Extract LinkedIn Posts and Engagement Data

import requests

# Prospect activity analysis — pull posts and rank by engagement
API_KEY = "YOUR_ACCESS_TOKEN"
BASE = "https://api.anysite.io"
headers = {"access-token": API_KEY}

def get_prospect_posts(username, max_pages=5):
    """Pull all recent posts for a prospect."""
    posts = []
    cursor = None

    for _ in range(max_pages):
        params = {"user": username, "count": 20}
        if cursor:
            params["cursor"] = cursor

        resp = requests.get(
            f"{BASE}/api/linkedin/user/posts",
            headers=headers, params=params
        )
        data = resp.json()
        posts.extend(data.get("posts", []))

        cursor = data.get("cursor")
        if not cursor:
            break

    return posts

# Analyze engagement
posts = get_prospect_posts("janedoe")
for post in sorted(posts, key=lambda p: p["likes"] + p["comments"], reverse=True)[:5]:
    engagement = post["likes"] + post["comments"] + post["shares"]
    print(f"Engagement: {engagement} | {post['text'][:80]}...")

# Brand monitoring — search posts mentioning your company
def search_brand_mentions(brand, pages=3):
    """Search all LinkedIn posts for brand mentions."""
    mentions = []
    cursor = None

    for _ in range(pages):
        params = {"keywords": brand, "count": 50}
        if cursor:
            params["cursor"] = cursor

        resp = requests.get(
            f"{BASE}/api/linkedin/search/posts",
            headers=headers, params=params
        )
        data = resp.json()
        mentions.extend(data.get("posts", []))
        cursor = data.get("cursor")
        if not cursor:
            break

    return mentions

mentions = search_brand_mentions("Acme Corp")
print(f"Found {len(mentions)} posts mentioning your brand")
for m in mentions[:10]:
    print(f"  {m['author']['name']}: {m['text'][:60]}... ({m['likes']} likes)")

# Competitive content analysis — compare engagement across companies
competitors = ["competitor-a", "competitor-b", "competitor-c"]

for company in competitors:
    resp = requests.get(
        f"{BASE}/api/linkedin/company/posts",
        headers=headers,
        params={"user": company, "count": 10}
    )
    posts = resp.json().get("posts", [])

    if posts:
        avg_likes = sum(p["likes"] for p in posts) / len(posts)
        avg_comments = sum(p["comments"] for p in posts) / len(posts)
        print(f"{company}: {avg_likes:.0f} avg likes, {avg_comments:.0f} avg comments")