import requests
import json  # Import the JSON module
API_KEY = "YOUR_API_KEY"
IP = "101.32.228.0" ## IP You Wann Exploreurl = f"https://api.ipstack.com/{IP}?access_key={API_KEY}&hostname=1"
response = requests.get(url)
# Pretty-print JSON response
print(json.dumps(response.json(), indent=2))

import requests
from bs4 import BeautifulSoup
params = {    'access_key': 'YOUR_API_KEY',    'url': 'https://scrapestack.com/documentation'}
api_result = requests.get('http://api.scrapestack.com/scrape', params)
website_content = api_result.content
# Parse HTML
soup = BeautifulSoup(website_content, "html.parser")
#print(soup.prettify()) ## Prettify The Scraped Content
# Extract all paragraph texts
paragraphs = [p.get_text() for p in soup.find_all('p')]
## If u plant to use Google Colab for this!!
from IPython.core.display import display, Markdown
display(Markdown("\n\n".join(paragraphs)))

# Python 3
import http.client, urllib.parse
import jsonconn = http.client.HTTPConnection('api.mediastack.com')


params = urllib.parse.urlencode({       
 'access_key': 'YOUR_API_KEY',      
   'categories': 'technology,science', 
    # Excluding general & sports       
     'sort': 'popularity',       
      'limit': 2,  # Fetch latest 2 articles    
           'sources':'cnn,bbc'    })
           conn.request('GET', '/v1/news?{}'.format(params))
           res = conn.getresponse()
           data = res.read()
           print(data.decode('utf-8'))

import requests
import jsonAPI_KEY = "YOUR_API_KEY"
url = f"https://api.weatherstack.com/current"
params = {"access_key": API_KEY, "query": "London"}
response = requests.get(url, params=params)
if response.status_code == 200:    
data = response.json()   
 current_weather = data.get("current", {})    
 location = data.get("location", {})    
 print(f"?? Location: {location.get('name')}, {location.get('country')}")    
 print(f"??? Temperature: {current_weather.get('temperature')}°C")    
 print(f"?? Condition: {', '.join(current_weather.get('weather_descriptions', []))}")    
 print(f"?? Wind Speed: {current_weather.get('wind_speed')} km/h")    
 print(f"?? Humidity: {current_weather.get('humidity')}%")    
 print(f"?? Feels Like: {current_weather.get('feelslike')}°C")

import requests
phone_number = "14158586273"
url = f"https://api.apilayer.com/number_verification/validate?number={phone_number}"
payload = {}
headers= {  "apikey": "YOUR_API_KEY"
}
response = requests.request("GET", url, headers=headers, data = payload)
status_code = response.status_codeprint(response.text)

import requests
url = "https://api.apilayer.com/text_to_emotion"
review = "The hotel service is worst, They should add a minus in front of 5 and make it a -5 star restaurant"
payload = f"{review}".encode("utf-8")
headers= {  "apikey": "YOUR_API_KEY"}
response = requests.request("POST", url, headers=headers, data = payload)
status_code = response.status_code
result = response.text
print(result)

import requests
# API URL with access key and document URL
URL = "https://realpython.com/python-news-february-2025/" ## URL You want to convert to PDFAPI_KEY = "YOUR_API_KEY"
url = f"http://api.pdflayer.com/api/convert?access_key={API_KEY}&document_url={URL}"
# Make the API request
response = requests.post(url)
# Check if the request was successful
if response.status_code == 200:    
# Save the response content as a PDF file    
with open("Feb_Roundup_Python.pdf", "wb") as pdf_file:        
pdf_file.write(response.content)    
print("? PDF downloaded successfully as 'Feb_Roundup_Python.pdf'")else:    
print(f"? Failed to download PDF. Status Code: {response.status_code}")

import requests
import pandas as pd
from IPython.display 
import display
# API request setup
url = "https://api.apilayer.com/bad_words?censor_character=censor_character"
review = "This product is absolute garbage! The quality is shit and the support team is useless as fuck. Total scam!"
headers = {"apikey": "GET_YOUR_OWN"}
# Make request
response = requests.post(url, headers=headers, data=review.encode("utf-8"))
# Parse JSON response
if response.status_code == 200:    
data = response.json()        
# Display Original & Censored Review     
print(f"\033[1mOriginal Review:\033[0m {data['content']}") # \033[1m -> For Bold Text on Terminal  \033[0m -> Reset formatting (stops bold and returns text to normal).    
print(f"\033[1mCensored Review:\033[0m {data['censored_content']}")    
print(f"\033[1mTotal Bad Words Found:\033[0m {data['bad_words_total']}\n")    
# Convert bad words list to DataFrame    
if data["bad_words_total"] > 0:        
df = pd.DataFrame(data["bad_words_list"])[["original", "start", "end", "word"]]        
df.columns = ["Bad Word", "Start Position", "End Position", "Detected Word"]        
# Fix the warning by applying styles safely        
styled_df = df.style.set_properties(            
subset=['Bad Word'], **{'background-color': 'red', 'color': 'white', 'font-weight': 'bold'}        )        
display(styled_df)  # Show styled DataFrame    
else:        
print("\033[92mNo bad words detected.\033[0m")  # Green text for clean reviewselse:    
print(f"\033[91mAPI request failed with status code {response.status_code}\033[0m")  # Red error message

import requests
import json
# API Endpointresume_link = "https://assets.apilayer.com/apis/codes/resume_parser/sample_resume.docx"
url = f"https://api.apilayer.com/resume_parser/url?url={resume_link}"
headers = {"apikey": "GET_YOUR_OWN"}
response = requests.get(url, headers=headers)
if response.status_code == 200:    
data = response.json()  # Convert response to JSON    
skills = data.get("skills", [])  # Extract skills list    
print("Extracted Skills:", skills)else:    
print(f"? API request failed with status code {response.status_code}")