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Python data parsing: a laptop with a chart on a desk by a window at sunset
Demonstration example

A competitor price scraper

The example shows a Python script for monitoring competitor prices on 5 marketplaces (WB, Ozon, SberMegaMarket, Yandex Market, AliExpress). The script runs on a schedule, collects data for 120 SKUs and builds an Excel report with price dynamics and alerts.

PythonData scrapingSeleniumExcelAutomationMarketplaces

Example code and report

🐍Demonstration code fragment
def check_price(sku, marketplace): # Opens the product card and captures the current price price = fetch_current_price(sku, marketplace) previous = load_last_price(sku, marketplace) if previous and price < previous * 0.95: send_telegram_alert( f"⚠️ {marketplace}: price for {sku} dropped by {(1 - price/previous):.0%}" ) save_price_history(sku, marketplace, price) return price
📊Example rows of the Excel report
SKUMarketplacePrice todayYesterdayChange
SKU-10432Wildberries1 290 ₽1 490 ₽−13.4% ⚠️
SKU-10432Ozon1 350 ₽1 350 ₽—
SKU-20187Yandex Market2 490 ₽2 190 ₽+13.7%

Results

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What the parser can do

Website data scraping in this example works like this: the script walks through competitors' pages, captures prices and stock, and puts everything into a table. Product parsing covers the whole catalogue, not individual links.

Competitor price monitoring runs on the same code on a schedule: once a day the table is updated, and you can see who changed their price and by how much.

See also