Python guide

Amazon Product API Python Quickstart.

Create an Amazon product data job with Python requests, wait for delivery and save ASIN results as a CSV file.

Get free sample See 100-row proof run View sample data

Output previewAmazon product record · 12 fields shown

ProductAvailabilityPrice

La Roche-Posay Cicaplast Balm B5 CreamB0060OUV5Y · 4.7 · 20,743 reviews

In stock$18.99

Maybelline Sky High MascaraB08H3JPH74 · 4.5 · 181,639 reviews

In stock$10.82

Aquaphor Healing OintmentB0107QPFBU · 4.8 · 138,730 reviews

In stock$12.79

Dove Sensitive Skin Body WashB00SK71SAG · 4.8 · 62,276 reviews

In stock$10.97

{
  "status": "succeeded",
  "marketplace": "amazon",
  "input_type": "product_url_list",
  "mode": "full_product",
  "delivered_records": 1,
  "charged_units": 5,
  "sample": {
    "product_id": "B0060OUV5Y",
    "title": "La Roche-Posay Cicaplast Balm B5 Cream",
    "brand": "La Roche-Posay",
    "price": 18.99,
    "currency": "USD",
    "ASIN": "available when Amazon renders this field",
    "rating": 4.7,
    "reviews_count": 20743,
    "stock": "In Stock",
    "images": [
      "https://m.media-amazon.com/images/I/713Ca5aXpyL._SL1500_.jpg"
    ],
    "category_path": [
      "Beauty & Personal Care",
      "Skin Care",
      "Face",
      "Creams"
    ],
    "product_url": "https://www.amazon.com/dp/B0060OUV5Y"
  },
  "exports": {
    "jsonl": "/api/v1/jobs/{job_id}/download/jsonl",
    "csv": "/api/v1/jobs/{job_id}/download/csv",
    "xlsx": "/api/v1/jobs/{job_id}/download/xlsx",
    "md": "/api/v1/jobs/{job_id}/download/md"
  }
}

curl -X POST https://parseshelf.com/api/v1/jobs \
  -H 'Authorization: Bearer $PARSESHELF_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"marketplace":"amazon","input_type":"product_url_list","input_value":"https://www.amazon.com/dp/B0060OUV5Y","mode":"full_product","target_count":20}'

Python integration path

ASIN list to CSV in three explicit steps.

Use a ParseShelf API key. Amazon Product Advertising API credentials are not required.

Step	Request	Result
1. Create	`POST /api/v1/jobs`	Persistent job ID for an ASIN list or Amazon URL
2. Poll	`GET /api/v1/jobs/{id}`	Status, delivered rows and export readiness
3. Download	`GET /api/v1/jobs/{id}/download?format=csv`	Normalized CSV from the completed job

Test 20 ASINs first Inspect OpenAPI JSON

Search intent

Terms this page answers.

Amazon product API PythonAmazon API Python ASINAmazon scraper API Pythonpython amazon simple product api alternative

Guide

How to use this ParseShelf resource.

When to use Python

Python is the best starting point for recurring research jobs, catalog QA scripts, pricing monitors and internal data pipelines. It works well when you want scheduled jobs, retries, export downloads and warehouse imports.

The quickstart keeps the workflow explicit: create the job, poll status, then download an export. That pattern is easier to debug than hiding the job lifecycle behind a black-box scraper function.

Production notes

Keep the API key in an environment variable, set request timeouts and store the job ID before polling. If a job is long-running, resume polling by job ID rather than creating a duplicate job.

For large ASIN lists, batch the inputs by research purpose or category. Smaller labeled jobs are easier for analysts to inspect in the dashboard and easier for engineers to compare over time.

Data handling

Use JSONL when every row should be processed independently. Use CSV when the output feeds a spreadsheet or BI import. Use XLSX when the end user expects a workbook and does not want to format columns manually.

The normalized product_id and product_url fields should be kept in downstream tables because they make deduplication and source attribution much easier.

Production checklist

Start with one small input and compare the delivered fields with the report, catalog or pipeline you actually need.

Keep the job ID, source URL, mode and run date with downstream exports so operators and developers can audit the same result.

PythonReference

import os
import time
import requests

base_url = "https://parseshelf.com"
headers = {"Authorization": f"Bearer {os.environ['PARSESHELF_KEY']}"}
job = requests.post(
    f"{base_url}/api/v1/jobs",
    headers=headers,
    json={
        "marketplace": "amazon",
        "input_type": "search_url",
        "input_value": "https://www.amazon.com/s?k=vitamin+c+serum&i=beauty",
        "mode": "full_product",
        "target_count": 50,
    },
    timeout=30,
).json()

while True:
    status = requests.get(f"{base_url}/api/v1/jobs/{job['id']}", headers=headers, timeout=30).json()
    if status["status"] in {"succeeded", "failed", "cancelled"}:
        break
    time.sleep(10)

csv_file = requests.get(f"{base_url}/api/v1/jobs/{job['id']}/download/csv", headers=headers, timeout=60)
open("amazon-products.csv", "wb").write(csv_file.content)

Open GitHub quickstart Python script Sample exports

Pick one Amazon input source: search URL, category URL, product URL list or ASIN list.
Use listing_only for broad discovery and full_product for richer product-page fields.
Keep product_id, source_url and product_url in downstream datasets for auditability.
Download JSONL for pipelines, CSV for imports, XLSX for operators and Markdown for reports.
Record job IDs so dashboard rows and API exports can be reconciled later.
Link related docs, samples and comparison pages when evaluating an Amazon data workflow.

Continue the Amazon data workflow.

FAQ

Amazon Product API Python Quickstart questions.

Does the Python example need a browser?

No. The Python example calls the ParseShelf API and downloads exports from completed jobs.

Does it require Amazon Product Advertising API credentials?

No. The example uses a ParseShelf API key rather than Amazon PA-API affiliate credentials.

Can I schedule it?

Yes. Store the API key securely and run the script from cron, Airflow or any scheduler.

Can Python download Excel files too?

Yes. Change the download format from csv to xlsx.