{
  "id": 12849439,
  "title": "What I Learned After My Instagram Scraper Broke While Vetting Influencers",
  "url": "https://urgent.news/2026/10/08/what-i-learned-after-my-instagram-scraper-broke-while-vetting",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-08T10:57:21.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/__e9807/what-i-learned-after-my-instagram-scraper-broke-while-vetting-influencers-bol"
  },
  "original_language": "en",
  "account": "When vetting influencers on Instagram, my previous method of using a scraper eventually failed. The issue wasn't the Python code itself; rather, it was the common challenges associated with scraping, such as requests failing and changes to the platform. This constant maintenance wasn't ideal for a simple task requiring only profile data. Consequently, I switched to an API approach utilizing HikerAPI, a REST Instagram API available at $0.001 per request with 100 free requests.\n\nTo get started, you'll need Python, the requests package, and an HikerAPI access key. If not already installed, you can install the requests package using pip: pip install requests. The actual request is straightforward, requiring just a few lines of code:\n\n```python\nimport requests\n\nheaders = { 'x-access-key': 'YOUR_KEY' }\nr = requests.get( 'https://api.hikerapi.com/v2/user/by/username', params={'username': 'natgeo'}, headers=headers )\nprint(r.json())\n```\n\nThe API returns profile information in JSON format, making it easy to inspect or pass into the rest of a Python workflow. Once you have the response, you can store it in a variable and access individual fields as needed:\n\n```python\nimport requests\n\nheaders = { 'x-access-key': 'YOUR_KEY' }\nr = requests.get( 'https://api.hikerapi.com/v2/user/by/username', params={'username': 'natgeo'}, headers=headers )\ndata = r.json()\n\nprint('Username: ', data.get('username'))\nprint('User ID: ', data.get('pk'))\nprint('Followers: ', data.get('follower_count'))\n```\n\nBy treating the response as JSON, you can easily print the JSON or access individual fields when building a new script. This approach is particularly useful for influencer vetting, allowing you to incorporate profile lookups into a larger workflow without manually opening and copying information from each profile. My main takeaway from this experience is that scraping and using an API serve different purposes: scraping requires maintaining the collection mechanism, while an API provides a defined interface for requesting data. For a small marketing workflow, this trade-off proves beneficial. By keeping Python code concise, executing requests only when necessary, and minimizing debugging efforts on the collection layer, the API approach simplifies the process of gathering profile data.",
  "summary": "What I Learned After My Instagram Scraper Broke While Vetting Influencers When I was checking Instagram profiles before paying influencers, my previous approach eventually broke. The problem wasn't the Python code itself—it was the usual scraping problems: requests failing, changes on the platform side, and more maintenance than I wanted for a fairly simple task. I only needed profile data. I…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}