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Update Data_Fetching_and_Rendering.py
Browse files
Data_Fetching_and_Rendering.py
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@@ -7,6 +7,7 @@ from transformers import pipeline
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from sessions import create_session
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from error_handling import display_error
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import logging
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@@ -131,6 +132,9 @@ def fetch_posts_and_stats(comm_client_id, community_token, count=10):
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post_urns = [p["id"] for p in raw_posts if ":share:" in p["id"] or ":ugcPost:" in p["id"]]
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stats_map = {}
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for i in range(0, len(post_urns), 20):
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batch = post_urns[i:i+20]
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params = {'q': 'organizationalEntity', 'organizationalEntity': org_urn}
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@@ -177,6 +181,9 @@ def fetch_posts_and_stats(comm_client_id, community_token, count=10):
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})
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logging.info(f"Appended post data for {post_id}: Likes={likes}, Comments={comments_count}, Shares={shares}, Clicks={clicks}")
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return posts, org_name, sentiments
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from sessions import create_session
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from error_handling import display_error
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from posts_categorization import batch_summarize_and_classify
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import logging
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post_urns = [p["id"] for p in raw_posts if ":share:" in p["id"] or ":ugcPost:" in p["id"]]
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stats_map = {}
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post_texts = [{"text": p["commentary"] or p.get("specificContent", {}).get("com.linkedin.ugc.ShareContent", {}).get("shareCommentaryV2", {}).get("text", "")} for p in raw_posts]
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structured_results = batch_summarize_and_classify(post_texts)
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for i in range(0, len(post_urns), 20):
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batch = post_urns[i:i+20]
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params = {'q': 'organizationalEntity', 'organizationalEntity': org_urn}
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})
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logging.info(f"Appended post data for {post_id}: Likes={likes}, Comments={comments_count}, Shares={shares}, Clicks={clicks}")
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for post, structured in zip(posts, structured_results):
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post["summary"] = structured["summary"]
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post["category"] = structured["category"]
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return posts, org_name, sentiments
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