Crest quickly tests any HTML web page for a simple way to solve your accessibility testing problems. Provide a website URL to our callable API and expose potential WCAG violations.

Getting Started with Crest in 5 Minutes

To get you started quickly let’s dive into the necessary steps needed to set up the environment.

To use Crest as a Python Library

Using Pip

  1. Install Crest using python package manager (Make sure pip is installed in your system).
pip install pythoncrest

To use Crest as a Service

Using Conda

  1. Download and Install Miniconda from

  2. For Windows, launch Miniconda prompt shell. For MacOS, launch the terminal.

  3. Clone the Crest repository. More details can be found at

  4. Go to "crest" folder in your terminal/prompt shell. Run command.

conda env create -f environment.yml
conda activate crest
  1. Install chromedriver. The details can be found in

  2. Download and Install google-chrome-stable from

  3. Once all the required libraries are installed, go to 'src/crest' folder and run the below command in your terminal/prompt shell. FLASK_ENV=development flask run --port 3000 --host

Using Docker

  1. Clone the repository. More details can be found at

  2. Download and Install docker from Note: Make sure your docker server as well as crest image is running.

  3. Go to "crest" folder in your terminal/prompt shell. Run command.

docker build -t crest .
  1. Once the docker image is created, run it by executing the following command.
docker container run --name crest_container -p 3000:3000 crest 

Note: A machine learning model will be downloaded from when you use the Heading Analysis/ Crest Single API for the first time. It will be saved in your system's cache for future use and could take approximately 2 GB of your system's memory.