Use Amazon Review Aggregates & Extended History Scraper with Python

Collect Amazon customer reviews and rating summaries by product URL, ASIN, or keyword across 19 marketplaces, with star-rating and sort filters, reviewer images, and an optional session for deeper review history.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "categoryUrls": [],
  "country": "amazon.com",
  "extendedHistory": true,
  "filterKeywords": [],
  "includeAggregates": true,
  "includeGdprSensitive": false,
  "includeImages": true,
  "keywords": [],
  "maxProductsToDiscover": 10,
  "maxReviews": 15,
  "mediaReviewsOnly": false,
  "mergeMarketplaces": [],
  "productUrls": [
    "https://www.amazon.com/dp/B09X7MPX8L"
  ],
  "reviewsNewerThan": "",
  "sortBy": "helpful",
  "verifiedPurchasesOnly": false
}

Download input.example.json and save your reviewed copy as input.json.

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/OgPzorRclF6tasDvP/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

One record per collected Amazon customer review — rating, title, body, verified-purchase/Vine flags, helpful-votes count, reviewer location, sentiment hint, images/videos, the pipeline that produced the row (`source`: productPage / extendedHistory / cookieMode), its marketplace, a stable dedup fingerprint, and product/source metadata. One additional `amazon_review_aggregate` record per product carries the product title, average rating, global ratings count, star histogram with derived per-star counts, and Amazon's "Customers say" summary with aspects. Empty / null fields are dropped at push time, so any field documented below may be absent if the source did not populate it. Records may carry `collectionCompleteness: "INLINE_SAMPLE"` when `sourceMode=FULL_PAGE` was requested without a valid `cookieString` and `onAuthRequired=RETURN_PARTIAL` fell back to the cookie-free product-page sample instead of the full paginated set.

Questions before you run

Generated from source build 3eBuV9sO4ltC6gYLd and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.