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57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
"""
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Basic example of scraping pipeline using SmartScraper with a custom rate limit
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"""
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import os
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from dotenv import load_dotenv
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from scrapegraphai.graphs import SmartScraperGraph
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from scrapegraphai.utils import prettify_exec_info
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# required environment variable in .env
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# AZURE_OPENAI_ENDPOINT
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# AZURE_OPENAI_CHAT_DEPLOYMENT_NAME
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# MODEL_NAME
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# AZURE_OPENAI_API_KEY
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# OPENAI_API_TYPE
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# AZURE_OPENAI_API_VERSION
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# AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME
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load_dotenv()
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# ************************************************
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# Initialize the model instances
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# ************************************************
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graph_config = {
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"llm": {
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"api_key": os.environ["AZURE_OPENAI_KEY"],
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"model": "azure_openai/gpt-4o",
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"rate_limit": {
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"requests_per_second": 1
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},
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},
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"verbose": True,
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"headless": False
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}
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smart_scraper_graph = SmartScraperGraph(
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prompt="""List me all the events, with the following fields: company_name, event_name, event_start_date, event_start_time,
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event_end_date, event_end_time, location, event_mode, event_category,
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third_party_redirect, no_of_days,
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time_in_hours, hosted_or_attending, refreshments_type,
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registration_available, registration_link""",
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# also accepts a string with the already downloaded HTML code
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source="https://www.hmhco.com/event",
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config=graph_config
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)
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result = smart_scraper_graph.run()
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print(result)
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# ************************************************
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# Get graph execution info
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# ************************************************
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graph_exec_info = smart_scraper_graph.get_execution_info()
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print(prettify_exec_info(graph_exec_info))
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