How to Scrape Pinterest Images and Pins

Pinterest is a valuable source of visual content data for market research, design inspiration analysis, and trend tracking. Here is how to scrape it effectively.

What You Can Extract from Pinterest

• Pin images (multiple resolutions)
• Pin descriptions and titles
• Board names and pin counts
• User profiles and follower data
• Related pins and recommendations

Method 1: ScraperAPI (Recommended)

Pinterest uses heavy JavaScript rendering and bot detection. ScraperAPI handles both.

import requests
from bs4 import BeautifulSoup
import json

API_KEY = "YOUR_SCRAPERAPI_KEY"

response = requests.get(
    "http://api.scraperapi.com",
    params={
        "api_key": API_KEY,
        "url": "https://www.pinterest.com/search/pins/?q=web+design",
        "render": "true"
    }
)

soup = BeautifulSoup(response.text, "html.parser")

# Pinterest embeds data in script tags
scripts = soup.find_all("script", {"type": "application/json"})
for script in scripts:
    try:
        data = json.loads(script.string)
        print(json.dumps(data, indent=2)[:500])
    except:
        pass

Method 2: Pinterest's Internal API

Pinterest's web app uses an internal API that returns JSON.

from curl_cffi import requests

session = requests.Session(impersonate="chrome136")

# Search for pins
search_url = "https://www.pinterest.com/resource/BaseSearchResource/get/"
params = {
    "source_url": "/search/pins/?q=web%20design",
    "data": '{"options":{"query":"web design","scope":"pins","page_size":25}}'
}

response = session.get(
    search_url,
    params=params,
    headers={
        "X-Requested-With": "XMLHttpRequest",
        "Referer": "https://www.pinterest.com/"
    }
)

if response.status_code == 200:
    data = response.json()
    results = data.get("resource_response", {}).get("data", {}).get("results", [])
    for pin in results[:5]:
        print(f"Title: {pin.get('title', 'N/A')}")
        print(f"Image: {pin.get('images', {}).get('orig', {}).get('url', 'N/A')}")
        print("---")

Method 3: Playwright for Dynamic Content

from playwright.sync_api import sync_playwright
import json

with sync_playwright() as p:
    browser = p.chromium.launch(headless=False)
    page = browser.new_page()

    images = []

    def capture_response(response):
        if "resource/BaseSearchResource" in response.url:
            try:
                data = response.json()
                results = data["resource_response"]["data"]["results"]
                for pin in results:
                    img = pin.get("images", {}).get("orig", {}).get("url")
                    if img:
                        images.append(img)
            except:
                pass

    page.on("response", capture_response)
    page.goto("https://www.pinterest.com/search/pins/?q=web+design")

    # Scroll to load more pins
    for _ in range(3):
        page.mouse.wheel(0, 3000)
        page.wait_for_timeout(2000)

    print(f"Collected {len(images)} image URLs")
    browser.close()

Downloading Images

import os
import requests

def download_images(image_urls, output_dir="pinterest_images"):
    os.makedirs(output_dir, exist_ok=True)

    for i, url in enumerate(image_urls):
        response = requests.get(url)
        if response.status_code == 200:
            ext = url.split(".")[-1].split("?")[0]
            filepath = os.path.join(output_dir, f"pin_{i}.{ext}")
            with open(filepath, "wb") as f:
                f.write(response.content)
            print(f"Downloaded: {filepath}")

Key Challenges

• Pinterest heavily relies on infinite scroll, requiring browser-based scraping for large datasets
• Rate limiting is aggressive on unauthenticated requests
• Image URLs contain expiring tokens on some endpoints
• The internal API structure changes periodically

For production Pinterest scraping, ScraperAPI with rendering is the most maintainable approach.