('failure')}")

                continue

            why = mismatch(entry, failed)

            if why:

                result["regressions"].append(f"{behaviour}: known failure ({entry['ticket']}) changed: {why}")

            else:

                key = "refused" if entry["outcome"] == "refused" else "expected_failures"

                result[key].append(f"{behaviour}: {entry['ticket']}")

        elif code == 77 and str(row.get("skip_reason", "")).startswith(CAPABILITY_SKIP_PREFIXES):

            if recorded is not None and behaviour not in expected_skips:

                result["unmeasured"].append(f"{behaviour}: coverage loss on {profile}: skipped "

                                            f"({row.get('skip_reason')}) but not an expected skip")

            elif recorded is None and not fs_dependent_skip_allowed(behaviour):

                result["unmeasured"].append(f"{behaviour}: skipped on unrecorded profile {profile} "

                                            f"({row.get('skip_reason')}); only known filesystem-dependent "

                                            "or gated behaviours may skip there")

            else:

                result["skipped"].append(f"{behaviour}: {row.get('skip_reason')}")

        else:

            result["unmeasured"].append(f"{behaviour}: {row.get('failure') or row.get('skip_reason') or code}")

    for behaviour in sorted(set(required or ()) - seen):

        result["unmeasured"].append(f"{behaviour}: no {subject} conformance row")

    if not seen:

        result["unmeasured"].append(f"no {subject} conformance rows")

    measured = sum(len(result[key]) for key in ("passed", "expected_failures", "refused", "fixed", "regressions"))

    result["measured"] = measured

    if seen and measured == 0:

        result["unmeasured"].append(f"zero measured {subject} behaviours (every row skipped or unmeasured)")

    result["verdict"] = ("REGRESSED" if result["regressions"] else

                         "UNMEASURED" if result["unmeasured"] else "PASS")

    return result

def summary_lines(result: dict) -> list:

    lines = [f"conformance ({result['subject']}, {','.join(result['profiles']) or 'no profile'}): "

             f"{result['verdict']} - {len(result['passed'])} pass, {len(result['expected_failures'])} expected-fail, "

             f"{len(result['refused'])} policy-refused, {len(result['fixed'])} fixed, "

             f"{len(result['regressions'])} regression(s), {len(result['unmeasured'])} unmeasured, "

             f"{len(result['skipped'])} capability/gated skip(s)"]

    for key, label in (("regressions", "REGRESSION"), ("fixed", "FIXED"), ("unmeasured", "UNMEASURED"),

                       ("expected_failures", "XFAIL"), ("refused", "REFUSED"), ("differential_differs", "GIT-DIFF"),

                       ("git_reference_failures", "GIT-REF"), ("skipped", "SKIP"), ("notes", "NOTE")):

        lines += [f"  {label} {item}" for item in result[key]]

    return lines