added dummy scraper
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@ -1,8 +1,10 @@
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import random
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import json
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import time
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import math
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from datetime import datetime
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from flask import Blueprint, jsonify, render_template, request, current_app, flash
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from ..models import VolumeConfig, ActivityLog, PaperMetadata, ActivityCategory
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from ..models import VolumeConfig, ActivityLog, PaperMetadata, ActivityCategory, ScheduleConfig
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from ..db import db
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from ..celery import celery
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@ -43,13 +45,15 @@ def start_scraper():
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ActivityLog.log_scraper_command(
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action="start_scraper",
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status="success",
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description="Scraper started manually"
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description="Scheduled scraper started - will follow hourly configuration"
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)
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# Trigger the schedule.py to start actual scheduling
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# Immediately trigger a task to test the scheduler and provide feedback
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dummy_scheduled_scraper.delay()
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return jsonify({
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"success": True,
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"message": "Scraper started"
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"message": "Scraper started - following hourly schedule configuration"
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})
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else:
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return jsonify({
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@ -283,3 +287,209 @@ def dummy_scrape_paper(self):
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"success": False,
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"error": error_message
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}
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@celery.task
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def calculate_papers_for_current_hour():
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"""
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Calculate how many papers should be downloaded in the current hour
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based on schedule configuration.
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Returns:
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int: Number of papers to download this hour
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"""
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current_hour = datetime.now().hour
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# Get volume configuration
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volume_config = VolumeConfig.query.first()
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if not volume_config:
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volume_config = VolumeConfig(volume=100) # Default to 100 papers per day
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db.session.add(volume_config)
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db.session.commit()
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# Get all schedule configurations to calculate total weight
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schedule_configs = ScheduleConfig.query.all()
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if not schedule_configs:
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# If no schedule configs, create default with equal weights
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for hour in range(24):
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config = ScheduleConfig(hour=hour, weight=1.0)
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db.session.add(config)
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db.session.commit()
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schedule_configs = ScheduleConfig.query.all()
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# Calculate total weight across all hours
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total_weight = sum(config.weight for config in schedule_configs)
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# Find the weight for the current hour
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current_hour_config = ScheduleConfig.query.get(current_hour)
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if not current_hour_config:
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# Create config for current hour if it doesn't exist
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current_hour_config = ScheduleConfig(hour=current_hour, weight=1.0)
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db.session.add(current_hour_config)
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db.session.commit()
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# Calculate papers for current hour: (hour_weight / total_weight) * daily_volume
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if total_weight > 0:
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weight_ratio = current_hour_config.weight / total_weight
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papers_this_hour = math.floor(weight_ratio * volume_config.volume)
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else:
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papers_this_hour = 0
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return papers_this_hour
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@celery.task
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def dummy_scheduled_scraper():
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"""
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The main scheduler task that runs every hour to process papers
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according to the configured schedule.
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"""
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global SCRAPER_ACTIVE, SCRAPER_PAUSED
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if not SCRAPER_ACTIVE or SCRAPER_PAUSED:
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ActivityLog.log_scraper_activity(
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action="scheduled_scraping",
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status="info",
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description=f"Scheduled scraping skipped: active={SCRAPER_ACTIVE}, paused={SCRAPER_PAUSED}"
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)
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return False
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# Calculate how many papers to download this hour
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papers_to_download = calculate_papers_for_current_hour()
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if papers_to_download <= 0:
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ActivityLog.log_scraper_activity(
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action="scheduled_scraping",
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status="info",
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description=f"No papers scheduled for current hour"
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)
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return True
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# Get all pending papers
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pending_papers = PaperMetadata.query.filter_by(status="Pending").all()
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# If no pending papers available, create some dummy pending papers
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if not pending_papers:
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ActivityLog.log_scraper_activity(
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action="scheduled_scraping",
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status="info",
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description=f"No pending papers found - creating {papers_to_download} dummy pending papers"
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)
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# Create dummy pending papers
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for i in range(papers_to_download):
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new_paper = PaperMetadata(
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title=f"Dummy Pending Paper {random.randint(1000, 9999)}",
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doi=f"10.1234/dummy-pending.{random.randint(1000, 9999)}",
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journal=random.choice([
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"Nature", "Science", "PLOS ONE", "Journal of Dummy Research",
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"Proceedings of the Dummy Society", "Cell", "Dummy Review Letters"
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]),
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type="article",
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language="en",
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published_online=datetime.now().date(),
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status="Pending"
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)
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db.session.add(new_paper)
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db.session.commit()
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# Get the newly created papers
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pending_papers = PaperMetadata.query.filter_by(status="Pending").all()
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# Select papers_to_download random papers from pending_papers
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selected_papers = random.sample(
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pending_papers,
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min(papers_to_download, len(pending_papers))
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)
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ActivityLog.log_scraper_activity(
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action="scheduled_scraping",
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status="info",
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description=f"Starting scheduled scraping of {len(selected_papers)} papers for hour {datetime.now().hour}"
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)
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# For each paper, schedule it to run at a random time within the hour
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current_time = time.time()
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one_hour_in_seconds = 3600
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for paper in selected_papers:
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# Random delay within this hour (0 to 60 minutes)
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random_delay = random.randint(0, one_hour_in_seconds)
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# Schedule the dummy_process_paper task with the random delay
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dummy_process_paper.apply_async(
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args=[paper.id],
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countdown=random_delay
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)
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return True
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@celery.task(bind=True)
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def dummy_process_paper(self, paper_id):
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"""
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Process a single paper for the dummy scraper.
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Args:
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paper_id (int): ID of the paper to process
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"""
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# Get the paper from database
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paper = PaperMetadata.query.get(paper_id)
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if not paper:
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# Log error if paper not found
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ActivityLog.log_scraper_activity(
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action="process_paper",
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status="error",
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description=f"Paper with ID {paper_id} not found"
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)
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return False
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# Simulate random success/failure (70% success rate)
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success = random.random() < 0.7
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# Simulate processing time (1-5 seconds)
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process_time = random.uniform(1, 5)
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time.sleep(process_time)
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if success:
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# Update paper status to "Done"
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paper.status = "Done"
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paper.file_path = f"/path/to/dummy/papers/{paper.doi.replace('/', '_')}.pdf"
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# Log success
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ActivityLog.log_scraper_activity(
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action="process_paper",
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paper_id=paper.id,
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status="success",
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description=f"Successfully processed paper: {paper.title}"
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)
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else:
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# Update paper status to "Failed"
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paper.status = "Failed"
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# Generate random error message
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error_message = random.choice([
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"Publisher website unavailable",
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"No PDF download link found",
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"Access restricted",
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"Download timeout",
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"Invalid DOI",
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"Rate limited by publisher"
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])
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paper.error_msg = error_message
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# Log failure
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ActivityLog.log_scraper_activity(
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action="process_paper",
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paper_id=paper.id,
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status="error",
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description=f"Failed to process paper: {error_message}"
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)
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# Update the timestamp
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paper.updated_at = datetime.utcnow()
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# Commit changes to database
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db.session.commit()
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return success
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@ -1,4 +1,5 @@
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from celery import Celery
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from celery.schedules import crontab
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# Create Celery instance without Flask app initially
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celery = Celery(
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@ -29,6 +30,14 @@ def configure_celery(app=None):
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worker_max_memory_per_child=1000000, # 1GB memory limit
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task_acks_late=True, # Acknowledge tasks after completion
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task_reject_on_worker_lost=True, # Requeue tasks if worker dies
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# Configure Beat schedule for periodic tasks
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beat_schedule={
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'scheduled-scraper-hourly': {
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'task': 'scipaperloader.blueprints.scraper.dummy_scheduled_scraper',
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'schedule': crontab(minute=0), # Run at the start of every hour
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'options': {'expires': 3600}
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},
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}
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)
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# Create a custom task class that pushes the Flask application context
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