Pharmacy Price Checker - Compare Drug Prices GoodRx avatar

Pharmacy Price Checker - Compare Drug Prices GoodRx

Pricing

Pay per usage

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Pharmacy Price Checker - Compare Drug Prices GoodRx

Pharmacy Price Checker - Compare Drug Prices GoodRx

Check pharmacy prescription pricing via GoodRx. Compare drug prices, find coupons, and calculate savings across pharmacies.

Pricing

Pay per usage

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Developer

Donny Nguyen

Donny Nguyen

Maintained by Community

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2

Total users

1

Monthly active users

a day ago

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Pharmacy Price Checker - Drug Price Comparison

What does Pharmacy Price Checker - Drug Price Comparison do?

Compare pharmacy drug prices via GoodRx. Find lowest prices, coupons, and savings on prescriptions. This Apify actor automates the data extraction process so you can collect structured data without writing any code. The results are delivered in clean JSON, CSV, or Excel format, ready for analysis, integration, or storage in your database or data warehouse.

Why use Pharmacy Price Checker - Drug Price Comparison?

  • No coding required — Simply configure your inputs in the Apify Console and click Start. No programming knowledge is needed to extract professional-grade data.
  • Export in multiple formats — Download your results as JSON, CSV, Excel, or connect directly via the Apify API for seamless programmatic access to your data.
  • Scheduled and automated runs — Set up recurring schedules to keep your data fresh. Run hourly, daily, or weekly with automatic email or webhook notifications when new data is ready.
  • Built-in proxy rotation — The actor handles proxy management and rotation automatically to ensure reliable data collection, avoid rate limiting, and maintain high success rates.
  • Scalable extraction — Process hundreds or thousands of items in a single run. The actor manages concurrency, retries, error handling, and memory allocation for you.
  • Reliable error handling — If individual requests fail, the actor retries them automatically and continues processing the remaining items. You get partial results even if some pages are unavailable.

How to use Pharmacy Price Checker - Drug Price Comparison

  1. Navigate to the Pharmacy Price Checker - Drug Price Comparison page on Apify Store and click Try for free to open the actor in Apify Console.
  2. Configure your input parameters using the visual editor in the Input tab. Set your search terms, URLs, or other parameters according to your needs.
  3. Click Start to begin the extraction. The actor will run in the Apify cloud and you can monitor progress in real time from the Log tab.
  4. Once complete, view your results in the Output tab. The data is displayed in a formatted overview table for easy browsing and quick analysis.
  5. Download your data as JSON, CSV, or Excel using the export buttons, or access it programmatically via the Apify API or direct dataset endpoint URLs.

Input configuration

FieldTypeDescriptionDefault
Drug NamesarrayList of drug names to look up pricing for (e.g. metformin, lisinopril, atorvastatin).["metformin","lisinopril"]
Direct GoodRx URLsarrayOptional direct GoodRx URLs to scrape. Use this if you have specific drug pages to check.[]
Max ResultsintegerMaximum number of price results to extract across all drugs.50
Use Residential ProxybooleanUse residential proxies for better success rates. Recommended for GoodRx as it has anti-bot protection.false

Output data

The actor stores results in a structured dataset. Each item in the dataset represents one extracted record and contains the following key fields:

  • Drug Name (drugName)
  • Generic Name (genericName)
  • Brand Name (brandName)
  • Lowest Price (lowestPrice)
  • Retail Price (retailPrice)
  • Savings (savings)
  • Savings Percent (savingsPercent)
  • Pharmacy Name (pharmacyName)

Each run also includes a scrapedAt timestamp indicating when the data was collected. You can use this field to track data freshness across multiple runs.

Example output:

{
"drugName": "Example drug name",
"genericName": "Example generic name",
"brandName": "Example brand name",
"lowestPrice": "Example lowest price",
"retailPrice": "Example retail price",
"savings": "Example savings",
"savingsPercent": "Example savings percent",
"pharmacyName": "Example pharmacy name",
"scrapedAt": "2026-02-18T00:00:00.000Z"
}

You can preview the data in the formatted Overview table on the Output tab, which displays the most important fields in an easy-to-read format. The full dataset with all fields is available for download or API access.

Cost of usage

This actor is priced using Apify's Pay-Per-Event model. Each successfully extracted result costs approximately $0.003 per item ($3.00 per 1,000 results).

  • Extracting 100 results costs approximately $0.30
  • Extracting 1,000 results costs approximately $3.00
  • On the free Apify plan ($5/month platform credit), you can extract approximately 1,666 results per month

Platform usage costs (compute units for memory and CPU time) are charged separately by Apify at standard rates. Most runs of this actor complete quickly with minimal compute overhead, so the per-event charge represents the majority of the total cost.

Tips and advanced usage

This actor uses a headless browser (Puppeteer) to render JavaScript-heavy pages. It requires more memory than simple HTTP scrapers but can handle dynamic content that loads via JavaScript. The default memory allocation is optimized for most use cases, but you can increase it for sites with heavy JavaScript or many concurrent pages.

You can schedule this actor to run automatically at regular intervals using Apify Schedules. This is ideal for monitoring price changes, tracking new listings, aggregating fresh data, or keeping your dataset up to date without manual intervention. Schedules support cron expressions for precise timing control.

For large-scale extraction or integration into automated workflows, use the Apify API to start runs programmatically and retrieve results directly into your data pipeline. The actor integrates seamlessly with tools like Google Sheets, Zapier, Make (Integromat), and n8n for building automated data workflows. You can also use webhooks to trigger downstream actions when a run completes successfully.


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