Bringing Transparency to online tracking - built by Cliqz and Ghostery.

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This repository contains:

• data on trackers and websites as shown on whotracks.me (WTM)
• database mapping tracker domains to companies
• code to render the whotracks.me site

Installation

Python 3.6 is needed to build the site. We recommend creating a virtualenv (or pipenv) to install the dependencies.

From Pypi

$ pip install whotracksme

From source

$ pip install -r requirements.txt
$ pip install -e .

That’s all you need to get started!

Using the data

To get started with the data, everything you need can be found in whotracksme.data:

from whotracksme.data.loader import DataSource

data = DataSource()

# available entities
data.trackers
data.companies
data.sites

Building the site

Building the site requires a few extra dependencies, not installed by default to not make the installation heavier than it needs to be. You will need to install whotracksme from the repository, because not all assets are packaged with whotracksme released on pypi:

$ pip install -r requirements-dev.txt
$ pip install -e '.[dev]'

Once this is done, you will have access to a whotracksme entry point that can be used this way:

$ whotracksme website [serve]

The serve part is optional and can be used while making changes on the website.

All generated artifacts can be found in the _site/ folder.

Tests

To run tests, you will need pytest, or simply install whotacksme with the dev extra:

$ pip install -e '.[dev]'
$ pytest

Publishing a new version

$ pip install twine
$ python setup.py sdist bdist_wheel
$ twine upload --username cliqz-oss dist/*

Contributing

We are happy to take contributions on:

• Guest articles for our blog in the topics of tracking, privacy and security. Feel free to use the data in this repository if you need inspiration.
• Feature requests that are doable using the WTM database.
• Curating our database of tracker profiles. Open an issue if you spot anything odd.

Right to Amend

Please read our Guideline for 3rd parties wanting to suggest corrections to their data.

License

The content of this project itself is licensed under the Creative Commons Attribution 4.0 license, and the underlying source code used to generate and display that content is licensed under the MIT license.