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| from apify_client import ApifyClient | |
| from dotenv import load_dotenv | |
| import os | |
| # Load environment variables from the .env file | |
| load_dotenv() | |
| # Initialize the ApifyClient with your API token | |
| APIFY_API_KEY= os.getenv("APIFY_API_KEY") | |
| client = ApifyClient(APIFY_API_KEY) | |
| # Prepare the Actor input | |
| run_input = { | |
| "action": "search_jobs", | |
| "country": "germany", | |
| "limit": 10, | |
| "title": "software engineer", | |
| "company": None, | |
| "site": None, | |
| "language": "en", | |
| "location": "berlin", | |
| "sort_field": "datetime_from", | |
| "sort_direction": -1, | |
| } | |
| # Run the Actor and wait for it to finish | |
| run = client.actor("3HJWd9KfGyItAD5N9").call(run_input=run_input, max_items=run_input["limit"]) | |
| # Fetch and print Actor results from the run's dataset (if there are any) | |
| for item in client.dataset(run["defaultDatasetId"]).iterate_items(): | |
| print(item) |