# Module for CSV and APKG export functions
import gradio as gr
import pandas as pd
import genanki
import random
from typing import List, Dict, Any, Optional
import csv
from datetime import datetime
import os
from ankigen_core.utils import get_logger, strip_html_tags
logger = get_logger()
# --- Helper function for formatting fields ---
def _format_field_as_string(value: Any) -> str:
if isinstance(value, list) or isinstance(value, tuple):
return ", ".join(str(item).strip() for item in value if str(item).strip())
if pd.isna(value) or value is None:
return ""
return str(value).strip()
# --- Constants for APKG Generation (Subtask 10) ---
ANKI_BASIC_MODEL_NAME = "AnkiGen Basic"
ANKI_CLOZE_MODEL_NAME = "AnkiGen Cloze"
# It's good practice to generate unique IDs. These are examples.
# Real applications might use a persistent way to store/retrieve these if models are updated.
DEFAULT_BASIC_MODEL_ID = random.randrange(1 << 30, 1 << 31)
DEFAULT_CLOZE_MODEL_ID = random.randrange(1 << 30, 1 << 31)
# --- Full Model Definitions with CSS (Restored) ---
BASIC_MODEL = genanki.Model(
DEFAULT_BASIC_MODEL_ID, # Use the generated ID
ANKI_BASIC_MODEL_NAME, # Use the constant name
fields=[
{"name": "Question"},
{"name": "Answer"},
{"name": "Explanation"},
{"name": "Example"},
{"name": "Prerequisites"},
{"name": "Learning_Outcomes"},
{"name": "Common_Misconceptions"},
{"name": "Difficulty"},
{"name": "SourceURL"}, # Added for consistency if used by template
{"name": "TagsStr"}, # Added for consistency if used by template
],
templates=[
{
"name": "Card 1",
"qfmt": """
""",
}
],
css="""
/* Base styles */
.card {
font-family: 'Inter', system-ui, -apple-system, sans-serif;
font-size: 16px;
line-height: 1.6;
color: #1a1a1a;
max-width: 800px;
margin: 0 auto;
padding: 20px;
background: #ffffff;
}
@media (max-width: 768px) {
.card {
font-size: 14px;
padding: 15px;
}
}
/* Question side */
.question-side {
position: relative;
min-height: 200px;
}
.difficulty-indicator {
position: absolute;
top: 10px;
right: 10px;
width: 10px;
height: 10px;
border-radius: 50%;
}
.difficulty-indicator.beginner { background: #4ade80; }
.difficulty-indicator.intermediate { background: #fbbf24; }
.difficulty-indicator.advanced { background: #ef4444; }
.question {
font-size: 1.3em;
font-weight: 600;
color: #2563eb;
margin-bottom: 1.5em;
}
.prerequisites {
margin-top: 1em;
font-size: 0.9em;
color: #666;
}
.prerequisites-toggle {
color: #2563eb;
cursor: pointer;
text-decoration: underline;
}
.prerequisites-content {
display: none;
margin-top: 0.5em;
padding: 0.5em;
background: #f8fafc;
border-radius: 4px;
}
.prerequisites.show .prerequisites-content {
display: block;
}
/* Answer side */
.answer-section,
.explanation-section,
.example-section {
margin: 1.5em 0;
padding: 1.2em;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.05);
}
.answer-section { /* Shared with question for cloze, but can be general */
background: #f0f9ff;
border-left: 4px solid #2563eb;
}
.back-extra-section {
background: #eef2ff; /* A slightly different shade for additional info */
border-left: 4px solid #818cf8; /* Indigo variant */
margin: 1.5em 0;
padding: 1.2em;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.05);
}
.explanation-section {
background: #f0fdf4;
border-left: 4px solid #4ade80;
}
.example-section {
background: #fefce8; /* Light yellow */
border-left: 4px solid #facc15; /* Yellow */
}
.example-section pre {
background-color: #2d2d2d; /* Darker background for code blocks */
color: #f8f8f2; /* Light text for contrast */
padding: 1em;
border-radius: 0.3em;
overflow-x: auto; /* Horizontal scroll for long lines */
font-family: 'Consolas', 'Monaco', 'Menlo', monospace;
font-size: 0.9em;
line-height: 1.4;
}
.example-section code {
font-family: 'Consolas', 'Monaco', 'Menlo', monospace;
}
.metadata-section {
margin-top: 2em;
padding-top: 1em;
border-top: 1px solid #e5e7eb; /* Light gray border */
font-size: 0.9em;
color: #4b5563; /* Cool gray */
}
.metadata-section h3 {
font-size: 1em;
color: #1f2937; /* Darker gray for headings */
margin-bottom: 0.5em;
}
.metadata-section > div {
margin-bottom: 0.8em;
}
.source-url a {
color: #2563eb;
text-decoration: none;
}
.source-url a:hover {
text-decoration: underline;
}
/* Styles for cloze deletion cards */
.cloze {
font-weight: bold;
color: blue;
}
.nightMode .cloze {
color: lightblue;
}
/* General utility */
hr {
border: none;
border-top: 1px dashed #cbd5e1; /* Light dashed line */
margin: 1.5em 0;
}
/* Rich text field styling (if Anki adds classes for these) */
.field ul, .field ol {
margin-left: 1.5em;
padding-left: 0.5em;
}
.field li {
margin-bottom: 0.3em;
}
""",
# model_type=genanki.Model.CLOZE, # This was still incorrect
model_type=1, # Corrected to use integer 1 for Cloze
)
# --- Helper functions for APKG (Subtask 10) ---
def _get_or_create_model(
model_id: int,
name: str,
fields: List[Dict[str, str]],
templates: List[Dict[str, str]],
) -> genanki.Model:
return genanki.Model(model_id, name, fields=fields, templates=templates)
# --- New CSV Exporter for List of Dictionaries ---
def export_cards_to_csv(
cards: List[Dict[str, Any]], filename: Optional[str] = None
) -> str:
"""Export a list of card dictionaries to a CSV file.
Args:
cards: A list of dictionaries, where each dictionary represents a card
and should contain 'front' and 'back' keys. Other keys like
'tags' and 'note_type' are optional.
filename: Optional. The desired filename/path for the CSV.
If None, a timestamped filename will be generated.
Returns:
The path to the generated CSV file.
Raises:
IOError: If there is an issue writing to the file.
KeyError: If a card dictionary is missing essential keys like 'front' or 'back'.
ValueError: If the cards list is empty or not provided.
"""
if not cards:
logger.warning("export_cards_to_csv called with an empty list of cards.")
raise ValueError("No cards provided to export.")
if not filename:
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
# Ensure filename is just the name, not a path if not intended
# For simplicity, this example saves in the current working directory if no path is specified.
filename = f"ankigen_cards_{timestamp}.csv"
logger.info(f"No filename provided, generated: {filename}")
# Define the fieldnames expected in the CSV.
# 'front' and 'back' are mandatory.
fieldnames = ["front", "back", "tags", "note_type"]
try:
logger.info(f"Attempting to export {len(cards)} cards to {filename}")
with open(filename, "w", newline="", encoding="utf-8") as csvfile:
writer = csv.DictWriter(
csvfile, fieldnames=fieldnames, extrasaction="ignore"
)
writer.writeheader()
for i, card in enumerate(cards):
try:
# Ensure mandatory fields exist, others are optional via card.get in row_to_write
if "front" not in card or "back" not in card:
raise KeyError(
f"Card at index {i} is missing 'front' or 'back' key."
)
row_to_write = {
"front": card["front"],
"back": card["back"],
"tags": card.get("tags", ""),
"note_type": card.get("note_type", "Basic"),
}
writer.writerow(row_to_write)
except KeyError as e_inner:
logger.error(
f"Skipping card due to KeyError: {e_inner}. Card data: {card}"
)
# Optionally re-raise if one bad card should stop the whole export,
# or continue to export valid cards.
# For this implementation, we log and continue.
continue
logger.info(f"Successfully exported cards to {filename}")
return filename
except IOError as e_io:
logger.error(f"IOError during CSV export to {filename}: {e_io}", exc_info=True)
raise # Re-raise the IOError
except Exception as e_general: # Catch any other unexpected errors
logger.error(
f"Unexpected error during CSV export to {filename}: {e_general}",
exc_info=True,
)
raise
def export_cards_to_apkg(
cards: List[Dict[str, Any]],
filename: Optional[str] = None,
deck_name: str = "Ankigen Generated Cards",
) -> str:
"""Exports a list of card dictionaries to an Anki .apkg file.
Args:
cards: List of dictionaries, where each dictionary represents a card.
It's expected that these dicts are prepared by export_dataframe_to_apkg
and contain keys like 'Question', 'Answer', 'Explanation', etc.
filename: The full path (including filename) for the exported file.
If None, a default filename will be generated in the current directory.
deck_name: The name of the deck if exporting to .apkg format.
Returns:
The path to the exported file.
"""
logger.info(f"Starting APKG export for {len(cards)} cards to deck '{deck_name}'.")
if not filename:
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"ankigen_deck_{timestamp}.apkg"
elif not filename.lower().endswith(".apkg"):
filename += ".apkg"
output_dir = os.path.dirname(filename)
if output_dir and not os.path.exists(output_dir):
os.makedirs(output_dir)
logger.info(f"Created output directory for APKG: {output_dir}")
anki_basic_model = BASIC_MODEL
anki_cloze_model = CLOZE_MODEL
deck_id = random.randrange(1 << 30, 1 << 31)
anki_deck = genanki.Deck(deck_id, deck_name)
notes_added_count = 0
for card_dict in cards:
note_type = card_dict.get("note_type", "Basic")
tags_for_note_object = card_dict.get("tags_for_note_object", [])
# Extract all potential fields, defaulting to empty strings
question = card_dict.get("Question", "")
answer = card_dict.get("Answer", "")
explanation = card_dict.get("Explanation", "")
example = card_dict.get("Example", "")
prerequisites = card_dict.get("Prerequisites", "")
learning_outcomes = card_dict.get("Learning_Outcomes", "")
common_misconceptions = card_dict.get("Common_Misconceptions", "")
difficulty = card_dict.get("Difficulty", "")
source_url = card_dict.get("SourceURL", "")
tags_str_field = card_dict.get(
"TagsStr", ""
) # This is the string for the model's TagsStr field
# The 'Question' field from card_dict is used as the main text for both basic and cloze.
# For cloze, this 'Question' field should contain the cloze-formatted text (e.g., "The capital of {{c1::France}} is Paris.")
if not question:
logger.error(
f"SKIPPING CARD DUE TO EMPTY 'Question' (front/text) field. Card data: {card_dict}"
)
continue
try:
if note_type.lower() == "cloze":
# CLOZE_MODEL fields: Text, Back Extra, Explanation, Example, Prerequisites,
# Learning_Outcomes, Common_Misconceptions, Difficulty, SourceURL, TagsStr
note_fields = [
question, # Text (this is the card_dict['Question'] which should be cloze-formatted)
answer, # Back Extra (this is card_dict['Answer'])
explanation,
example,
prerequisites,
learning_outcomes,
common_misconceptions,
difficulty,
source_url,
tags_str_field,
]
note = genanki.Note(
model=anki_cloze_model,
fields=note_fields,
tags=tags_for_note_object,
)
else: # Basic
# BASIC_MODEL fields: Question, Answer, Explanation, Example, Prerequisites,
# Learning_Outcomes, Common_Misconceptions, Difficulty, SourceURL, TagsStr
note_fields = [
question,
answer,
explanation,
example,
prerequisites,
learning_outcomes,
common_misconceptions,
difficulty,
source_url,
tags_str_field,
]
note = genanki.Note(
model=anki_basic_model,
fields=note_fields,
tags=tags_for_note_object,
)
anki_deck.add_note(note)
notes_added_count += 1
except Exception as e:
logger.error(
f"Failed to create genanki.Note for card: {card_dict}. Error: {e}",
exc_info=True,
)
logger.warning(f"Skipping card due to error: Question='{question[:50]}...'")
if notes_added_count == 0 and cards: # Some cards were provided but none were added
logger.error( # Changed to error for more visibility
"No valid notes could be created from the provided cards. APKG generation aborted."
)
# This error should be caught by the calling function in app.py to inform the user
raise gr.Error("Failed to create any valid Anki notes from the input.")
elif not cards: # No cards provided initially
logger.info("No cards provided to export to APKG. APKG generation skipped.")
# Depending on desired behavior, could raise or return a specific status/filename
# For now, let's assume an empty/default filename or None indicates no action if no cards
# However, the function is typed to return str, so raising is more consistent if no file is made.
raise gr.Error("No cards were provided to generate an APKG file.")
else: # notes_added_count > 0
logger.info(
f"Added {notes_added_count} notes to deck '{deck_name}'. Proceeding to package."
)
# Only proceed to package and write if notes were successfully added
package = genanki.Package(anki_deck)
try:
package.write_to_file(filename)
logger.info(f"Successfully exported Anki deck to {filename}")
except Exception as e:
logger.error(f"Failed to write .apkg file to {filename}: {e}", exc_info=True)
raise IOError(f"Could not write .apkg file: {e}")
return filename
def export_cards_from_crawled_content(
cards: List[Dict[str, Any]],
output_path: Optional[
str
] = None, # Changed from filename to output_path for clarity
export_format: str = "csv", # Added export_format parameter
deck_name: str = "Ankigen Generated Cards",
) -> str:
"""Exports cards (list of dicts) to the specified format (CSV or APKG).
Args:
cards: List of dictionaries, where each dictionary represents a card.
Expected keys: 'front', 'back'. Optional: 'tags' (space-separated string), 'source_url', 'note_type' ('Basic' or 'Cloze').
output_path: The full path (including filename) for the exported file.
If None, a default filename will be generated in the current directory.
export_format: The desired format, either 'csv' or 'apkg'.
deck_name: The name of the deck if exporting to .apkg format.
Returns:
The path to the exported file.
"""
if not cards:
logger.warning("No cards provided to export_cards_from_crawled_content.")
# MODIFIED: Raise error immediately if no cards, as per test expectation
raise ValueError("No cards provided to export.")
logger.info(
f"Exporting {len(cards)} cards to format '{export_format}' with deck name '{deck_name}'."
)
if export_format.lower() == "csv":
return export_cards_to_csv(cards, filename=output_path)
elif export_format.lower() == "apkg":
return export_cards_to_apkg(cards, filename=output_path, deck_name=deck_name)
else:
supported_formats = ["csv", "apkg"]
logger.error(
f"Unsupported export format: {export_format}. Supported formats: {supported_formats}"
)
# MODIFIED: Updated error message to include supported formats
raise ValueError(
f"Unsupported export format: {export_format}. Supported formats: {supported_formats}"
)
# --- New DataFrame CSV Exporter (Subtask 11) ---
def export_dataframe_to_csv(
data: Optional[pd.DataFrame],
filename_suggestion: Optional[str] = "ankigen_cards.csv",
) -> Optional[str]:
"""Exports a Pandas DataFrame to a CSV file, designed for Gradio download.
Args:
data: The Pandas DataFrame to export.
filename_suggestion: A suggestion for the base filename (e.g., from subject).
Returns:
The path to the temporary CSV file, or None if an error occurs or data is empty.
"""
logger.info(
f"Attempting to export DataFrame to CSV. Suggested filename: {filename_suggestion}"
)
if data is None or data.empty:
logger.warning(
"No data provided to export_dataframe_to_csv. Skipping CSV export."
)
raise gr.Error(
"No card data available"
) # Notify user via Gradio with Error instead of Info
# return None # This line is now unreachable due to the raise
try:
# Create a specific filename using both suggestion and timestamp
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
base_name_from_suggestion = "ankigen_cards" # Default base part
# Sanitize and use the suggestion (e.g., subject name) if provided
if filename_suggestion and isinstance(filename_suggestion, str):
# Remove .csv if present, then sanitize
processed_suggestion = filename_suggestion.removesuffix(".csv")
safe_suggestion = (
processed_suggestion.replace(" ", "_")
.replace("/", "-")
.replace("\\\\", "-")
)
if (
safe_suggestion
): # If suggestion wasn't just '.csv' or empty after processing
base_name_from_suggestion = f"ankigen_{safe_suggestion[:50]}"
# If suggestion was empty or only '.csv', default base_name_from_suggestion remains 'ankigen_cards'
final_filename = f"{base_name_from_suggestion}_{timestamp}.csv"
# Ensure output directory exists if filename contains path
output_dir = os.path.dirname(final_filename)
if output_dir and not os.path.exists(output_dir):
os.makedirs(output_dir)
logger.info(f"Created output directory for CSV: {output_dir}")
data.to_csv(final_filename, index=False) # MODIFIED: Write to final_filename
logger.info(f"Successfully exported DataFrame to CSV: {final_filename}")
gr.Info(
f"CSV ready for download: {os.path.basename(final_filename)}"
) # User-friendly message
return final_filename # MODIFIED: Return final_filename
except Exception as e:
logger.error(f"Error exporting DataFrame to CSV: {e}", exc_info=True)
gr.Error(f"Error exporting DataFrame to CSV: {e}")
return None
# --- New DataFrame to APKG Exporter (for Main Generator Tab) ---
def export_dataframe_to_apkg(
df: pd.DataFrame,
output_path: Optional[str],
deck_name: str,
) -> str:
"""Exports a DataFrame of cards to an Anki .apkg file."""
if df.empty:
logger.warning("export_dataframe_to_apkg called with an empty DataFrame.")
raise ValueError("No cards in DataFrame to export.")
logger.info(
f"Starting APKG export for DataFrame with {len(df)} rows to deck '{deck_name}'. Output: {output_path}"
)
cards_for_apkg: List[Dict[str, Any]] = []
for _, row in df.iterrows():
try:
note_type_val = (
_format_field_as_string(row.get("Card_Type", "Basic")) or "Basic"
)
topic = _format_field_as_string(row.get("Topic", ""))
difficulty_raw = _format_field_as_string(row.get("Difficulty", ""))
difficulty_plain_for_tag = strip_html_tags(
difficulty_raw
) # Strip HTML for the tag
tags_list_for_note_obj = [] # For genanki.Note(tags=...)
if topic:
tags_list_for_note_obj.append(topic.replace(" ", "_").replace(",", "_"))
if difficulty_plain_for_tag: # Use the plain text version for the tag
# Further sanitize for Anki tags: replace spaces with underscores, remove other invalid chars if any.
# Anki tags also often don't like colons or other special chars except underscore/hyphen.
# For now, just replacing space, as that's the error seen.
safe_difficulty_tag = difficulty_plain_for_tag.replace(" ", "_")
tags_list_for_note_obj.append(safe_difficulty_tag)
tags_str_for_field = " ".join(
tags_list_for_note_obj
) # For the 'TagsStr' model field
# Prepare a dictionary that contains all possible fields our models might need.
card_data_for_note = {
"note_type": note_type_val,
"tags_for_note_object": tags_list_for_note_obj,
"TagsStr": tags_str_for_field,
"Question": _format_field_as_string(row.get("Question", "")),
"Answer": _format_field_as_string(row.get("Answer", "")),
"Explanation": _format_field_as_string(row.get("Explanation", "")),
"Example": _format_field_as_string(row.get("Example", "")),
"Prerequisites": _format_field_as_string(row.get("Prerequisites", "")),
"Learning_Outcomes": _format_field_as_string(
row.get("Learning_Outcomes", "")
),
"Common_Misconceptions": _format_field_as_string(
row.get("Common_Misconceptions", "")
),
"Difficulty": difficulty_raw, # Keep the original HTML for the 'Difficulty' field itself
"SourceURL": _format_field_as_string(row.get("Source_URL", "")),
}
cards_for_apkg.append(card_data_for_note)
except Exception as e:
logger.error(
f"Error processing DataFrame row for APKG: {row}. Error: {e}",
exc_info=True,
)
continue
if not cards_for_apkg:
logger.error("No cards could be processed from DataFrame for APKG export.")
raise ValueError("No processable cards found in DataFrame for APKG export.")
return export_cards_to_apkg(
cards_for_apkg, filename=output_path, deck_name=deck_name
)
# --- Compatibility Exports for Tests and Legacy Code ---
# These aliases ensure that tests expecting these names will find them.
# Export functions under expected names
export_csv = (
export_dataframe_to_csv # Update this to export_dataframe_to_csv for compatibility
)
# MODIFIED: export_deck is now a wrapper to provide a default deck_name
def export_deck(
df: pd.DataFrame,
output_path: Optional[str] = None,
deck_name: str = "Ankigen Generated Cards",
) -> str:
"""Alias for exporting a DataFrame to APKG, providing a default deck name."""
if df is None or df.empty:
logger.warning("export_deck called with None or empty DataFrame.")
# Match the error type and message expected by tests
raise gr.Error("No card data available")
# Original logic to call export_dataframe_to_apkg
# Ensure all necessary parameters for export_dataframe_to_apkg are correctly passed.
# The export_dataframe_to_apkg function itself will handle its specific error conditions.
# The 'output_path' for export_dataframe_to_apkg needs to be handled.
# If 'output_path' is None here, export_cards_to_apkg (called by export_dataframe_to_apkg)
# will generate a default filename.
# If output_path is not provided to export_deck, it's None.
# export_dataframe_to_apkg expects output_path: Optional[str].
# And export_cards_to_apkg (which it calls) also handles Optional[str] filename.
# So, passing output_path directly should be fine.
return export_dataframe_to_apkg(df, output_path=output_path, deck_name=deck_name)
export_dataframe_csv = export_dataframe_to_csv
export_dataframe_apkg = export_dataframe_to_apkg
__all__ = [
"BASIC_MODEL",
"CLOZE_MODEL",
"export_csv",
"export_deck",
"export_dataframe_csv",
"export_dataframe_apkg",
"export_cards_to_csv",
"export_cards_to_apkg",
"export_cards_from_crawled_content",
"export_dataframe_to_csv",
"export_dataframe_to_apkg",
]