Linux + Docker

  1. Install Docker.

  2. Pull the image:

    $ sudo docker pull scrapinghub/splash
  3. Start the container:

    $ sudo docker run -p 5023:5023 -p 8050:8050 -p 8051:8051 scrapinghub/splash
  4. Splash is now available at at ports 8050 (http), 8051 (https) and 5023 (telnet).

OS X + Docker

  1. Install Docker (via the Toolbox Instructions).

  2. Create, run & load the configuration for the docker-machine

    $ docker-machine create default

    $ docker-machine start default

    $ eval “$(docker-machine env default)”

  1. Pull the image:

    $ docker pull scrapinghub/splash
  2. Start the container:

    $ docker run -p 5023:5023 -p 8050:8050 -p 8051:8051 scrapinghub/splash
  3. Figure out the ip address of the docker-machine:

    $ docker-machine ip default
  4. Splash is available at the returned IP address at ports 8050 (http), 8051 (https) and 5023 (telnet).

Ubuntu 14.04 (manual way)

1. Install system dependencies (check <>)

  1. Clone the repo from GitHub:

    $ git clone
  2. Install dependencies with pip:

    $ cd splash
    $ pip3 install -r requirements.txt

To run the server execute the following command:

python3 -m splash.server

Run python -m splash.server --help to see options available.

By default, Splash API endpoints listen to port 8050 on all available IPv4 addresses. To change the port use --port option:

python3 -m splash.server --port=5000

Required Python packages

# install PyQt5 (Splash is tested on PyQT 5.5.1)
# and the following packages:
twisted >= 15.5.0, < 16.3.0
adblockparser >= 0.5

# for scripting support
lupa >= 1.3
funcparserlib >= 0.3.6

Splash Versions

docker pull scrapinghub/splash will give you the latest stable Splash release. To obtain the latest development version use docker pull scrapinghub/splash:master. Specific Splash versions are also available, e.g. docker pull scrapinghub/splash:1.8.

Customizing Dockerized Splash

Passing Custom Options

To run Splash with custom options pass them to docker run. For example, let’s increase log verbosity:

$ docker run -p 8050:8050 scrapinghub/splash -v3

To see all possible options pass --help. Not all options will work the same inside Docker: changing ports doesn’t make sense (use docker run options instead), and paths are paths in the container.

Folders Sharing

To set custom Request Filters use -v Docker option. First, create a folder with request filters on your local filesystem, then make it available to the container:

$ docker run -p 8050:8050 -v <my-filters-dir>:/etc/splash/filters scrapinghub/splash

Replace <my-filters-dir> with a path of your local folder with request filters.

Docker Data Volume Containers can also be used. Check for more info.

Proxy Profiles and Javascript Profiles can be added in a similar way:

$ docker run -p 8050:8050 \
      -v <my-proxy-profiles-dir>:/etc/splash/proxy-profiles \
      -v <my-js-profiles-dir>:/etc/splash/js-profiles \

To setup Adding Your Own Modules mount a folder to /etc/splash/lua_modules. If you use a Lua sandbox (default) don’t forget to list safe modules using --lua-sandbox-allowed-modules option:

$ docker run -p 8050:8050 \
      -v <my-lua-modules-dir>:/etc/splash/lua_modules \
      --lua-sandbox-allowed-modules 'module1;module2' \


Folder sharing (-v option) doesn’t work on OS X and Windows (see It should be fixed in future Docker & Boot2Docker releases. For now use one of the workarounds mentioned in issue comments or clone Splash repo and customize its Dockerfile.

Building Local Docker Images

To build your own Docker image, checkout Splash source code using git, then execute the following command from Splash source root:

$ docker build -t my-local-splash .

To build Splash-Jupyter Docker image use this command:

$ docker build -t my-local-splash-jupyter -f  dockerfiles/splash-jupyter/Dockerfile .

You may have to change FROM line in dockerfiles/splash-jupyter/Dockerfile if you want it to be based on your local Splash Docker container.