Last updated: April 08, 2024
DQOps Data Quality Operations Center installation options
This guide lists all options of installing DQOps Data Quality Operations Center, using pip, docker, or compiling the code directly.
Install DQOps to play and learn
-
If you have Python >=3.8 installed, installing the
dqops
pip package is the easiest way to start. Running DQOps as a pip package is meant for the non-production usage.Before running this command, please read the rest of the installing from pip manual.
Install DQOps for production use
-
Run DQOps as a Docker container
You can also start DQOps as a Docker container that is published on Docker Hub.
docker pull dqops/dqo docker run -v [path to local DQOps user home folder]:/dqo/userhome \ -it -p 8888:8888 dqops/dqo [--dqo.cloud.api-key=here-your-DQOps-Cloud-API-key]
All required parameters for starting DQOps in Docker are described in the running DQOps in Docker manual.
-
Download a DQOps release package
DQOps releases are published in the dqops\dqo (https://github.com/dqops/dqo/releases) releases archive on GitHub.
If you need to configure DQOps instance for your needs, running DQOps even on bare metal, follow the installing DQOps from release package manual.
You will need Python >=3.8 and Java >= 17 installed to start DQOps.
-
If you wish to contribute to DQOps, check out the GitHub repository and compile the code.
Follow the install from GitHub manual to compile and start DQOps. If you have Java JDK 17 or newer on the PATH, you can just start the
dqo.cmd
or./dqo
script after check out. DQOps will compile itself before the first start.
What's more
- Follow the getting started guide to understand how to run DQOps for the first time.
- Read the DQOps concepts guide to learn how to configure data quality checks in DQOps.