Complete developer guide, lightweight Python client SDK, and high-performance API reference for Google Places API powered by APINEED. Fast, structured, and cost-effective data extraction with zero browser automation overhead, automated anti-bot defense, and enterprise gateway reliability.
Integrating the Google Places API into automated data pipelines, autonomous web scrapers, and AI workflows often results in IP blocks, dynamic CAPTCHA challenges, and severe 429 Too Many Requests rate limit errors. Scraping directly without managed proxies requires costly residential IP infrastructure and endless headless browser maintenance.
This repository routes all requests through the APINEED Managed Gateway, giving you rock-solid, production-grade access to Google Places API:
- Unified Authentication: A single Bearer API key unlocks Google Places API along with all APINEED intelligence tools.
- Dramatic Cost Reduction: Query the service at $0.00125 per request (96% more affordable than Google Cloud Platform).
- Automated Anti-Bot Defense: Upstream proxy rotation, browser fingerprint impersonation, and automated CAPTCHA solving are entirely handled by the gateway.
- Zero Headless Browsers: No Puppeteer, Playwright, or Selenium binaries required—just fast, structured JSON returned directly from the endpoint.
- Direct Portal Link: Get Instant Google Places API API Key on APINEED (Free Test Credits Included)
- Executive Overview
- Key Features & Data Extraction Capabilities
- Installation & Quick Setup
- Python Quickstart & Implementation
- API Methods & Reference
- Structured Response Schema
- AI Agent & RAG Pipeline Integration
- Large-Scale Pagination & Concurrency Guide
- Enterprise Production Best Practices
- Cost Comparison: APINEED vs Google Cloud Platform
- Direct HTTP cURL Command Reference
- Security, Privacy & Data Compliance
- Troubleshooting & Status Codes
- Frequently Asked Questions (FAQ)
- License
The Google Places API provides high-throughput, structured access to Google's data and intelligence ecosystem. Extract Google Places, business listings, addresses, customer ratings, contact numbers, websites, and coordinates at scale without paying $17-$32 per 1,000 requests to Google Cloud Platform.
Operating production data scrapers, automated search pipelines, or autonomous AI agent tool callers against Google directly is notoriously difficult. Developers face continuous friction including strict rate limits, geo-blocking, headless browser maintenance overhead, dynamic DOM changes, and aggressive anti-scraping defenses. Furthermore, legacy commercial platforms charge steep enterprise premiums that make high-volume data retrieval financially unsustainable.
The APINEED Managed Gateway solves these operational challenges. By proxying requests through a resilient global infrastructure, the APINEED Google Places API delivers clean, standardized JSON data with sub-second response times, automated proxy rotation, CAPTCHA bypass, and up to 96% cost savings compared to Google Cloud Platform.
- Substantial Cost Reduction: Official Google Places API (New) charges $17-$32 per 1,000 requests. APINEED provides normalized place search at $1.25 per 1,000 requests.
- Normalized Data Shape: Every listing includes Title, Full Address, Rating, Review Count, Category/Type, Coordinates, Website, and Phone Number.
- Location Pinning and Bounding: Search with natural language queries or precise geographic map centers (@latitude,longitude,zoom).
- Dual Search Modes: Text-based place discovery and coordinate-centered map search.
- AI Agent Ready: Structured JSON output optimized for LLM consumption and agent tool calling.
Install the lightweight dependency and clone the repository:
# Install requests (the only required runtime dependency)
pip install requests
# Or clone the official repository
git clone https://github.com/Apineed/google-places-api.git
cd google-places-apiObtain your APINEED API key and set it in your environment:
# Set your APINEED API key in the shell
export APINEED_API_KEY="your_apineed_api_key_here"
# On Windows PowerShell:
# $env:APINEED_API_KEY="your_apineed_api_key_here"Tip: Sign up at APINEED (Google Places API) to receive instant API credentials and free test credits.
Execute queries using the bundled, zero-dependency client.py client:
from client import GooglePlacesClient
client = GooglePlacesClient(api_key="your_apineed_api_key")
# Search for local businesses
results = client.search(
query="Italian restaurants",
location="Downtown Chicago, Illinois",
country="us",
language="en",
page=1
)
for place in results.get("places", []):
rating = place.get("rating", "N/A")
reviews = place.get("rating_count", 0)
print(f"- {place['title']} (Rating: {rating}/5.0 - {reviews} reviews)")
print(f" Address: {place.get('address')}")
print(f" Phone: {place.get('phone_number')}")
print(f" Website: {place.get('website')}\n")The included client.py wrapper encapsulates all REST endpoints for Google Places API into simple, typed Python methods:
Search Google Places with optional country, location, and language.
- Gateway Endpoint:
/v1/tools/google_places/invoke - HTTP Method:
POST - Output Return: Clean JSON dictionary containing extracted result attributes.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
query |
str |
Yes | - |
Search query string |
location |
Optional[str] |
No | None |
Location name (e.g. 'Austin, TX') |
country |
Optional[str] |
No | None |
Two-letter country code |
language |
Optional[str] |
No | "en" |
Language code |
page |
Optional[int] |
No | 1 |
Page number |
Search Google Maps centered at @lat,long,zoom.
- Gateway Endpoint:
/v1/tools/google_maps/invoke - HTTP Method:
POST - Output Return: Clean JSON dictionary containing extracted result attributes.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
query |
str |
Yes | - |
Search query string |
ll |
Optional[str] |
No | None |
Map center @latitude,longitude,zoom |
place_id |
Optional[str] |
No | None |
Google Place ID |
language |
Optional[str] |
No | "en" |
Language code |
page |
Optional[int] |
No | 1 |
Page number |
All queries processed by the APINEED Google Places API gateway return deterministic, standardized JSON objects:
{
"request_id": "req_place_412",
"tool": "google_places",
"output": {
"query": "coffee shops",
"page": 1,
"places": [
{
"position": 1,
"title": "Sightglass Coffee",
"type": "Coffee shop",
"types": ["Coffee shop", "Cafe", "Espresso bar"],
"address": "270 7th St, San Francisco, CA 94103",
"rating": 4.6,
"rating_count": 1820,
"price_level": "$$",
"phone_number": "+1 415-861-1313",
"website": "https://sightglasscoffee.com",
"latitude": 37.7768,
"longitude": -122.4087,
"place_id": "ChIJb_example_id"
}
]
},
"usage": { "price_usd": "0.00125", "quota": 625 }
}Empower autonomous AI agents and Retrieval-Augmented Generation (RAG) systems with real-time intelligence from Google Places API:
from langchain.tools import tool
from client import GooglePlacesClient
places_client = GooglePlacesClient(api_key="your_api_key")
@tool
def find_local_businesses(query: str, location: str) -> str:
"""Search for local businesses and places near a location."""
data = places_client.search(query=query, location=location)
results = []
for p in data.get("places", [])[:5]:
results.append(f"{p['title']} - Rating: {p.get('rating', 'N/A')} - {p.get('address', '')}")
return "\n".join(results)When processing high-volume requests with Google Places API, follow this concurrent execution pattern using Python's built-in concurrent.futures:
import concurrent.futures
from client import GooglePlacesClient
# Initialize client
client = GooglePlacesClient()
targets = [
{"query": "specialty coffee", "location": "Seattle, WA"},
{"query": "data science consultancies", "location": "Austin, TX"},
{"query": "coworking spaces", "location": "New York, NY"},
]
def process_target(target):
try:
return client.search(query=target["query"], location=target["location"])
except Exception as err:
print(f"Error searching {target}: {err}")
return None
# Execute parallel extraction with thread pool
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
results = list(executor.map(process_target, targets))
print(f"Successfully processed {len(results)} queries via Google Places API.")To ensure maximum throughput, stability, and cost-efficiency when deploying Google Places API in production:
- Implement Intelligent Result Caching: Cache repetitive requests using Redis, Memcached, or local LRU cache to reduce latency and save API usage credits.
- Handle Transient Network Failures: Use exponential backoff retry algorithms with jitter to gracefully handle occasional network timeouts.
- Optimize Result Boundaries: Set result limits (
max_resultsorpage) appropriately for LLM contexts to avoid prompt token bloating while preserving semantic relevance. - Environment Variable Management: Never hardcode API keys in source control. Always read credentials via environment variables (
APINEED_API_KEY). - Connection Pooling: Use the client's internal requests session for connection reuse across repeated requests.
Compare the operational savings of utilizing APINEED for Google Places API workloads:
| Provider Platform | Starting Plan | Monthly Quota | Cost per 1,000 Requests | Cost per Individual Request |
|---|---|---|---|---|
| Google Cloud Places (New) | GCP Billing Required | Pay-per-use | $17.00 - $32.00 | $0.017 - $0.032 |
| SerpApi Google Maps | $25.00 / mo | 1,000 | $25.00 | $0.025 |
| APINEED | Pay-As-You-Go | Unlimited | $1.25 | $0.00125 (Up to 96% Lower) |
Key Takeaway: APINEED eliminates steep upfront monthly subscriptions and per-query surcharges, saving up to 96% compared to Google Cloud Platform.
You can also interact directly with the Google Places API gateway using standard cURL commands:
curl -X POST "https://apineed.com/v1/tools/google_places/invoke" \
-H "Authorization: Bearer YOUR_APINEED_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "veterinary clinics",
"location": "Seattle, WA",
"country": "us",
"language": "en",
"page": 1
}'- Encrypted in Transit: All interactions with the APINEED Google Places API are secured using TLS 1.3 encryption.
- Zero Query Logging Option: APINEED operates a stateless gateway architecture ensuring your search parameters, business intelligence targets, and proprietary customer queries are not permanently stored or harvested.
- Enterprise SLA: Guaranteed 99.9% uptime SLA backed by redundant multi-region proxy clusters.
| HTTP Status | Diagnosis | Resolution |
|---|---|---|
401 Unauthorized |
Invalid or missing APINEED API key | Verify that APINEED_API_KEY is exported and valid on your APINEED dashboard. |
400 Bad Request |
Malformed JSON payload or missing required parameter | Validate your request body matches the parameters in the API Methods & Reference. |
429 Too Many Requests |
Concurrency limit reached for your account tier | Implement exponential backoff retries or upgrade your account quota on APINEED. |
502 / 504 Gateway Delay |
Upstream data provider timeout | Retry the request with standard exponential backoff. |
Yes. Unlike official Google Cloud Platform pricing where contact details are billed under separate expensive SKUs, APINEED includes complete business details (address, phone, website, coordinates) in a single request.
Direct browser scraping of Google Maps encounters aggressive bot detection, dynamic canvas rendering, and frequent DOM changes. APINEED normalizes upstream data into clean JSON with sub-second response times.
Yes. Use the search_maps method with the ll parameter in @latitude,longitude,zoom format to center your search on specific coordinates.
Each result includes title, type, full address, rating, review count, price level, phone number, website URL, latitude, longitude, and Google Place ID.
This repository, sample code, and the Python client SDK are open-sourced under the permissive MIT License. Free for commercial and non-commercial usage.