If you get an empty report, there are several steps to understand what went wrong and try and fix it.1. Validate elementary dbt package is deployed and working:
  • Check that dbt package version is the latest
  • Refer to the dbt package installation guide, and validate that your version in packages.yml is the one mentioned there. If not, upgrade and run dbt deps. Make sure to execute dbt run --select elementary for the package tables to be created.
  • Check if the table elementary_test_results exists and has data
  • If the table does not exist - refer to the dbt package installation guide. Make sure to execute dbt run --select elementary for the package tables to be created.
  • If the table exists but has no data - Did you execute dbt test since deploying the package and creating the models?
  • If yes, make sure the table was created as an incremental table (not a regular table or view).
  • If not, there is a materialization configuration in your dbt_project.yml file that overrides the package config. Remove it, and run dbt run --select elementary --full-refresh to recreate the tables. After that run dbt test again and check if there is data.
  • Still no data in the table? Reach out to the elementary team at #support on Slack.
2. Validate that the CLI was properly installed
  • Check the CLI version is the latest
  • Use the command pip show elementary-data to detect your version, and validate that it is the latest one. If not, run pip install elementary-data --upgrade.
  • Try to force update the CLI internal packages
  • Run the CLI with the flag for force updating the packages: edr report -u true
3. Validate that the CLI has a working connection profile
  • Check that the connection profile exists in the right path and format
  • Check that the connection profile points to the elementary package schema
4. Still not working? Collect the following logs and reach our to the elementary team at #support on Slack
  • edr.log - Created on the execution folder of the CLI.
  • dbt.log - Created under the package location at /site-packages/monitor/dbt_project/logs/dbt.log You can find the full path of the package location using pip show elementary-data.
Elementary dbt package includes macros that run insert commands to some of the models. This error means that these models were materialized as views, and not as tables. The reason for the error is probably a configuration on your dbt_project.yml file, under the key materialization.
## In your dbt_project.yml
## This is causing the problem:

models:
  materialization: <some_config>
We recommend moving this config to be strictly for models in your package, or else it will override the materialization of packages:
## Change to this:

models:
  your_project_name:
    models:
      materialization: <some_config>
In Python on macOS, when you globally install a package that has executables, such as Elementary’s edr, it places the executable in a location that is not under the default PATH which is the environment variable that is used for executable lookups. Here’s an example of the warning you might receive upon running python3 -m pip install elementary-data.
$ python3 -m pip install elementary-data
...
WARNING: The script edr is installed in '/Users/user/Library/Python/3.8/bin' which is not on PATH.
  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
...
$ edr
zsh: command not found: edr
As you can see, edr is not found by default upon installation. There are multiple ways to solve this.
  1. Use the absolute path.
$ ~/Library/Python/3.8/bin/edr
    ________                          __
   / ____/ /__  ____ ___  ___  ____  / /_____ ________  __
  / __/ / / _ \/ __ `__ \/ _ \/ __ \/ __/ __ `/ ___/ / / /
 / /___/ /  __/ / / / / /  __/ / / / /_/ /_/ / /  / /_/ /
/_____/_/\___/_/ /_/ /_/\___/_/ /_/\__/\__,_/_/   \__, /
                                                 /____/

Usage: edr [OPTIONS] COMMAND [ARGS]...

  Open source data reliability solution (https://docs.elementary-data.com/)
...
  1. Edit your shell’s configuration file(~/.zshrc) and append Python’s library path.
export PATH=$PATH:$HOME/Library/Python/3.8/bin
  1. Use Python’s virtual environment.
If you got a message Successfully installed elementary-data but get a command not found error, it is probably because of a missing path in your environment variables.Look for a warning in your terminal saying: Warning: the script edr.exe is installed in '<path>' which is not on PATHThis is the path that needs to be added to your windows env vars, run:
set PATH='%PATH%;<path from error message>'
After that restart your CMD and try edr again.
This means the installation was not completed successfully. This is usually a Python dependencies issue.Please try installing again on a clean virtual env:
pip install virtualenv
python3 -m venv virtualenv_elementary
source virtualenv_elementary/bin/activate
python3 -m ensurepip --upgrade
python3 -m pip install --upgrade pip
python3 -m pip install elementary-data
python3 -m pip install elementary-data[<adapter>]
Elementary tests have a var named training_period. If you change it after executing elementary tests, you will need to run a full refresh to the metrics collected. This will make the next tests collect data for the new training_period timeframe. The steps are:
  1. Change var training_period in your dbt_project.yml.
  2. Full refresh of the model ‘data_monitoring_metrics’ by running dbt run --select data_monitoring_metrics --full-refresh.
  3. Running the elementary tests again.
If you want the Elementary UI to show data for a longer period of time, use the days-back option of the CLI: edr report --days-back 45
If you want to prevent elementary tests from running the simplest way is to exclude the tag that marks all of them in your dbt command:
dbt test --exclude tag:elementary-tests
If you add the following to your dbt_project.yml, elementary models will not run and elementary tests will be executed but will do nothing and always pass.
models:
  elementary:
    enabled: false
If you’re experiencing issues of any kind, please contact us on the #support channel.

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Other issues?

Ask us on Slack, we are very responsive!