hebrew_flash_cards/image_fetch.py

#!/usr/bin/env python3
"""
Fetch images for concrete Hebrew nouns from Wikipedia / Wikimedia Commons.

Scope: Noun PoS entries only. Concreteness heuristic:
  - English meaning has no abstract suffixes (-tion, -ity, -ness, -ment, -ance, -ism, -hood,
    -ship, -ure, -al, -ing when not a gerund, -ence)
  - Meaning is ≤ 4 words

Image sources (tried in order):
  1. Wikipedia page image via pageimages API
  2. Wikimedia Commons search (first image file result)

Cache: data/image_cache.json  (word_no_nikkud → filename or null)
Output: data/images/<safe_name>.jpg

Usage:
  python3 image_fetch.py [--limit N] [--sample] [--word WORD] [--dry-run]
"""

import argparse
import json
import logging
import re
import time
from pathlib import Path

import requests

from helpers import strip_nikkud as _strip_nikkud

logger = logging.getLogger(__name__)

DATA_DIR = Path(__file__).parent / "data"
IMAGES_DIR = DATA_DIR / "images"
CACHE_PATH = DATA_DIR / "image_cache.json"

REQUEST_DELAY = 0.5
REQUEST_TIMEOUT = 10

# Abstract noun suffixes — words whose English meaning ends in these are skipped
ABSTRACT_SUFFIXES = (
    "tion",
    "ity",
    "ness",
    "ment",
    "ance",
    "ence",
    "ism",
    "hood",
    "ship",
    "ure",
    "age",
)

session = requests.Session()
session.headers.update(
    {"User-Agent": "pealim-anki/3.0 (educational Hebrew Anki deck builder; contact: anki@pealim.invalid)"}
)



def is_concrete(english_meaning: str) -> bool:
    """Return True if the English meaning looks like a concrete noun."""
    meaning = english_meaning.strip().lower()
    # Strip leading article
    meaning = re.sub(r"^(a|an|the)\s+", "", meaning)
    words = meaning.split()
    if len(words) > 4:
        return False
    # Check last word for abstract suffixes
    last = words[-1] if words else ""
    return not any(last.endswith(suffix) for suffix in ABSTRACT_SUFFIXES)


def _safe_name(word_no_nikkud: str) -> str:
    """Create a safe ASCII-ish filename from a Hebrew word (strip to Hebrew letters only)."""
    hebrew_only = re.sub(r"[^\u05d0-\u05ea]", "", _strip_nikkud(word_no_nikkud))
    return hebrew_only if hebrew_only else "unknown"


def _try_wikipedia(query: str) -> str | None:
    """Try Wikipedia pageimages API. Returns image URL or None."""
    url = "https://en.wikipedia.org/w/api.php"
    params = {
        "action": "query",
        "titles": query,
        "prop": "pageimages",
        "format": "json",
        "pithumbsize": 200,
        "redirects": 1,
    }
    try:
        resp = session.get(url, params=params, timeout=REQUEST_TIMEOUT)
        resp.raise_for_status()
        data = resp.json()
        pages = data.get("query", {}).get("pages", {})
        for page in pages.values():
            if "thumbnail" in page:
                return page["thumbnail"]["source"]
    except Exception as e:
        logger.debug(f"Wikipedia API error for {query!r}: {e}")
    return None


def _try_commons(query: str) -> str | None:
    """Try Wikimedia Commons file search. Returns thumbnail URL or None."""
    url = "https://commons.wikimedia.org/w/api.php"
    params = {
        "action": "query",
        "list": "search",
        "srnamespace": 6,
        "srsearch": query,
        "format": "json",
        "srlimit": 1,
    }
    try:
        resp = session.get(url, params=params, timeout=REQUEST_TIMEOUT)
        resp.raise_for_status()
        data = resp.json()
        hits = data.get("query", {}).get("search", [])
        if not hits:
            return None
        file_title = hits[0]["title"]  # e.g. "File:Cat_portrait.jpg"
        # Fetch imageinfo to get thumbnail URL
        info_params = {
            "action": "query",
            "titles": file_title,
            "prop": "imageinfo",
            "iiprop": "url",
            "iiurlwidth": 200,
            "format": "json",
        }
        resp2 = session.get(url, params=info_params, timeout=REQUEST_TIMEOUT)
        resp2.raise_for_status()
        data2 = resp2.json()
        pages2 = data2.get("query", {}).get("pages", {})
        for page in pages2.values():
            info = page.get("imageinfo", [])
            if info and "thumburl" in info[0]:
                return info[0]["thumburl"]
    except Exception as e:
        logger.debug(f"Commons API error for {query!r}: {e}")
    return None


def _download_image(image_url: str, dest_path: Path) -> bool:
    """Download image_url to dest_path. Returns True on success."""
    try:
        resp = session.get(image_url, timeout=REQUEST_TIMEOUT, stream=True)
        resp.raise_for_status()
        content_type = resp.headers.get("content-type", "")
        if "image" not in content_type:
            return False
        dest_path.write_bytes(resp.content)
        return True
    except Exception as e:
        logger.debug(f"Download failed {image_url}: {e}")
        return False


def get_image(english_meaning: str, word_no_nikkud: str) -> str | None:
    """
    Fetch a thumbnail image for the word. Returns filename (in IMAGES_DIR) or None.
    Downloads to IMAGES_DIR/<safe_name>.jpg.
    """
    if not is_concrete(english_meaning):
        return None

    safe = _safe_name(word_no_nikkud)
    dest = IMAGES_DIR / f"{safe}.jpg"

    if dest.exists():
        return dest.name

    # Try Wikipedia first, then Commons
    query = english_meaning.strip().lower()
    query = re.sub(r"^(a|an|the)\s+", "", query)

    image_url = _try_wikipedia(query)
    time.sleep(REQUEST_DELAY)
    if not image_url:
        image_url = _try_commons(query)
        time.sleep(REQUEST_DELAY)

    if not image_url:
        return None

    IMAGES_DIR.mkdir(parents=True, exist_ok=True)
    if _download_image(image_url, dest):
        logger.info(f"  {word_no_nikkud!r} ({english_meaning!r}) → {dest.name}")
        return dest.name

    return None


def load_cache() -> dict:
    if CACHE_PATH.exists():
        try:
            with open(CACHE_PATH, encoding="utf-8") as f:
                return json.load(f)
        except Exception:  # noqa: S110
            pass
    return {}


def save_cache(cache: dict) -> None:
    CACHE_PATH.parent.mkdir(parents=True, exist_ok=True)
    with open(CACHE_PATH, "w", encoding="utf-8") as f:
        json.dump(cache, f, ensure_ascii=False, indent=2, sort_keys=True)


def run(limit: int | None = None, dry_run: bool = False, single_word: str | None = None) -> dict:
    """
    Fetch images for all Noun-PoS words in pealim_dict_for_anki.csv.
    Returns the updated image_cache dict.
    """
    import pandas as pd

    dict_csv = DATA_DIR / "hebrew_dict_for_anki.csv"
    if not dict_csv.exists():
        dict_csv = DATA_DIR / "hebrew_dict.csv"
    if not dict_csv.exists():
        dict_csv = DATA_DIR / "pealim_dict_for_anki.csv"
    if not dict_csv.exists():
        dict_csv = DATA_DIR / "pealim_dict.csv"
    if not dict_csv.exists():
        logger.error("Dictionary CSV not found")
        return {}

    try:
        df = pd.read_csv(dict_csv, sep=";", index_col=0)
        if df.shape[1] < 3:
            raise ValueError("too few columns")
    except (ValueError, pd.errors.ParserError):
        df = pd.read_csv(dict_csv, index_col=0)

    cache = load_cache()
    processed = 0
    hits = 0
    skipped_abstract = 0
    skipped_cached = 0

    for _, row in df.iterrows():
        if limit is not None and processed >= limit:
            break

        word = str(row.get("Word", "")).strip()
        meaning = str(row.get("Meaning", "")).strip()
        word_plain = str(row.get("Word Without Nikkud", "")).strip()
        pos_raw = str(row.get("Part of speech", row.get("Part of Speech", ""))).strip()

        if not word or not meaning or meaning in ("nan", "None"):
            continue
        if "nan" in pos_raw.lower() or "Noun" not in pos_raw:
            continue

        if single_word and word_plain != single_word:
            continue

        cache_key = word_plain or _strip_nikkud(word)

        if cache_key in cache:
            skipped_cached += 1
            continue

        if not is_concrete(meaning):
            skipped_abstract += 1
            cache[cache_key] = None
            continue

        processed += 1
        logger.info(f"[{processed}] {word_plain!r} ({meaning!r}) …")

        if dry_run:
            logger.info("  [dry-run] would fetch image")
            cache[cache_key] = None
            continue

        filename = get_image(meaning, cache_key)
        cache[cache_key] = filename
        if filename:
            hits += 1

        # Save cache periodically
        if processed % 10 == 0:
            save_cache(cache)

    save_cache(cache)

    logger.info(
        f"Image fetch complete: {hits} found, "
        f"{processed - hits} not found, "
        f"{skipped_abstract} abstract (skipped), "
        f"{skipped_cached} cached"
    )
    return cache


def main() -> None:
    logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")

    p = argparse.ArgumentParser(description="Fetch images for concrete Hebrew nouns")
    p.add_argument("--limit", type=int, metavar="N", help="Process at most N nouns (for testing)")
    p.add_argument("--dry-run", action="store_true", help="Don't download, just check concreteness")
    p.add_argument("--word", metavar="WORD", help="Fetch image for a specific word (no-nikkud form)")
    args = p.parse_args()

    cache = run(limit=args.limit, dry_run=args.dry_run, single_word=args.word)
    found = [(k, v) for k, v in cache.items() if v]
    print(f"\n{len(found)} words with images (of {len(cache)} in cache)")
    if found[:5]:
        print("Sample:", found[:5])


if __name__ == "__main__":
    main()