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Package for ingesting Tableau metadata into Google Cloud Data Catalog

Project description


Package for ingesting Tableau metadata into Google Cloud Data Catalog, currently supporting below asset types:

  • Workbook
  • Sheet
  • Dashboard

Python package PyPi License Issues

Disclaimer: This is not an officially supported Google product.

Table of Contents

1. Installation

Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.

With virtualenv, it's possible to install this library without needing system install permissions, and without clashing with the installed system dependencies. Make sure you use Python 3.6+.

1.1. Mac/Linux

pip3 install virtualenv
virtualenv --python python3.6 <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-datacatalog-tableau-connector

1.2. Windows

pip3 install virtualenv
virtualenv --python python3.6 <your-env>
<your-env>\Scripts\pip.exe install google-datacatalog-tableau-connector

1.3. Install from source

1.3.1. Get the code

git clone
cd datacatalog-connectors-bi/google-datacatalog-tableau-connector

1.3.2. Create and activate a virtualenv

pip3 install virtualenv
virtualenv --python python3.6 <your-env> 
source <your-env>/bin/activate

1.3.3. Install the library

pip install .

2. Environment setup

2.1. Auth credentials

2.1.1. Create a service account and grant it below roles

  • Data Catalog Admin

2.1.2. Download a JSON key and save it as

  • <YOUR-CREDENTIALS_FILES_FOLDER>/tableau2dc-datacatalog-credentials.json

Please notice this folder and file will be required in next steps.

2.2. Set environment variables

Replace below values according to your environment:

export GOOGLE_APPLICATION_CREDENTIALS=data_catalog_credentials_file

export TABLEAU2DC_TABLEAU_SERVER=tableau_server
export TABLEAU2DC_TABLEAU_API_VERSION=tableau_api_version
export TABLEAU2DC_TABLEAU_USERNAME=tableau_username
export TABLEAU2DC_TABLEAU_PASSWORD=tableau_password
export TABLEAU2DC_TABLEAU_SITE=tableau_site (optional)
export TABLEAU2DC_DATACATALOG_PROJECT_ID=google_cloud_project_id

Replace above values according to your environment. The Data Catalog credentials file was saved in step 2.1.2.

3. Running the connector

3.1. Python entry point

  • Virtualenv
google-datacatalog-tableau-connector \
  --tableau-server $TABLEAU2DC_TABLEAU_SERVER \
  --tableau-api-version $TABLEAU2DC_TABLEAU_API_VERSION \
  --tableau-username $TABLEAU2DC_TABLEAU_USERNAME \
  --tableau-password $TABLEAU2DC_TABLEAU_PASSWORD \
  [--tableau-site $TABLEAU2DC_TABLEAU_SITE \]
  --datacatalog-project-id $TABLEAU2DC_DATACATALOG_PROJECT_ID

3.2. Docker entry point

docker build --rm --tag tableau2datacatalog .
docker run --rm --tty -v YOUR-CREDENTIALS_FILES_FOLDER:/data \
  tableau2datacatalog \
  --tableau-server $TABLEAU2DC_TABLEAU_SERVER \ 
  --tableau-api-version $TABLEAU2DC_TABLEAU_API_VERSION \
  --tableau-username $TABLEAU2DC_TABLEAU_USERNAME \
  --tableau-password $TABLEAU2DC_TABLEAU_PASSWORD \
  [--tableau-site] $TABLEAU2DC_TABLEAU_SITE \]
  --datacatalog-project-id $TABLEAU2DC_DATACATALOG_PROJECT_ID

4. Set up a Tableau demo server

To quickly set up a Tableau demo server, please visit

Click on SIGN UP FOR THE TABLEAU DEVELOPER PROGRAM. Once you have signed up you will receive an e-mail with subject Tableau Online Developer - Activate your Site.

In the e-mail contents click on: Activate My Developer Site. Once you've done that you will receive another e-mail with subject You've Successfully Created Your Site.

Then you will be able to use your Tableau Online dev server.

5. Developer environment

5.1. Install and run Yapf formatter

pip install --upgrade yapf

# Auto update files
yapf --in-place --recursive src tests

# Show diff
yapf --diff --recursive src tests

# Set up pre-commit hook
# From the root of your git project.
curl -o
chmod a+x
mv .git/hooks/pre-commit

6.2. Install and run Flake8 linter

pip install --upgrade flake8
flake8 src tests

6.3. Run Tests

python test

6.4. Additional resources

Please refer to the Developer Resources documentation.

7. Troubleshooting

In the case a connector execution hits Data Catalog quota limit, an error will be raised and logged with the following detailment, depending on the performed operation READ/WRITE/SEARCH:

status = StatusCode.RESOURCE_EXHAUSTED
details = "Quota exceeded for quota metric 'Read requests' and limit 'Read requests per minute' of service '' for consumer 'project_number:1111111111111'."
debug_error_string = 
"{"created":"@1587396969.506556000", "description":"Error received from peer ipv4:","file":"src/core/lib/surface/","file_line":1056,"grpc_message":"Quota exceeded for quota metric 'Read requests' and limit 'Read requests per minute' of service '' for consumer 'project_number:1111111111111'.","grpc_status":8}"

For more information on Data Catalog quota, please refer to: Data Catalog quota docs

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