--- /dev/null
+# kotoba-to-anki
+
+Extract "KOTOBA" Japanese vocabulary slides (image + Japanese word + English
+translation) from a folder of PDF slide decks into a single CSV that's ready
+to import into Anki.
+
+## How it works
+
+Each PDF's first page is treated as a title/cover slide and skipped. Every
+other page contains one or two vocabulary items, each made up of:
+
+- one illustration/photo,
+- a Japanese headword (sometimes with a smaller furigana reading next to it),
+- an English translation,
+- occasionally a small grammar tag such as `N`, `V`, or `adverb`.
+
+The script finds every embedded image on a page, splits the page into
+left/right (or single, full-width) zones around those images, and assigns
+each piece of text to the nearest zone based on its position. Grammar tags
+are filtered out using a list in `src/kotoba_to_anki/config.py` (`POS_TAGS`)
+before the remaining text is classified as Japanese or English by character
+range. The larger of two Japanese text fragments becomes the headword; the
+smaller becomes its furigana reading, shown in parentheses.
+
+This is a geometry-based (not fixed-order) approach, so it's robust to PDFs
+where the tag/column layout order shifts from slide to slide -- as long as
+each vocabulary item still has exactly one image nearby.
+
+## Setup
+
+Requires Python 3.10+. Using [uv](https://docs.astral.sh/uv/) (recommended):
+
+```bash
+cd kotoba_to_anki
+uv venv
+uv pip install -e .
+```
+
+Or with a plain venv + pip:
+
+```bash
+cd kotoba_to_anki
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -e .
+```
+
+## Usage
+
+1. Drop your PDFs into `input/` (subfolders are fine, all `*.pdf` files are
+ found recursively).
+2. Run the tool:
+
+ ```bash
+ uv run kotoba-to-anki
+ # or, without the installed console script:
+ uv run python -m kotoba_to_anki.main
+ ```
+
+3. Results:
+ - `output/kotoba_anki_deck.apkg` -- a self-contained Anki package with
+ every note (including its image) bundled inside. This is the
+ recommended way to get the deck into Anki -- see "Importing the .apkg"
+ below.
+ - `output/kotoba_anki_deck.csv` -- one row per vocabulary item, columns
+ `Media, Japanese, English`. The `Media` column contains an
+ `<img src="...">` tag pointing at the matching file in `output/media/`.
+ Kept as a plain-text/spreadsheet-friendly alternative -- see
+ "Importing the CSV instead" below for how to actually get the media
+ into Anki when using this route.
+ - `output/media/` -- every extracted image, named
+ `<pdf-stem>_p<page>_<slot>.<ext>` (e.g. `Step2Unit575859_kotoha_p2_1.png`).
+ - `kotoba_to_anki.log` -- an INFO-level log in the directory you ran the
+ command from. It is **appended to** on every run, so history builds up
+ across sessions -- useful for tracking down which page of which PDF
+ broke on a given run.
+
+ Use `--no-csv` or `--no-apkg` to skip either output, and `--deck-name` /
+ `--apkg-name` / `--csv-name` to rename them.
+
+All PDFs found in `input/` are combined into that single CSV/media output
+(many PDFs -> one deck), matching a typical "one Anki deck per unit batch"
+workflow.
+
+### Options
+
+```
+--input-dir DIR Directory of source PDFs (default: input)
+--output-dir DIR Directory for the CSV + apkg + media/ folder (default: output)
+--csv-name NAME Output CSV filename (default: kotoba_anki_deck.csv)
+--apkg-name NAME Output .apkg filename (default: kotoba_anki_deck.apkg)
+--deck-name NAME Deck name inside the .apkg (default: KOTOBA Vocabulary)
+--no-csv Skip writing the CSV
+--no-apkg Skip writing the .apkg
+--log-name NAME Log filename, written to the current directory (default: kotoba_to_anki.log)
+```
+
+## Importing the .apkg (recommended)
+
+This is the easiest path and the one most people should use:
+
+1. In Anki, *File > Import*, choose `output/kotoba_anki_deck.apkg`.
+2. That's it -- the note type ("KOTOBA Vocabulary"), the deck, every note,
+ and every image are all bundled inside the file. Anki extracts the
+ images into `collection.media` and creates the notes automatically; no
+ manual file copying, no path/field mapping step.
+3. The default card shows the image + Japanese term on the front and the
+ English translation on the back. Feel free to edit the note type's card
+ template afterward in Anki (*Tools > Manage Note Types*) -- as long as
+ you don't change `config.ANKI_MODEL_ID`/`ANKI_DECK_ID` in a later run,
+ re-importing after regenerating the deck will merge into the same note
+ type/deck rather than creating duplicates (each note's identity is
+ derived from its field content, so unchanged entries are recognized as
+ the same note and only new/changed ones are added or updated).
+
+## Importing the CSV instead
+
+Use this only if you specifically want a plain CSV (e.g. to inspect/edit in
+a spreadsheet before importing, or to feed a different tool). The CSV's
+`Media` column contains bare `<img src="filename.jpg">` tags -- Anki fields
+store raw HTML, and `<img src="...">` is resolved by Anki against a single
+**flat** `collection.media` folder (no subfolders), never as a filesystem
+path relative to the CSV. That lookup only succeeds if you've put the
+matching file into that folder yourself first:
+
+1. Copy every file from `output/media/` into your Anki profile's
+ `collection.media` folder (Anki: *Tools > Check Media...* will tell you
+ where that folder is if you're not sure; e.g. on macOS it's
+ `~/Library/Application Support/Anki2/<profile>/collection.media`, on
+ Windows `%APPDATA%\Anki2\<profile>\collection.media`, on Linux
+ `~/.local/share/Anki2/<profile>/collection.media`).
+2. In Anki, *File > Import*, choose `output/kotoba_anki_deck.csv`.
+3. Map the three columns to fields on a note type that has an image field
+ and accepts HTML (e.g. Basic, with the Media column mapped to the Front
+ or a dedicated "Picture" field). Since the first row is a header
+ (`Media,Japanese,English`), tell the importer to skip/ignore the first
+ line, or delete it from the CSV before importing if your Anki version
+ doesn't offer that option.
+4. Do step 1 *before* you review the new cards -- if the image isn't in
+ `collection.media` yet, the card just shows a broken-image icon instead
+ of an error.
+
+## Debugging a broken run
+
+If a PDF's layout doesn't match expectations (e.g. a brand new grammar tag,
+or a slide with an unusual number of images), the script logs a `WARNING`
+line rather than crashing, and continues to the next page/PDF. Check
+`kotoba_to_anki.log` for lines like:
+
+```
+... p4 slot 1: 1 extra English line(s) ignored near x=310: ['Adj'] (if these are a new grammar tag, add it to config.POS_TAGS)
+```
+
+That means a piece of text wasn't recognized as a known tag and got treated
+as a stray English line. Add the new tag to `POS_TAGS` in
+`src/kotoba_to_anki/config.py` and re-run.
+
+Other useful log signals:
+
+- `no embedded images found, skipping page` -- a page had no images at all
+ (nothing to build a card from).
+- `missing Japanese text` / `missing English text` -- an item's image was
+ found but its paired text wasn't; the row is still written with the
+ missing field left blank so you can spot and fix it manually.
--- /dev/null
+[project]
+name = "kotoba-to-anki"
+version = "0.1.0"
+description = "Extract KOTOBA Japanese vocabulary flashcards (image + Japanese + English) from PDF slide decks into a single Anki-importable CSV."
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+ "pymupdf>=1.24.0",
+ "genanki>=0.13.0",
+]
+
+[project.scripts]
+kotoba-to-anki = "kotoba_to_anki.main:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/kotoba_to_anki"]
--- /dev/null
+"""kotoba_to_anki: extract KOTOBA Japanese vocabulary slides from PDFs into an Anki-ready CSV."""
+
+__version__ = "0.1.0"
--- /dev/null
+"""Build a native Anki package (.apkg) from extracted vocabulary entries.
+
+Unlike the CSV output, a .apkg bundles its media files inside the package
+itself. Anki copies them into the profile's collection.media folder
+automatically on import, so there is no manual "find my collection.media
+folder and copy files into it" step, and no ambiguity about how the image
+reference in a field resolves to a file on disk.
+"""
+from __future__ import annotations
+
+import logging
+from pathlib import Path
+
+import genanki
+
+from . import config
+from .extractor import VocabEntry
+
+logger = logging.getLogger("kotoba_to_anki")
+
+_CSS = """
+.card {
+ font-family: "Helvetica Neue", Arial, sans-serif;
+ text-align: center;
+ color: #222;
+ background-color: white;
+}
+.media img {
+ max-width: 320px;
+ max-height: 320px;
+ margin-bottom: 12px;
+}
+.jp {
+ font-size: 32px;
+ margin-top: 8px;
+}
+.en {
+ font-size: 26px;
+ margin-top: 8px;
+ color: #2a6b2a;
+}
+"""
+
+
+def _build_model() -> genanki.Model:
+ return genanki.Model(
+ config.ANKI_MODEL_ID,
+ "KOTOBA Vocabulary",
+ fields=[
+ {"name": "Media"},
+ {"name": "Japanese"},
+ {"name": "English"},
+ ],
+ templates=[
+ {
+ "name": "Picture + Japanese -> English",
+ "qfmt": '<div class="media">{{Media}}</div>\n<div class="jp">{{Japanese}}</div>',
+ "afmt": '{{FrontSide}}\n<hr id="answer">\n<div class="en">{{English}}</div>',
+ }
+ ],
+ css=_CSS,
+ )
+
+
+def write_apkg(
+ entries: list[VocabEntry],
+ media_dir: Path,
+ apkg_path: Path,
+ deck_name: str = config.DEFAULT_DECK_NAME,
+) -> int:
+ """Write all entries to a single .apkg file. Returns the number of notes written."""
+ model = _build_model()
+ deck = genanki.Deck(config.ANKI_DECK_ID, deck_name)
+
+ media_files: list[str] = []
+ written = 0
+
+ for entry in entries:
+ image_path = media_dir / entry.image_filename
+ if not image_path.exists():
+ logger.warning(
+ "Skipping apkg note for %r: media file not found at %s",
+ entry.japanese or entry.english,
+ image_path,
+ )
+ continue
+
+ note = genanki.Note(
+ model=model,
+ fields=[f'<img src="{entry.image_filename}">', entry.japanese, entry.english],
+ )
+ deck.add_note(note)
+ media_files.append(str(image_path))
+ written += 1
+
+ package = genanki.Package(deck)
+ package.media_files = media_files
+ package.write_to_file(apkg_path)
+
+ logger.info("Wrote %d note(s) to Anki package %s (deck %r)", written, apkg_path, deck_name)
+ return written
--- /dev/null
+"""Configuration constants for the KOTOBA -> Anki extraction pipeline.
+
+Tweak these values if a new PDF unit uses a layout convention (e.g. a new
+grammar tag) that the extractor doesn't recognize yet. Check the log file
+after a run -- unrecognized tags usually show up as "extra English line(s)
+ignored" warnings, which is the signal to add a new entry to POS_TAGS below.
+"""
+from __future__ import annotations
+
+from pathlib import Path
+
+# ---------------------------------------------------------------------------
+# Directories / filenames (all overridable via CLI flags, see main.py --help)
+# ---------------------------------------------------------------------------
+DEFAULT_INPUT_DIR = Path("input")
+DEFAULT_OUTPUT_DIR = Path("output")
+DEFAULT_MEDIA_SUBDIR = "media"
+DEFAULT_CSV_NAME = "kotoba_anki_deck.csv"
+DEFAULT_APKG_NAME = "kotoba_anki_deck.apkg"
+DEFAULT_DECK_NAME = "KOTOBA Vocabulary"
+DEFAULT_LOG_NAME = "kotoba_to_anki.log"
+
+# Fixed genanki model/deck IDs. These MUST stay constant across runs: Anki
+# uses them (plus each note's guid, which genanki derives from its field
+# content) to recognize "this is the same note type / deck" on re-import,
+# so re-running the pipeline updates/merges instead of duplicating cards.
+# Do not change these unless you want re-imports to create a brand new,
+# unrelated note type and deck.
+ANKI_MODEL_ID = 1607392319934
+ANKI_DECK_ID = 1607392319935
+
+# Number of leading pages to skip in every PDF (title/cover page(s)).
+TITLE_PAGES_TO_SKIP = 1
+
+# ---------------------------------------------------------------------------
+# Part-of-speech / grammar tag labels that appear as small standalone
+# annotations on a slide (e.g. "N", "V", "adverb"). These are discarded
+# before the remaining text on the slide is classified as Japanese or
+# English. Matching is case-insensitive against the FULL stripped text of a
+# line (punctuation/whitespace removed), so "N", "n", "N " and "(N)" all
+# match the same "n" entry below.
+POS_TAGS = {
+ "n", "v", "adj", "adj-i", "adj-na", "adj-no", "i-adj", "na-adj",
+ "adv", "adverb",
+ "exp", "expression", "phrase",
+ "conj", "conjunction",
+ "prep", "preposition",
+ "pron", "pronoun",
+ "part", "particle",
+ "interj", "interjection",
+ "noun", "verb", "adjective",
+ "counter", "suffix", "prefix",
+ "aux", "auxiliary",
+ "num", "numeral",
+}
+
+# ---------------------------------------------------------------------------
+# Unicode ranges used to detect Japanese text (hiragana, katakana, kanji,
+# and common Japanese/fullwidth punctuation).
+# ---------------------------------------------------------------------------
+JAPANESE_RANGES = (
+ (0x3040, 0x309F), # Hiragana
+ (0x30A0, 0x30FF), # Katakana
+ (0x4E00, 0x9FFF), # CJK Unified Ideographs (Kanji)
+ (0x3000, 0x303F), # CJK punctuation (incl. the full-width brackets/dot)
+ (0xFF00, 0xFFEF), # Fullwidth forms
+)
+
+# Output CSV column order (matches: media / Japanese / English request).
+CSV_HEADERS = ["Media", "Japanese", "English"]
--- /dev/null
+"""Core PDF -> vocabulary-entry extraction logic.
+
+Layout assumption (observed across KOTOBA vocabulary slides):
+
+- Page 1 of every PDF is a title/cover page and is skipped.
+- Each remaining page contains 1-2 "vocabulary items" laid out side by side
+ (occasionally just one, centered / full width).
+- Each item = one embedded image + one Japanese text line (optionally with a
+ smaller furigana reading line near it) + one English translation line.
+- Some slides also show a small grammar/part-of-speech tag ("N", "V",
+ "adverb", ...) which is not part of any vocabulary item and must be
+ discarded (see config.POS_TAGS).
+
+Slide designs vary quite a bit (highlight colors, tag position, one vs two
+columns, text stacking order), so extraction is done geometrically rather
+than by assuming a fixed text order:
+
+1. Every embedded image on the page is located (with its bounding box).
+2. The page width is split into horizontal "slots", one per image, using the
+ midpoints between neighboring image centers as slot boundaries. This
+ works for any number of images (1, 2, or more) per page.
+3. Every text line on the page is assigned to the slot whose image center is
+ horizontally closest.
+4. Within a slot, text lines are classified as Japanese or English by
+ character ranges. Grammar tags are dropped beforehand.
+5. The largest Japanese text in a slot is treated as the headword; a second,
+ smaller Japanese text is treated as its furigana reading. The
+ bottom-most English line is treated as the translation.
+"""
+from __future__ import annotations
+
+import logging
+import re
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Optional
+
+import pymupdf
+
+from . import config
+
+logger = logging.getLogger("kotoba_to_anki")
+
+_TAG_STRIP_RE = re.compile(r"[\s.:()\[\]・、。]+")
+
+
+@dataclass
+class VocabEntry:
+ japanese: str
+ english: str
+ image_filename: str
+
+
+@dataclass
+class _Line:
+ text: str
+ x0: float
+ y0: float
+ x1: float
+ y1: float
+ size: float
+
+ @property
+ def x_center(self) -> float:
+ return (self.x0 + self.x1) / 2
+
+
+@dataclass
+class _ImageSlot:
+ xref: int
+ x0: float
+ y0: float
+ x1: float
+ y1: float
+ slot_x0: float = 0.0
+ slot_x1: float = 0.0
+ japanese_lines: list[_Line] = field(default_factory=list)
+ english_lines: list[_Line] = field(default_factory=list)
+
+ @property
+ def x_center(self) -> float:
+ return (self.x0 + self.x1) / 2
+
+
+def _is_japanese_char(ch: str) -> bool:
+ code = ord(ch)
+ return any(lo <= code <= hi for lo, hi in config.JAPANESE_RANGES)
+
+
+def _contains_japanese(text: str) -> bool:
+ return any(_is_japanese_char(ch) for ch in text)
+
+
+def _is_pos_tag(text: str) -> bool:
+ cleaned = _TAG_STRIP_RE.sub("", text).strip().lower()
+ return cleaned in config.POS_TAGS
+
+
+def _extract_lines(page: "pymupdf.Page") -> list[_Line]:
+ """Flatten the page's text into line-level records with bounding boxes."""
+ lines: list[_Line] = []
+ page_dict = page.get_text("dict")
+ for block in page_dict.get("blocks", []):
+ for line in block.get("lines", []):
+ spans = line.get("spans", [])
+ if not spans:
+ continue
+ text = "".join(span.get("text", "") for span in spans).strip()
+ if not text:
+ continue
+ x0 = min(s["bbox"][0] for s in spans)
+ y0 = min(s["bbox"][1] for s in spans)
+ x1 = max(s["bbox"][2] for s in spans)
+ y1 = max(s["bbox"][3] for s in spans)
+ size = max(s.get("size", 0.0) for s in spans)
+ lines.append(_Line(text=text, x0=x0, y0=y0, x1=x1, y1=y1, size=size))
+ return lines
+
+
+def _build_slots(page: "pymupdf.Page") -> list[_ImageSlot]:
+ """One slot per embedded image, with slot x-boundaries splitting the page."""
+ infos = [info for info in page.get_image_info(xrefs=True) if info.get("xref")]
+ if not infos:
+ return []
+
+ slots = [
+ _ImageSlot(
+ xref=info["xref"],
+ x0=info["bbox"][0],
+ y0=info["bbox"][1],
+ x1=info["bbox"][2],
+ y1=info["bbox"][3],
+ )
+ for info in infos
+ ]
+ slots.sort(key=lambda s: s.x_center)
+
+ page_width = page.rect.width
+ for i, slot in enumerate(slots):
+ if i == 0:
+ left_bound = 0.0
+ else:
+ left_bound = (slots[i - 1].x_center + slot.x_center) / 2
+ if i == len(slots) - 1:
+ right_bound = page_width
+ else:
+ right_bound = (slot.x_center + slots[i + 1].x_center) / 2
+ slot.slot_x0 = left_bound
+ slot.slot_x1 = right_bound
+ return slots
+
+
+def _assign_lines_to_slots(
+ lines: list[_Line], slots: list[_ImageSlot], pdf_name: str, page_number: int
+) -> None:
+ for line in lines:
+ if _is_pos_tag(line.text):
+ logger.debug("%s p%s: dropping tag-like line %r", pdf_name, page_number, line.text)
+ continue
+
+ best_slot = min(slots, key=lambda s: abs(line.x_center - s.x_center))
+
+ if _contains_japanese(line.text):
+ best_slot.japanese_lines.append(line)
+ else:
+ best_slot.english_lines.append(line)
+
+
+def _resolve_japanese(slot: _ImageSlot, pdf_name: str, page_number: int) -> Optional[str]:
+ if not slot.japanese_lines:
+ return None
+ ordered = sorted(slot.japanese_lines, key=lambda l: l.size, reverse=True)
+ headword = ordered[0]
+ reading = ordered[1] if len(ordered) > 1 else None
+ if len(ordered) > 2:
+ logger.warning(
+ "%s p%s: %d extra Japanese line(s) ignored near x=%.0f: %s",
+ pdf_name,
+ page_number,
+ len(ordered) - 2,
+ slot.x_center,
+ [l.text for l in ordered[2:]],
+ )
+ if reading:
+ return f"{headword.text} ({reading.text})"
+ return headword.text
+
+
+def _resolve_english(slot: _ImageSlot, pdf_name: str, page_number: int) -> Optional[str]:
+ if not slot.english_lines:
+ return None
+ ordered = sorted(slot.english_lines, key=lambda l: l.y0)
+ translation = ordered[-1]
+ if len(ordered) > 1:
+ logger.warning(
+ "%s p%s: %d extra English line(s) ignored near x=%.0f: %s "
+ "(if these are a new grammar tag, add it to config.POS_TAGS)",
+ pdf_name,
+ page_number,
+ len(ordered) - 1,
+ slot.x_center,
+ [l.text for l in ordered[:-1]],
+ )
+ return translation.text
+
+
+def _save_image(doc: "pymupdf.Document", xref: int, media_dir: Path, base_name: str) -> Optional[str]:
+ try:
+ image = doc.extract_image(xref)
+ except Exception:
+ logger.exception("Failed to extract image xref=%s (%s)", xref, base_name)
+ return None
+ ext = image.get("ext", "png")
+ filename = f"{base_name}.{ext}"
+ out_path = media_dir / filename
+ try:
+ out_path.write_bytes(image["image"])
+ except Exception:
+ logger.exception("Failed to write image file %s", out_path)
+ return None
+ return filename
+
+
+def extract_pdf(pdf_path: Path, media_dir: Path) -> list[VocabEntry]:
+ """Extract all vocabulary entries from a single PDF (skipping its title page)."""
+ entries: list[VocabEntry] = []
+ pdf_name = pdf_path.name
+
+ try:
+ doc = pymupdf.open(pdf_path)
+ except Exception:
+ logger.exception("Could not open PDF: %s", pdf_path)
+ return entries
+
+ logger.info("Processing %s (%d pages)", pdf_name, doc.page_count)
+
+ for page_index in range(config.TITLE_PAGES_TO_SKIP, doc.page_count):
+ page_number = page_index + 1
+ page = doc.load_page(page_index)
+
+ try:
+ slots = _build_slots(page)
+ if not slots:
+ logger.warning("%s p%s: no embedded images found, skipping page", pdf_name, page_number)
+ continue
+
+ lines = _extract_lines(page)
+ _assign_lines_to_slots(lines, slots, pdf_name, page_number)
+
+ for slot_index, slot in enumerate(slots, start=1):
+ japanese = _resolve_japanese(slot, pdf_name, page_number)
+ english = _resolve_english(slot, pdf_name, page_number)
+
+ if not japanese and not english:
+ logger.warning(
+ "%s p%s slot %d: no text found near image xref=%s, skipping item",
+ pdf_name,
+ page_number,
+ slot_index,
+ slot.xref,
+ )
+ continue
+ if not japanese:
+ logger.warning(
+ "%s p%s slot %d: missing Japanese text (english=%r)",
+ pdf_name, page_number, slot_index, english,
+ )
+ if not english:
+ logger.warning(
+ "%s p%s slot %d: missing English text (japanese=%r)",
+ pdf_name, page_number, slot_index, japanese,
+ )
+
+ base_name = f"{pdf_path.stem}_p{page_number}_{slot_index}"
+ filename = _save_image(doc, slot.xref, media_dir, base_name)
+ if not filename:
+ logger.warning(
+ "%s p%s slot %d: skipping item, image could not be saved",
+ pdf_name, page_number, slot_index,
+ )
+ continue
+
+ entry = VocabEntry(
+ japanese=japanese or "",
+ english=english or "",
+ image_filename=filename,
+ )
+ entries.append(entry)
+ logger.info(
+ "%s p%s slot %d: extracted entry JP=%r EN=%r image=%s",
+ pdf_name, page_number, slot_index, entry.japanese, entry.english, filename,
+ )
+ except Exception:
+ logger.exception("%s p%s: unexpected error, skipping page", pdf_name, page_number)
+ continue
+
+ doc.close()
+ logger.info("Finished %s: %d entries extracted", pdf_name, len(entries))
+ return entries
--- /dev/null
+"""Logging configuration.
+
+Logs at INFO level (and above) to both the console and a log file in the
+base directory (the directory the script is run from). The log file is
+opened in append mode so history builds up across multiple runs, which is
+useful for debugging intermittent PDF layout issues over time.
+"""
+from __future__ import annotations
+
+import logging
+from pathlib import Path
+
+_LOGGER_NAME = "kotoba_to_anki"
+
+
+def setup_logging(base_dir: Path, log_name: str) -> logging.Logger:
+ """Configure and return the package logger.
+
+ Safe to call multiple times (e.g. in tests) -- handlers are only
+ attached once per process.
+ """
+ base_dir.mkdir(parents=True, exist_ok=True)
+ log_path = base_dir / log_name
+
+ logger = logging.getLogger(_LOGGER_NAME)
+ logger.setLevel(logging.INFO)
+ logger.propagate = False
+
+ if logger.handlers:
+ return logger
+
+ fmt = logging.Formatter(
+ fmt="%(asctime)s [%(levelname)s] %(message)s",
+ datefmt="%Y-%m-%d %H:%M:%S",
+ )
+
+ file_handler = logging.FileHandler(log_path, mode="a", encoding="utf-8")
+ file_handler.setLevel(logging.INFO)
+ file_handler.setFormatter(fmt)
+
+ console_handler = logging.StreamHandler()
+ console_handler.setLevel(logging.INFO)
+ console_handler.setFormatter(fmt)
+
+ logger.addHandler(file_handler)
+ logger.addHandler(console_handler)
+
+ logger.info("=" * 78)
+ logger.info("Logging initialized -> %s (append mode)", log_path)
+
+ return logger
--- /dev/null
+"""CLI entry point: convert a directory of KOTOBA vocabulary PDFs into a
+single Anki-importable CSV (many PDFs -> one CSV + one media folder).
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import sys
+from pathlib import Path
+
+from . import config
+from .anki_package import write_apkg
+from .extractor import extract_pdf
+from .logging_setup import setup_logging
+
+
+def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
+ parser = argparse.ArgumentParser(
+ description=(
+ "Extract KOTOBA vocabulary (image + Japanese + English) from every "
+ "PDF in --input-dir into a single Anki-importable CSV in --output-dir."
+ )
+ )
+ parser.add_argument(
+ "--input-dir",
+ type=Path,
+ default=config.DEFAULT_INPUT_DIR,
+ help="Directory containing the source PDFs, searched recursively. Default: %(default)s",
+ )
+ parser.add_argument(
+ "--output-dir",
+ type=Path,
+ default=config.DEFAULT_OUTPUT_DIR,
+ help="Directory to write the CSV and media/ folder into. Default: %(default)s",
+ )
+ parser.add_argument(
+ "--csv-name",
+ default=config.DEFAULT_CSV_NAME,
+ help="Filename for the combined output CSV. Default: %(default)s",
+ )
+ parser.add_argument(
+ "--apkg-name",
+ default=config.DEFAULT_APKG_NAME,
+ help="Filename for the combined output Anki package (.apkg). Default: %(default)s",
+ )
+ parser.add_argument(
+ "--deck-name",
+ default=config.DEFAULT_DECK_NAME,
+ help="Deck name to use inside the generated .apkg. Default: %(default)s",
+ )
+ parser.add_argument(
+ "--no-csv",
+ action="store_true",
+ help="Skip writing the CSV output.",
+ )
+ parser.add_argument(
+ "--no-apkg",
+ action="store_true",
+ help="Skip writing the .apkg output.",
+ )
+ parser.add_argument(
+ "--log-name",
+ default=config.DEFAULT_LOG_NAME,
+ help="Filename for the log file, written to the current working directory "
+ "and appended to on every run. Default: %(default)s",
+ )
+ return parser.parse_args(argv)
+
+
+def main(argv: list[str] | None = None) -> int:
+ args = parse_args(argv)
+ base_dir = Path.cwd()
+ logger = setup_logging(base_dir, args.log_name)
+
+ input_dir: Path = args.input_dir
+ output_dir: Path = args.output_dir
+ media_dir = output_dir / config.DEFAULT_MEDIA_SUBDIR
+ csv_path = output_dir / args.csv_name
+ apkg_path = output_dir / args.apkg_name
+
+ if not input_dir.exists():
+ logger.error("Input directory does not exist: %s", input_dir)
+ return 1
+
+ pdf_paths = sorted(input_dir.rglob("*.pdf"))
+ if not pdf_paths:
+ logger.warning("No PDFs found in %s", input_dir)
+ return 0
+
+ output_dir.mkdir(parents=True, exist_ok=True)
+ media_dir.mkdir(parents=True, exist_ok=True)
+
+ logger.info("Run started: %d PDF(s) found in %s", len(pdf_paths), input_dir)
+
+ all_entries = []
+ pdf_success = 0
+ pdf_failed = 0
+
+ for pdf_path in pdf_paths:
+ try:
+ entries = extract_pdf(pdf_path, media_dir)
+ except Exception:
+ logger.exception(
+ "Fatal error while processing %s, continuing with remaining PDFs", pdf_path
+ )
+ pdf_failed += 1
+ continue
+
+ if entries:
+ pdf_success += 1
+ else:
+ logger.warning("%s produced no vocabulary entries", pdf_path.name)
+
+ all_entries.extend(entries)
+
+ if not args.no_csv:
+ with csv_path.open("w", newline="", encoding="utf-8") as f:
+ writer = csv.writer(f)
+ writer.writerow(config.CSV_HEADERS)
+ writer.writerows(
+ [f'<img src="{e.image_filename}">', e.japanese, e.english] for e in all_entries
+ )
+ logger.info("Wrote %d row(s) to CSV %s", len(all_entries), csv_path)
+ else:
+ logger.info("Skipping CSV output (--no-csv)")
+
+ if not args.no_apkg:
+ write_apkg(all_entries, media_dir, apkg_path, deck_name=args.deck_name)
+ else:
+ logger.info("Skipping .apkg output (--no-apkg)")
+
+ logger.info(
+ "Run finished: %d PDF(s) OK, %d PDF(s) failed, %d total vocabulary entries",
+ pdf_success,
+ pdf_failed,
+ len(all_entries),
+ )
+ logger.info("Media files written to %s", media_dir)
+
+ return 0
+
+
+if __name__ == "__main__":
+ sys.exit(main())
--- /dev/null
+version = 1
+revision = 3
+requires-python = ">=3.10"
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projects / kotoba_to_anki.git / commitdiff