DDGS | Dux Distributed Global Search

A metasearch library that aggregates results from diverse web search services.

Table of Contents

• Install
• CLI version
• API Server
• DHT Network (BETA)
• MCP Server
• Engines
• DDGS class
• 1. text()
• 2. images()
• 3. videos()
• 4. news()
• 5. books()
• 6. extract()
• Disclaimer

---

Install

pip install -U ddgs       # Base install
pip install -U ddgs[api]  # API server (FastAPI)
pip install -U ddgs[mcp]  # MCP server (stdio)

CLI version

ddgs --help

Go To TOP

---

API Server

-- Install

pip install -U ddgs[api]

-- CLI

ddgs api              # Start server in foreground
ddgs api -d           # Start in detached mode (background)
ddgs api -s           # Stop detached server
ddgs api --host 127.0.0.1 --port 4479  # Default port 4479
ddgs api -pr socks5h://127.0.0.1:9150  # With proxy

-- Docker compose

git clone https://github.com/deedy5/ddgs && cd ddgs
docker-compose up --build

-- Bash script

git clone https://github.com/deedy5/ddgs && cd ddgs
chmod +x start_api.sh
./start_api.sh

Endpoints

Endpoint	Method	Description
/search/text	GET, POST	Text search
/search/images	GET, POST	Image search
/search/news	GET, POST	News search
/search/videos	GET, POST	Video search
/search/books	GET, POST	Book search
/extract	GET, POST	Extract content from URL
/health	GET	Health check
/docs	GET	Swagger UI
/redoc	GET	ReDoc documentation

Go To TOP

---

DHT Network (BETA)

DDGS includes an optional peer-to-peer distributed cache network. Search results are shared anonymously between users, drastically reducing rate limits and latency for everyone.

This is the only metasearch engine that can actually get faster the more people use it.

---

Why this exists

Every DDGS user currently hits search engines independently. Everyone gets rate limited individually. Everyone waits 1-2 seconds for exactly the same results.

The DHT network fixes this:

• ✅ 90% faster repeated queries (50ms instead of 1-2s)
• ✅ No rate limits for common queries
• ✅ Zero infrastructure cost - runs entirely on user machines
• ✅ No central server - cannot be blocked or shut down
• ✅ Anonymous - no one sees your queries, no logs

How it works

When running:

1. Your node automatically discovers other DDGS users
2. All existing API endpoints automatically check the network first
3. If found, returns results immediately
4. If not, searches normally and shares the result anonymously
5. Every new user makes the network faster for everyone else

---

Installation

# Install base DHT package
pip install -U ddgs[dht]

# Install required dependencies (works on Linux and macOS)
pip install coincurve@git+https://github.com/ofek/coincurve.git@7829b29c08ebb1cc80386a1cdaf8c2243c4ef5c5
pip install libp2p@git+https://github.com/libp2p/py-libp2p.git@0e88584c89377086883c6f5b26cd1a8052399be7

# macOS only: First install gmp
brew install gmp

# Windows: DHT is not supported. Use base package only.

When installed, DHT:

• Adds persistent local result cache
• Adds /dht/* endpoints to the API server automatically
• Starts full distributed network node when you run ddgs api
• Works fully transparently - all existing search methods automatically use cache

Platform Support: DHT works on Linux and macOS. Windows is not currently supported due to libp2p dependencies.

Running

1. Using terminal

ddgs api -d

2. Using DDGS initialization

from ddgs import DDGS

ddgs = DDGS(api_url="http://localhost:4479", spawn_api=True)

You do not need to change any existing code. Any Python script using DDGS().text(), images(), etc. will automatically use both the local cache and the distributed DHT network.

DHT will automatically start in the background and begin participating in the network.

DHT API Endpoints

Endpoint	Method	Description
/dht/cache	GET	Get cached results
/dht/cache	POST	Store results to cache
/dht/cache	DELETE	Invalidate cached results
/dht/status	GET	DHT service status and metrics
/dht/peers	GET	List connected peers
/dht/peers/detailed	GET	Detailed peer information
/dht/map	GET	Network graph view
/dht/metrics	GET	Prometheus format metrics

---

Beta Status

This is working beta software. All functionality is complete, but network performance will improve as more users join:

Network Size	Performance
< 50 nodes	Marginal - expect timeouts
50-200 nodes	Good - >95% success rate
>200 nodes	Excellent - near perfect

Results use eventual consistency and may take 1-5 minutes to propagate.

Please report any issues here: https://github.com/deedy5/ddgs/issues

Go To TOP

---

MCP Server

• Install

pip install -U ddgs[mcp]

• CLI

ddgs mcp    # Start MCP server (stdio transport)
ddgs mcp -pr socks5h://127.0.0.1:9150  # With proxy

Available Tools

Tool	Description
search_text	Web text search
search_images	Image search
search_news	News search
search_videos	Video search
search_books	Book search
extract_content	Extract content from a URL

Client Configuration

For MCP clients like Cursor or Claude Desktop:

{
  "mcpServers": {
    "ddgs": {
      "command": "ddgs",
      "args": ["mcp"]
    }
  }
}

Go To TOP

---

Engines

DDGS function	Available backends
text()	bing, brave, duckduckgo, google, grokipedia, mojeek, yandex, yahoo, wikipedia
images()	bing, duckduckgo
videos()	duckduckgo
news()	bing, duckduckgo, yahoo
books()	annasarchive

Go To TOP

DDGS class

DDGS class is lazy-loaded.

class DDGS:
    """Dux Distributed Global Search. A metasearch library that aggregates results from diverse web search services.

    Args:
        proxy (str, optional): proxy for the HTTP client, supports http/https/socks5 protocols.
            example: "http://user:pass@example.com:3128". Defaults to None.
        timeout (int, optional): Timeout value for the HTTP client. Defaults to 5.
        verify: (bool | str):  True to verify, False to skip, or a str path to a PEM file. Defaults to True.
    """

Here is an example of initializing the DDGS class.

from ddgs import DDGS

results = DDGS().text("python programming", max_results=5)
print(results)

Go To TOP

1. text()

def text(
    query: str,
    region: str = "us-en",
    safesearch: str = "moderate",
    timelimit: str | None = None,
    max_results: int | None = 10,
    page: int = 1,
    backend: str = "auto",
) -> list[dict[str, str]]:
    """DDGS text metasearch.

    Args:
        query: text search query.
        region: us-en, uk-en, ru-ru, etc. Defaults to us-en.
        safesearch: on, moderate, off. Defaults to "moderate".
        timelimit: d, w, m, y. Defaults to None.
        max_results: maximum number of results. Defaults to 10.
        page: page of results. Defaults to 1.
        backend: A single or comma-delimited backends. Defaults to "auto".

    Returns:
        List of dictionaries with search results.
    """

Example

results = DDGS().text("live free or die", region="us-en", safesearch="off", timelimit="y", page=1, backend="auto")
# Searching for pdf files
results = DDGS().text("russia filetype:pdf", region="us-en", safesearch="off", timelimit="y", page=1, backend="auto")
print(results)
[
    {
        "title": "News, sport, celebrities and gossip | The Sun",
        "href": "https://www.thesun.co.uk/",
        "body": "Get the latest news, exclusives, sport, celebrities, showbiz, politics, business and lifestyle from The Sun",
    },
    ...,
]

Go To TOP

2. images()

def images(
    query: str,
    region: str = "us-en",
    safesearch: str = "moderate",
    timelimit: str | None = None,
    max_results: int | None = 10,
    page: int = 1,
    backend: str = "auto",
    size: str | None = None,
    color: str | None = None,
    type_image: str | None = None,
    layout: str | None = None,
    license_image: str | None = None,
) -> list[dict[str, str]]:
    """DDGS images metasearch.

    Args:
        query: images search query.
        region: us-en, uk-en, ru-ru, etc. Defaults to us-en.
        safesearch: on, moderate, off. Defaults to "moderate".
        timelimit: d, w, m, y. Defaults to None.
        max_results: maximum number of results. Defaults to 10.
        page: page of results. Defaults to 1.
        backend: A single or comma-delimited backends. Defaults to "auto".
        size: Small, Medium, Large, Wallpaper. Defaults to None.
        color: color, Monochrome, Red, Orange, Yellow, Green, Blue,
            Purple, Pink, Brown, Black, Gray, Teal, White. Defaults to None.
        type_image: photo, clipart, gif, transparent, line.
            Defaults to None.
        layout: Square, Tall, Wide. Defaults to None.
        license_image: any (All Creative Commons), Public (PublicDomain),
            Share (Free to Share and Use), ShareCommercially (Free to Share and Use Commercially),
            Modify (Free to Modify, Share, and Use), ModifyCommercially (Free to Modify, Share, and
            Use Commercially). Defaults to None.

    Returns:
        List of dictionaries with images search results.
    """

Example

results = DDGS().images(
    query="butterfly",
    region="us-en",
    safesearch="off",
    timelimit="m",
    page=1,
    backend="auto",
    size=None,
    color="Monochrome",
    type_image=None,
    layout=None,
    license_image=None,
)
print(images)
[
    {
        "title": "File:The Sun by the Atmospheric Imaging Assembly of NASA's Solar ...",
        "image": "https://upload.wikimedia.org/wikipedia/commons/b/b4/The_Sun_by_the_Atmospheric_Imaging_Assembly_of_NASA's_Solar_Dynamics_Observatory_-_20100819.jpg",
        "thumbnail": "https://tse4.mm.bing.net/th?id=OIP.lNgpqGl16U0ft3rS8TdFcgEsEe&pid=Api",
        "url": "https://en.wikipedia.org/wiki/File:The_Sun_by_the_Atmospheric_Imaging_Assembly_of_NASA's_Solar_Dynamics_Observatory_-_20100819.jpg",
        "height": 3860,
        "width": 4044,
        "source": "Bing",
    },
    ...,
]

Go To TOP

3. videos()

def videos(
    query: str,
    region: str = "us-en",
    safesearch: str = "moderate",
    timelimit: str | None = None,
    max_results: int | None = 10,
    page: int = 1,
    backend: str = "auto",
    resolution: str | None = None,
    duration: str | None = None,
    license_videos: str | None = None,
) -> list[dict[str, str]]:
    """DDGS videos metasearch.

    Args:
        query: videos search query.
        region: us-en, uk-en, ru-ru, etc. Defaults to us-en.
        safesearch: on, moderate, off. Defaults to "moderate".
        timelimit: d, w, m. Defaults to None.
        max_results: maximum number of results. Defaults to 10.
        page: page of results. Defaults to 1.
        backend: A single or comma-delimited backends. Defaults to "auto".
        resolution: high, standart. Defaults to None.
        duration: short, medium, long. Defaults to None.
        license_videos: creativeCommon, youtube. Defaults to None.

    Returns:
        List of dictionaries with videos search results.
    """

Example

results = DDGS().videos(
    query="cars",
    region="us-en",
    safesearch="off",
    timelimit="w",
    page=1,
    backend="auto",
    resolution="high",
    duration="medium",
)
print(results)
[
    {
        "content": "https://www.youtube.com/watch?v=6901-C73P3g",
        "description": "Watch the Best Scenes of popular Tamil Serial #Meena that airs on Sun TV. Watch all Sun TV serials immediately after the TV telecast on Sun NXT app. *Free for Indian Users only Download here: Android - http://bit.ly/SunNxtAdroid iOS: India - http://bit.ly/sunNXT Watch on the web - https://www.sunnxt.com/ Two close friends, Chidambaram ...",
        "duration": "8:22",
        "embed_html": '<iframe width="1280" height="720" src="https://www.youtube.com/embed/6901-C73P3g?autoplay=1" frameborder="0" allowfullscreen></iframe>',
        "embed_url": "https://www.youtube.com/embed/6901-C73P3g?autoplay=1",
        "image_token": "6c070b5f0e24e5972e360d02ddeb69856202f97718ea6c5d5710e4e472310fa3",
        "images": {
            "large": "https://tse4.mm.bing.net/th?id=OVF.JWBFKm1u%2fHd%2bz2e1GitsQw&pid=Api",
            "medium": "https://tse4.mm.bing.net/th?id=OVF.JWBFKm1u%2fHd%2bz2e1GitsQw&pid=Api",
            "motion": "",
            "small": "https://tse4.mm.bing.net/th?id=OVF.JWBFKm1u%2fHd%2bz2e1GitsQw&pid=Api",
        },
        "provider": "Bing",
        "published": "2024-07-03T05:30:03.0000000",
        "publisher": "YouTube",
        "statistics": {"viewCount": 29059},
        "title": "Meena - Best Scenes | 02 July 2024 | Tamil Serial | Sun TV",
        "uploader": "Sun TV",
    },
    ...,
]

Go To TOP

4. news()

def news(
    query: str,
    region: str = "us-en",
    safesearch: str = "moderate",
    timelimit: str | None = None,
    max_results: int | None = 10,
    page: int = 1,
    backend: str = "auto",
) -> list[dict[str, str]]:
    """DDGS news metasearch.

    Args:
        query: news search query.
        region: us-en, uk-en, ru-ru, etc. Defaults to us-en.
        safesearch: on, moderate, off. Defaults to "moderate".
        timelimit: d, w, m. Defaults to None.
        max_results: maximum number of results. Defaults to 10.
        page: page of results. Defaults to 1.
        backend: A single or comma-delimited backends. Defaults to "auto".

    Returns:
        List of dictionaries with news search results.
    """

Example

results = DDGS().news(query="sun", region="us-en", safesearch="off", timelimit="m", page=1, backend="auto")
print(results)
[
    {
        "date": "2024-07-03T16:25:22+00:00",
        "title": "Murdoch's Sun Endorses Starmer's Labour Day Before UK Vote",
        "body": "Rupert Murdoch's Sun newspaper endorsed Keir Starmer and his opposition Labour Party to win the UK general election, a dramatic move in the British media landscape that illustrates the country's shifting political sands.",
        "url": "https://www.msn.com/en-us/money/other/murdoch-s-sun-endorses-starmer-s-labour-day-before-uk-vote/ar-BB1plQwl",
        "image": "https://img-s-msn-com.akamaized.net/tenant/amp/entityid/BB1plZil.img?w=2000&h=1333&m=4&q=79",
        "source": "Bloomberg on MSN.com",
    },
    ...,
]

Go To TOP

5. books()

def books(
    query: str,
    max_results: int | None = 10,
    page: int = 1,
    backend: str = "auto",
) -> list[dict[str, str]]:
    """DDGS books metasearch.

    Args:
        query: news search query.
        max_results: maximum number of results. Defaults to 10.
        page: page of results. Defaults to 1.
        backend: A single or comma-delimited backends. Defaults to "auto".

    Returns:
        List of dictionaries with news search results.
    """

Example

results = DDGS().books(query="sea wolf jack london", page=1, backend="auto")
print(results)
[
    {
        "title": "The Sea-Wolf",
        "author": "Jack London",
        "publisher": "DigiCat, 2022",
        "info": "English [en], .epub, 🚀/zlib, 0.5MB, 📗 Book (unknown)",
        "url": "https://annas-archive.li/md5/574f6556f1df6717de4044e36c7c2782",
        "thumbnail": "https://s3proxy.cdn-zlib.sk//covers299/collections/userbooks/da4954486be7c2b2b9f70b2aa5bcf01292de3ea510b5656f892821950ded9ada.jpg",
    },
    ...,
]

Go To TOP

6. extract()

Fetch a URL and extract its content in various formats.

def extract(
    url: str,
    fmt: str = "text_markdown",
) -> dict[str, str | bytes]:
    """Fetch a URL and extract its content.

    Args:
        url: The URL to fetch and extract content from.
        fmt: Output format:
            "text_markdown" (HTML→Markdown, preserves links/headers/lists),
            "text_plain" (HTML→plain text),
            "text_rich" (HTML→rich text with headers/lists),
            "text" (raw HTML),
            "content" (raw bytes).

    Returns:
        Dictionary with 'url' and 'content' keys.
    """

Examples

# Markdown (default) - preserves links, headers, lists
result = DDGS().extract("https://example.com")
print(result)
{"url": "https://example.com", "content": "# Example Domain\n\nThis domain is for use in..."}

# Plain text
result = DDGS().extract("https://example.com", fmt="text_plain")

# Rich text (headers/lists, no link URLs)
result = DDGS().extract("https://example.com", fmt="text_rich")

# Raw HTML
result = DDGS().extract("https://example.com", fmt="text")

# Raw bytes
result = DDGS().extract("https://example.com", fmt="content")

CLI

ddgs extract -u https://example.com
ddgs extract -u https://example.com -f text_plain
ddgs extract -u https://example.com -f content -o output.json

Go To TOP

Disclaimer

This library is for educational purposes only.