The Complete Instagram Data API

import requests

API_KEY = "YOUR_API_KEY"
BASE = "https://api.anysite.io"
headers = {"access-token": API_KEY}

competitors = ["brand_a", "brand_b", "brand_c"]

for brand in competitors:
    # Get profile for follower count
    profile = requests.get(
        f"{BASE}/api/instagram/user",
        headers=headers, params={"user": brand}
    ).json()

    # Get recent posts for engagement
    posts = requests.get(
        f"{BASE}/api/instagram/user/posts",
        headers=headers, params={"user": brand, "count": 12}
    ).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)
        eng_rate = (avg_likes + avg_comments) / profile["followers"] * 100
        print(f"{brand}: {profile['followers']:,} followers, {eng_rate:.2f}% engagement")

# Search posts by hashtag
anysite instagram search posts --keywords "#sustainablefashion" --count 20

# Pipe results to jq for analysis
anysite instagram search posts --keywords "#sustainablefashion" --count 20 \
  | jq '[.posts[] | {user: .author.username, likes: .likes, comments: .comments}] | sort_by(-.likes)'

# Export top posts to CSV
anysite instagram search posts --keywords "#sustainablefashion" --count 20 --format csv > hashtag_results.csv

name: product-intelligence
schedule: "0 9 * * *"
steps:
  - source: instagram/search/posts
    params:
      keywords: "#yourbrand OR @yourbrand"
      count: 20
    output: brand_mentions

  - source: instagram/search/posts
    params:
      keywords: "#competitorbrand"
      count: 20
    output: competitor_mentions

  - filter:
      min_likes: 50

  - output:
      format: json
      path: ./data/product-intel-Apr 9, 2026.json