Publix Products Scraper

Publix Products Scraper creates a structured dataset of grocery products collected from Publix delivery and pickup catalogs. Each dataset item represents one product and can include name, brand, price, stock level, package size, image, and product URL. Query the source with a Publix collection or weekly-ad URL (url) plus a delivery or pickup location (location). Control the result limit with maxProducts, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, XML, or another supported format.

Dataset at a glance

Property	Value
Source	Publix delivery / pickup catalog (delivery.publix.com, publix.com)
Record unit	One Publix product for the selected location and service type
Input methods	Collection or weekly-ad URL (url) plus address or postal code (location)
Main identifiers	productId, product URL (url)
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML (Apify dataset exports)
Update model	Fresh records per Actor run
Pricing	$15 / 1,000 products

Coverage and available records

The Actor collects public Publix catalog products for one location and one service type per run.

• URL-based: url is a Publix collection or weekly-ad page (for example https://delivery.publix.com/store/publix/collections/rc-bogo-dry-grocery or https://www.publix.com/savings/weekly-ad/bogo).
• Location: location is an address or postal code used to resolve store-specific prices and availability (for example 2300 Griffin Road).
• Service type: serviceType is delivery (default) or pickup. Prices and stock can differ between the two.

Record types and limits:

• Product records include name, brand, price string, stock level, image, and product URL. Additional nested catalog fields from Publix may appear on the same item.
• Result cap: maxProducts limits how many products are collected (0 means unlimited, the default).

Known exclusions: content Publix only shows after login is not collected; each run captures catalog state at run time (no historical snapshots); assortment, prices, and stock are location-specific and are not a nationwide catalog.

Data dictionary

Field names below match dataset record JSON properties exactly. Values come from Publix for the selected location and service type. Nested catalog objects may also be present on the record; the fields below are the stable overview fields.

Field	Type	Nullable	Description	Example
productId	string	Yes	Publix product identifier; recommended deduplication key with location	34903
name	string	Yes	Product title	Pillsbury Ready to Bake! Chocolate Chip Cookies
brandName	string	Yes	Brand name as shown in the catalog	pillsbury
size	string	Yes	Package size as shown by Publix	16 oz
url	string	Yes	Product page URL; secondary deduplication key	https://delivery.publix.com/store/publix/products/34903-pillsbury-ready-to-bake-chocolate-chip-cookies-24-count-16-000-oz
priceString	string	Yes	Display price for the selected location	$6.69
stockLevel	string	Yes	Availability code as returned by Publix	highlyInStock
imageUrl	string	Yes	Primary product image URL	https://d2lnr5mha7bycj.cloudfront.net/product-image/file/large_f9ec7c17-d448-47d9-ba81-827578431fe7.png

The Actor does not calculate prices or stock. Combine productId with location and serviceType when you merge runs from different stores or fulfillment modes.

Example dataset record

Product from the BOGO dry-grocery collection at location 2300 Griffin Road with serviceType delivery.

{
  "productId": "34903",
  "name": "Pillsbury Ready to Bake! Chocolate Chip Cookies",
  "brandName": "pillsbury",
  "size": "16 oz",
  "url": "https://delivery.publix.com/store/publix/products/34903-pillsbury-ready-to-bake-chocolate-chip-cookies-24-count-16-000-oz",
  "stockLevel": "highlyInStock",
  "priceString": "$6.69",
  "imageUrl": "https://d2lnr5mha7bycj.cloudfront.net/product-image/file/large_f9ec7c17-d448-47d9-ba81-827578431fe7.png"
}

The record above was produced with this input:

{
  "url": "https://delivery.publix.com/store/publix/collections/rc-bogo-dry-grocery",
  "location": "2300 Griffin Road",
  "maxProducts": 10,
  "serviceType": "delivery"
}

Query and input reference

Input	Type	Required	Default	Accepted values	Description
url	string	Yes	Collection URL prefill	Publix collection or weekly-ad URL	Catalog page to collect products from
location	string	No	2300 Griffin Road	Address or postal code	Store / delivery location used for price and stock
maxProducts	integer	No	0	0 or any positive integer	Maximum products to collect; 0 = unlimited
serviceType	string	No	delivery	delivery, pickup	Fulfillment mode for prices and availability
proxyConfiguration	object	No	Apify proxy, RESIDENTIAL, country US	Apify proxy groups or custom proxies	Residential US proxies are recommended

Minimal request:

{
  "url": "https://delivery.publix.com/store/publix/collections/rc-bogo-dry-grocery",
  "location": "2300 Griffin Road"
}

Advanced request (pickup, capped):

{
  "url": "https://www.publix.com/savings/weekly-ad/bogo",
  "location": "4771 W Atlantic Ave",
  "maxProducts": 50,
  "serviceType": "pickup",
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" }
}

Retrieve the data through the API

Records are delivered through the Apify Actor and Dataset APIs — not an official Publix API.

1. Start the Actor with a JSON input (console or API).
2. Wait for the run to finish, or use a synchronous endpoint if you want the response inline.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset.

Python example:

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")

run_input = {
    "url": "https://delivery.publix.com/store/publix/collections/rc-bogo-dry-grocery",
    "location": "2300 Griffin Road",
    "maxProducts": 10,
    "serviceType": "delivery",
}

run = client.actor("datascrapers/publix-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("productId"), item.get("name"), item.get("priceString"))

Apify generates ready-to-run Python, JavaScript, and cURL examples on the Actor's API tab. Do not put a real API token in shared code or URLs.

Data quality and record handling

• Location dependence: price and stock apply to the resolved store for location and serviceType. The same productId can have different values at another address.
• Source changes: Publix catalog structure and values can change; unreadable fields are omitted or returned empty rather than fabricated.
• Deduplication: within a run, products are collected from the requested URL. Across runs, records are appended. Use productId plus location as the stable key.
• Normalization: priceString and stockLevel are stored as Publix returns them. The Actor does not convert price to a number.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL / Supabase	Dataset API poll or webhook consumer	Store location-level prices and stock
Google Sheets	Apify Google Sheets integration	Share weekly-ad and collection shortlists
PIM / catalog systems	Dataset API or completion webhook	Grocery-feed refresh
S3 / cloud storage	Scheduled export via Apify scheduler + integration	Archival of market snapshots

Pricing and cost examples

The Actor uses pay-per-event pricing. Each product written to the dataset is charged as a result. Residential proxies are recommended. Proxy and compute are billed by your Apify plan.

Event	Trigger	Rate
apify-default-dataset-item (result)	Each product written to the dataset	$0.015 / product ($15 / 1,000)

Example costs (plan-tier discounts not applied):

Records	Configuration	Estimated base cost
1,000	Products for one location	$15.00
10,000	Products for one location	$150.00

Estimates depend on the verified pricing model and the number of products collected.

Limitations and responsible data use

• The Actor collects publicly accessible Publix catalog data for the supplied location only.
• Field availability depends on what Publix renders at run time; some values can be empty or missing.
• The Actor does not provide historical snapshots unless you store them yourself. Prices and stock differ by store and service type.
• Large runs should use residential US proxies; without them, coverage may degrade.
• You are responsible for compliance with Publix's terms of service, applicable privacy law, and any contractual obligations before using the data.

Dataset questions

What does one dataset item represent?

One Publix product for the selected location and serviceType. Nested catalog fields, when present, stay on that same product record.

Which field should I use as a unique identifier?

productId is the recommended key within one location. Combine it with location and serviceType when you merge multi-store or delivery-versus-pickup runs. url is a reasonable secondary key.

Are fields nullable or conditional?

Yes. Brand, size, price, stock, and image can be empty when Publix does not render them for a product. Additional nested objects appear only when the catalog returns them.

Can I retrieve the records as CSV or JSON?

Yes. The dataset can be exported as JSON, CSV, Excel, XML, or HTML from the Apify Console, and queried through the Dataset API.

Does the Actor return historical data?

No. Each run captures catalog state at run time. To track price or stock changes, schedule repeated runs and store the outputs yourself.

What counts as a billable result?

Each product written to the dataset is charged at $0.015 ($15 per 1,000 products).

Related datasets from Data Scrapers

• Instacart Scraper — Grocery catalog products that can be compared with Publix prices and availability.
• Costco Product Scraper — Warehouse-club grocery and household products in overlapping categories.
• Target.com Product Scraper — US retail catalog records for the same price-monitoring pipelines.
• Lidl Product Scraper — European grocery and household products for cross-market comparison.
• Amazon Search Scraper — Marketplace search products that often overlap grocery and household SKUs.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.