A11yWatch Lite is a previous and open-source version of A11yWatch (a paid, hosted Web accessibility and Vitals Tool). It was the first version of our software, and has been downloaded a lot!

While we are no longer adding features to this Lite version, we will be continuing to maintain it long-term and fix any bugs that come up.

A11yWatch is much more detailed, feature-rich, efficient, and faster, than A11yWatch Lite. Sign up for A11yWatch today and level up your accessibility automation. We offer high performance API integrations for paid accounts that will save your wallet in folds and better mother nature. Web accessibility automation in the current tools outside of A11yWatch can be very harmful due to the cost for the latency, improper algorithms and protocols that waste tons of energy/cpu cycles, and much more due to the state of the challenges of the job without the expertise and dedication required. A11yWatch leads the way in speed, efficiency, accuracy, and robustness when it comes to testing accessibility with more coverage than any other.

• Rust is required if building locally.
• Nodejs is required if building locally.
• Docker is required if you are not building locally.

The CLI can be used to test and build your own instance anywhere.
We have clients in multiple languages and protocols to integrate with your app easier.
See the documentation for more information on getting started with development and etc.

To get started with the fastest and most precise web accessibility platform pick between the Cloud, CLI, Docker, or Sidecar.

A11yWatch Cloud is the fastest way to get started with A11yWatch. It provides managed infrastructure as well as an instant and free access for development projects and concepts.

For a step-by-step guide on A11yWatch Cloud, see the docs.

A11yWatch CLI is an alternative way to get started with A11yWatch. It brings the tools to manage infrastructure, powerful commands for interactivity, and has the ability to automate workflows using tools like Github Actions and more.

Example of a multi page crawl with valid instance up using a11ywatch_cli v0.8.23:

For a step by step view the docs.

You can also get started using the standlone docker image locally or self host it.

With a valid docker installation up in a new folder run the following command (replace latest with darwin on macOS or use the IMAGE env var):

# create the bridge network for front-end and backend
docker network create --driver bridge a11ywatch-net
# start the backend
docker run -p 3280:3280 -v ${PWD}:/a11ywatch/conf \
  --network a11ywatch-net \
  --name a11ywatch-backend \
  -e SUPER_MODE=true \
  a11ywatch/a11ywatch:${IMAGE:-latest}
# start the frontend
docker run -p 3000:3000 -v ${PWD}:/a11ywatch/conf \
  --network a11ywatch-net \
  --name a11ywatch-frontend \
  -e SUPER_MODE=true \
  a11ywatch/web

Afterwards open http://localhost:3000 in your browser to continue.

Example of the dashboard crawling multi websites with live updates:

For step by step instructions, view the docs.

If you want to integrate your system with A11yWatch the simplest way is to use the javascript sidecar. The sidecar provides utility methods and launches the system locally for integration with nodejs.

View the contributing docs to get started.

Benchmarks below are done on a Apple M1 Max 64gb memory.

Case: https://a11ywatch.com multi site scan. 10x simultaneous runs each ran via localhost to avoid latency.

Benchmarks using the CLI and hyperfine with network latency.

Single page scan:

hyperfine 'a11ywatch scan -u https://a11ywatch.com' 

Benchmark 1: a11ywatch scan -u https://a11ywatch.com
  Time (mean ± σ):     109.44 ms ±  10 ms    [User: 1.9 ms, System: 2.8 ms]
  Range (min … max):   98.35 ms … 154.3 ms    11 runs

Multi page scan (30 pages):

hyperfine 'a11ywatch crawl -u https://a11ywatch.com' 

Benchmark 1: a11ywatch crawl -u https://a11ywatch.com
  Time (mean ± σ):      0.6715 s ±  0.026 s    [User: 0.003 s, System: 0.003 s]
  Range (min … max):    0.6355 s …  0.714 s    10 runs

A11yWatch helps builds confidence due to handling dynamic parameters and amount of coverage from reports. The system can handle up to 1 million pages under 1 min with 8gb of memory on linux without a sweat.

Some examples on how to integrate with the system. Learn how to use the react-a11ywatch-js hooks and components lib to build custom products or tools.

If you need support, start with the troubleshooting guide, if you still need help please contact us contact.

Check the license file in the root of the project.