算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
walmart-keyword-search【设计与创意】Walmart keyword search scraper: input a search keyword and page number, navigate to walmart.com search results, extract paginated product listings with itemId, url, title, brand, image, price, wasPrice, rating, reviewCount, availability, seller info, fulfillmentBadge, classType, and shortDescription. Use when user mentions walmart search, walmart key…
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
keyword + page → paginated product list from walmart.com search results
All process output to user (progress updates, process notifications) follows the user's language.
Extract product listings from Walmart's keyword search results page, returning structured item data with pricing, rating, availability, and seller info.
https://www.walmart.com/search?q={keyword}&page={page}If browser-act has been confirmed available in the current session → skip this step.
Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.
This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the
scripts/directory, invoked viaeval "$(python scripts/xxx.py {params})".$(...)is bash syntax; it is recommended to use the bash tool for execution.
Below are all atomic capabilities discovered and verified during the exploration phase, listed by command template with parameters. Simply invoke them as needed — no need to read scripts/*.py source code or re-verify. Only inspect scripts when execution fails for troubleshooting. Combine freely as needed during execution.
Navigate to the target search URL first, then extract:
navigate "https://www.walmart.com/search?q={keyword}&page={page}&sort={sort}"wait stableeval "$(python scripts/extract-listing.py)"Parameters in URL:
{keyword}: URL-encoded search keyword (e.g., laptop, apple+iphone, running+shoes){page}: page number, starting from 1{sort}: sort order — best_match (default), price_low, price_high, rating_high, newOutput example:
{
"pageType": "SearchPage",
"query": "laptop",
"currentPage": 1,
"totalCount": 16174,
"maxPage": 12,
"itemCount": 57,
"items": [
{
"itemId": "18656507313",
"url": "https://www.walmart.com/ip/HP-14-N150-4-128-Blue/18656507313",
"title": "HP 14 inch HD Windows Laptop Intel Processor N150 4GB 128GB UFS Waterfall Blue",
"brand": null,
"image": "https://i5.walmartimages.com/seo/HP-14.jpeg",
"price": 229,
"priceString": "$229.00",
"wasPrice": null,
"rating": 4.2,
"reviewCount": 274,
"availability": "IN_STOCK",
"availabilityText": "In stock",
"sellerName": "Walmart.com",
"sellerType": null,
"fulfillmentBadge": null,
"classType": "VARIANT",
"shortDescription": null
}
]
}
Error response (when extraction fails or wrong page):
{"error": true, "message": "No searchResult in __NEXT_DATA__. Ensure the page is fully loaded at the correct search URL."}
sort [collection failed]: URL parameter values observed during exploration: best_match, price_low, price_high, rating_high, new. Full enum list not exposed via API or DOM; additional values may exist.
URL Pagination: URL pattern https://www.walmart.com/search?q={keyword}&page={N}&sort={sort}. Increment page by 1 each iteration. Termination: page > maxPage (from response maxPage field) OR itemCount === 0. Note: Walmart caps search results at maxPage (typically 11–25 pages max regardless of totalCount).
itemCount >= 1 AND items[0].itemId is non-null AND items[0].url starts with https://www.walmart.com/ip/
brand field is null for many items in search listing (available in product detail)shortDescription is null for most non-food items in search listingwasPrice is null unless the item has an active markdown/rollbacksellerType is null for Walmart.com first-party listingsPath: {working-directory}/browser-act-skill-forge-memories/walmart-scraper-walmart-keyword-search.memory.md (working directory is determined by the Agent running the Skill, typically the project root or current working directory)
Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.
After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line:
{YYYY-MM-DD}: {what happened} → {conclusion}
Normal execution does not write to the file. Do not record what keywords were used or how many results were returned — those are task outputs, not experience.