Git setup
Overview
Whale supports a free hosted backend + lightweight GUI through Github and Github actions (though any git remote server + CI/CD system will work - you'll simply have to write your own config). This is possible because the metadata and user-generated content accessed by whale are stored as markdown in the ~/.whale
subdirectory.
We have provided a series of simple commands and instructions to get started easily, but these can be executed manually quite easily as well.
Getting started
Set up ~/.whale/ as a git repository
Run the following command to set up and push your ~/.whale
directory to the provided git remote (replace <YOUR_GIT_REMOTE>
with your git address). This will add a .gitignore
file, add all files, and push to your git remote server.
This will also push your connections.yaml
file to your repo. If you'd like to avoid doing this, mv
your ~/.whale/config/connections.yaml
file elsewhere first and see Advanced usage.
wh git-setup <YOUR_GIT_REMOTE>
Set up a CI/CD pipeline to scrape metadata
Below, we illustrate how to set up github actions to scrape metadata for you, but the steps can be easily adapted to any CI/CD platform. We chose github actions because github supplies 2000 free minutes/month, even for private repos and organizations, which is generally more than enough to cover these simple scraping jobs.
First, create a local directory for your github actions workflows:
mkdir -p ~/.whale/.github/workflows
Then, within this directory, create a new file (e.g. metadata.yml
), paste in the following file, then git add
, commit
, & push
to master.
name: Whale Runner
on:
schedule:
- cron: "0 */12 * * *"
jobs:
run-etl:
runs-on: ubuntu-latest
steps:
# Setup python + clone repos
- uses: actions/setup-python@v2
with:
python-version: '3.8'
- uses: actions/checkout@v2
- name: Copy to ~/.whale
run: |
cp -r . ~/.whale/
- uses: actions/checkout@v2
with:
repository: dataframehq/whale
path: whale
# Scrape from warehouse
- name: etl
working-directory: ./whale
run: |
make python
source ~/.whale/libexec/env/bin/activate
python3 ~/.whale/libexec/build_script.py
# Push to git
- name: push-to-git
working-directory: /home/runner/.whale
run: |
git config user.name 'GHA Runner'
git config user.email '<your_username>@users.noreply.github.com'
git add .
git commit -m "Automated push." || echo "No changes to commit"
git push
Update your local whale instance
Now that you have a remote git server pulling metadata, you'll want to avoid scraping metadata independently from your warehouse, and instead periodically rebase your table stubs over your git remote. If you desire, you can set a git pull --autostash --rebase
to occur programmatically. To do this, run the following command:
wh git-enable
This will add a is_git_etl_enabled: "true"
flag to the file located at ~/.whale/config/config.yaml
. This file can be accessed by running wh config
and manually edited at any point to turn the flag off.
Team setup
Now that you've set up a git as your SSOT, have others Install whale, then run the following series of commands to clone your central repo and set up a cron job to periodically rebase onto your remote:
git clone <YOUR_GIT_REMOTE> ~/.whale
wh schedule
wh git-enable
Make sure to not have an existing ~/.whale
directory or the clone will fail.
Advanced usage
Manual setup
Though we have enabled convenient install hooks to make this git setup process easy, if you're familiar with git and a CI/CD platform, it is quite simple to implement all of this manually. In short, wh git-setup
is doing the following:
Creating a
.gitignore
file.git add . && git commit -m "Whale on our way" && git push
If you would rather not install the command-line tool, you can therefore simply create a repo, manually create a credentials.yaml
file in config/credentials.yaml
, and create a CI/CD pipeline that does the following (or use our github action above):
Checkout your repo, and copy it to
~/.whale
on your CI/CD runner.Install python.
pip install whalebuilder
Run
python -c 'import whalebuilder as wh; wh.run()'
.Push the results back to git.
If you want improved logging, see here for an example (in short, simply import logging
and adjust the logging level).
Storing credentials
If storing credentials as plaintext is a concern, a workaround is to simply save the full connections.yaml
file as a Github secret (named CONNECTIONS
in the example below), then echo this into the ~/.whale/config/connections.yaml
file. For example, with Github actions:
run: |
echo '${{ secrets.CONNECTIONS }}' > ~/.whale/config/connections.yaml
Then remove the file before the push step.
run: |
rm ~/.whale/config/connections.yaml
The full file would then be:
name: Whale Runner
on:
schedule:
- cron: "0 */12 * * *"
jobs:
run-etl:
runs-on: ubuntu-latest
steps:
# Setup python + clone repos
- uses: actions/setup-python@v2
with:
python-version: '3.8'
- uses: actions/checkout@v2
- name: Copy to ~/.whale
run: |
cp -r . ~/.whale/
- uses: actions/checkout@v2
with:
repository: dataframehq/whale
path: whale
# Scrape from warehouse
- name: etl
working-directory: ./whale
run: |
make python
source ~/.whale/libexec/env/bin/activate
echo '${{ secrets.CONNECTIONS }}' > ~/.whale/config/connections.yaml
python3 ~/.whale/libexec/build_script.py
rm ~/.whale/config/connections.yaml
# Push to git
- name: push-to-git
working-directory: /home/runner/.whale
run: |
git config user.name 'GHA Runner'
git config user.email '<your_username>@users.noreply.github.com'
git add metadata manifests metrics
git commit -m "Automated push." || echo "No changes to commit"
git push
For Bigquery, specifically, the credentials file alone could alternatively be echoed at runtime into the correct path, as follows:
run: |
echo '${{ secrets.BIGQUERY_JSON }}' > ~/.whale/credentials.json
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