FindMyProfessor / src /scraper /GSBS_faculty_scraper.py
dawnlaker's picture
Refactor faculty scraping functionality and add new scrapers for various departments. Update main.py to comment out sum calculations and chart plotting. Introduce profile_to_vector_database notebook for faculty data processing. Remove simple.ipynb as it is no longer needed.
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from bs4 import BeautifulSoup
import requests
import json
from typing import Dict, List, Optional
from typing_extensions import override
import time
from urllib.parse import urljoin
from summarize import summarize
from src.scraper.faculty_scraper import FacultyScraper
class GSBSFacultyScraper(FacultyScraper):
"""A class to scrape faculty information from GSBS websites."""
def __init__(self, base_url: str = "https://gsbs.uth.edu/directory/",
delay: float = 0.1, debug: bool = False):
"""
Initialize the GSBS FacultyScraper.
Args:
base_url (str): Base URL of the GSBS directory website
delay (float): Delay between requests in seconds
debug (bool): Enable debug mode (limits to first 5 faculty)
"""
super().__init__(base_url, delay, debug)
@override
def _get_faculty_divs(self) -> List:
"""
Get faculty divs from the GSBS directory page.
Returns:
List: List of faculty divs
"""
# GSBS uses <a> tags with class "cell callout grid-x" for each faculty member
faculty_divs = self.soup.find_all('a', class_='cell callout grid-x')
return faculty_divs
@override
def _extract_name(self, faculty_div) -> Optional[str]:
"""
Extract faculty name from the faculty div.
Args:
faculty_div: BeautifulSoup element containing faculty info
Returns:
Optional[str]: Faculty name if found, None otherwise
"""
# GSBS stores name in <span class="name"><strong>Name</strong></span>
name_span = faculty_div.find('span', class_='name')
if name_span:
strong_tag = name_span.find('strong')
if strong_tag:
return strong_tag.get_text().strip()
return None
@override
def _extract_profile_url(self, faculty_div) -> Optional[str]:
"""
Extract the profile URL from the faculty div.
Args:
faculty_div: BeautifulSoup element containing faculty info
Returns:
Optional[str]: Profile URL if found, None otherwise
"""
# GSBS stores the profile URL in the href attribute of the main <a> tag
href = faculty_div.get('href')
if href:
return self.get_absolute_url(self.base_url, href)
return None
@override
def _extract_image_url(self, faculty_div) -> Optional[str]:
"""
Extract faculty image URL.
Args:
faculty_div: BeautifulSoup element containing faculty info
Returns:
Optional[str]: Image URL if found, None otherwise
"""
# GSBS stores image in the background-style of profile__picture div
profile_picture_div = faculty_div.find('div', class_='profile__picture')
if profile_picture_div:
style = profile_picture_div.get('style', '')
if 'background:url(' in style:
# Extract URL from style attribute
start = style.find("background:url('") + len("background:url('")
end = style.find("')", start)
if start != -1 and end != -1:
img_url = style[start:end]
return self.get_absolute_url(self.base_url, img_url)
return None
def _extract_position(self, faculty_div) -> Optional[str]:
"""
Extract faculty position/label.
Args:
faculty_div: BeautifulSoup element containing faculty info
Returns:
Optional[str]: Position if found, None otherwise
"""
labels_span = faculty_div.find('span', class_='labels')
if labels_span:
return labels_span.get_text().strip()
return None
def _get_next_page_url(self) -> Optional[str]:
"""
Get the URL for the next page if pagination exists.
Returns:
Optional[str]: Next page URL if found, None otherwise
"""
# Look for the specific pagination structure used by GSBS
# The next page link is in a div with class "small-4 cell" and contains an <a> with "Next Page" text
next_link = self.soup.find('a', class_='next')
if not next_link:
# Alternative: look for link containing "Next Page" text
next_link = self.soup.find('a', string=lambda text: text and 'Next Page' in text)
if next_link and 'href' in next_link.attrs:
href = next_link['href']
# Convert relative URL to absolute URL
return self.get_absolute_url(self.base_url, href)
return None
@override
def scrape_faculty_list(self) -> List[Dict]:
"""
Scrape faculty information from all pages of the GSBS directory.
Returns:
List[Dict]: List of dictionaries containing faculty information
"""
faculty_list = []
current_url = self.base_url
page_num = 1
while current_url:
print(f"Scraping page {page_num}...")
# Get page content
response = requests.get(current_url)
if response.status_code != 200:
print(f"Failed to load page {page_num}: {current_url}")
break
self.soup = BeautifulSoup(response.content, 'html.parser')
faculty_divs = self._get_faculty_divs()
if self.debug and page_num == 1:
faculty_divs = faculty_divs[:5]
print(f"Debug: Only scraping first 5 faculty members from first page")
# Process faculty on current page
for i, faculty_div in enumerate(faculty_divs):
faculty_info = {}
# Add delay between each professor
if len(faculty_list) > 0 or i > 0:
time.sleep(self.delay)
# Extract image URL
image_url = self._extract_image_url(faculty_div)
if image_url:
faculty_info['image_url'] = image_url
# Extract name
name = self._extract_name(faculty_div)
if name:
faculty_info['name'] = name
# Extract position/label
position = self._extract_position(faculty_div)
if position:
faculty_info['position'] = position
# Extract profile URL and get profile summary
profile_url = self._extract_profile_url(faculty_div)
if profile_url:
profile_summary = self._get_faculty_profile(profile_url)
faculty_info['profile'] = profile_summary
faculty_info['profile_url'] = profile_url
faculty_list.append(faculty_info)
print(f"Processed {len(faculty_list)} faculty members total")
# Check for next page (unless in debug mode)
if self.debug:
break
next_url = self._get_next_page_url()
if next_url and next_url != current_url:
current_url = next_url
page_num += 1
# Add delay between pages
time.sleep(self.delay * 2)
else:
current_url = None
print(f"Completed scraping {page_num} page(s), total faculty: {len(faculty_list)}")
self.faculty_list = faculty_list
def main():
"""Main function to run the GSBS faculty scraper."""
base_url = 'https://gsbs.uth.edu/directory/'
# Create scraper instance and run
scraper = GSBSFacultyScraper(base_url, debug=False)
faculty_list = scraper.scrape_faculty_list()
# Save the faculty list as jsonl file
scraper.save_to_jsonl('data/gsbs_faculty_list.jsonl')
if __name__ == "__main__":
main()