Google Custom Search API Key and CX ID to be configured
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@zaasmi said in Google Custom Search API Key and CX ID to be configured:
how to restrict this API key so others can’t use your daily quota if they find your code?
Smart move. Leaving an API key unrestricted is like leaving your house keys in the front door—anyone who finds them can use your “quota” (and potentially your money if billing is enabled).
To protect your credentials, you should apply API Restrictions in the Google Cloud Console.
How to Secure Your API Key
- Go to Credentials: Navigate to APIs & Services > Credentials.
- Edit the Key: Click the pencil icon next to your specific API Key.
- Set “Application Restrictions”: This limits where the request can come from.
- Website (HTTP referrers): Choose this if your search bar is on a public website. Add your domain (e.g.,
*.yourwebsite.com/*). - IP addresses: Choose this if you are running the script from a specific server.
- Set “API Restrictions”: This is the most important part.
- Select Restrict key.
- From the dropdown, select Custom Search API. This ensures that even if someone steals the key, they can’t use it for expensive services like Google Maps or Translate.
Managing Your Quota (The “Free” Reality)
Since you are likely on the free tier, it’s helpful to know what you’re working with to avoid “429 Too Many Requests” errors:
Feature Limit Daily Free Limit 100 queries per day Additional Queries $5.00 per 1,000 queries (up to 10k/day) Image Search Counts the same as a text query Pro-Tip: If you are developing locally, cache your search results in a JSON file or a local database while testing. This prevents you from burning through your 100-query daily limit in 10 minutes just by refreshing your browser!
Would you like to show how to write a simple “cache” function in Python so you don’t waste your daily 100 queries while testing?
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Would you like to show how to write a simple “cache” function in Python so you don’t waste your daily 100 queries while testing?
@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Would you like me to show you how to write a simple “cache” function in Python so you don’t waste your daily 100 queries while testing?
Caching is a lifesaver when you only have 100 free requests per day. This script saves the results of a search to a local file (
cache.json). If you search for the same thing twice, it pulls from your hard drive instead of hitting the Google API.The Caching Script
This version checks if the search term exists locally before asking Google for the image.
import json import os from googleapiclient.discovery import build CACHE_FILE = 'search_cache.json' def get_cached_results(): if os.path.exists(CACHE_FILE): with open(CACHE_FILE, 'r') as f: return json.load(f) return {} def save_to_cache(query, data): cache = get_cached_results() cache[query] = data with open(CACHE_FILE, 'w') as f: json.dump(cache, f, indent=4) def smart_image_search(api_key, cx_id, query): cache = get_cached_results() # Check if we already searched this today if query in cache: print(f"--- Fetching '{query}' from CACHE (Free!) ---") return cache[query] # If not in cache, call the API print(f"--- Calling GOOGLE API for '{query}' (Costs 1 credit) ---") service = build("customsearch", "v1", developerKey=api_key) res = service.cse().list(q=query, cx=cx_id, searchType='image', num=1).execute() if 'items' in res: image_url = res['items'][0]['link'] save_to_cache(query, image_url) return image_url return "No images found." # Usage API_KEY = 'YOUR_API_KEY' CX_ID = 'YOUR_CX_ID' # Try running this twice for the same word! print(smart_image_search(API_KEY, CX_ID, 'Cyberpunk City'))
How the flow works
- Search Input: You enter a keyword.
- The Interceptor: The script looks at
search_cache.json. - The Decision:
- Found? It returns the URL instantly.
- Not Found? It uses 1 of your 100 Google credits, then saves the result so it’s free next time.
Pro-Tip: “Development Mode”
When building a UI, developers often use “Mock Data.” Instead of calling the API at all, you can create a toggle that just returns a random placeholder image URL while you are styling your buttons and layout. This ensures you have all 100 requests available for when you actually launch the app.
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@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Would you like me to show you how to write a simple “cache” function in Python so you don’t waste your daily 100 queries while testing?
Caching is a lifesaver when you only have 100 free requests per day. This script saves the results of a search to a local file (
cache.json). If you search for the same thing twice, it pulls from your hard drive instead of hitting the Google API.The Caching Script
This version checks if the search term exists locally before asking Google for the image.
import json import os from googleapiclient.discovery import build CACHE_FILE = 'search_cache.json' def get_cached_results(): if os.path.exists(CACHE_FILE): with open(CACHE_FILE, 'r') as f: return json.load(f) return {} def save_to_cache(query, data): cache = get_cached_results() cache[query] = data with open(CACHE_FILE, 'w') as f: json.dump(cache, f, indent=4) def smart_image_search(api_key, cx_id, query): cache = get_cached_results() # Check if we already searched this today if query in cache: print(f"--- Fetching '{query}' from CACHE (Free!) ---") return cache[query] # If not in cache, call the API print(f"--- Calling GOOGLE API for '{query}' (Costs 1 credit) ---") service = build("customsearch", "v1", developerKey=api_key) res = service.cse().list(q=query, cx=cx_id, searchType='image', num=1).execute() if 'items' in res: image_url = res['items'][0]['link'] save_to_cache(query, image_url) return image_url return "No images found." # Usage API_KEY = 'YOUR_API_KEY' CX_ID = 'YOUR_CX_ID' # Try running this twice for the same word! print(smart_image_search(API_KEY, CX_ID, 'Cyberpunk City'))
How the flow works
- Search Input: You enter a keyword.
- The Interceptor: The script looks at
search_cache.json. - The Decision:
- Found? It returns the URL instantly.
- Not Found? It uses 1 of your 100 Google credits, then saves the result so it’s free next time.
Pro-Tip: “Development Mode”
When building a UI, developers often use “Mock Data.” Instead of calling the API at all, you can create a toggle that just returns a random placeholder image URL while you are styling your buttons and layout. This ensures you have all 100 requests available for when you actually launch the app.
How to set up a “Mock Mode” toggle so you can design your app without using any API credits at all?
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How to set up a “Mock Mode” toggle so you can design your app without using any API credits at all?
@zaasmi said in Google Custom Search API Key and CX ID to be configured:
How to set up a “Mock Mode” toggle so you can design your app without using any API credits at all?
A “Mock Mode” is the ultimate developer hack. It allows you to build your layout, test your CSS, and fix bugs without ever touching your Google quota.
By adding a simple
MOCK_MODEboolean to your code, you can switch between “Real Google Data” and “Instant Fake Data.”The Updated Script with Mock Toggle
import random # --- CONFIGURATION --- MOCK_MODE = True # Set to False when you are ready to use your real Google credits API_KEY = 'YOUR_API_KEY' CX_ID = 'YOUR_CX_ID' def get_image(query): if MOCK_MODE: print(f"--- MOCK MODE: Returning placeholder for '{query}' ---") # Returns a random high-quality placeholder image width, height = random.randint(800, 1200), random.randint(600, 900) return f"https://picsum.photos/{width}/{height}" # If MOCK_MODE is False, it runs your real API logic return smart_image_search(API_KEY, CX_ID, query) # Example usage during UI design image_to_display = get_image("Ocean Sunset") print(f"Displaying Image: {image_to_display}")
Why use Mock Mode?
- Speed: Placeholder images load instantly; API calls take 1–2 seconds.
- Offline Development: You can keep coding even if you lose internet access.
- Infinite Testing: You can refresh your app 10,000 times a day and it won’t cost you a cent.
The Developer Workflow
- Phase 1 (Design):
MOCK_MODE = True. Focus on how the images look on the screen. - Phase 2 (Functionality):
MOCK_MODE = False. Use the Cache logic we built earlier to ensure the API is connecting correctly. - Phase 3 (Deployment): Go live with the API and Caching enabled to save on long-term costs.
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Backend logic is solid, would you help me create a simple HTML/CSS interface to display these images in a clean gallery grid?
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Backend logic is solid, would you help me create a simple HTML/CSS interface to display these images in a clean gallery grid?
@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Backend logic is solid, would you help me create a simple HTML/CSS interface to display these images in a clean gallery grid?
Let’s wrap this up by building a frontend. To keep things lightweight and modern, we’ll use a simple HTML/CSS/JavaScript setup. This interface will include a search bar and a “Mock Mode” status indicator so you always know if you’re using real credits or fake data.
The “Search Center” Interface
Copy this into an
index.htmlfile to see it in action.<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Image Search Gallery</title> <style> body { font-family: 'Segoe UI', sans-serif; background: #f4f4f9; padding: 20px; text-align: center; } .search-container { margin-bottom: 30px; } input { padding: 12px; width: 300px; border: 1px solid #ddd; border-radius: 5px; } button { padding: 12px 20px; background: #4285f4; color: white; border: none; border-radius: 5px; cursor: pointer; } /* Grid Layout */ .gallery { display: grid; grid-template-columns: repeat(auto-fill, minmax(250px, 1fr)); gap: 20px; max-width: 1200px; margin: 0 auto; } .card { background: white; padding: 10px; border-radius: 8px; box-shadow: 0 4px 6px rgba(0,0,0,0.1); } .card img { width: 100%; height: 200px; object-fit: cover; border-radius: 4px; } .status-badge { font-size: 0.8em; color: #666; margin-top: 10px; } </style> </head> <body> <div class="search-container"> <h1>Community Image Finder</h1> <input type="text" id="searchInput" placeholder="Search for images..."> <button onclick="performSearch()">Search</button> <div class="status-badge" id="modeStatus">Current Mode: 🟢 Mock Mode (Free)</div> </div> <div class="gallery" id="gallery"> </div> <script> const MOCK_MODE = true; // Switch to false when your API is connected function performSearch() { const query = document.getElementById('searchInput').value; const gallery = document.getElementById('gallery'); // Create a "Card" for the result const card = document.createElement('div'); card.className = 'card'; let imageUrl = ""; if (MOCK_MODE) { imageUrl = `https://picsum.photos/seed/${Math.random()}/400/300`; } else { // This is where you'd call your Python/Node backend API imageUrl = "https://via.placeholder.com/400x300?text=API+Result+Here"; } card.innerHTML = `<img src="${imageUrl}"><p>${query}</p>`; gallery.prepend(card); // Put newest search at the top } </script> </body> </html>
How this connects to your setup
- Frontend (HTML/JS): The user types a query and hits “Search.”
- The Bridge: In a real-world app, your JavaScript would send that query to your Python script (the one we wrote earlier) using a “Fetch” request.
- Backend (Python): Your script checks the Cache, and if it’s a new request, it uses the API Key to talk to Google.
- The Result: The image URL travels back to the browser and pops into that CSS grid.
Final Checklist before going “Live”
- API Key created and restricted to “Custom Search API.”
- CX ID created with “Image Search” toggled ON.
- Billing enabled (optional, only if you need more than 100 daily searches).
- Cache logic implemented to save your free credits.
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@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Backend logic is solid, would you help me create a simple HTML/CSS interface to display these images in a clean gallery grid?
Let’s wrap this up by building a frontend. To keep things lightweight and modern, we’ll use a simple HTML/CSS/JavaScript setup. This interface will include a search bar and a “Mock Mode” status indicator so you always know if you’re using real credits or fake data.
The “Search Center” Interface
Copy this into an
index.htmlfile to see it in action.<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Image Search Gallery</title> <style> body { font-family: 'Segoe UI', sans-serif; background: #f4f4f9; padding: 20px; text-align: center; } .search-container { margin-bottom: 30px; } input { padding: 12px; width: 300px; border: 1px solid #ddd; border-radius: 5px; } button { padding: 12px 20px; background: #4285f4; color: white; border: none; border-radius: 5px; cursor: pointer; } /* Grid Layout */ .gallery { display: grid; grid-template-columns: repeat(auto-fill, minmax(250px, 1fr)); gap: 20px; max-width: 1200px; margin: 0 auto; } .card { background: white; padding: 10px; border-radius: 8px; box-shadow: 0 4px 6px rgba(0,0,0,0.1); } .card img { width: 100%; height: 200px; object-fit: cover; border-radius: 4px; } .status-badge { font-size: 0.8em; color: #666; margin-top: 10px; } </style> </head> <body> <div class="search-container"> <h1>Community Image Finder</h1> <input type="text" id="searchInput" placeholder="Search for images..."> <button onclick="performSearch()">Search</button> <div class="status-badge" id="modeStatus">Current Mode: 🟢 Mock Mode (Free)</div> </div> <div class="gallery" id="gallery"> </div> <script> const MOCK_MODE = true; // Switch to false when your API is connected function performSearch() { const query = document.getElementById('searchInput').value; const gallery = document.getElementById('gallery'); // Create a "Card" for the result const card = document.createElement('div'); card.className = 'card'; let imageUrl = ""; if (MOCK_MODE) { imageUrl = `https://picsum.photos/seed/${Math.random()}/400/300`; } else { // This is where you'd call your Python/Node backend API imageUrl = "https://via.placeholder.com/400x300?text=API+Result+Here"; } card.innerHTML = `<img src="${imageUrl}"><p>${query}</p>`; gallery.prepend(card); // Put newest search at the top } </script> </body> </html>
How this connects to your setup
- Frontend (HTML/JS): The user types a query and hits “Search.”
- The Bridge: In a real-world app, your JavaScript would send that query to your Python script (the one we wrote earlier) using a “Fetch” request.
- Backend (Python): Your script checks the Cache, and if it’s a new request, it uses the API Key to talk to Google.
- The Result: The image URL travels back to the browser and pops into that CSS grid.
Final Checklist before going “Live”
- API Key created and restricted to “Custom Search API.”
- CX ID created with “Image Search” toggled ON.
- Billing enabled (optional, only if you need more than 100 daily searches).
- Cache logic implemented to save your free credits.
Would you like to show how to turn your Python script into a “Web API” using Flask so the HTML page can actually talk to it?
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Would you like to show how to turn your Python script into a “Web API” using Flask so the HTML page can actually talk to it?
@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Would you like to show how to turn your Python script into a “Web API” using Flask so the HTML page can actually talk to it?
To make your HTML page talk to your Python script, we’ll use Flask. It acts as the “waiter” in a restaurant: the Frontend (Customer) places an order, and Flask (the waiter) takes that order to the Python script (the kitchen) and brings back the image.
Step 1: Install Flask
Run this in your terminal:
pip install flask flask-corsStep 2: Create the “Waiter” (app.py)
This script combines your API Key, CX ID, and Caching logic into a web service.
from flask import Flask, request, jsonify from flask_cors import CORS from googleapiclient.discovery import build import json import os app = Flask(__name__) CORS(app) # This allows your HTML file to talk to this script # --- CONFIG --- API_KEY = 'YOUR_API_KEY' CX_ID = 'YOUR_CX_ID' CACHE_FILE = 'search_cache.json' def get_image_from_google(query): # (Same caching logic we built earlier) if os.path.exists(CACHE_FILE): with open(CACHE_FILE, 'r') as f: cache = json.load(f) if query in cache: return cache[query] service = build("customsearch", "v1", developerKey=API_KEY) res = service.cse().list(q=query, cx=CX_ID, searchType='image', num=1).execute() url = res['items'][0]['link'] if 'items' in res else None if url: # Save to cache cache = {} if os.path.exists(CACHE_FILE): with open(CACHE_FILE, 'r') as f: cache = json.load(f) cache[query] = url with open(CACHE_FILE, 'w') as f: json.dump(cache, f) return url @app.route('/search') def search(): query = request.args.get('q') image_url = get_image_from_google(query) return jsonify({"url": image_url}) if __name__ == '__main__': app.run(port=5000)Step 3: Connect the HTML
In your
index.html, update theperformSearch()function to fetch data from your new Python server instead of using mock data:async function performSearch() { const query = document.getElementById('searchInput').value; const gallery = document.getElementById('gallery'); // Fetch from your local Python server const response = await fetch(`http://127.0.0.1:5000/search?q=${query}`); const data = await response.json(); if (data.url) { const card = document.createElement('div'); card.className = 'card'; card.innerHTML = `<img src="${data.url}"><p>${query}</p>`; gallery.prepend(card); } else { alert("No image found!"); } }
How the Data Flows
Summary of your new System
- The User types “Electric Car” in the browser.
- JavaScript sends a request to
http://127.0.0.1:5000/search?q=Electric+Car. - Flask checks your
search_cache.jsonfirst. - Google API is only called if the cache is empty (saving you money/quota).
- The Image appears on your screen instantly.
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@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Would you like to show how to turn your Python script into a “Web API” using Flask so the HTML page can actually talk to it?
To make your HTML page talk to your Python script, we’ll use Flask. It acts as the “waiter” in a restaurant: the Frontend (Customer) places an order, and Flask (the waiter) takes that order to the Python script (the kitchen) and brings back the image.
Step 1: Install Flask
Run this in your terminal:
pip install flask flask-corsStep 2: Create the “Waiter” (app.py)
This script combines your API Key, CX ID, and Caching logic into a web service.
from flask import Flask, request, jsonify from flask_cors import CORS from googleapiclient.discovery import build import json import os app = Flask(__name__) CORS(app) # This allows your HTML file to talk to this script # --- CONFIG --- API_KEY = 'YOUR_API_KEY' CX_ID = 'YOUR_CX_ID' CACHE_FILE = 'search_cache.json' def get_image_from_google(query): # (Same caching logic we built earlier) if os.path.exists(CACHE_FILE): with open(CACHE_FILE, 'r') as f: cache = json.load(f) if query in cache: return cache[query] service = build("customsearch", "v1", developerKey=API_KEY) res = service.cse().list(q=query, cx=CX_ID, searchType='image', num=1).execute() url = res['items'][0]['link'] if 'items' in res else None if url: # Save to cache cache = {} if os.path.exists(CACHE_FILE): with open(CACHE_FILE, 'r') as f: cache = json.load(f) cache[query] = url with open(CACHE_FILE, 'w') as f: json.dump(cache, f) return url @app.route('/search') def search(): query = request.args.get('q') image_url = get_image_from_google(query) return jsonify({"url": image_url}) if __name__ == '__main__': app.run(port=5000)Step 3: Connect the HTML
In your
index.html, update theperformSearch()function to fetch data from your new Python server instead of using mock data:async function performSearch() { const query = document.getElementById('searchInput').value; const gallery = document.getElementById('gallery'); // Fetch from your local Python server const response = await fetch(`http://127.0.0.1:5000/search?q=${query}`); const data = await response.json(); if (data.url) { const card = document.createElement('div'); card.className = 'card'; card.innerHTML = `<img src="${data.url}"><p>${query}</p>`; gallery.prepend(card); } else { alert("No image found!"); } }
How the Data Flows
Summary of your new System
- The User types “Electric Car” in the browser.
- JavaScript sends a request to
http://127.0.0.1:5000/search?q=Electric+Car. - Flask checks your
search_cache.jsonfirst. - Google API is only called if the cache is empty (saving you money/quota).
- The Image appears on your screen instantly.
Would you like to show how to add a “Loading Spinner” to the HTML so users know the search is happening?
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Would you like to show how to add a “Loading Spinner” to the HTML so users know the search is happening?
@zaasmi said in Google Custom Search API Key and CX ID to be configured:
Would you like to show how to add a “Loading Spinner” to the HTML so users know the search is happening?
A loading spinner is essential for a good user experience. Without it, the user might think the app is broken while the Python backend is busy talking to Google’s servers.
Here is how to add a clean, CSS-only spinner that appears during the search and disappears once the image loads.
1. Add the CSS Spinner
Add this to the
<style>section of yourindex.html. It creates a classic rotating ring./* The Spinner Animation */ .loader { border: 4px solid #f3f3f3; border-top: 4px solid #3498db; border-radius: 50%; width: 30px; height: 30px; animation: spin 1s linear infinite; display: none; /* Hidden by default */ margin: 10px auto; } @keyframes spin { 0% { transform: rotate(0deg); } 100% { transform: rotate(360deg); } }2. Update the HTML
Place the loader div right above your gallery so users see it immediately after clicking search.
<div id="loader" class="loader"></div> <div class="gallery" id="gallery"></div>3. Update the JavaScript Logic
Modify your
performSearchfunction to toggle the loader’s visibility usingdisplay: blockanddisplay: none.async function performSearch() { const query = document.getElementById('searchInput').value; const loader = document.getElementById('loader'); const gallery = document.getElementById('gallery'); if (!query) return; // 1. Show the loader loader.style.display = "block"; try { const response = await fetch(`http://127.0.0.1:5000/search?q=${query}`); const data = await response.json(); if (data.url) { const card = document.createElement('div'); card.className = 'card'; card.innerHTML = `<img src="${data.url}"><p>${query}</p>`; gallery.prepend(card); } } catch (error) { console.error("Error fetching image:", error); } finally { // 2. Hide the loader (whether it worked or failed) loader.style.display = "none"; } }
Visualizing the Feedback Loop
The loader bridges the gap between the user’s action and the server’s reaction.
Why this matters for your Google API
Because the Google Custom Search API can sometimes take 1-2 seconds to respond, a “silent” screen makes users click the button multiple times. Each click could potentially trigger a new API call, wasting your 100-query daily limit. The spinner tells the user: “I’m working, please wait.”
Final Pro-Tip: Debouncing
If you want to be extra safe, you can disable the “Search” button as soon as it’s clicked so the user cannot trigger multiple API requests until the current one finishes.
// Add this inside performSearch document.querySelector('button').disabled = true; // Re-enable it in the 'finally' block document.querySelector('button').disabled = false; -
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