Test_E5 / search.py
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# Library Imports
import requests
from bs4 import BeautifulSoup
from googlesearch import search
from duckduckgo_search import DDGS
import concurrent.futures
import re
# Search Functions -------------------------------------------------------------->
# Function to search DuckDuckGo
def search_duckduckgo(query):
try:
results = DDGS().text(f"{query} manual filetype:pdf", max_results=5)
return [res['href'] for res in results]
except:
return []
# Function to search Google
def search_google(query):
links = []
try:
api_key = 'AIzaSyDV_uJwrgNtawqtl6GDfeUj6NqO-H1tA4c'
search_engine_id = 'c4ca951b9fc6949cb'
url = f"https://www.googleapis.com/customsearch/v1"
params = {
"key": api_key,
"cx": search_engine_id,
"q": query + " manual filetype:pdf"
}
response = requests.get(url, params=params)
results = response.json()
for item in results.get('items', []):
links.append(item['link'])
except:
pass
try:
extension = "ext:pdf"
for result in search(query + " manual " + extension, num_results=5):
if result.endswith('.pdf'):
links.append(result)
except:
pass
return links
# Function to search Internet Archive
def search_archive(query):
try:
url = "https://archive.org/advancedsearch.php"
params = {
'q': f'{query} manual',
'fl[]': ['identifier', 'title', 'format'],
'rows': 50,
'page': 1,
'output': 'json'
}
# Make the request
response = requests.get(url, params=params)
data = response.json()
# Function to extract hyperlinks from a webpage
def extract_hyperlinks(url):
# Send a GET request to the URL
response = requests.get(url)
# Check if the request was successful
if response.status_code == 200:
# Parse the HTML content of the page
soup = BeautifulSoup(response.text, 'html.parser')
# Find all <a> tags (hyperlinks)
for link in soup.find_all('a', href=True):
href = link['href']
if href.endswith('.pdf'):
pdf_files.append(url+'/'+href)
if href.endswith('.iso'):
# If the link ends with .iso, follow the link and extract .pdf hyperlinks
extract_pdf_from_iso(url+'/'+href+'/')
# Function to extract .pdf hyperlinks from an .iso file
def extract_pdf_from_iso(iso_url):
# Send a GET request to the ISO URL
iso_response = requests.get(iso_url)
# Check if the request was successful
if iso_response.status_code == 200:
# Parse the HTML content of the ISO page
iso_soup = BeautifulSoup(iso_response.text, 'html.parser')
# Find all <a> tags (hyperlinks) in the ISO page
for link in iso_soup.find_all('a', href=True):
href = link['href']
if href.endswith('.pdf'):
pdf_files.append('https:'+href)
pdf_files = []
def process_doc(doc):
identifier = doc.get('identifier', 'N/A')
# title = doc.get('title', 'N/A')
# format = doc.get('format', 'N/A')
pdf_link = f"https://archive.org/download/{identifier}"
extract_hyperlinks(pdf_link)
with concurrent.futures.ThreadPoolExecutor() as executor:
futures = [executor.submit(process_doc, doc) for doc in data['response']['docs']]
# Optionally, wait for all futures to complete and handle any exceptions
for future in concurrent.futures.as_completed(futures):
try:
future.result() # This will raise an exception if the function call raised
except Exception as exc:
print(f'Generated an exception: {exc}')
return pdf_files
except:
return []
def search_github(query):
try:
# GitHub Search API endpoint
url = f"https://api.github.com/search/code?q={query}+extension:md"
headers = {
'Authorization': 'Token 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'
}
# Make the request
response = requests.get(url,headers=headers)
data = response.json()
links = [item['html_url'] for item in data['items']]
return links
except:
return []
def search_wikipedia(product):
api_url = "https://en.wikipedia.org/w/api.php"
params = {
"action": "opensearch",
"search": product,
"limit": 5,
"namespace": 0,
"format": "json"
}
try:
response = requests.get(api_url, params=params)
response.raise_for_status() # Raise an HTTPError for bad responses (4xx and 5xx)
data = response.json()
if data and len(data) > 3 and len(data[3]) > 0:
return data[3] # The URL is in the fourth element of the response array
else:
return []
except requests.RequestException as e:
print(f"An error occurred: {e}")
return []
# def search_all(product,num):
# similar_products = extract_similar_products(product)[num]
# # results = {
# # product : [{'duckduckgo': duckduckgo_search(product)},{'google': google_search(product)},{'github': github_search(product)},{'archive': archive_search(product)}]
# # }
# results = {}
# def search_product(p):
# return {
# 'product': p,
# 'duckduckgo': duckduckgo_search(p),
# 'google': google_search(p),
# 'github': github_search(p),
# 'archive': archive_search(p),
# 'wikipedia': wikipedia_search(p)
# }
# with concurrent.futures.ThreadPoolExecutor() as executor:
# future_to_product = {executor.submit(search_product, p): p for p in similar_products}
# for future in concurrent.futures.as_completed(future_to_product):
# result = future.result()
# product = result['product']
# results[product] = [
# {'duckduckgo': result['duckduckgo']},
# {'google': result['google']},
# {'github': result['github']},
# {'archive': result['archive']},
# {'wikipedia': result['wikipedia']}
# ]
# return results
def search_images(product):
results = DDGS().images(f"{product}", max_results=5)
# print(results)
return [r['image'] for r in results]
# Similarity Check -------------------------------------->
def extract_similar_products(query):
print(f"\n--> Fetching similar items of - {query}")
results = DDGS().chat(f'{query} Similar Products')
pattern = r'^\d+\.\s(.+)$'
matches = re.findall(pattern, results, re.MULTILINE)
matches = [item.split(': ')[0] for item in matches]
return matches