Skip to main content

Official Python SDK for SerpShot API - Google Search Results

Project description

SerpShot Python SDK

Official Python client for the SerpShot API - Get real-time Google search results programmatically.

Python Version License

中文文档 | English

Key Features

  • Lightning Fast - Get results in 1-2 seconds with optimized infrastructure
  • 🌍 Global Coverage - Support for 200+ countries and regions
  • 🔒 Reliable & Secure - 99.9% uptime SLA with enterprise-grade security
  • 🚀 Developer Friendly - Sync/async support, full type hints, intuitive API
  • 🔄 Batch Queries - Process up to 100 queries in a single request
  • 🛡️ Smart Retries - Built-in retry logic handles network issues automatically

API Endpoints

The SDK uses the following SerpShot API endpoints:

  • Main Search: /api/search/google - For regular and image searches

Installation

Using pip

pip install serpshot

Using uv

uv add serpshot

Get Your API Key

Free to use, just register to get your API key.

Quick Start

Synchronous Usage

from serpshot import SerpShot

# Initialize client (API key can be provided or read from SERPSHOT_API_KEY env var)
client = SerpShot(api_key="your-api-key")

# Perform a search
response = client.search("Python programming")

# Process results
for result in response.results:
    print(f"{result.title}: {result.link}")

# Clean up
client.close()

With Context Manager (Recommended)

from serpshot import SerpShot

with SerpShot(api_key="your-api-key") as client:
    response = client.search("Python programming")
    print(f"Found {len(response.results)} results")

Asynchronous Usage

import asyncio
from serpshot import AsyncSerpShot

async def main():
    async with AsyncSerpShot(api_key="your-api-key") as client:
        response = await client.search("Python programming")
        print(f"Found {len(response.results)} results")

asyncio.run(main())

Using Environment Variable

You can set your API key via the SERPSHOT_API_KEY environment variable, eliminating the need to pass it explicitly:

export SERPSHOT_API_KEY="your-api-key"
from serpshot import SerpShot

# API key will be automatically read from environment variable
with SerpShot() as client:
    response = client.search("Python programming")

API Reference

SerpShot Client

Initialize

from serpshot import SerpShot

client = SerpShot(
    api_key="your-api-key",      # Optional: Your SerpShot API key (or set SERPSHOT_API_KEY env var)
    base_url=None,                # Optional: Custom API endpoint
    timeout=30.0,                 # Optional: Request timeout in seconds
    max_retries=3,                # Optional: Maximum retry attempts
)

search()

Perform a Google search. Supports both single query and batch queries (up to 100 queries per request).

from serpshot import SerpShot

# Single search
response = client.search(
    query="search query",         # Required: Search query string or list of queries (max 100)
    num=10,                       # Optional: Number of results per page (1-100)
    page=1,                       # Optional: Page number for pagination (starts from 1)
    gl="us",                      # Optional: Country code (e.g., 'us', 'uk', 'cn')
    hl="en",                      # Optional: Language code (e.g., 'en', 'zh-CN')
    lr="en",                      # Optional: Content language restriction (e.g., 'en', 'zh-CN')
    location="US",                # Optional: Location for local search (e.g., 'US', 'GB', 'CN')
)

# Batch search (recommended for multiple queries)
responses = client.search(
    query=["Python", "JavaScript", "Rust"],  # List of queries (1-100)
    num=10,
    gl="us",
    location="US",               # String location parameter supported
)
# Returns list[SearchResponse] when query is a list

Note: The location parameter accepts strings (recommended) or LocationType enum values.

image_search()

Perform a Google image search. Supports both single query and batch queries (up to 100 queries per request).

# Single image search
response = client.image_search(
    query="cute puppies",         # Required: Image search query string or list (max 100)
    num=10,                       # Optional: Number of results per page (1-100)
    page=1,                       # Optional: Page number for pagination (starts from 1)
    gl="us",                      # Optional: Country code
    hl="en",                      # Optional: Language code
    lr="en",                      # Optional: Content language restriction
)

# Batch image search
responses = client.image_search(
    query=["cats", "dogs", "birds"],  # List of queries (1-100)
    num=10,
)

Response Model

The SearchResponse object contains:

class SearchResponse:
    success: bool                 # Request success status
    query: str                    # Original search query
    total_results: str            # Estimate of total results (e.g., "About 12,300,000 results")
    search_time: str              # Search execution time in seconds (as string)
    results: list[SearchResult] | list[ImageResult]  # List of search results
    credits_used: int             # Credits consumed

Note: When using batch search (passing a list of queries), search() returns list[SearchResponse] instead of a single SearchResponse.

Search Result Model

Each result in response.results contains:

class SearchResult:
    title: str                    # Result title
    link: str                     # Result URL
    snippet: str                  # Description snippet
    position: int                 # Position in results (1-based)

Image Result Model

For image searches, results contain:

class ImageResult:
    title: str                    # Image title
    link: str                     # Image source URL
    thumbnail: str                # Thumbnail URL
    source: str                   # Source website
    source_link: str              # Source page URL
    width: int                    # Image width in pixels
    height: int                   # Image height in pixels
    position: int                 # Result position

Advanced Examples

Batch Search

Batch search allows you to process multiple queries (up to 100) in a single API call, which is more efficient than separate calls:

from serpshot import SerpShot

with SerpShot(api_key="your-api-key") as client:
    queries = ["Python", "JavaScript", "Rust", "Go"]
    responses = client.search(queries, num=10)  # Returns list[SearchResponse]
    
    for query, response in zip(queries, responses):
        print(f"{query}: {len(response.results)} results")
        if response.results:
            print(f"  Top result: {response.results[0].title}\n")

Pagination

from serpshot import SerpShot

with SerpShot(api_key="your-api-key") as client:
    page1 = client.search("Python", num=10, page=1)
    page2 = client.search("Python", num=10, page=2)
    page3 = client.search("Python", num=10, page=3)

Asynchronous Batch Search

import asyncio
from serpshot import AsyncSerpShot

async def main():
    async with AsyncSerpShot(api_key="your-api-key") as client:
        queries = ["Python", "JavaScript", "Rust"]
        responses = await client.search(queries, num=10)
        for response in responses:
            print(f"Found {len(response.results)} results")

asyncio.run(main())

Error Handling

from serpshot import (
    SerpShot,
    AuthenticationError,
    RateLimitError,
    InsufficientCreditsError,
    APIError,
    NetworkError,
)

try:
    with SerpShot(api_key="your-api-key") as client:
        response = client.search("test query")
except AuthenticationError as e:
    print(f"Invalid API key: {e}")
except RateLimitError as e:
    print(f"Rate limit exceeded. Retry after {e.retry_after}s")
except InsufficientCreditsError as e:
    print(f"Insufficient credits. Need: {e.credits_required}")
except APIError as e:
    print(f"API error ({e.status_code}): {e.message}")
except NetworkError as e:
    print(f"Network error: {e}")

Custom Configuration

client = SerpShot(
    api_key="your-api-key",
    timeout=60.0,        # Longer timeout for slow connections
    max_retries=5,       # More retries for reliability
)

Get Available Credits

from serpshot import SerpShot

with SerpShot(api_key="your-api-key") as client:
    credits = client.get_available_credits()
    print(f"Available credits: {credits}")

Rate Limits

Please refer to your SerpShot account dashboard for rate limit information. The SDK automatically handles rate limiting with exponential backoff.

Credit Costs

Different search operations consume different amounts of credits.

Use the response.credits_used field to track actual credit consumption for each request.

Development

Setup

# Clone the repository
git clone https://github.com/downdawn/serpshot-python.git
cd serpshot-python

# Install with dev dependencies using uv
uv sync --dev

# Or using pip
pip install -e ".[dev]"

Run Tests

pytest

Type Checking

mypy serpshot

Linting

ruff check serpshot

Examples

Check out the examples directory for more usage examples:

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

serpshot-0.2.0.tar.gz (75.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

serpshot-0.2.0-py3-none-any.whl (20.4 kB view details)

Uploaded Python 3

File details

Details for the file serpshot-0.2.0.tar.gz.

File metadata

  • Download URL: serpshot-0.2.0.tar.gz
  • Upload date:
  • Size: 75.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.5

File hashes

Hashes for serpshot-0.2.0.tar.gz
Algorithm Hash digest
SHA256 5c987e606526e407b5ea9ed9d1c59ce81ca31741731e171f9decb2b23c33f22f
MD5 794bff5131d33142bc5bb9157bffdcf9
BLAKE2b-256 f4c06906c225817e7cda061af198ad971fec040d02a1fd6ef3505f1d3abcd5ad

See more details on using hashes here.

File details

Details for the file serpshot-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: serpshot-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 20.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.5

File hashes

Hashes for serpshot-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 2578faddfcbf58bcbcd0334bfd60352fb20f0a5dc521cef0c1fac52a328edf79
MD5 3c23e006e27ff33b008523d6a689f1cf
BLAKE2b-256 d50088404b7b58791d8c93e0fdd033a568bbeccf29bc765f7adf037f2f6d39d2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page