Files
crosspost/server/queue/tasks.py
Dylan De Faoite 01d6bd0164 fix(connectors): category / search fields breaking
Ideally category and search are fully optional, however some sites break if one or the other is not provided.

Unfortuntely `boards.ie` has a different page type for searches and I'm not bothered to implement a scraper from scratch.

In addition, removed comment limit options.
2026-03-11 21:16:26 +00:00

61 lines
2.2 KiB
Python

import pandas as pd
import logging
from server.queue.celery_app import celery
from server.analysis.enrichment import DatasetEnrichment
from server.db.database import PostgresConnector
from server.core.datasets import DatasetManager
from server.connectors.registry import get_available_connectors
logger = logging.getLogger(__name__)
@celery.task(bind=True, max_retries=3)
def process_dataset(self, dataset_id: int, posts: list, topics: dict):
db = PostgresConnector()
dataset_manager = DatasetManager(db)
try:
df = pd.DataFrame(posts)
processor = DatasetEnrichment(df, topics)
enriched_df = processor.enrich()
dataset_manager.save_dataset_content(dataset_id, enriched_df)
dataset_manager.set_dataset_status(dataset_id, "complete", "NLP Processing Completed Successfully")
except Exception as e:
dataset_manager.set_dataset_status(dataset_id, "error", f"An error occurred: {e}")
@celery.task(bind=True, max_retries=3)
def fetch_and_process_dataset(self,
dataset_id: int,
source_info: list[dict],
topics: dict):
connectors = get_available_connectors()
db = PostgresConnector()
dataset_manager = DatasetManager(db)
posts = []
try:
for metadata in source_info:
name = metadata["name"]
search = metadata.get("search")
category = metadata.get("category")
limit = metadata.get("limit", 100)
connector = connectors[name]()
raw_posts = connector.get_new_posts_by_search(
search=search,
category=category,
post_limit=limit
)
posts.extend(post.to_dict() for post in raw_posts)
df = pd.DataFrame(posts)
processor = DatasetEnrichment(df, topics)
enriched_df = processor.enrich()
dataset_manager.save_dataset_content(dataset_id, enriched_df)
dataset_manager.set_dataset_status(dataset_id, "complete", "NLP Processing Completed Successfully")
except Exception as e:
dataset_manager.set_dataset_status(dataset_id, "error", f"An error occurred: {e}")