scraper handoff + updated reqs
This commit is contained in:
coleWesterveld
parent
725f028d69
commit
b1f3115999
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@ -1,2 +1,4 @@
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.env
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marketline_cookies.json
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marketline_cookies.json
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venv/
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marketline_session/
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@ -240,8 +240,8 @@ def main():
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# basic required-field check (we want the API-required fields present)
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if not is_valid_transaction(tx):
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print(" ⚠️ Skipping — missing required API fields in extracted transaction:", tx)
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continue
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print(" ⚠️ missing required API fields in extracted transaction:", tx)
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#continue
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# Optionally normalize some fields (convert "amount" to a canonical string) - keep simple for now
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# Save the item
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@ -1 +1 @@
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*.json
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*.json
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@ -1,186 +1,138 @@
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# NOT USED CURRENTLY
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# temporairily, if not permanently switched to using the handoff file to get around captchas and stuff
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# the handoff is very similar anyways
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import asyncio
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from playwright.async_api import async_playwright, Page
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from playwright.async_api import async_playwright
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import json
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import os
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from crawl4ai import BrowserConfig, AsyncWebCrawler, CrawlerRunConfig
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from crawl4ai.deep_crawling import BFSDeepCrawlStrategy
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from crawl4ai.content_scraping_strategy import ContentScrapingStrategy, ScrapingResult, LXMLWebScrapingStrategy
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from crawl4ai.processors.pdf import PDFContentScrapingStrategy
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from crawl4ai.deep_crawling import DFSDeepCrawlStrategy, BFSDeepCrawlStrategy, BestFirstCrawlingStrategy
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from crawl4ai.content_scraping_strategy import LXMLWebScrapingStrategy
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from crawl4ai.deep_crawling.scorers import KeywordRelevanceScorer
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from crawl4ai.deep_crawling.filters import URLPatternFilter
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from datetime import datetime
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import logging
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import time
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# --- CONFIGURATION ---
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# TODO: this will need to change for different organizations (ie univiersities)
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# make this the link for university login when accessing marketline
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LOGIN_URL = "https://login.microsoftonline.com/be62a12b-2cad-49a1-a5fa-85f4f3156a7d/saml2?SAMLRequest=fZLBbtswEER%2FReBdokhJjk1YBtz4UANpasRODrkUK2plE6BIlUsl7d9Xtls0ufhIcPhmZ5ZLgt4Oaj3Gk3vCnyNSTH711pG6XNRsDE55IEPKQY%2Bkolb79bcHJbNcDcFHr71lyZoIQzTe3XtHY49hj%2BHNaHx%2BeqjZKcaBFOcwmWTWNNnojyPa4ZRp4NP5%2BE4D359M03iLk4TI87OH5Lvv%2BwNLNtNQxsEZ%2Fx9m%2FdG4rDc6ePJd9M4ah5n2PW9wJkHIJpUa2rRcgEih6iCdV13ZFaKawV3Lz%2BkkS7abmv1Y6Hne5lgVQhSFkPlMgABcdHPddvOmnE0yohG3jiK4WDOZyyrN71K5OEipylIV8pUlu79lfDGuNe54u7nmKiL19XDYpdeYLxjoEnESsNXyPKG6GIcPG7mNhX9rYKubpdOw5B%2F4V7NBPU7A7WbnrdG%2Fk7W1%2Fv0%2BIESsmWB8dX3y%2Ba%2Bs%2FgA%3D&RelayState=https%3A%2F%2Fauth.lib.uoguelph.ca%2Fopenathens%2Fsaml%2F%3Fuuid%3Db3nuk1o5lh78w6j657yd773oxfeqzc0v%26csrfmiddlewaretoken%3D4EzWMhPgP6L5YXtK3FGIgKKQ5KguVDwOuod2abzLQRV6kagUu0BBVWsJVI8N78tT%26opshib%3DLogin%2Bwith%2Byour%2BGryphmail%2BPassword%26staff_mode%3DTrue&sso_reload=true"
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# shouldnt need to change. this is what we will wait for to load after logging in to trigger saving cookies.
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LOGIN_URL = "https://login.microsoftonline.com/be62a12b-2cad-49a1-a5fa-85f4f3156a7d/saml2?SAMLRequest=fZLBbtswEER%2FReBdokhJjk1YBtz4UANpasRODrkUK2plE6BIlUsl7d9Xtls0ufhIcPhmZ5ZLgt4Oaj3Gk3vCnyNSTH711pG6XNRsDE55IEPKQY%2Bkolb79bcHJbNcDcFHr71lyZoIQzTe3XtHY49hj%2BHNaHx%2BeqjZKcaBFOcwmWTWNNnojyPa4ZRp4NP5%2BE4D359M03iLk4TI87OH5Lvv%2BwNLNtNQxsEZ%2Fx9m%2FdG4rDc6ePJd9M4ah5n2PW9wJkHIJpUa2rRcgEih6iCdV13ZFaKawV3Lz%2BkkS7abmv1Y6Hne5lgVQhSFkPlMgABcdHPddvOmnE0yohG3jiK4WDOZyyrN71K5OEipylIV8pUlu79lfDGuNe54u7nmKiL19XDYpdeYLxjoEnESsNXyPKG6GIcPG7mNhX9rYKubpdOw5B%2F4V7NBPU7A7WbnrdG%2Fk7W1%2Fv0%2BIESsmWB8dX3y%2Ba%2Fs%2FgA%3D&RelayState=https%3A%2F%2Fauth.lib.uoguelph.ca%2Fopenathens%2Fsaml%2F%3Fuuid%3Db3nuk1o5lh78w6j657yd773oxfeqzc0v%26csrfmiddlewaretoken%3D4EzWMhPgP6L5YXtK3FGIgKKQ5KguVDwOuod2abzLQRV6kagUu0BBVWsJVI8N78tT%26opshib%3DLogin%2Bwith%2Byour%2BGryphmail%2BPassword%26staff_mode%3DTrue&sso_reload=true"
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LOGIN_URL = "https://login.microsoftonline.com/be62a12b-2cad-49a1-a5fa-85f4f3156a7d/saml2?SAMLRequest=fVLBbsIwDP2VKvc2aaBAI4rE4DAktiFgO%2BwypcGFSGnSxenY%2Fn4FNo1dOFp%2Bfs%2Fv2WOUtWnEtA0Hu4b3FjBEn7WxKM6NgrTeCidRo7CyBhRBic30YSl4wkTjXXDKGRJNEcEH7ezMWWxr8BvwH1rB83pZkEMIDQpKZSeSGF0mrdu3YJpDoiTt6v0RG7o56LJ0BjoIoqMnDU5XT5stiebdUtrKE%2F0fmXF7bZNaK%2B%2FQVcFZoy0kytW0hAGXKS9jruQu7ucyjWVWyXiUVf2ql2YDOdzRkztOosW8IG9pztRI5izLh9BPcz5i%2BY4N0q6oFAz7vQ6G2MLCYpA2FIQznsUsj1lvy5hgPcGGryRa%2FYRxp%2B1O2%2F3t5MoLCMX9druKLzZfwOPZYgcgk%2FFpQ3EW9lcXuU0rf89AJjdDx2ZMr%2FgvYo147AgX85UzWn1FU2PcceZBBihISujkMvL%2FVybf&RelayState=https%3A%2F%2Fauth.lib.uoguelph.ca%2Fopenathens%2Fsaml%2F%3Fuuid%3Dsa3ysaynan5loqzpdleq8f1v4ji31utw%26csrfmiddlewaretoken%3DVnbRmbY0l1tnxKqHdJnkZ1yYGlJgPueoiNOMivmejDxCbeVl3A0iV5FdEFmO3DgG%26opshib%3DLogin%2Bwith%2Byour%2BGryphmail%2BPassword%26staff_mode%3DTrue"
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HOMEPAGE_URL = "https://advantage.marketline.com/HomePage/Home"
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# the root page to seed crawling
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CRAWLPAGE_URL = "https://advantage.marketline.com/Search?industry=2800001"
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# trying out another page
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# CRAWLPAGE_URL = "https://www.defensenews.com/"
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# name of file where cookies are saved
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CRAWLPAGE_URL = "https://advantage.marketline.com/News/NewsListing?q[]=aerospace+and+defense&IsSearchApi=true"
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COOKIES_FILE = "marketline_cookies.json"
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# --- CRAWLER SETTINGS ---
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DEPTH = 3
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COUNT = 100
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# TODO: maybe make this list more comprehensive?
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DEPTH = 2 # A depth of 2 is enough: Page 1 (List) -> Page 2 (Articles)
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COUNT = 50
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# UPDATED: Expanded keywords to better score article pages
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SCRAPER_KEYWORDS = [
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# Core Terms
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"arms export", "arms sale", "arms trade", "weapons export", "weapons deal",
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"military export", "defence contract", "defense contract",
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# Canadian Context
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"canadian armed forces", "global affairs canada", "canadian defence",
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"canadian military", "royal canadian navy", "royal canadian air force",
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# Equipment & Technology
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"armoured vehicle", "light armoured vehicle", "lav", "naval ship", "warship",
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"frigate", "fighter jet", "military aircraft", "surveillance", "radar",
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"artillery", "munitions", "firearms", "aerospace",
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# Action & Policy Terms
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"procurement", "acquisition", "military aid", "export permit", "itar"
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"arms", "weapons", "military", "defence", "defense", "aerospace",
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"canadian armed forces", "caf", "dnd", "global affairs canada",
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"export", "sale", "contract", "procurement", "acquisition",
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"armoured vehicle", "lav", "naval", "warship", "frigate", "fighter jet",
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"aircraft", "surveillance", "radar", "drone", "uav", "missile", "artillery",
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"general dynamics", "lockheed martin", "bombardier", "cae", "thales canada", "wescam"
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]
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# runs login process and saves cookies so that we can run the scraping with authentication
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async def login_and_save_cookies():
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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async def login_and_save_cookies():
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=False)
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context = await browser.new_context()
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page = await context.new_page()
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try:
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logging.info("Starting login process... Please complete login in the browser.")
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await page.goto(LOGIN_URL)
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await page.wait_for_url(HOMEPAGE_URL, timeout=300000)
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print("Login detected. Saving session cookies...")
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time.sleep(45)
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# await page.wait_for_url(HOMEPAGE_URL, timeout=300000)
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logging.info("Login successful. Saving session cookies...")
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cookies = await context.cookies()
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with open(COOKIES_FILE, "w") as f:
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json.dump(cookies, f)
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print("Cookies saved successfully!")
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await crawl_with_saved_cookies()
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json.dump(cookies, f, indent=2)
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logging.info(f"Cookies saved to '{COOKIES_FILE}'.")
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except Exception as e:
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print(f"Login failed: {e}")
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print("Error details:")
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print(await page.content())
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logging.error(f"Login failed: {e}")
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finally:
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await context.close()
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await browser.close()
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def save_results_to_json(successful_data, failed_pages):
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"""
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Saves the successful and failed crawl results into separate JSON files
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in a dedicated directory.
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"""
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output_dir = "crawl_results"
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_dir = f"crawl_results_{timestamp}"
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os.makedirs(output_dir, exist_ok=True)
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print(f"\n💾 Saving results to '{output_dir}' directory...")
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logging.info(f"Saving results to '{output_dir}' directory...")
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# Define file paths
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successful_file = os.path.join(output_dir, "successful_pages.json")
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failed_file = os.path.join(output_dir, "failed_pages.json")
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# Save successfully scraped data
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with open(successful_file, "w", encoding="utf-8") as f:
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json.dump(successful_data, f, indent=4, ensure_ascii=False)
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print(f" Saved data for {len(successful_data)} successful pages to '{successful_file}'")
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logging.info(f"Saved {len(successful_data)} pages to '{successful_file}'")
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# Save failed pages if any
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if failed_pages:
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failed_file = os.path.join(output_dir, "failed_pages.json")
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with open(failed_file, "w", encoding="utf-8") as f:
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json.dump(failed_pages, f, indent=4, ensure_ascii=False)
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print(f" Saved info for {len(failed_pages)} failed pages to '{failed_file}'")
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logging.info(f"Saved {len(failed_pages)} failed pages to '{failed_file}'")
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# runs the crawler with the cookies collected during login
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async def crawl_with_saved_cookies():
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if not os.path.exists(COOKIES_FILE):
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print("No cookies found. Please run login first.")
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return
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logging.warning("No cookies found. Running login first...")
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await login_and_save_cookies()
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if not os.path.exists(COOKIES_FILE):
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logging.error("Login failed or was aborted. Exiting.")
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return
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with open(COOKIES_FILE, "r") as f:
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cookies = json.load(f)
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try:
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cookies = json.load(f)
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except json.JSONDecodeError:
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logging.error(f"Error reading cookies file. Please delete '{COOKIES_FILE}' and run again.")
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return
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browser_config = BrowserConfig(cookies=cookies)
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logging.info(f"Loaded {len(cookies)} cookies for crawling.")
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browser_config = BrowserConfig(cookies=cookies, headless=False)
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# NEW: Define a filter to only follow links that are news articles
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article_filter = URLPatternFilter(patterns=[r"/news/"])
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config = CrawlerRunConfig(
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deep_crawl_strategy=BFSDeepCrawlStrategy(
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deep_crawl_strategy=BestFirstCrawlingStrategy(
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max_depth=DEPTH,
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max_pages=COUNT,
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url_scorer=KeywordRelevanceScorer(keywords=SCRAPER_KEYWORDS,),
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#url_scorer=(),
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# url_filters=[article_filter] # UPDATED: Add the filter to the strategy
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),
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scraping_strategy=LXMLWebScrapingStrategy(),
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# TODO: scrape the PDFs better
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# scraping_strategy=PDFCrawlerStrategy(),
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verbose=True,
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stream=True,
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page_timeout=30000
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# scraping_strategy=
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# LXMLWebScrapingStrategy(),
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verbose=True, stream=True, page_timeout=120000,
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wait_until="domcontentloaded"
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)
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successful_data = []
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failed_pages = []
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logging.info("Starting crawl...")
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async with AsyncWebCrawler(config=browser_config) as crawler:
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# We start with the list page. The filter will ensure we only crawl article links from it.
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async for result in await crawler.arun(CRAWLPAGE_URL, config=config):
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if result.success:
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depth = result.metadata.get("depth", 0)
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print("RESIULT:", result)
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score = result.metadata.get("score", 0)
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# here we could look at a few things, the HTML, markdown, raw text, etc.
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scraped_content = result.markdown
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print(f"✅ Depth {depth} | Score: {score:.2f} | {result.url}")
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# NEW: Print a preview of the content to confirm it's being scraped
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print(f" 📄 Content length: {len(scraped_content)}. Preview: {scraped_content[:120]}...")
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print(f"✅ Scraped: {result.url} (Score: {score:.2f})")
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successful_data.append({
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"url": result.url,
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"content": scraped_content,
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"depth": depth,
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"score": round(score, 2)
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"url": result.url, "content": result.markdown,
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"depth": result.metadata.get("depth", 0), "score": round(score, 2),
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"timestamp": datetime.now().isoformat()
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})
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else:
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failed_pages.append({
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'url': result.url,
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'error': result.error_message,
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'depth': result.metadata.get("depth", 0)
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})
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print(f"❌ Failed: {result.url} - {result.error_message}")
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print(f"📊 Results: {len(successful_data)} successful, {len(failed_pages)} failed")
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failed_pages.append({'url': result.url, 'error': result.error_message})
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logging.info(f"Crawl completed! Successful: {len(successful_data)}, Failed: {len(failed_pages)}")
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save_results_to_json(successful_data, failed_pages)
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# Analyze failures by depth
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if failed_pages:
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failure_by_depth = {}
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for failure in failed_pages:
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depth = failure['depth']
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failure_by_depth[depth] = failure_by_depth.get(depth, 0) + 1
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print("❌ Failures by depth:")
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for depth, count in sorted(failure_by_depth.items()):
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print(f" Depth {depth}: {count} failures")
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if __name__ == "__main__":
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# Choose which function to run
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# 1. First, run the login function once to get your cookies
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# asyncio.run(login_and_save_cookies())
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# 2. Then, comment out the login line and run the crawl
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asyncio.run(crawl_with_saved_cookies())
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@ -0,0 +1,176 @@
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# like the crawler but with a session hand off instead of a cookies sharing approach
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# opens non-headless browser, user logs in and does captchas and then hands off to scraper
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# more reliable, easier to debug and captcha resistant
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import asyncio
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from itertools import chain
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from playwright.async_api import async_playwright
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import json
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import os
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from crawl4ai import BrowserConfig, AsyncWebCrawler, CrawlerRunConfig
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from crawl4ai.deep_crawling import BestFirstCrawlingStrategy
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from crawl4ai.deep_crawling.filters import URLPatternFilter
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from datetime import datetime
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import logging
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from crawl4ai.deep_crawling.scorers import KeywordRelevanceScorer
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from crawl4ai.deep_crawling.filters import FilterChain, URLPatternFilter
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# --- CONFIGURATION ---
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# MODIFIED: Only the login URL is needed for the initial navigation.
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# The user will navigate to the crawl starting page manually.
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LOGIN_URL = "https://guides.lib.uoguelph.ca/az/databases?q=marketline"
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# --- CRAWLER SETTINGS ---
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DEPTH = 2
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COUNT = 50
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SCRAPER_KEYWORDS = [
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"arms", "weapons", "military", "defence", "defense", "aerospace",
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"canadian armed forces", "caf", "dnd", "global affairs canada",
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"export", "sale", "contract", "procurement", "acquisition",
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"armoured vehicle", "lav", "naval", "warship", "frigate", "fighter jet",
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"aircraft", "surveillance", "radar", "drone", "uav", "missile", "artillery",
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"general dynamics", "lockheed martin", "bombardier", "cae", "thales canada", "wescam"
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]
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# class DebugFilter(BaseFilter):
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# def apply(self, urls):
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# print("\n=== LINKS BEFORE FILTERING ===")
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# for u in urls:
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# print(u)
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# return urls # don’t drop anything
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include_words = URLPatternFilter(patterns=["*News*", "*news*"])
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deny_words = URLPatternFilter(patterns=["*Analysis*", "*Sectors*", "*Commentsandopinions*", "*Dashboard*", "*Homepage*"], reverse=True)
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# --- SETUP LOGGING ---
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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|
||||
def save_results_to_json(successful_data, failed_pages):
|
||||
"""Saves the crawl results to timestamped JSON files in a new directory."""
|
||||
# timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
|
||||
# could timestamp this but im not cuz its easier to analyze.
|
||||
# later we will prolly have one folder with all the timestamped files that we will go through regex'd
|
||||
# for now well just overwrite.
|
||||
output_dir = f"crawl_results"
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
logging.info(f"Saving results to '{output_dir}' directory...")
|
||||
|
||||
successful_file = os.path.join(output_dir, "successful_pages.json")
|
||||
with open(successful_file, "w", encoding="utf-8") as f:
|
||||
json.dump(successful_data, f, indent=4, ensure_ascii=False)
|
||||
logging.info(f"Saved {len(successful_data)} successful pages to '{successful_file}'")
|
||||
|
||||
if failed_pages:
|
||||
failed_file = os.path.join(output_dir, "failed_pages.json")
|
||||
with open(failed_file, "w", encoding="utf-8") as f:
|
||||
json.dump(failed_pages, f, indent=4, ensure_ascii=False)
|
||||
logging.info(f"Saved {len(failed_pages)} failed pages to '{failed_file}'")
|
||||
|
||||
async def main():
|
||||
"""
|
||||
Main function to handle manual login, capture the session state from the
|
||||
active tab, and then hand it off to the crawler.
|
||||
"""
|
||||
# --- STEP 1: Manual Login in a Temporary Browser ---
|
||||
async with async_playwright() as p:
|
||||
browser = await p.chromium.launch(headless=False)
|
||||
context = await browser.new_context()
|
||||
page = await context.new_page() # This is the initial page
|
||||
|
||||
logging.info("A browser window has opened. Please complete the following steps:")
|
||||
logging.info(f"1. Log in and navigate to the exact page where you want the crawl to begin.")
|
||||
logging.info("2. Solve any CAPTCHAs or 2FA prompts.")
|
||||
await page.goto(LOGIN_URL)
|
||||
|
||||
input("\n>>> Press Enter in this console window once you are logged in and on the starting page... <<<\n")
|
||||
|
||||
# MODIFIED: Instead of using the original 'page' object, get the current active tab.
|
||||
# This correctly handles cases where the login process opens a new tab.
|
||||
print("ALL PAGES:")
|
||||
for page in context.pages:
|
||||
print("URL: ", page.url)
|
||||
active_page = context.pages[-1]
|
||||
start_url = "https://advantage.marketline.com/News/NewsListing?q%5B%5D=aerospace+and+defence&IsSearchApi=true&exactword=1"
|
||||
|
||||
logging.info(f"Login complete. Using active tab URL to start crawl: {start_url}")
|
||||
|
||||
# Capture the full session state (cookies, localStorage, etc.)
|
||||
storage_state = await context.storage_state()
|
||||
|
||||
# We no longer need this temporary browser.
|
||||
await browser.close()
|
||||
|
||||
# --- STEP 2: Configure and Run the Crawler with the Captured State ---
|
||||
|
||||
# Pass the captured 'storage_state' dictionary to the crawler's browser configuration.
|
||||
browser_config = BrowserConfig(
|
||||
headless=False,
|
||||
storage_state=storage_state # This injects your logged-in session.
|
||||
)
|
||||
|
||||
scorer = KeywordRelevanceScorer(
|
||||
keywords=SCRAPER_KEYWORDS,
|
||||
weight=0.7
|
||||
)
|
||||
|
||||
filter = FilterChain([
|
||||
# DebugFilter(),
|
||||
include_words,
|
||||
deny_words
|
||||
])
|
||||
|
||||
# This configuration remains the same
|
||||
config = CrawlerRunConfig(
|
||||
|
||||
deep_crawl_strategy=BestFirstCrawlingStrategy(
|
||||
max_depth=DEPTH,
|
||||
max_pages=COUNT,
|
||||
url_scorer=scorer,
|
||||
filter_chain=filter
|
||||
),
|
||||
verbose=True,
|
||||
stream=True,
|
||||
page_timeout=120000,
|
||||
wait_until="domcontentloaded"
|
||||
)
|
||||
|
||||
successful_data = []
|
||||
failed_pages = []
|
||||
|
||||
logging.info("Starting crawler with the captured session state...")
|
||||
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
# The crawler will now begin at the correct URL you navigated to.
|
||||
async for result in await crawler.arun(start_url, config=config):
|
||||
if result.success:
|
||||
all_links = [
|
||||
l["href"]
|
||||
for l in chain(result.links.get("internal", []), result.links.get("external", []))
|
||||
]
|
||||
|
||||
print(f"✅ Scraped: {result.url}")
|
||||
print("Filtered links:")
|
||||
|
||||
# Apply filters one URL at a time
|
||||
for url in all_links:
|
||||
if include_words.apply(url) and deny_words.apply(url):
|
||||
print(" ->", url)
|
||||
score = result.metadata.get("score", 0)
|
||||
print(f"✅ Scraped: {result.url} (Score: {score:.2f})")
|
||||
successful_data.append({
|
||||
"url": result.url, "content": result.markdown,
|
||||
"depth": result.metadata.get("depth", 0), "score": round(score, 2),
|
||||
"timestamp": datetime.now().isoformat()
|
||||
})
|
||||
else:
|
||||
print(f"❌ Failed: {result.url} - {result.error_message}")
|
||||
failed_pages.append({'url': result.url, 'error': result.error_message})
|
||||
|
||||
logging.info(f"Crawl completed! Successful: {len(successful_data)}, Failed: {len(failed_pages)}")
|
||||
save_results_to_json(successful_data, failed_pages)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
|
|
@ -0,0 +1,93 @@
|
|||
import asyncio
|
||||
import os
|
||||
import json
|
||||
from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
|
||||
from crawl4ai.processors.pdf import PDFCrawlerStrategy, PDFContentScrapingStrategy
|
||||
# import database
|
||||
|
||||
# --- Configuration ---
|
||||
PDF_QUEUE_FILE = "pdf_queue.txt"
|
||||
COOKIES_FILE = "marketline_cookies.json"
|
||||
IMAGE_OUTPUT_DIR = "./extracted_images"
|
||||
CHECK_INTERVAL_SECONDS = 60
|
||||
|
||||
def load_cookies():
|
||||
"""Loads cookies from the JSON file if it exists."""
|
||||
if not os.path.exists(COOKIES_FILE):
|
||||
print("Warning: cookies.json not found. Crawling without authentication.")
|
||||
return None
|
||||
with open(COOKIES_FILE, 'r') as f:
|
||||
cookies = json.load(f)
|
||||
return {c['name']: c['value'] for c in cookies}
|
||||
|
||||
async def process_pdf_queue(cookies):
|
||||
"""
|
||||
Processes all unique URLs found in the PDF queue file.
|
||||
"""
|
||||
if not os.path.exists(PDF_QUEUE_FILE):
|
||||
return
|
||||
|
||||
print("--- Checking PDF queue for new links ---")
|
||||
with open(PDF_QUEUE_FILE, "r") as f:
|
||||
urls_to_process = set(line.strip() for line in f if line.strip())
|
||||
|
||||
if not urls_to_process:
|
||||
print("PDF queue is empty.")
|
||||
return
|
||||
|
||||
print(f"Found {len(urls_to_process)} PDF(s) to process.")
|
||||
os.makedirs(IMAGE_OUTPUT_DIR, exist_ok=True)
|
||||
|
||||
pdf_scraping_cfg = PDFContentScrapingStrategy(
|
||||
extract_images=True,
|
||||
save_images_locally=True,
|
||||
image_save_dir=IMAGE_OUTPUT_DIR,
|
||||
)
|
||||
pdf_run_cfg = CrawlerRunConfig(scraping_strategy=pdf_scraping_cfg)
|
||||
|
||||
async with AsyncWebCrawler(crawler_strategy=PDFCrawlerStrategy()) as crawler:
|
||||
for url in urls_to_process:
|
||||
print(f"\nProcessing PDF: {url}")
|
||||
try:
|
||||
result = await crawler.arun(url=url, config=pdf_run_cfg, cookies=cookies)
|
||||
if not result.success:
|
||||
print(f"Failed to process PDF {result.url}. Error: {result.error_message}")
|
||||
continue
|
||||
|
||||
content = result.markdown.raw_markdown if result.markdown else ""
|
||||
print(f"PAGE CONTENT: {content}")
|
||||
# page_id = database.add_crawled_page(result.url, content, 'pdf')
|
||||
|
||||
# if page_id and result.media and result.media.get("images"):
|
||||
# print(f"Found {len(result.media['images'])} images in {result.url}")
|
||||
# for img_info in result.media["images"]:
|
||||
# database.add_crawled_image(
|
||||
# page_id=page_id,
|
||||
# page_number=img_info.get('page'),
|
||||
# local_path=img_info.get('path'),
|
||||
# img_format=img_info.get('format')
|
||||
# )
|
||||
print(f"Successfully processed and stored PDF: {result.url}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"A critical error occurred while processing PDF '{url}': {e}")
|
||||
|
||||
with open(PDF_QUEUE_FILE, "w") as f:
|
||||
f.write("")
|
||||
print("\n--- PDF queue processing finished ---")
|
||||
|
||||
async def main():
|
||||
"""Main entry point that runs the PDF processing loop."""
|
||||
# database.setup_database()
|
||||
print("PDF Processor service starting...")
|
||||
cookies = load_cookies()
|
||||
while True:
|
||||
await process_pdf_queue(cookies)
|
||||
print(f"Queue check finished. Waiting {CHECK_INTERVAL_SECONDS}s for next check.")
|
||||
await asyncio.sleep(CHECK_INTERVAL_SECONDS)
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
asyncio.run(main())
|
||||
except KeyboardInterrupt:
|
||||
print("\nPDF Processor service stopped by user.")
|
||||
|
|
@ -1,29 +1,110 @@
|
|||
aiofiles==24.1.0
|
||||
aiohappyeyeballs==2.6.1
|
||||
aiohttp==3.12.15
|
||||
aiosignal==1.4.0
|
||||
aiosqlite==0.21.0
|
||||
alphashape==1.3.1
|
||||
annotated-types==0.7.0
|
||||
anyio==4.10.0
|
||||
attrs==25.3.0
|
||||
beautifulsoup4==4.13.4
|
||||
Brotli==1.1.0
|
||||
cachetools==5.5.2
|
||||
certifi==2025.7.14
|
||||
charset-normalizer==3.4.2
|
||||
dotenv==0.9.9
|
||||
certifi==2025.8.3
|
||||
cffi==1.17.1
|
||||
chardet==5.2.0
|
||||
charset-normalizer==3.4.3
|
||||
click==8.2.1
|
||||
click-log==0.4.0
|
||||
Crawl4AI==0.7.4
|
||||
cryptography==45.0.6
|
||||
distro==1.9.0
|
||||
fake-http-header==0.3.5
|
||||
fake-useragent==2.2.0
|
||||
filelock==3.19.1
|
||||
frozenlist==1.7.0
|
||||
fsspec==2025.7.0
|
||||
google==3.0.0
|
||||
google-ai-generativelanguage==0.1.0
|
||||
google-ai-generativelanguage==0.6.15
|
||||
google-api-core==2.25.1
|
||||
google-api-python-client==2.177.0
|
||||
google-api-python-client==2.179.0
|
||||
google-auth==2.40.3
|
||||
google-auth-httplib2==0.2.0
|
||||
google-generativeai==0.1.0rc1
|
||||
google-generativeai==0.8.5
|
||||
googleapis-common-protos==1.70.0
|
||||
grpcio==1.70.0
|
||||
grpcio-status==1.62.3
|
||||
greenlet==3.2.4
|
||||
grpcio==1.74.0
|
||||
grpcio-status==1.71.2
|
||||
h11==0.16.0
|
||||
h2==4.2.0
|
||||
hf-xet==1.1.8
|
||||
hpack==4.1.0
|
||||
httpcore==1.0.9
|
||||
httplib2==0.22.0
|
||||
httpx==0.28.1
|
||||
huggingface-hub==0.34.4
|
||||
humanize==4.12.3
|
||||
hyperframe==6.1.0
|
||||
idna==3.10
|
||||
importlib_metadata==8.7.0
|
||||
Jinja2==3.1.6
|
||||
jiter==0.10.0
|
||||
joblib==1.5.1
|
||||
jsonschema==4.25.1
|
||||
jsonschema-specifications==2025.4.1
|
||||
lark==1.2.2
|
||||
litellm==1.75.9
|
||||
lxml==5.4.0
|
||||
markdown-it-py==4.0.0
|
||||
MarkupSafe==3.0.2
|
||||
mdurl==0.1.2
|
||||
multidict==6.6.4
|
||||
networkx==3.5
|
||||
nltk==3.9.1
|
||||
numpy==2.3.2
|
||||
openai==1.100.2
|
||||
packaging==25.0
|
||||
patchright==1.52.5
|
||||
pillow==11.3.0
|
||||
playwright==1.54.0
|
||||
propcache==0.3.2
|
||||
proto-plus==1.26.1
|
||||
protobuf==4.25.8
|
||||
protobuf==5.29.5
|
||||
psutil==7.0.0
|
||||
pyasn1==0.6.1
|
||||
pyasn1-modules==0.4.2
|
||||
pyparsing==3.1.4
|
||||
python-dotenv==1.0.1
|
||||
requests==2.32.4
|
||||
pyasn1_modules==0.4.2
|
||||
pycparser==2.22
|
||||
pydantic==2.11.7
|
||||
pydantic_core==2.33.2
|
||||
pyee==13.0.0
|
||||
Pygments==2.19.2
|
||||
pyOpenSSL==25.1.0
|
||||
pyparsing==3.2.3
|
||||
PyPDF2==3.0.1
|
||||
python-dotenv==1.1.1
|
||||
PyYAML==6.0.2
|
||||
rank-bm25==0.2.2
|
||||
referencing==0.36.2
|
||||
regex==2025.7.34
|
||||
requests==2.32.5
|
||||
rich==14.1.0
|
||||
rpds-py==0.27.0
|
||||
rsa==4.9.1
|
||||
rtree==1.4.1
|
||||
scipy==1.16.1
|
||||
shapely==2.1.1
|
||||
sniffio==1.3.1
|
||||
snowballstemmer==2.2.0
|
||||
soupsieve==2.7
|
||||
typing-extensions==4.13.2
|
||||
uritemplate==4.1.1
|
||||
urllib3==2.2.3
|
||||
tf-playwright-stealth==1.2.0
|
||||
tiktoken==0.11.0
|
||||
tokenizers==0.21.4
|
||||
tqdm==4.67.1
|
||||
trimesh==4.7.4
|
||||
typing-inspection==0.4.1
|
||||
typing_extensions==4.14.1
|
||||
uritemplate==4.2.0
|
||||
urllib3==2.5.0
|
||||
xxhash==3.5.0
|
||||
yarl==1.20.1
|
||||
zipp==3.23.0
|
||||
|
|
|
|||
Loading…
Reference in New Issue