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🛒 Temu Product Scraper — Python SDK

PyPI version License: MIT Python 3.9+ CI

40+ enrichment fields per Temu product. $0.003 each. Shopify-CSV ready. Profit-margin estimator + unicorn detector built in. No login required.

Direct alternative to Sell The Trend / Ecomhunt / Niche Scraper ($30-100/mo subscriptions) for use cases the official APIs can't cover: USD-normalized prices across 10 currencies, parsed sold counts (10K+ → 10000), demand score 0-100, profit margin estimator with arbitrage tier (low/medium/high/unicorn), 15-category auto-tagging, trend detection, risk flags, and one-click research links to AliExpress / Amazon / TikTok / Pinterest.

pip install git+https://github.com/apivault-labs/temu-product-scraper-python
from temu_scraper import TemuScraperClient

client = TemuScraperClient(api_token="apify_api_xxxxxx")

products, summary = client.scrape([
    "https://www.temu.com/wireless-bluetooth-earbuds-g-601099527041816.html",
    "https://www.temu.com/portable-blender-g-601099528000001.html",
])

# The unicorns: ≥65% margin AND ≥10K sold
for p in client.filter_unicorns(products):
    print(f"{p['title'][:60]:60}  "
          f"{p['estimatedProfitMarginPct']:.0f}% margin  "
          f"{p['soldCountInt']:,} sold")

What you get for $0.003 per product

For every Temu product analyzed, you get 40+ structured fields — core product data plus 14 derived enrichment layers.

⭐ Core (Temu)

  • title, priceText, originalPriceText, discountPct
  • rating, reviewsCountText, soldCountText
  • shopName, description, category
  • shippingInfo, availability
  • imageUrl (main), images[] (gallery up to 10), variants{}

💵 Price normalizer (USD-converted)

  • priceUsd, originalPriceUsd, priceLocal, currency
  • 10 currencies recognized: USD/EUR/GBP/CAD/AUD/JPY/INR/BRL/MXN/PLN
  • FX-converted to USD using mid-market rates
  • discountPct, savingsUsd
  • Handles US ($1,234.56) and EU (€1.234,56) thousand-separator styles

🔥 Sold count parser (Temu's signature metric)

  • soldCountInt — 10K+ → 10000, 1.2M+ → 1200000
  • soldCountTier — viral / hot / warm / cool / cold
  • soldCountIsBucket — flag when value was a "+" approximation

⭐ Reviews count parser

  • reviewsCountInt — same K/M/+ parsing

📦 Image gallery

  • images[] — list of all product images parsed from "All Images"
  • imagesCount — needed for full Shopify CSV migration

🎨 Variants extractor

  • variants{} — {color: ['Red', 'Blue'], size: ['S', 'M', 'L']}
  • variantsCount, colorOptions, sizeOptions

🚚 Shipping parser

  • freeShipping boolean
  • freeShippingThresholdUsd (e.g. $35 free shipping threshold)
  • shippingDaysMin, shippingDaysMax

🏷️ Auto-categorization (15 categories)

electronics / fashion_women / fashion_men / fashion_unisex / home_kitchen / home_decor / home_garden / beauty / baby_kids / toys_games / pet_supplies / sports_outdoor / automotive / office_school / tools_hardware

📊 demandScore (0-100) + tier + reasons

Composite of sold count × rating × reviews × discount aggressiveness:

  • demandTier — cold / warm / hot / scorching
  • demandScoreReasons[] — explainable signals (e.g. "50,000+ sold (hot)", "4.8★ exceptional", "-56% discount on volume mover")

💰 Profit margin estimator

Assumes retail = Temu cost × markup (configurable via retail_markup, default 3.0):

  • estimatedRetailUsd — suggested Shopify/Amazon price
  • estimatedGrossProfitUsd, estimatedProfitMarginPct
  • arbitrage_tier — low / medium / high / unicorn
  • Unicorn = ≥65 % margin AND ≥10K sold — best dropshipping picks

🎯 hotProductScore (0-100) + tier + reasons

The "should I add this to my Shopify?" composite — combines demand, margin, free shipping, photos, variants, and risk penalties:

  • hotProductTier — cold / warm / hot / scorching
  • hotProductReasons[] — explainable signals (e.g. "high demand (85)", "66% margin", "variants available")

🚀 Trend detection

  • isTrending — sold ≥ 10K AND rating ≥ 4.4

⚠️ Risk flags (4)

  • riskLowReviews — < 50 reviews (unverified product)
  • riskNewListing — < 100 sold + < 20 reviews (might be flop)
  • riskPoorRating — rating < 3.5
  • riskSeasonal — seasonal keyword in title (christmas/halloween/...)
  • riskCount — total risk count

📞 One-click research links

  • aliexpress_search_url — find original supplier (often cheaper than Temu)
  • amazon_search_url — check competitor pricing
  • ebay_search_url, google_shopping_url
  • tiktok_search_url — viral content potential
  • youtube_review_search_url — "[product] review"
  • pinterest_search_url — organic-traffic potential

📊 Free aggregate KV records on bulk runs

SUMMARY — avg/median/min/max price, by_category, by_demand_tier, by_arbitrage_tier, total units sold across run, trending count, free-shipping count, with-variants count.

TOP_PRODUCTS — top 20 products sorted by hotProductScore (your daily best-dropshipping-picks digest). Read with:

top = client.get_top_products()
for prod in top["top_products"][:10]:
    print(prod["hotProductScore"], prod["title"])

Sample output

{
  "success": true,
  "productUrl": "https://www.temu.com/wireless-bluetooth-earbuds-g-601099527041816.html",
  "productId": "601099527041816",
  "title": "Wireless Bluetooth Earbuds with Charging Case",
  "shopName": "TopTech Store",
  "category": "Electronics > Audio > Earbuds",
  "autoCategory": "electronics",

  "priceText": "US$10.99",
  "priceUsd": 10.99,
  "currency": "USD",
  "originalPriceUsd": 24.99,
  "discountPct": 56,
  "savingsUsd": 14.00,

  "rating": 4.8,
  "soldCountText": "50K+",
  "soldCountInt": 50000,
  "soldCountTier": "hot",
  "reviewsCountInt": 12000,

  "freeShipping": true,
  "freeShippingThresholdUsd": 10,
  "shippingDaysMin": 5,
  "shippingDaysMax": 12,

  "images": [
    "https://img.temu.com/o/abc.jpg",
    "https://img.temu.com/o/def.jpg"
  ],
  "imagesCount": 8,
  "variants": {
    "color": ["Black", "White", "Blue"],
    "size": ["Standard"]
  },
  "variantsCount": 4,

  "demandScore": 85,
  "demandTier": "scorching",
  "demandScoreReasons": [
    "50,000+ sold (hot)",
    "4.8★ exceptional",
    "12,000+ reviews",
    "-56% discount on volume mover"
  ],

  "estimatedRetailUsd": 32.97,
  "estimatedGrossProfitUsd": 21.98,
  "estimatedProfitMarginPct": 66.7,
  "arbitrage_tier": "unicorn",
  "assumedMarkup": 3.0,

  "hotProductScore": 88,
  "hotProductTier": "scorching",
  "hotProductReasons": [
    "high demand (85)",
    "66% margin",
    "free shipping",
    "good photos",
    "variants available"
  ],

  "isTrending": true,
  "riskLowReviews": false,
  "riskNewListing": false,
  "riskCount": 0,

  "outreachLinks": {
    "aliexpress_search_url": "https://www.aliexpress.com/wholesale?SearchText=Wireless+Bluetooth+Earbuds+with+Charging+Case",
    "amazon_search_url": "https://www.amazon.com/s?k=Wireless+Bluetooth+Earbuds+with+Charging+Case",
    "tiktok_search_url": "https://www.tiktok.com/search?q=Wireless+Bluetooth+Earbuds+with+Charging+Case",
    "youtube_review_search_url": "https://www.youtube.com/results?search_query=Wireless+Bluetooth+Earbuds+review"
  }
}

Use cases

🥇 Dropshipping winners pipeline

# Find unicorn-tier picks (≥65% margin AND ≥10K sold) ready for Shopify
products, _ = client.scrape(URLS,
                            retail_markup=3.0,
                            min_hot_product_score=50,
                            only_free_shipping=True)

winners = client.filter_unicorns(products)
winners = client.filter_low_risk(winners, max_risks=0)
winners = client.filter_by_min_images(winners, min_images=5)

for w in sorted(winners, key=lambda p: -p["hotProductScore"]):
    print(f"[{w['hotProductScore']:3}] {w['title'][:60]}")
    print(f"  margin {w['estimatedProfitMarginPct']:.0f}%, "
          f"sold {w['soldCountInt']:,}")

💰 Shopify migration (one-click)

# export_format="shopify-csv" returns 19-column rows ready to import
products, _ = client.scrape(URLS, export_format="shopify-csv")
# → write to .csv, upload at Shopify Admin → Products → Import

🛍️ Google Shopping ads feed

products, _ = client.scrape(URLS, export_format="google-merchant")
# → JSON rows ready to drop into Google Merchant Center

📈 Trend spotting / daily digest

# Daily monitoring with cross-run dedup — only charge for new listings
today, summary = client.scrape(WATCHED_URLS)
new_listings = client.deduplicate_across_runs(yesterday, today)
fresh_unicorns = client.filter_unicorns(new_listings)

🔍 Niche category research

# Pet supplies sweet-spot pricing
products, summary = client.scrape(SEED_URLS)
in_niche = client.filter_by_category(products, "pet_supplies")
in_niche = client.filter_by_min_rating(in_niche, 4.0)
in_niche = client.filter_by_min_sold(in_niche, 1000)

⚠️ Risk audit before bulk import

# Drop products with any risk flag before adding to your store
catalog = client.filter_low_risk(products, max_risks=0)

🏪 Amazon arbitrage research

# Compare Temu cost to Amazon retail
for p in products:
    amazon_url = p["outreachLinks"]["amazon_search_url"]
    print(f"Temu ${p['priceUsd']:.2f} vs Amazon → {amazon_url}")

Pricing

Volume Cost
1 product $0.003
100 $0.30
1,000 $3.00
10,000 $30.00 
client.estimate_cost(2_500)   # 7.5 USD

The Apify free tier ($5 credit) covers ~1,650 products. Pay only for successfully scraped products — failed pages don't trigger pay-per-event charging.

Installation

pip install git+https://github.com/apivault-labs/temu-product-scraper-python

Or pin to a release tag:

pip install git+https://github.com/apivault-labs/temu-product-scraper-python@v0.1.0

Setup

  1. Create an Apify account: https://console.apify.com/sign-up
  2. Get your API token: https://console.apify.com/account/integrations
  3. Either pass it explicitly or export APIFY_API_TOKEN:
export APIFY_API_TOKEN="apify_api_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
client = TemuScraperClient()                        # picks up env var
client = TemuScraperClient(api_token="apify_...")   # explicit

Examples

File What it shows
examples/quickstart.py Single product with full enrichment breakdown
examples/bulk_scrape.py Multi-product run + SUMMARY/TOP_PRODUCTS
examples/dropshipping_winners_pipeline.py Full unicorn-finder workflow
examples/shopify_csv_migration.py One-click Shopify import flow
examples/google_merchant_feed.py Google Shopping ads feed export
examples/daily_monitoring.py Cross-run dedup with productId
examples/niche_category_research.py Deep dive into a single category
examples/export_to_csv.py Flat CSV for spreadsheet analysis

API reference

TemuScraperClient(api_token=None, timeout=1200, poll_interval=3.0)

scrape(product_urls, **kwargs) -> (products, summary)

Forwards all 26 actor input flags. See full list in temu_scraper/client.py.

Key parameters: retail_markup (default 3.0), min_demand_score, min_hot_product_score, only_trending, only_free_shipping, export_format (default/shopify-csv/google-merchant), write_summary, top_products_n, max_concurrency (default 3).

scrape_one(product_url, **kwargs) -> dict | None

Convenience wrapper for single-product scrapes. Sets write_summary=False and max_concurrency=1 by default.

KV record helpers

  • get_summary() -> dict | None
  • get_top_products() -> dict | None

Filters (return new lists)

  • filter_by_demand_tier(products, *tiers) — cold/warm/hot/scorching
  • filter_by_hot_product_tier(products, *tiers)
  • filter_by_arbitrage_tier(products, *tiers) — low/medium/high/unicorn
  • filter_unicorns(products) — shortcut for arbitrage_tier=unicorn
  • filter_trending(products) — isTrending = true
  • filter_free_shipping(products)
  • filter_by_category(products, *categories) — 15 categories
  • filter_by_min_margin(products, min_pct)
  • filter_by_min_sold(products, min_units)
  • filter_by_min_rating(products, min_rating)
  • filter_by_price_range(products, min_usd, max_usd)
  • filter_low_risk(products, max_risks=0)
  • filter_with_variants(products)
  • filter_by_min_images(products, min_images)

Helpers

  • estimate_cost(expected_products) -> float
  • deduplicate_across_runs(previous, new) -> list — for daily monitoring

How it works

your_code → TemuScraperClient → Apify API
                                    ↓
                            Apify actor v1.2
                                    ↓
                        Thunderbit (Temu data)
                                    ↓
              14-layer enrichment (price/sold/demand/margin/...)
                                    ↓
                        Server-side filters
                                    ↓
                  default JSON / Shopify CSV / Google Merchant
                                    ↓
              + free SUMMARY + TOP_PRODUCTS in KV store
                                    ↓
                          you, in Python

FAQ

Q: Do I need a Temu account? A: No. The actor scrapes public product pages — no login.

Q: How accurate is estimatedProfitMarginPct? A: It's a heuristic based on a configurable markup (default 3×, the industry rule for Amazon/Shopify dropshipping). For eBay/Mercari use 1.8-2.2; for niche/branded stores use 4-6. Set via retail_markup.

Q: How accurate is soldCountInt? A: Temu shows bucketed values like "10K+", "50K+". The parser converts these to the lower bound (10K+ → 10000) and sets soldCountIsBucket=true to flag the approximation.

Q: Can I get the actual photos for Shopify import? A: Yes — extract_images=True (default) returns up to 10 image URLs per product in images[]. The Shopify CSV export uses these automatically.

Q: Does it work for non-US Temu (eu.temu.com / temu.de)? A: Yes — the actor parses prices in 10 currencies (EUR/GBP/CAD/...) and auto-converts to USD for sortable comparison.

Q: How is this better than Sell The Trend / Ecomhunt / Niche Scraper? A: Pay-as-you-go ($0.003/product) instead of $30-100/month subscription. You get raw structured data — no "curated" filter forcing you into someone else's picks. Plus Shopify CSV and Google Merchant exports the others charge extra for.

Q: Will I get blocked / banned? A: All scraping happens on Apify infrastructure via Thunderbit's whitelisted pool. You don't connect to Temu directly — your IP is never touched.

Q: Why are some products success: false? A: Temu is sensitive to aggressive parallelism. Lower max_concurrency to 2-3 (already the default) and rerun. Failed products are still pushed (with success: false) but don't trigger pay-per-event charging.

Q: Can I track listings over time? A: Yes — see examples/daily_monitoring.py. Use deduplicate_across_runs() to avoid re-paying for unchanged listings.

Keywords

temu temu-scraper temu-api temu-product-scraper temu-without-login temu-without-api-key dropshipping dropshipping-tools dropshipping-research winning-products product-research shopify-import shopify-csv shopify-csv-import shopify-migration google-merchant-feed google-shopping-feed ecommerce-scraper ecommerce-data marketplace-scraper amazon-arbitrage ebay-arbitrage retail-arbitrage profit-margin-estimator competitor-pricing price-monitoring niche-scraper-alternative sell-the-trend-alternative ecomhunt-alternative spocket-alternative trend-detection viral-products tiktok-shop-research apify python-sdk

License

MIT — see LICENSE.

About

Python SDK for the Temu Product Scraper Apify actor — 40+ enrichment fields per product: USD-normalized prices (10 currencies), parsed sold counts + tier, demand score 0-100, profit margin estimator with arbitrage tier (incl. unicorn), hot product score, 15-category auto-tagging, trend detection, risk flags. Shopify CSV + Google Merchant export. No

apify.com/apivault_labs/temu-product-scraper

Topics

python-sdk apify dropshipping product-research temu temu-scraper shopify-import dropshipping-tools shopify-csv temu-api google-merchant-feed viral-products temu-product-scraper temu-without-login winning-products amazon-arbitrage profit-margin-estimator niche-scraper-alternative sell-the-trend-alternative ecomhunt-alternative

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MIT license

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