Dun & Bradstreet Business Directory Scraper
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Dun & Bradstreet Business Directory Scraper
2 hours trial then $15.00/month - No credit card required now
Extract company information such as name, sales revenue, address, and URL from the DNB directory. Get an overview of the number of companies that can be scraped.
You can access the Dun & Bradstreet Business Directory Scraper programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9 "listingUrls": [{ "url": "https://www.dnb.com/business-directory/company-information.manufacturing.eg.html" }],
10 "maxPagesPerListing": 1,
11 "overviewCountryName": "",
12 "proxy": {
13 "useApifyProxy": True,
14 "apifyProxyCountry": "CA",
15 "apifyProxyGroups": ["RESIDENTIAL"],
16 },
17}
18
19# Run the Actor and wait for it to finish
20run = client.actor("mscraper/dun-bradstreet-business-directory-scraper").call(run_input=run_input)
21
22# Fetch and print Actor results from the run's dataset (if there are any)
23print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
24for item in client.dataset(run["defaultDatasetId"]).iterate_items():
25 print(item)
26
27# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startDun & Bradstreet Business Directory Scraper API in Python
The Apify API client for Python is the official library that allows you to use Dun & Bradstreet Business Directory Scraper API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
pip install apify-clientOther API clients include:
mscraperActor Metrics
12 monthly users
-
4 stars
>99% runs succeeded
Created in Jul 2023
Modified 14 hours ago
