serpex 2.6.0

Official Python SDK for Serpex Search API - Fetch search results in JSON format

serpex

Official Python SDK for the Serpex SERP API - Fetch search results in JSON format.

Installation

pip install serpex

Or with poetry:

poetry add serpex

Quick Start

from serpex import SerpexClient

# Initialize the client with your API key
client = SerpexClient('your-api-key-here')

# Search with auto-routing (recommended for simple use cases)
results = client.search({
    'q': 'python tutorial',
    'engine': 'auto'
})

# Or using SearchParams object for type safety
from serpex import SearchParams

params = SearchParams(q='python tutorial', engine='auto')
results = client.search(params)

print(results.results[0].title)

API Reference

SerpexClient

Constructor

SerpexClient(api_key: str, base_url: str = "https://api.serpex.dev")

• api_key: Your API key from the Serpex dashboard
• base_url: Optional base URL (defaults to 'https://api.serpex.dev')

Methods

extract(params: ExtractParams | Dict[str, Any]) -> ExtractResponse

Extract content from web pages and convert them to LLM-ready markdown data. Accepts up to 10 URLs per request.

# Basic usage
results = client.extract({
    'urls': [
        'https://example.com',
        'https://httpbin.org'
    ]
})

# With stealth mode and HTML output
results = client.extract({
    'urls': ['https://example.com'],
    'stealth': True,
    'format': 'html'
})

# Using ExtractParams object (type-safe approach)
from serpex import ExtractParams

params = ExtractParams(
    urls=['https://example.com'],
    stealth=True,
    format='html'
)
results = client.extract(params)

Extract Parameters

The ExtractParams dataclass supports extraction parameters:

@dataclass
class ExtractParams:
    # Required: URLs to extract (max 10)
    urls: List[str]

    # Optional: Route through premium unblocker for difficult-to-crawl pages (default: False)
    stealth: bool = False

    # Optional: Output format — 'markdown' (default) or 'html'
    format: str = 'markdown'

Extract Response Format

@dataclass
class ExtractResponse:
    success: bool
    results: List[ExtractResult]
    metadata: ExtractMetadata

@dataclass
class ExtractResult:
    url: str
    success: bool
    markdown: Optional[str] = None
    html: Optional[str] = None         # Populated when format='html'
    stealth: Optional[bool] = None     # Whether stealth mode was used for this result
    error: Optional[str] = None
    status_code: Optional[int] = None

@dataclass
class ExtractMetadata:
    total_urls: int
    processed_urls: int
    successful_crawls: int
    failed_crawls: int
    credits_used: int
    response_time: int
    timestamp: str
    cached_free: Optional[int] = None  # URLs served from cache (no credit charge)

Search Parameters

The SearchParams dataclass supports all search parameters:

@dataclass
class SearchParams:
    # Required: search query
    q: str

    # Optional: Engine selection (defaults to 'auto')
    engine: Optional[str] = 'auto'

    # Optional: Search category ('web' for general search, 'news' for news articles - always returns latest news)
    category: Optional[str] = 'web'  # Supports: 'web', 'news'

    # Optional: Time range filter (only applicable for 'web' category, ignored for 'news')
    time_range: Optional[str] = 'all'

    # Optional: Response format
    format: Optional[str] = 'json'

News Search Example

News search always returns the latest news articles. The time_range parameter is ignored for news searches.

# Search for latest news articles
news_results = client.search({
    'q': 'artificial intelligence',
    'engine': 'google',
    'category': 'news'  # Always returns latest news
})

print(news_results.results[0].title)
print(news_results.results[0].published_date)

## Supported Engines

- **auto**: Automatically routes to the best available search engine
- **google**: Google's primary search engine
- **bing**: Microsoft's search engine
- **duckduckgo**: Privacy-focused search engine
- **brave**: Privacy-first search engine
- **yahoo**: Yahoo search engine
- **yandex**: Russian search engine

## Response Format

```python
@dataclass
class SearchResponse:
    metadata: SearchMetadata
    id: str
    query: str
    engines: List[str]
    results: List[SearchResult]
    answers: List[Any]
    corrections: List[str]
    infoboxes: List[Any]
    suggestions: List[str]

Error Handling

The SDK raises SerpApiException for API errors:

from serpex import SerpexClient, SerpApiException

try:
    results = client.search(SearchParams(q='test query'))
except SerpApiException as e:
    print(f"API error: {e}")
    print(f"Status code: {e.status_code}")
    print(f"Details: {e.details}")

Examples

Basic Search

results = client.search({
    'q': 'coffee shops near me'
})

Advanced Search with Filters

results = client.search({
    'q': 'latest AI news',
    'engine': 'google',
    'time_range': 'day',
    'category': 'web'
})

Using SearchParams Object

from serpex import SearchParams

params = SearchParams(
    q='machine learning',
    engine='auto',
    time_range='month'
)
results = client.search(params)

Extract Web Content to LLM-Ready Data

Extract from a Single URL

# Extract content from one website (markdown, default)
result = client.extract({
    'urls': ['https://example.com']
})

if result.results[0].success:
    print(f"✅ Extracted {len(result.results[0].markdown)} characters")
    print("Markdown content:", result.results[0].markdown[:200] + "...")

# Extract with stealth mode and HTML output
stealth_result = client.extract({
    'urls': ['https://example.com'],
    'stealth': True,
    'format': 'html'
})

if stealth_result.results[0].success:
    print("HTML content:", stealth_result.results[0].html[:200])

Extract from Multiple URLs (up to 10 at once)

# Extract content from multiple websites (up to 10 URLs)
extract_results = client.extract({
    'urls': [
        'https://example.com',
        'https://httpbin.org',
        'https://github.com'
    ]
})

print(f"Successfully extracted {extract_results.metadata.successful_crawls} pages")
print(f"Total credits used: {extract_results.metadata.credits_used}")

for result in extract_results.results:
    if result.success:
        print(f"✅ {result.url}: {len(result.markdown)} characters")
        # Use result.markdown for LLM processing
    else:
        print(f"❌ {result.url}: {result.error}")

Sample Response

# Example response structure
{
    'success': True,
    'results': [
        {
            'url': 'https://example.com',
            'success': True,
            'markdown': '# Example Domain\n\nThis domain is for use in...',
            'stealth': False,
            'status_code': 200
        }
    ],
    'metadata': {
        'total_urls': 1,
        'processed_urls': 1,
        'successful_crawls': 1,
        'failed_crawls': 0,
        'credits_used': 3,
        'cached_free': 0,
        'response_time': 255,
        'timestamp': '2025-11-13T10:30:00.000Z'
    }
}

Using ExtractParams Object

from serpex import ExtractParams

params = ExtractParams(urls=[
    'https://example.com',
    'https://httpbin.org'
])
results = client.extract(params)

Requirements

• Python 3.8+
• requests

License

MIT