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import io
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import base64
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from datetime import datetime, timezone
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import logging
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import matplotlib.pyplot as plt
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from .mongo_db import (
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get_collection,
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insert_document,
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find_documents,
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update_document,
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delete_document
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)
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logger = logging.getLogger(__name__)
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COLLECTION_NAME = 'student_discourse_analysis'
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def store_student_discourse_result(username, text1, text2, analysis_result):
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"""
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Guarda el resultado del análisis de discurso comparativo en MongoDB.
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"""
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try:
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graph1_data = None
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graph2_data = None
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combined_graph_data = None
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if 'graph1' in analysis_result and analysis_result['graph1'] is not None:
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try:
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graph1_data = base64.b64encode(analysis_result['graph1']).decode('utf-8')
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except Exception as e:
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logger.error(f"Error al codificar gráfico 1: {str(e)}")
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if 'graph2' in analysis_result and analysis_result['graph2'] is not None:
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try:
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graph2_data = base64.b64encode(analysis_result['graph2']).decode('utf-8')
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except Exception as e:
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logger.error(f"Error al codificar gráfico 2: {str(e)}")
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if 'combined_graph' in analysis_result and analysis_result['combined_graph'] is not None:
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try:
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combined_graph_data = base64.b64encode(analysis_result['combined_graph']).decode('utf-8')
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except Exception as e:
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logger.error(f"Error al codificar gráfico combinado: {str(e)}")
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analysis_document = {
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'username': username,
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'timestamp': datetime.now(timezone.utc).isoformat(),
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'text1': text1,
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'text2': text2,
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'analysis_type': 'discourse',
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'key_concepts1': analysis_result.get('key_concepts1', []),
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'key_concepts2': analysis_result.get('key_concepts2', []),
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'graph1': graph1_data,
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'graph2': graph2_data,
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'combined_graph': combined_graph_data
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}
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result = insert_document(COLLECTION_NAME, analysis_document)
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if result:
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logger.info(f"Análisis del discurso guardado con ID: {result} para el usuario: {username}")
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return True
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logger.error("No se pudo insertar el documento en MongoDB")
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return False
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except Exception as e:
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logger.error(f"Error al guardar el análisis del discurso: {str(e)}")
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return False
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def get_student_discourse_analysis(username, limit=10):
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"""
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Recupera los análisis del discurso de un estudiante.
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"""
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try:
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collection = get_collection(COLLECTION_NAME)
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if collection is None:
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logger.error("No se pudo obtener la colección discourse")
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return []
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query = {
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"username": username,
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"analysis_type": "discourse"
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}
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projection = {
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"timestamp": 1,
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"combined_graph": 1,
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"_id": 1
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}
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try:
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cursor = collection.find(query, projection).sort("timestamp", -1)
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if limit:
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cursor = cursor.limit(limit)
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results = list(cursor)
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logger.info(f"Recuperados {len(results)} análisis del discurso para {username}")
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return results
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except Exception as db_error:
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logger.error(f"Error en la consulta a MongoDB: {str(db_error)}")
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return []
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except Exception as e:
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logger.error(f"Error recuperando análisis del discurso: {str(e)}")
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return []
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def get_student_discourse_data(username):
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"""
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Obtiene un resumen de los análisis del discurso de un estudiante.
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"""
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try:
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analyses = get_student_discourse_analysis(username, limit=None)
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formatted_analyses = []
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for analysis in analyses:
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formatted_analysis = {
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'timestamp': analysis['timestamp'],
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'text1': analysis.get('text1', ''),
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'text2': analysis.get('text2', ''),
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'key_concepts1': analysis.get('key_concepts1', []),
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'key_concepts2': analysis.get('key_concepts2', [])
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}
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formatted_analyses.append(formatted_analysis)
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return {'entries': formatted_analyses}
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except Exception as e:
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logger.error(f"Error al obtener datos del discurso: {str(e)}")
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return {'entries': []}
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def update_student_discourse_analysis(analysis_id, update_data):
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"""
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Actualiza un análisis del discurso existente.
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"""
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try:
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query = {"_id": analysis_id}
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update = {"$set": update_data}
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return update_document(COLLECTION_NAME, query, update)
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except Exception as e:
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logger.error(f"Error al actualizar análisis del discurso: {str(e)}")
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return False
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def delete_student_discourse_analysis(analysis_id):
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"""
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Elimina un análisis del discurso.
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"""
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try:
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query = {"_id": analysis_id}
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return delete_document(COLLECTION_NAME, query)
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except Exception as e:
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logger.error(f"Error al eliminar análisis del discurso: {str(e)}")
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return False |