Metadata-Version: 2.4
Name: google-search-scraper-api
Version: 0.0.5
Summary: Python client for scraping Google Search results using the ScrapingBee Google Search API
Author-email: Your Name <you@example.com>
License: MIT
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests
Dynamic: license-file

# google-search-scraper-api

A production-ready Python client for the Google Search Scraper API powered by ScrapingBee.

This package provides a clean and reliable way to scrape Google Search results using a managed infrastructure layer. Instead of dealing with proxies, CAPTCHA solving, fingerprint rotation, and layout instability, you can use a structured google scraper api that returns consistent JSON responses.

[Built on top of ScrapingBee's Google Search API](https://www.scrapingbee.com/features/google/)


If you're looking for:

- google search scraper api  
- google scraper api  
- google search scraper  

This package provides a simple, scalable implementation.


## Why Use a Google Search Scraper API?

Scraping Google manually is fragile.

A basic HTTP request often leads to:

- IP blocking  
- Rate limiting  
- CAPTCHA challenges  
- Incomplete HTML responses  
- Frequent DOM structure changes  

A managed **google search scraper api** handles:

- Proxy rotation  
- Anti-bot protection  
- Google-specific request routing  
- Geo-targeting  
- Structured JSON output  

This allows developers to focus on data extraction instead of scraping infrastructure.


## Installation

```bash
pip install google-search-scraper-api
```

Dependencies:

- Python 3.8+
- requests



## Quick Start

```python
from google_search_scraper_api import GoogleSearchScraper

API_KEY = "YOUR_API_KEY"

scraper = GoogleSearchScraper(api_key=API_KEY)

results = scraper.search(
    query="python web scraping",
    country="us",
    language="en"
)

for result in results["organic_results"]:
    print(result["title"])
    print(result["link"])
    print(result["snippet"])
    print("-" * 40)
```



## How It Works

This package sends requests to ScrapingBee's Google endpoint:

```
https://app.scrapingbee.com/api/v1/
```

With:

```
search=google
```

Under the hood, the API handles:

- Proxy management  
- Google anti-bot mitigation  
- Premium routing  
- Geo-targeted queries  
- Structured SERP parsing  

Official product page:
https://www.scrapingbee.com/features/google/



## Full Example

```python
from google_search_scraper_api import GoogleSearchScraper

scraper = GoogleSearchScraper(api_key="YOUR_API_KEY")

response = scraper.search(
    query="best seo tools",
    country="us",
    language="en",
    device="desktop",
    premium=True
)

print(response.keys())
```


## Extract Organic Results

```python
for result in response.get("organic_results", []):
    print({
        "position": result.get("position"),
        "title": result.get("title"),
        "url": result.get("link"),
        "snippet": result.get("snippet")
    })
```



## Pagination

```python
page_2 = scraper.search(
    query="python scraping",
    start=10
)
```

The `start` parameter increments in steps of 10.



## Extract Advanced SERP Features

The API supports structured extraction of:

- Featured snippets  
- Related searches  
- People Also Ask  
- Ads  
- Knowledge panels  

Example:

```python
featured = response.get("featured_snippet")

if featured:
    print(featured.get("title"))
    print(featured.get("snippet"))
```



## Configuration Options

| Parameter        | Description |
|------------------|------------|
| query            | Search query string |
| country          | Country code (us, uk, de, fr, etc.) |
| language         | Language code |
| device           | desktop or mobile |
| start            | Pagination offset |
| premium          | Enable premium proxy routing |



## Production Use Cases

This google search scraper is commonly used for:

- Rank tracking systems  
- SEO monitoring dashboards  
- Competitor intelligence platforms  
- Keyword research pipelines  
- SERP analysis tools  
- Content optimization platforms  



## Why This Google Scraper API Is Reliable

Unlike raw scraping approaches, this implementation:

- Avoids brittle HTML parsing  
- Returns structured JSON  
- Handles Google layout changes  
- Reduces maintenance overhead  
- Scales across regions  

Using a dedicated **google search scraper api** significantly reduces infrastructure complexity.



## Error Handling Example

```python
try:
    results = scraper.search(query="data extraction")
except Exception as e:
    print(f"Request failed: {e}")
```



## Scaling Architecture Example

For large-scale scraping:

- Distribute queries via task queues (Redis, Celery, Kafka)
- Process requests asynchronously
- Store structured JSON in databases
- Monitor failure rates
- Cache repeated queries

The managed google scraper api layer ensures request stability while your system handles orchestration.


## Example JSON Response

```json
{
  "organic_results": [
    {
      "position": 1,
      "title": "Python Web Scraping Tutorial",
      "link": "https://example.com",
      "snippet": "Learn how to scrape websites using Python..."
    }
  ],
  "related_searches": [
    "web scraping python tutorial",
    "scrape google search results python"
  ]
}
```


## When to Use This Package

Use this google search scraper if you:

- Need structured SERP data  
- Want stable scraping without proxy management  
- Are building production-grade SEO tools  
- Require geo-targeted search results  
- Need reliable pagination support  


## Documentation

[Google Search API documentation](https://www.scrapingbee.com/features/google/)

[ScrapingBee main site](https://www.scrapingbee.com/)


## License

MIT


## Disclaimer

This package is a client wrapper built on top of ScrapingBee's Google Search API. Users are responsible for complying with Google's terms of service and applicable regulations.


## Final Thoughts

Scraping Google at scale requires infrastructure, monitoring, and continuous adaptation. By using a managed **google search scraper api**, developers can avoid brittle implementations and focus on building reliable data products.

This package provides a clean, production-ready way to integrate a google scraper api into Python applications.
