gematria_date_sums / app.py.bak
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Rename app.py to app.py.bak
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import gradio as gr
import json
import re
import sqlite3
import logging
from collections import defaultdict
from typing import Tuple, Dict, List
# Assuming you have these files in your project
from util import process_json_files
from gematria import calculate_gematria
from deep_translator import GoogleTranslator, exceptions
from urllib.parse import quote_plus
from tqdm import tqdm
# Constants
DATABASE_FILE = 'gematria.db'
MAX_PHRASE_LENGTH_LIMIT = 20
BATCH_SIZE = 10000
# Set up logging
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
# Global variables
conn: sqlite3.Connection = None
translator: GoogleTranslator = None
book_names: Dict[int, str] = {}
gematria_cache: Dict[Tuple[int, int], List[Tuple[str, str, int, int, int, str]]] = {}
translation_cache: Dict[str, str] = {}
total_word_count: int = 0 # Global counter for word position
def initialize_database() -> None:
"""Initializes the SQLite database."""
global conn
conn = sqlite3.connect(DATABASE_FILE)
cursor = conn.cursor()
cursor.execute('''
CREATE TABLE IF NOT EXISTS results (
gematria_sum INTEGER,
words TEXT,
translation TEXT,
book TEXT,
chapter INTEGER,
verse INTEGER,
phrase_length INTEGER,
word_position TEXT,
PRIMARY KEY (gematria_sum, words, book, chapter, verse, word_position)
)
''')
cursor.execute('''
CREATE INDEX IF NOT EXISTS idx_results_gematria
ON results (gematria_sum)
''')
cursor.execute('''
CREATE TABLE IF NOT EXISTS processed_books (
book TEXT PRIMARY KEY,
max_phrase_length INTEGER
)
''')
conn.commit()
def initialize_translator() -> None:
"""Initializes the Google Translator."""
global translator
translator = GoogleTranslator(source='iw', target='en')
logging.info("Translator initialized.")
def process_book(book_id: int, max_phrase_length: int, cursor):
"""Processes a single book and returns phrases to insert."""
global book_names, total_word_count
book_data = process_json_files(book_id, book_id)
phrases_to_insert = []
if book_id in book_data:
book_data = book_data[book_id]
if 'title' not in book_data or not isinstance(book_data['title'], str):
logging.warning(f"Skipping book {book_id} due to missing 'title' field.")
return phrases_to_insert
title = book_data['title']
book_names[book_id] = title
# Check if this book has already been processed for this phrase length
cursor.execute('''SELECT max_phrase_length FROM processed_books WHERE book = ?''', (title,))
result = cursor.fetchone()
if result and result[0] >= max_phrase_length:
logging.info(f"Skipping book {title}: Already processed with max_phrase_length {result[0]}")
return phrases_to_insert
if 'text' not in book_data or not isinstance(book_data['text'], list):
logging.warning(f"Skipping book {book_id} due to missing 'text' field.")
return phrases_to_insert
chapters = book_data['text']
for chapter_id, chapter in enumerate(chapters):
for verse_id, verse in enumerate(chapter):
verse_text = flatten_text(verse)
verse_text = re.sub(r'\[.*?\]', '', verse_text)
verse_text = re.sub(r"[^\u05D0-\u05EA ]+", "", verse_text)
verse_text = re.sub(r" +", " ", verse_text)
words = verse_text.split()
for length in range(1, max_phrase_length + 1):
for start in range(len(words) - length + 1):
phrase_candidate = " ".join(words[start:start + length])
gematria_sum = calculate_gematria(phrase_candidate.replace(" ", ""))
word_position_range = f"{total_word_count + start + 1}-{total_word_count + start + length}"
phrases_to_insert.append(
(gematria_sum, phrase_candidate, None, title, chapter_id + 1, verse_id + 1, length,
word_position_range))
total_word_count += len(words)
return phrases_to_insert
def populate_database(start_book: int, end_book: int, max_phrase_length: int = 1) -> None:
"""Populates the database with phrases from the Tanach."""
global conn, book_names, total_word_count
logging.info(f"Populating database with books from {start_book} to {end_book}...")
with sqlite3.connect(DATABASE_FILE) as conn:
cursor = conn.cursor()
for book_id in tqdm(range(start_book, end_book + 1), desc="Processing Books"):
phrases_to_insert = process_book(book_id, max_phrase_length, cursor)
if phrases_to_insert:
cursor.executemany('''
INSERT OR IGNORE INTO results (gematria_sum, words, translation, book, chapter, verse, phrase_length, word_position)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
''', phrases_to_insert)
# Update processed_books after processing each book
cursor.execute('''
INSERT OR REPLACE INTO processed_books (book, max_phrase_length)
VALUES (?, ?)
''', (book_names[book_id], max_phrase_length))
conn.commit()
total_word_count = 0 # Reset for the next set of phrase lengths
def get_translation(phrase: str) -> str:
"""Retrieves or generates the English translation of a Hebrew phrase
and caches it in the database.
"""
global conn, translator, translation_cache
# Check if the translation exists in the database
with sqlite3.connect(DATABASE_FILE) as conn:
cursor = conn.cursor()
cursor.execute("SELECT translation FROM results WHERE words = ? LIMIT 1", (phrase,))
result = cursor.fetchone()
if result and result[0]: # If a translation exists, use it
return result[0]
# If no translation in the database, translate and store it
translation = translate_and_store(phrase)
translation_cache[phrase] = translation
# Update the database with the new translation
with sqlite3.connect(DATABASE_FILE) as conn:
cursor = conn.cursor()
cursor.execute("UPDATE results SET translation = ? WHERE words = ?", (translation, phrase))
conn.commit()
return translation
def translate_and_store(phrase: str) -> str:
"""Translates a Hebrew phrase to English using Google Translate."""
global translator
max_retries = 3
retries = 0
while retries < max_retries:
try:
translation = translator.translate(phrase)
return translation
except (exceptions.TranslationNotFound, exceptions.NotValidPayload,
exceptions.ServerException, exceptions.RequestError) as e:
retries += 1
logging.warning(f"Error translating phrase '{phrase}': {e}. Retrying... ({retries}/{max_retries})")
logging.error(f"Failed to translate phrase '{phrase}' after {max_retries} retries.")
return "[Translation Error]"
def search_gematria_in_db(gematria_sum: int, max_words: int) -> List[Tuple[str, str, int, int, int, str]]:
"""Searches the database for phrases with a given Gematria value."""
global conn
with sqlite3.connect(DATABASE_FILE) as conn:
cursor = conn.cursor()
cursor.execute('''
SELECT words, book, chapter, verse, phrase_length, word_position
FROM results
WHERE gematria_sum = ? AND phrase_length <= ?
''', (gematria_sum, max_words))
results = cursor.fetchall()
return results
def gematria_search_interface(phrases: str, max_words: int, show_translation: bool) -> str:
"""The main function for the Gradio interface, handling multiple phrases."""
global conn, book_names, gematria_cache
results = []
all_results = [] # Store results for each phrase
middle_words_results = [] # Store middle word results for all books
all_names_average_position = 0 # Initialize variable for average position across all names and books
total_name_count = 0 # Initialize counter for the total number of names processed
phrases = phrases.strip().splitlines()
if not phrases:
return "Please enter at least one phrase."
for phrase in phrases:
if not phrase.strip():
continue # Skip empty lines
numbers = re.findall(r'\d+', phrase)
text_without_numbers = re.sub(r'\d+', '', phrase)
phrase_gematria = calculate_gematria(text_without_numbers.replace(" ", ""))
phrase_gematria += sum(int(number) for number in numbers)
if (phrase_gematria, max_words) in gematria_cache:
matching_phrases = gematria_cache[(phrase_gematria, max_words)]
else:
matching_phrases = search_gematria_in_db(phrase_gematria, max_words)
gematria_cache[(phrase_gematria, max_words)] = matching_phrases
if not matching_phrases:
results.append(f"No matching phrases found for: {phrase}")
continue
sorted_phrases = sorted(matching_phrases,
key=lambda x: (int(list(book_names.keys())[list(book_names.values()).index(x[1])]), x[2],
x[3]))
results_by_book = defaultdict(list)
for words, book, chapter, verse, phrase_length, word_position in sorted_phrases:
results_by_book[book].append((words, chapter, verse, phrase_length, word_position))
results.append(f"<h2>Results for: {phrase} (Gematria: {phrase_gematria})</h2>")
results.append("<div class='results-container'>")
for book, phrases in results_by_book.items():
for words, chapter, verse, phrase_length, word_position in phrases:
translation = get_translation(words) if show_translation else ""
link = f"https://www.biblegateway.com/passage/?search={quote_plus(book)}+{chapter}%3A{verse}&version=CJB"
results.append(f"""
<div class='result-item'>
<p><b>Book:</b> {book}</p>
<p><b>Chapter:</b> {chapter}, <b>Verse:</b> {verse}</p>
<p class='hebrew-phrase'><b>Hebrew Phrase:</b> {words}</p>
<p><b>Translation:</b> {translation}</p>
<p><b>Phrase Length:</b> {phrase_length} words</p>
<p><b>Phrase Gematria:</b> {phrase_gematria}</p>
<p><b>Word Position in the Tanach:</b> {word_position}</p>
<a href='{link}' target='_blank' class='bible-link'>[See on Bible Gateway]</a>
</div>
""")
# Calculate average position for the current name across all books
name_average_position = calculate_average_position_for_name(results_by_book)
if name_average_position is not None:
results.append(f"<p><b>Average Word Position for '{phrase}' across all books:</b> {name_average_position:.2f}</p>")
all_names_average_position += name_average_position
total_name_count += 1
results.append("</div>")
all_results.append(results_by_book) # Store results by book without the phrase
# Calculate the average word position across all names and all their books
if total_name_count > 0:
all_names_average_position /= total_name_count
results.append(f"<h2>Average Word Position Across All Names and Books: {all_names_average_position:.2f}</h2>")
# Calculate middle words for all input lines (common books)
if len(all_results) >= 2:
results.append("<h2>Middle Words (Common Books):</h2>")
results.append("<div class='results-container'>")
common_books = set.intersection(*[set(results.keys()) for results in all_results])
logging.debug(f"Common books: {common_books}")
for book in common_books:
logging.debug(f"Processing book: {book}")
# Find nearest positions for all phrases in the current book
nearest_positions = find_nearest_positions([results[book] for results in all_results])
logging.debug(f"Nearest positions in {book}: {nearest_positions}")
if nearest_positions:
middle_word_position = sum(nearest_positions) / len(nearest_positions)
logging.debug(f"Calculated middle word position in {book}: {middle_word_position}")
start_position = int(middle_word_position)
end_position = start_position + 1 if middle_word_position % 1 != 0 else start_position
logging.debug(f"Middle word position range in {book}: {start_position}-{end_position}")
middle_words_data = get_words_from_db(book, start_position, end_position)
logging.debug(f"Middle words data fetched from database: {middle_words_data}")
if middle_words_data:
# Store middle word data along with book name for sorting
middle_words_results.extend([(book, data) for data in middle_words_data])
else:
# Handle edge case: fetch words independently for start and end positions
logging.debug(f"No middle words found for range {start_position}-{end_position}. "
f"Fetching words independently.")
middle_words_data_start = get_words_from_db(book, start_position, start_position)
middle_words_data_end = get_words_from_db(book, end_position, end_position)
if middle_words_data_start or middle_words_data_end:
middle_words_results.extend([(book, data) for data in middle_words_data_start + middle_words_data_end])
# Sort middle words results by book order before displaying
middle_words_results.sort(key=lambda x: int(list(book_names.keys())[list(book_names.values()).index(x[0])]))
for book, (words, chapter, verse, phrase_length, word_position) in middle_words_results:
translation = get_translation(words) if show_translation else ""
link = f"https://www.biblegateway.com/passage/?search={quote_plus(book)}+{chapter}%3A{verse}&version=CJB"
results.append(f"""
<div class='result-item'>
<p><b>Book:</b> {book}</p>
<p><b>Chapter:</b> {chapter}, <b>Verse:</b> {verse}</p>
<p class='hebrew-phrase'><b>Hebrew Phrase:</b> {words}</p>
<p><b>Translation:</b> {translation}</p>
<p><b>Phrase Length:</b> {phrase_length} words</p>
<p><b>Word Position in the Tanach:</b> {word_position}</p>
<a href='{link}' target='_blank' class='bible-link'>[See on Bible Gateway]</a>
</div>
""")
results.append("</div>")
# Style modified to position search on top and results below
style = """
<style>
.results-container {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
width: 100%; /* Make results container take full width */
}
.result-item {
border: 1px solid #ccc;
padding: 15px;
border-radius: 5px;
box-shadow: 2px 2px 5px rgba(0, 0, 0, 0.1);
}
.hebrew-phrase {
font-family: 'SBL Hebrew', 'Ezra SIL', serif;
direction: rtl;
}
.bible-link {
display: block;
margin-top: 10px;
color: #007bff;
text-decoration: none;
}
</style>
"""
return style + "\n".join(results)
def calculate_average_position_for_name(results_by_book: Dict[str, List[Tuple]]) -> float:
"""Calculates the average word position for a single name across all books."""
positions = []
for book, phrases in results_by_book.items():
for _, _, _, _, word_position in phrases:
start, end = map(int, word_position.split('-'))
positions.append((start + end) / 2)
return sum(positions) / len(positions) if positions else None
def find_nearest_positions(results_lists: List[List]) -> List[int]:
"""Finds the nearest word positions among multiple lists of results."""
nearest_positions = []
for i in range(len(results_lists)):
positions_i = [(int(pos.split('-')[0]) + int(pos.split('-')[1])) / 2
for _, _, _, _, pos in results_lists[i]] # Get average of start and end positions
logging.debug(f"Positions for phrase {i+1}: {positions_i}")
# Calculate the average position for the current phrase
average_position = sum(positions_i) / len(positions_i) if positions_i else None
logging.debug(f"Average position for phrase {i+1}: {average_position}")
if average_position is not None:
nearest_positions.append(average_position)
return nearest_positions
def get_words_from_db(book: str, start_position: int, end_position: int) -> List[Tuple]:
"""Fetches words from the database based on the book and exact word position range."""
global conn
logging.debug(f"Fetching words from database for {book} at positions {start_position}-{end_position}")
with sqlite3.connect(DATABASE_FILE) as conn:
cursor = conn.cursor()
cursor.execute("""
SELECT words, chapter, verse, phrase_length, word_position
FROM results
WHERE book = ? AND word_position = ?
""", (book, f"{start_position}-{end_position}")) # Directly compare word_position
results = cursor.fetchall()
logging.debug(f"Words fetched from database: {results}")
return results
def flatten_text(text: List) -> str:
"""Flattens nested lists into a single list."""
if isinstance(text, list):
return " ".join(flatten_text(item) if isinstance(item, list) else item for item in text)
return text
def run_app() -> None:
"""Initializes and launches the Gradio app."""
global conn
initialize_database()
initialize_translator()
logging.info("Starting database population...")
for max_phrase_length in range(1, MAX_PHRASE_LENGTH_LIMIT + 1):
populate_database(1, 39, max_phrase_length=max_phrase_length)
logging.info("Database population complete.")
with gr.Blocks() as iface: # Use gr.Blocks() for layout control
with gr.Row(): # Place inputs in a row
textbox = gr.Textbox(label="Enter word(s) or numbers (one phrase per line)", lines=5)
slider = gr.Slider(label="Max Word Count in Result Phrases", minimum=1,
maximum=MAX_PHRASE_LENGTH_LIMIT, step=1,
value=1)
checkbox = gr.Checkbox(label="Show Translation", value=True)
with gr.Row(): # Place buttons in a row
clear_button = gr.Button("Clear")
submit_button = gr.Button("Submit", variant="primary")
html_output = gr.HTML(label="Results") # Output for the results
submit_button.click(fn=gematria_search_interface,
inputs=[textbox, slider, checkbox],
outputs=html_output)
clear_button.click(fn=lambda: "", inputs=None, outputs=html_output) # Clear the output
iface.launch()
if __name__ == "__main__":
run_app()