Update other_function.py

other_function.py

@@ -11,12 +11,7 @@ import os
 from pypdf import PdfReader
 from ai71 import AI71
 import os
-from selenium import webdriver
-from selenium.webdriver.chrome.service import Service
-from selenium.webdriver.chrome.options import Options
-from selenium.webdriver.common.by import By
-from selenium.webdriver.support.ui import WebDriverWait
-from selenium.webdriver.support import expected_conditions as EC
+
 import pandas as pd
 
 from inference_sdk import InferenceHTTPClient
@@ -108,46 +103,40 @@ def get_weather(city):
 
   soup=BeautifulSoup(r.text,'html.parser')
   temperature=soup.find('div',attrs={'class':'BNeawe iBp4i AP7Wnd'}).text
-  degree=temperature[:-2]
-  celcius=str(round((int(degree) - 32)* 5/9,1))+temperature[-2]+'C'
-  return (celcius)
+  
+  return (temperature)
 
 
+from zenrows import ZenRowsClient
+from bs4 import BeautifulSoup
+Zenrow_api=os.environ.get('Zenrow_api')
+# Initialize ZenRows client with your API key
+client = ZenRowsClient(str(Zenrow_api))
 
+def get_rates():    # URL to scrape
+    url = "https://www.kisandeals.com/mandiprices/ALL/TAMIL-NADU/ALL"
 
-from twisted.internet import reactor, defer
-from scrapy.crawler import CrawlerRunner
-from scrapy.utils.project import get_project_settings
-import scrapy
+    # Fetch the webpage content using ZenRows
+    response = client.get(url)
 
-class RateSpider(scrapy.Spider):
-    name = 'rates'
-    start_urls = ['https://www.kisandeals.com/mandiprices/ALL/TAMIL-NADU/ALL']
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Parse the raw HTML content with BeautifulSoup
+        soup = BeautifulSoup(response.content, 'html.parser')
 
-    def parse(self, response):
-        rows = response.xpath('//table/tbody/tr')
+        # Find the table rows containing the data
+        rows = soup.select('table tbody tr')
         data = {}
         for row in rows:
-            commodity = row.xpath('td[1]/text()').get()
-            price = row.xpath('td[2]/text()').get()
-            data[commodity] = price
-        yield data
-
-def get_rates():
-    runner = CrawlerRunner(get_project_settings())
-    deferred = runner.crawl(RateSpider)
-    
-    @defer.inlineCallbacks
-    def wait_for_results():
-        yield deferred
-        reactor.stop()
-    
-    reactor.callWhenRunning(wait_for_results)
-    reactor.run()
-    
-    # Since we're using reactor.stop(), Scrapy won't return the result immediately.
-    # You may need to capture results using global variables or another method if needed.
+            # Extract commodity and price using BeautifulSoup
+            columns = row.find_all('td')
+            if len(columns) >= 2:
+                commodity = columns[0].get_text(strip=True)
+                price = columns[1].get_text(strip=True)
+                if '₹' in price:
+                    data[commodity] = price
+    return str(data)+" This are the prices for 1 kg"
+
+
+
 
-    # Dummy data for demonstration purposes; replace with actual data handling logic.
-    result = 'Dummy data: These prices are for 1 kg'
-    return result