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Dun and Bradstreet (DNB) Scraper

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Dun and Bradstreet (DNB) Scraper

Dun and Bradstreet (DNB) Scraper

curious_coder/dun-and-bradstreet-dnb-com-scraper
Try for free

1 day trial then $25.00/month - No credit card required now

Scrape companies and contacts details from DnB database based on industry, job title, employee count, entity types etc.

You can access the Dun and Bradstreet (DNB) 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    "action": "scrapeSearch",
10    "searchTerm": "marketing",
11    "searchType": "company",
12    "startPage": 1,
13    "proxy": {
14        "useApifyProxy": True,
15        "apifyProxyGroups": ["RESIDENTIAL"],
16        "apifyProxyCountry": "US",
17    },
18}
19
20# Run the Actor and wait for it to finish
21run = client.actor("curious_coder/dun-and-bradstreet-dnb-com-scraper").call(run_input=run_input)
22
23# Fetch and print Actor results from the run's dataset (if there are any)
24print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
25for item in client.dataset(run["defaultDatasetId"]).iterate_items():
26    print(item)
27
28# πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start

Dun and Bradstreet (DNB) Scraper API in Python

The Apify API client for Python is the official library that allows you to use Dun and Bradstreet (DNB) Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

Developer
Maintained by Community
Actor metrics
  • 13 monthly users
  • 2 stars
  • 12.9% runs succeeded
  • 0.51 hours response time
  • Created in Jun 2023
  • Modified 4 months ago