Running your code

Running your code#

Set up your development environment#

If you have not already done so, follow the Quick start guide to sign into the Union UI, set up your local Python environment, and install the union command line tool.

CLI commands for running your code#

The union CLI provides a set of commands that allow you to deploy and run your code at different stages of the development cycle:

  1. union run: For deploying and running a single script immediately in your local Python environment.

  2. union run --remote: For deploying and running a single script immediately in the cloud on Union.

  3. union register: For deploying multiple scripts to Union and running them from the Web interface.

  4. union package and uctl register: For deploying workflows to production and for scripting within a CI/CD pipeline.

Note

In some cases, you may want to test your code in a local cluster before deploying it to Union. This step corresponds to using the commands 2, 3, or 4, but targeting your local cluster instead of Union. For more details, see Running in a local cluster.

Running a script in local Python with union run#

During the development cycle you will want to run a specific workflow or task in your local Python environment to test it. To quickly try out the code locally use union run:

$ union run workflows/example.py wf --name 'Albert'

Here you are invoking union run and passing the name of the Python file and the name of the workflow within that file that you want to run. In addition, you are passing the named parameter name and its value.

This command is useful for quickly testing a workflow locally to check for basic errors. For more details see union run details.

Running a script on Union with union run --remote#

To quickly run a workflow on Union, use union run --remote:

$ union run --remote --project basic-example --domain development workflows/example.py wf --name 'Albert'

Here we are invoking union run --remote and passing:

  • The project, basic-example

  • The domain, development

  • The Python file, workflows/example.py

  • The workflow within that file that you want to run, wf

  • The named parameter name, and its value

This command will:

  • Build the container image defined in your ImageSpec.

  • Push the image to the container registry specified in that ImageSpec.

    • (Don’t forget make the image accessible to Union. For example, if you are using GitHub Container Registry, you will need to make the image public.)

  • Package up your code and deploy it to the specified project and domain in Union.

  • Run the workflow on Union.

This command is useful for quickly deploying and running a specific workflow on Union. For more details see union run details.

Deploying your code to Union with union register#

$ union register workflows --project basic-example --domain development

Here we are registering all the code in the workflows directory to the project basic-example in the domain development.

This command will:

  • Build the container image defined in your ImageSpec.

  • Push the image to the container registry specified in that ImageSpec.

    • (Don’t forget make the image accessible to Union. For example, if you are using GitHub Container Registry, you will need to make the image public.)

  • Package up your code and deploy it to the specified project and domain in Union.

    • The package will contain the code in the Python package located in the workflows directory. Note that the presence of the __init__.py file in this directory is necessary in order to make it a Python package.

    all the workflows in the workflows directory. The command will not run the workflow. You can run it from the Web interface.

This command is useful for deploying your full set of workflows to Union for testing.

Deploying your code to production with union package and uctl register#

The combination of union package and uctl register is the standard way of deploying your code to production. This method is often used in scripts to build and deploy workflows in a CI/CD pipeline.

First, package your workflows:

$ union --pkgs workflows package

This will create a tar file called flyte-package.tgz of the Python package located in the workflows directory. Note that the presence of the __init__.py file in this directory is necessary in order to make it a Python package.

Once the code is packaged you register it using the uctl CLI:

$ uctl register files --project basic-example --domain development \
       --archive flyte-package.tgz --version 1.0

See UCTL CLI for more details on how to install and use the uctl CLI.

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