src/edgeeda/orfs/metrics.py

from __future__ import annotations

import glob
import gzip
import json
import logging
import os
from typing import Any, Dict, Optional, Tuple, List


def _list_json_files(dir_path: str):
    if not os.path.isdir(dir_path):
        return []
    out = []
    for fn in os.listdir(dir_path):
        if fn.endswith(".json"):
            out.append(os.path.join(dir_path, fn))
    return out


def _list_json_and_gz_files(dir_path: str) -> List[str]:
    """Return .json and .json.gz files in directory (non-recursive)."""
    if not os.path.isdir(dir_path):
        return []
    out: List[str] = []
    for fn in os.listdir(dir_path):
        if fn.endswith(".json") or fn.endswith(".json.gz"):
            out.append(os.path.join(dir_path, fn))
    return out


def find_best_metadata_json(
    orfs_flow_dir: str,
    platform: str,
    design: str,
    variant: str,
) -> Optional[str]:
    """
    ORFS convention:
      reports/<platform>/<design>/<FLOW_VARIANT>/
    We search for likely metadata / metrics files and pick most recently modified.
    
    Tries multiple patterns in order of preference:
    1. Exact matches: metadata.json, metrics.json
    2. Pattern matches: *metadata*.json, *metrics*.json
    3. Fallback: any .json file
    """
    base = os.path.join(orfs_flow_dir, "reports", platform, design, variant)
    
    if not os.path.exists(base):
        logging.debug(f"Reports directory does not exist: {base}")
        return None
    
    if not os.path.isdir(base):
        logging.warning(f"Reports path exists but is not a directory: {base}")
        return None
    
    # Try multiple patterns, searching recursively so nested report dirs are found
    patterns = [
        "**/metadata.json",
        "**/metrics.json",
        "**/*metadata*.json",
        "**/*metrics*.json",
        "**/*final*.json",
        "**/*report*.json",
        "**/*results*.json",
    ]

    candidates: List[str] = []
    for pattern in patterns:
        matches = glob.glob(os.path.join(base, pattern), recursive=True)
        if matches:
            candidates.extend(matches)
            logging.debug(f"Found {len(matches)} files matching pattern '{pattern}' under {base}")
            break  # Prefer the first matching pattern set
    
    # Fallback: any .json or .json.gz file in the dir (non-recursive)
    if not candidates:
        candidates = _list_json_and_gz_files(base)
        if candidates:
            logging.debug(f"Using fallback: found {len(candidates)} JSON(/gz) files in {base}")
    
    if not candidates:
        logging.warning(f"No JSON files found in {base}")
        return None
    
    # If still empty, try searching one level up or across siblings
    if not candidates:
        parent = os.path.dirname(base)
        siblings = glob.glob(os.path.join(parent, "**/*.json"), recursive=True)
        if siblings:
            candidates = siblings
            logging.debug(f"Fallback: found {len(siblings)} JSON files under {parent}")

    if not candidates:
        logging.warning(f"No JSON files found in {base} or nearby")
        return None

    # Sort by modification time (most recent first)
    candidates.sort(key=lambda p: os.path.getmtime(p), reverse=True)
    selected = candidates[0]
    logging.debug(f"Selected metadata file: {selected} (from {len(candidates)} candidates)")
    return selected


def load_json(path: str) -> Dict[str, Any]:
    """Load JSON file with error handling."""
    try:
        if path.endswith('.gz') or path.endswith('.json.gz'):
            with gzip.open(path, 'rt', encoding='utf-8') as f:
                return json.load(f)
        with open(path, "r", encoding="utf-8") as f:
            return json.load(f)
    except json.JSONDecodeError as e:
        logging.warning(f"Failed to parse JSON from {path}: {e}. Trying lenient read.")
        # Try a lenient read: read file and attempt to find JSON-like substring
        try:
            if path.endswith('.gz') or path.endswith('.json.gz'):
                with gzip.open(path, 'rt', encoding='utf-8', errors='ignore') as f:
                    txt = f.read()
            else:
                with open(path, 'r', encoding='utf-8', errors='ignore') as f:
                    txt = f.read()
            # attempt to locate first JSON object within text
            start = txt.find('{')
            end = txt.rfind('}')
            if start != -1 and end != -1 and end > start:
                snippet = txt[start:end+1]
                return json.loads(snippet)
        except Exception as e2:
            logging.error(f"Lenient parse failed for {path}: {e2}")
        raise
    except FileNotFoundError:
        logging.error(f"JSON file not found: {path}")
        raise
    except Exception as e:
        logging.error(f"Unexpected error loading JSON from {path}: {e}")
        raise


def flatten_metrics(obj: Any, prefix: str = "") -> Dict[str, Any]:
    """
    Flattens nested dicts into key paths joined by '__'.
    Keeps non-dict leaf values.
    """
    out: Dict[str, Any] = {}
    if isinstance(obj, dict):
        for k, v in obj.items():
            kk = f"{prefix}__{k}" if prefix else str(k)
            out.update(flatten_metrics(v, kk))
    else:
        out[prefix] = obj
    return out


def coerce_float(x: Any) -> Optional[float]:
    if x is None:
        return None
    if isinstance(x, (int, float)):
        return float(x)
    if isinstance(x, str):
        try:
            return float(x)
        except ValueError:
            return None
    return None


def pick_first(metrics_flat: Dict[str, Any], keys: list[str]) -> Optional[float]:
    for k in keys:
        if k in metrics_flat:
            v = coerce_float(metrics_flat[k])
            if v is not None:
                return v
    # also try case-insensitive match
    lower = {kk.lower(): kk for kk in metrics_flat.keys()}
    for k in keys:
        kk = lower.get(k.lower())
        if kk:
            v = coerce_float(metrics_flat[kk])
            if v is not None:
                return v
    return None