diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..d2e9a11
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,30 @@
+default_install_hook_types:
+ - pre-commit
+ - commit-msg
+ - pre-push
+
+repos:
+ - repo: https://github.com/pre-commit/pre-commit-hooks
+ rev: v4.3.0
+ hooks:
+ - id: end-of-file-fixer
+ - id: trailing-whitespace
+ - id: check-toml
+
+ - repo: https://github.com/psf/black
+ rev: 22.10.0
+ hooks:
+ - id: black
+ #exclude: ^aodn_cloud_optimised/bin/create_aws_registry_dataset.py$ # issue with black!
+
+ - repo: https://github.com/python-poetry/poetry
+ rev: '1.8.3'
+ hooks:
+ - id: poetry-check
+ args: ["--lock", "--quiet"] # Add --quiet to run poetry-check quietly
+ verbose: false
+ - id: poetry-lock
+ args: ["--no-update"]
+ verbose: true
+ - id: poetry-install
+ args: ["--quiet"]
diff --git a/koreader_highlights_2_anki/__main__.py b/koreader_highlights_2_anki/__main__.py
index 155afb5..b4583bf 100755
--- a/koreader_highlights_2_anki/__main__.py
+++ b/koreader_highlights_2_anki/__main__.py
@@ -53,11 +53,13 @@
logging.getLogger("transformers").setLevel(logging.ERROR)
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logging.basicConfig(
+ level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
logger = logging.getLogger(__name__)
-def get_word_importance(sentence, language='en'):
+def get_word_importance(sentence, language="en"):
"""
Use BERT to score word importance by masking each word and predicting it.
Words that are harder for BERT to predict will be considered more important.
@@ -71,17 +73,17 @@ def get_word_importance(sentence, language='en'):
model = BertForMaskedLM.from_pretrained(model_name)
# Download NLTK stopwords if you haven't already
- nltk.download('stopwords', quiet=True)
+ nltk.download("stopwords", quiet=True)
from nltk.corpus import stopwords
stop_words_dict = {
- 'en-US': set(stopwords.words('english')),
- 'fr': set(stopwords.words('french')),
- 'de': set(stopwords.words('german')),
- 'es': set(stopwords.words('spanish')),
- 'it': set(stopwords.words('italian')),
+ "en-US": set(stopwords.words("english")),
+ "fr": set(stopwords.words("french")),
+ "de": set(stopwords.words("german")),
+ "es": set(stopwords.words("spanish")),
+ "it": set(stopwords.words("italian")),
}
- stop_words = stop_words_dict.get(language, stop_words_dict['en-US'])
+ stop_words = stop_words_dict.get(language, stop_words_dict["en-US"])
words = sentence.split()
word_scores = []
@@ -92,8 +94,12 @@ def get_word_importance(sentence, language='en'):
continue
# Tokenize and mask the current word
- masked_sentence = words[:i] + ['[MASK]'] + words[i + 1:]
- inputs = tokenizer(' '.join(masked_sentence), return_tensors='pt', clean_up_tokenization_spaces=True)
+ masked_sentence = words[:i] + ["[MASK]"] + words[i + 1 :]
+ inputs = tokenizer(
+ " ".join(masked_sentence),
+ return_tensors="pt",
+ clean_up_tokenization_spaces=True,
+ )
# Get BERT predictions
with torch.no_grad():
@@ -101,11 +107,15 @@ def get_word_importance(sentence, language='en'):
predictions = outputs.logits
# Get the token ID for the masked word
- masked_index = (inputs.input_ids == tokenizer.mask_token_id).nonzero(as_tuple=True)[1]
+ masked_index = (inputs.input_ids == tokenizer.mask_token_id).nonzero(
+ as_tuple=True
+ )[1]
predicted_token_id = torch.argmax(predictions[0, masked_index, :], dim=-1)
# Score based on the predicted token's probability
- predicted_prob = torch.softmax(predictions[0, masked_index, :], dim=-1)[0, predicted_token_id].item()
+ predicted_prob = torch.softmax(predictions[0, masked_index, :], dim=-1)[
+ 0, predicted_token_id
+ ].item()
importance_score = 1 - predicted_prob # Lower probability means more important
word_scores.append((word, importance_score))
@@ -115,7 +125,15 @@ def get_word_importance(sentence, language='en'):
return word_scores
-def generate_cloze_with_ai(highlight_text, highlight_sentences, note_text, model, deck, highlight, language="en-US"):
+def generate_cloze_with_ai(
+ highlight_text,
+ highlight_sentences,
+ note_text,
+ model,
+ deck,
+ highlight,
+ language="en-US",
+):
"""
Generates cloze deletions using AI to select the most important words while keeping the full highlight text.
@@ -131,11 +149,13 @@ def generate_cloze_with_ai(highlight_text, highlight_sentences, note_text, model
deck: The updated Anki deck with added cloze notes.
"""
# Ensure NLTK punkt tokenizer models are downloaded
- nltk.download('punkt', quiet=True)
+ nltk.download("punkt", quiet=True)
# Create a copy of the original highlight text for replacement
full_highlight_cloze = highlight_text
- logger.debug(f"Starting to process {len(highlight_sentences)} highlight sentences...")
+ logger.debug(
+ f"Starting to process {len(highlight_sentences)} highlight sentences..."
+ )
for sentence in highlight_sentences:
words = sentence.split()
@@ -157,10 +177,12 @@ def generate_cloze_with_ai(highlight_text, highlight_sentences, note_text, model
end_index = min(len(words), most_important_index + 3) # 3 words after
# Create a cloze text from the important word and context
- cloze_text = ' '.join(words[start_index:end_index])
+ cloze_text = " ".join(words[start_index:end_index])
# Replace the selected words with cloze syntax in the full highlight text
- full_highlight_cloze = full_highlight_cloze.replace(cloze_text, f"{{{{c1::{cloze_text}}}}}")
+ full_highlight_cloze = full_highlight_cloze.replace(
+ cloze_text, f"{{{{c1::{cloze_text}}}}}"
+ )
logger.debug("Finished processing all sentences.")
# Create the datetime string for the bottom right
datetime_info = f"{highlight['datetime']}"
@@ -168,14 +190,19 @@ def generate_cloze_with_ai(highlight_text, highlight_sentences, note_text, model
# Add the note to the deck with the full highlight text containing cloze deletions
note = genanki.Note(
model=model,
- fields=[note_text + full_highlight_cloze, datetime_info] # Add datetime in Extra field
+ fields=[
+ note_text + full_highlight_cloze,
+ datetime_info,
+ ], # Add datetime in Extra field
)
deck.add_note(note)
return deck
-def create_anki_flashcards_ai(parsed_data, output_apkg_path, deck_name="Books Highlights 📚"):
+def create_anki_flashcards_ai(
+ parsed_data, output_apkg_path, deck_name="Books Highlights 📚"
+):
"""
Creates cloze flashcards for Anki from the highlights.
@@ -188,31 +215,39 @@ def create_anki_flashcards_ai(parsed_data, output_apkg_path, deck_name="Books Hi
None
"""
# Download NLTK punkt tokenizer models if you haven't already
- nltk.download('punkt_tab')
- nltk.download('punkt')
+ nltk.download("punkt_tab")
+ nltk.download("punkt")
- language = parsed_data['language']
+ language = parsed_data["language"]
- book_title = parsed_data['title'].replace(' ', '_')
- author_name = parsed_data['authors'].replace(' ', '_')
+ book_title = parsed_data["title"].replace(" ", "_")
+ author_name = parsed_data["authors"].replace(" ", "_")
# Set deck name in format 'Books Highlights::[book_title]-[author_name]'
- deck_full_name = f"{deck_name}::{book_title.replace('_', ' ')}-{author_name.replace('_', ' ')}"
+ deck_full_name = (
+ f"{deck_name}::{book_title.replace('_', ' ')}-{author_name.replace('_', ' ')}"
+ )
# Generate deck ID using a hash of the deck_full_name
- deck_id = int(hashlib.md5(deck_full_name.encode('utf-8')).hexdigest(), 16) % (10 ** 10)
+ deck_id = int(hashlib.md5(deck_full_name.encode("utf-8")).hexdigest(), 16) % (
+ 10**10
+ )
deck = genanki.Deck(deck_id=deck_id, name=deck_full_name)
model = genanki.CLOZE_MODEL
# Generate cards for each highlight
- for highlight in tqdm(parsed_data['entries'], desc="Processing book highlights", unit="highlight"):
- highlight_text = highlight['notes']
+ for highlight in tqdm(
+ parsed_data["entries"], desc="Processing book highlights", unit="highlight"
+ ):
+ highlight_text = highlight["notes"]
# Use regex to split sentences by both '.' and ';'
- highlight_sentences = re.split(r'(?<=[.!?;]) +', highlight_text) # Tokenize sentences
- page_number = highlight['page']
+ highlight_sentences = re.split(
+ r"(?<=[.!?;]) +", highlight_text
+ ) # Tokenize sentences
+ page_number = highlight["page"]
chapter_info = f"Chapter: {highlight['chapter']} - Page: {page_number}"
# Keep your original formatting for title and note_text
@@ -220,11 +255,19 @@ def create_anki_flashcards_ai(parsed_data, output_apkg_path, deck_name="Books Hi
note_text = f"{title}{chapter_info}
" # Decrease font size of the note text
# Generate cloze deletions using AI
- deck = generate_cloze_with_ai(highlight_text, highlight_sentences, note_text, model, deck, highlight, language=language)
+ deck = generate_cloze_with_ai(
+ highlight_text,
+ highlight_sentences,
+ note_text,
+ model,
+ deck,
+ highlight,
+ language=language,
+ )
# Check if output_apkg_path is a folder, and if so, append a default file name
if os.path.isdir(output_apkg_path):
- default_filename = f"{book_title}_{author_name}.apkg".replace('/', '.')
+ default_filename = f"{book_title}_{author_name}.apkg".replace("/", ".")
output_apkg_path = os.path.join(output_apkg_path, default_filename)
# Create the Anki package and save it
@@ -232,7 +275,9 @@ def create_anki_flashcards_ai(parsed_data, output_apkg_path, deck_name="Books Hi
package.write_to_file(output_apkg_path)
-def create_anki_flashcards(parsed_data, output_apkg_path, deck_name="Books Highlights 📚"):
+def create_anki_flashcards(
+ parsed_data, output_apkg_path, deck_name="Books Highlights 📚"
+):
"""
Creates cloze flashcards for Anki from the highlights.
@@ -245,29 +290,35 @@ def create_anki_flashcards(parsed_data, output_apkg_path, deck_name="Books Highl
None
"""
# Download NLTK punkt tokenizer models if you haven't already
- nltk.download('punkt_tab')
- nltk.download('punkt')
+ nltk.download("punkt_tab")
+ nltk.download("punkt")
- book_title = parsed_data['title'].replace(' ', '_')
- author_name = parsed_data['authors'].replace(' ', '_')
+ book_title = parsed_data["title"].replace(" ", "_")
+ author_name = parsed_data["authors"].replace(" ", "_")
# Set deck name in format 'Books Highlights::[book_title]-[author_name]'
- deck_full_name = f"{deck_name}::{book_title.replace('_', ' ')}-{author_name.replace('_', ' ')}"
+ deck_full_name = (
+ f"{deck_name}::{book_title.replace('_', ' ')}-{author_name.replace('_', ' ')}"
+ )
# Generate deck ID using a hash of the deck_full_name
- deck_id = int(hashlib.md5(deck_full_name.encode('utf-8')).hexdigest(), 16) % (10 ** 10)
+ deck_id = int(hashlib.md5(deck_full_name.encode("utf-8")).hexdigest(), 16) % (
+ 10**10
+ )
deck = genanki.Deck(deck_id=deck_id, name=deck_full_name)
model = genanki.CLOZE_MODEL
# Generate cards for each highlight
- for highlight in parsed_data['entries']:
- highlight_text = highlight['notes']
+ for highlight in parsed_data["entries"]:
+ highlight_text = highlight["notes"]
# Use regex to split sentences by both '.' and ';'
- highlight_sentences = re.split(r'(?<=[.!?;]) +', highlight_text) # Tokenize sentences
- page_number = highlight['page']
+ highlight_sentences = re.split(
+ r"(?<=[.!?;]) +", highlight_text
+ ) # Tokenize sentences
+ page_number = highlight["page"]
chapter_info = f"Chapter: {highlight['chapter']} - Page: {page_number}"
# Keep your original formatting for title and note_text
@@ -281,11 +332,13 @@ def create_anki_flashcards(parsed_data, output_apkg_path, deck_name="Books Highl
continue
# Determine how many words to cloze (between 2 and 4)
- cloze_count = random.randint(2, min(4, len(words))) # Ensure we don't exceed the sentence length
+ cloze_count = random.randint(
+ 2, min(4, len(words))
+ ) # Ensure we don't exceed the sentence length
# Randomly select a starting index for cloze deletion
start_index = random.randint(0, len(words) - cloze_count)
- cloze_text = ' '.join(words[start_index:start_index + cloze_count])
+ cloze_text = " ".join(words[start_index : start_index + cloze_count])
# Replace the selected words with cloze syntax
cloze_sentence = sentence.replace(cloze_text, f"{{{{c1::{cloze_text}}}}}")
@@ -298,13 +351,16 @@ def create_anki_flashcards(parsed_data, output_apkg_path, deck_name="Books Highl
note = genanki.Note(
model=model,
- fields=[note_text + full_highlight_cloze, datetime_info] # Add datetime in Extra field
+ fields=[
+ note_text + full_highlight_cloze,
+ datetime_info,
+ ], # Add datetime in Extra field
)
deck.add_note(note)
# Check if output_apkg_path is a folder, and if so, append a default file name
if os.path.isdir(output_apkg_path):
- default_filename = f"{book_title}_{author_name}.apkg".replace('/', '.')
+ default_filename = f"{book_title}_{author_name}.apkg".replace("/", ".")
output_apkg_path = os.path.join(output_apkg_path, default_filename)
# Create the Anki package and save it
@@ -328,7 +384,7 @@ def parse_lua_highlights_annotations(filepath):
lua = LuaRuntime(unpack_returned_tuples=True)
# Load the Lua file content
- with open(filepath, 'r', encoding='utf-8') as file:
+ with open(filepath, "r", encoding="utf-8") as file:
lua_content = file.read()
# Wrap the Lua content in a function for execution
@@ -341,28 +397,32 @@ def parse_lua_highlights_annotations(filepath):
lua_table = lua.globals().load_data()
# Access the bookmarks and annotations
- annotations = lua_table['annotations']
+ annotations = lua_table["annotations"]
highlighted_entries = []
try:
for annotation in annotations.values():
- if annotation['text']:
- highlighted_entries.append({
- 'chapter': annotation['chapter'],
- 'datetime': annotation['datetime'],
- 'notes': annotation['text'],
- 'page': annotation['pageno'],
- })
+ if annotation["text"]:
+ highlighted_entries.append(
+ {
+ "chapter": annotation["chapter"],
+ "datetime": annotation["datetime"],
+ "notes": annotation["text"],
+ "page": annotation["pageno"],
+ }
+ )
except Exception as e:
- logger.debug(f'Error parsing Lua file with {inspect.currentframe().f_code.co_name}')
+ logger.debug(
+ f"Error parsing Lua file with {inspect.currentframe().f_code.co_name}"
+ )
return None
# Extract book metadata (authors, title, language)
metadata = {
- 'title': lua_table['stats']['title'],
- 'authors': lua_table['stats']['authors'],
- 'language': lua_table['stats']['language'],
- 'entries': highlighted_entries
+ "title": lua_table["stats"]["title"],
+ "authors": lua_table["stats"]["authors"],
+ "language": lua_table["stats"]["language"],
+ "entries": highlighted_entries,
}
# Return None if no highlighted entries found
@@ -388,22 +448,22 @@ def parse_lua_highlights_bookmarks(filepath):
lua = LuaRuntime(unpack_returned_tuples=True)
# Load the Lua file content
- with open(filepath, 'r', encoding='utf-8') as file:
+ with open(filepath, "r", encoding="utf-8") as file:
lua_content = file.read()
# Evaluate the Lua content
lua_table = lua.execute(lua_content)
- bookmarks = lua_table['bookmarks']
+ bookmarks = lua_table["bookmarks"]
highlighted_entries = []
try:
for bookmark in bookmarks.values():
- if bookmark['highlighted']:
- page = bookmark['page']
+ if bookmark["highlighted"]:
+ page = bookmark["page"]
# Regular expression to match the number after "DocFragment"
- match = re.search(r'DocFragment\[(\d+)\]', page)
+ match = re.search(r"DocFragment\[(\d+)\]", page)
# If a match is found, extract the number
if match:
@@ -411,22 +471,26 @@ def parse_lua_highlights_bookmarks(filepath):
else:
page = None
- highlighted_entries.append({
- 'chapter': bookmark['chapter'],
- 'datetime': bookmark['datetime'],
- 'notes': bookmark['notes'],
- 'page': page,
- })
+ highlighted_entries.append(
+ {
+ "chapter": bookmark["chapter"],
+ "datetime": bookmark["datetime"],
+ "notes": bookmark["notes"],
+ "page": page,
+ }
+ )
except Exception as e:
- logger.debug(f'Error parsing Lua file with {inspect.currentframe().f_code.co_name}')
+ logger.debug(
+ f"Error parsing Lua file with {inspect.currentframe().f_code.co_name}"
+ )
return None
# Extract book metadata (authors, title, language)
metadata = {
- 'title': lua_table['stats']['title'],
- 'authors': lua_table['stats']['authors'],
- 'language': lua_table['stats']['language'],
- 'entries': highlighted_entries
+ "title": lua_table["stats"]["title"],
+ "authors": lua_table["stats"]["authors"],
+ "language": lua_table["stats"]["language"],
+ "entries": highlighted_entries,
}
# Return None if no highlighted entries found
@@ -437,53 +501,53 @@ def parse_lua_highlights_bookmarks(filepath):
# def parse_lua_highlights(filepath):
- # """
- # Parses a Lua file to extract highlighted bookmarks and book metadata.
-
- # Args:
- # filepath (str): Path to the Lua file.
-
- # Returns:
- # dict: Dictionary containing the highlighted bookmarks, book title, and author.
- # Returns None if no highlights are found.
- # """
- # # Create a Lua runtime environment
- # lua = LuaRuntime(unpack_returned_tuples=True)
-
- # # Load the Lua file content
- # with open(filepath, 'r', encoding='utf-8') as file:
- # lua_content = file.read()
-
- # # Evaluate the Lua content
- # lua_table = lua.execute(lua_content)
-
- # # Extract 'bookmarks' and filter for highlighted entries
- # bookmarks = lua_table['bookmarks']
- # highlighted_bookmarks = []
- # if bookmarks is None:
- # return None
-
- # for bookmark in bookmarks.values():
- # if bookmark['highlighted']:
- # highlighted_bookmarks.append({
- # 'chapter': bookmark['chapter'],
- # 'datetime': bookmark['datetime'],
- # 'notes': bookmark['notes'],
- # })
-
- # # Extract book metadata (authors, title)
- # metadata = {
- # 'title': lua_table['stats']['title'],
- # 'authors': lua_table['stats']['authors'],
- # 'language': lua_table['stats']['language'],
- # 'bookmarks': highlighted_bookmarks
- # }
-
- # # Return None if no highlighted bookmarks found
- # if not highlighted_bookmarks:
- # return None
-
- # return metadata
+# """
+# Parses a Lua file to extract highlighted bookmarks and book metadata.
+
+# Args:
+# filepath (str): Path to the Lua file.
+
+# Returns:
+# dict: Dictionary containing the highlighted bookmarks, book title, and author.
+# Returns None if no highlights are found.
+# """
+# # Create a Lua runtime environment
+# lua = LuaRuntime(unpack_returned_tuples=True)
+
+# # Load the Lua file content
+# with open(filepath, 'r', encoding='utf-8') as file:
+# lua_content = file.read()
+
+# # Evaluate the Lua content
+# lua_table = lua.execute(lua_content)
+
+# # Extract 'bookmarks' and filter for highlighted entries
+# bookmarks = lua_table['bookmarks']
+# highlighted_bookmarks = []
+# if bookmarks is None:
+# return None
+
+# for bookmark in bookmarks.values():
+# if bookmark['highlighted']:
+# highlighted_bookmarks.append({
+# 'chapter': bookmark['chapter'],
+# 'datetime': bookmark['datetime'],
+# 'notes': bookmark['notes'],
+# })
+
+# # Extract book metadata (authors, title)
+# metadata = {
+# 'title': lua_table['stats']['title'],
+# 'authors': lua_table['stats']['authors'],
+# 'language': lua_table['stats']['language'],
+# 'bookmarks': highlighted_bookmarks
+# }
+
+# # Return None if no highlighted bookmarks found
+# if not highlighted_bookmarks:
+# return None
+
+# return metadata
def main():
@@ -496,13 +560,38 @@ def main():
Returns:
None
"""
- parser = argparse.ArgumentParser(description="Create Anki flashcards from Koreader highlights.")
- parser.add_argument("--input-folder", "-i", required=True, help="Path to the folder containing metadata.epub.lua files in KOReader.")
- parser.add_argument("--output-folder", "-o", required=True, help="Path to the folder where .apkg files will be saved.")
- parser.add_argument("--deck-name", "-n", default="Books Highlights 📚" ,required=False, help="Name of the Anki deck (e.g., 'deck::subdeck') (Default to Books Highlights 📚 .")
- parser.add_argument("--no-ai", action="store_true",
- help="Decide if we don't use AI to find which part of the sentence to 'cloze'.")
- parser.add_argument("--select-files", action="store_true", help="If set, allows you to select files interactively for processing.")
+ parser = argparse.ArgumentParser(
+ description="Create Anki flashcards from Koreader highlights."
+ )
+ parser.add_argument(
+ "--input-folder",
+ "-i",
+ required=True,
+ help="Path to the folder containing metadata.epub.lua files in KOReader.",
+ )
+ parser.add_argument(
+ "--output-folder",
+ "-o",
+ required=True,
+ help="Path to the folder where .apkg files will be saved.",
+ )
+ parser.add_argument(
+ "--deck-name",
+ "-n",
+ default="Books Highlights 📚",
+ required=False,
+ help="Name of the Anki deck (e.g., 'deck::subdeck') (Default to Books Highlights 📚 .",
+ )
+ parser.add_argument(
+ "--no-ai",
+ action="store_true",
+ help="Decide if we don't use AI to find which part of the sentence to 'cloze'.",
+ )
+ parser.add_argument(
+ "--select-files",
+ action="store_true",
+ help="If set, allows you to select files interactively for processing.",
+ )
args = parser.parse_args()
# Check if the output folder exists, create it if it doesn't
@@ -516,7 +605,7 @@ def main():
lua_files = []
for root, _, files in os.walk(args.input_folder):
for file in files:
- if fnmatch.fnmatch(file, 'metadata.*.lua'):
+ if fnmatch.fnmatch(file, "metadata.*.lua"):
file_path = os.path.join(root, file)
lua_files.append(file_path)
@@ -528,13 +617,13 @@ def main():
if args.select_files:
questions = [
inquirer.Checkbox(
- 'selected_files',
+ "selected_files",
message="Select the files to process (use space to select, arrows to navigate):",
- choices=lua_files
+ choices=lua_files,
)
]
answers = inquirer.prompt(questions)
- selected_files = answers.get('selected_files', [])
+ selected_files = answers.get("selected_files", [])
else:
selected_files = lua_files
@@ -544,21 +633,28 @@ def main():
try:
clipped_highlights = parse_lua_highlights_bookmarks(file_path)
if clipped_highlights is None:
- logger.debug(f"Error parsing Bookmarks from Lua file, try using Annotations instead: {file_path}")
+ logger.debug(
+ f"Error parsing Bookmarks from Lua file, try using Annotations instead: {file_path}"
+ )
clipped_highlights = parse_lua_highlights_annotations(file_path)
if clipped_highlights:
# Create Anki flashcards
if args.no_ai is True:
- create_anki_flashcards(clipped_highlights, args.output_folder, deck_name=args.deck_name)
+ create_anki_flashcards(
+ clipped_highlights, args.output_folder, deck_name=args.deck_name
+ )
else:
- create_anki_flashcards_ai(clipped_highlights, args.output_folder,
- deck_name=args.deck_name)
+ create_anki_flashcards_ai(
+ clipped_highlights, args.output_folder, deck_name=args.deck_name
+ )
else:
logger.warning(f"No highlights found for {file_path}")
except Exception as e:
- logger.error(f"An error occurred while processing the highlights from {file_path}: {e}\n {traceback.print_exc()}")
+ logger.error(
+ f"An error occurred while processing the highlights from {file_path}: {e}\n {traceback.print_exc()}"
+ )
if __name__ == "__main__":
diff --git a/poetry.lock b/poetry.lock
index d10cabf..c2833a3 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -49,6 +49,52 @@ jinxed = {version = ">=1.1.0", markers = "platform_system == \"Windows\""}
six = ">=1.9.0"
wcwidth = ">=0.1.4"
+[[package]]
+name = "build"
+version = "1.2.2.post1"
+description = "A simple, correct Python build frontend"
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "build-1.2.2.post1-py3-none-any.whl", hash = "sha256:1d61c0887fa860c01971625baae8bdd338e517b836a2f70dd1f7aa3a6b2fc5b5"},
+ {file = "build-1.2.2.post1.tar.gz", hash = "sha256:b36993e92ca9375a219c99e606a122ff365a760a2d4bba0caa09bd5278b608b7"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "os_name == \"nt\""}
+importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
+packaging = ">=19.1"
+pyproject_hooks = "*"
+tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
+test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
+typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+uv = ["uv (>=0.1.18)"]
+virtualenv = ["virtualenv (>=20.0.35)"]
+
+[[package]]
+name = "cachecontrol"
+version = "0.14.0"
+description = "httplib2 caching for requests"
+optional = false
+python-versions = ">=3.7"
+files = [
+ {file = "cachecontrol-0.14.0-py3-none-any.whl", hash = "sha256:f5bf3f0620c38db2e5122c0726bdebb0d16869de966ea6a2befe92470b740ea0"},
+ {file = "cachecontrol-0.14.0.tar.gz", hash = "sha256:7db1195b41c81f8274a7bbd97c956f44e8348265a1bc7641c37dfebc39f0c938"},
+]
+
+[package.dependencies]
+filelock = {version = ">=3.8.0", optional = true, markers = "extra == \"filecache\""}
+msgpack = ">=0.5.2,<2.0.0"
+requests = ">=2.16.0"
+
+[package.extras]
+dev = ["CacheControl[filecache,redis]", "black", "build", "cherrypy", "furo", "mypy", "pytest", "pytest-cov", "sphinx", "sphinx-copybutton", "tox", "types-redis", "types-requests"]
+filecache = ["filelock (>=3.8.0)"]
+redis = ["redis (>=2.10.5)"]
+
[[package]]
name = "cached-property"
version = "1.5.2"
@@ -71,6 +117,96 @@ files = [
{file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
]
+[[package]]
+name = "cffi"
+version = "1.17.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
+ {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
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+]
+
+[package.dependencies]
+pycparser = "*"
+
+[[package]]
+name = "cfgv"
+version = "3.4.0"
+description = "Validate configuration and produce human readable error messages."
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
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+]
+
[[package]]
name = "charset-normalizer"
version = "3.4.0"
@@ -196,6 +332,21 @@ files = [
{file = "chevron-0.14.0.tar.gz", hash = "sha256:87613aafdf6d77b6a90ff073165a61ae5086e21ad49057aa0e53681601800ebf"},
]
+[[package]]
+name = "cleo"
+version = "2.1.0"
+description = "Cleo allows you to create beautiful and testable command-line interfaces."
+optional = false
+python-versions = ">=3.7,<4.0"
+files = [
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+]
+
+[package.dependencies]
+crashtest = ">=0.4.1,<0.5.0"
+rapidfuzz = ">=3.0.0,<4.0.0"
+
[[package]]
name = "click"
version = "8.1.7"
@@ -295,6 +446,66 @@ files = [
[package.extras]
toml = ["tomli"]
+[[package]]
+name = "crashtest"
+version = "0.4.1"
+description = "Manage Python errors with ease"
+optional = false
+python-versions = ">=3.7,<4.0"
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@@ -335,6 +644,20 @@ files = [
[package.extras]
test = ["pytest (>=6)"]
+[[package]]
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@@ -440,13 +763,13 @@ tqdm = ["tqdm"]
[[package]]
name = "genanki"
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description = "Generate Anki decks programmatically"
optional = false
python-versions = ">=3.6"
files = [
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typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
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version = "3.10"
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editor = ">=1.6.0"
readchar = ">=4.2.0"
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tests = ["pytest (>=4.6)"]
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twitter = ["twython"]
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testing = ["pytest", "pytest-benchmark"]
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version = "4.12.2"
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socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
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[[package]]
name = "wcwidth"
version = "0.2.13"
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+ {file = "xattr-1.1.0-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:96ca300c0acca4f0cddd2332bb860ef58e1465d376364f0e72a1823fdd58e90d"},
+ {file = "xattr-1.1.0.tar.gz", hash = "sha256:fecbf3b05043ed3487a28190dec3e4c4d879b2fcec0e30bafd8ec5d4b6043630"},
+]
+
+[package.dependencies]
+cffi = ">=1.16.0"
+
+[package.extras]
+test = ["pytest"]
+
[[package]]
name = "xmod"
version = "1.8.1"
@@ -1965,7 +2899,26 @@ files = [
{file = "xmod-1.8.1.tar.gz", hash = "sha256:38c76486b9d672c546d57d8035df0beb7f4a9b088bc3fb2de5431ae821444377"},
]
+[[package]]
+name = "zipp"
+version = "3.20.2"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
+ {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
+]
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
+
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
-content-hash = "fe13b9527501bdeb0964c18bd49dd5755ca6149821895eea20b06b62f27f16f2"
+content-hash = "423e3f86de601bfc90df025f1f4a57b60dda81fc433ced24e680c1cd94c463ff"
diff --git a/pyproject.toml b/pyproject.toml
index 4b7eb2b..6e6a96e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ readme = "README.md"
[tool.poetry.dependencies]
python = "^3.10"
-genanki = "^0.12.0"
+genanki = ">=0.13.1"
inquirer = "^3.1.1"
nltk = "^3.8.1"
torch = "^2.0.0"
@@ -28,3 +28,11 @@ pytest = "^8.2.1"
ipdb = "^0.13"
ipython = "^7.5.3"
coverage = "^7.5.3"
+pre-commit = "^3.7.1"
+poetry-pre-commit-plugin = "^0.1.2"
+
+
+
+[tool.pre_commit]
+version = "2.3.0"
+config = ".pre-commit-config.yaml"