how do you define multiple code locations in workspace.yaml @Scout

To define multiple code locations in a

workspace.yaml

file, you can specify each code location as an entry under the

load_from

key. Each entry can either point to a Python file or a Python module that contains your code location definition. Here's an example of how you might define multiple code locations in your `workspace.yaml`:

yaml # workspace.yaml  load_from:   - python_file:       relative_path: path/to/first_code_location.py   - python_module:       module_name: second_code_location_module   - python_file:       relative_path: path/to/third_code_location.py       working_directory: path/to/working_directory   - python_module:       module_name: fourth_code_location_module       working_directory: path/to/another_working_directory

In this example, there are four code locations defined. The first and third are loaded from Python files, while the second and fourth are loaded from Python modules. You can also specify a

working_directory

if you need to set a specific working directory for the code location. Remember that each code location is loaded in its own process, and Dagster tools use an RPC protocol to communicate with these processes. This allows for process separation and ensures that errors in user code can't impact Dagster system code. For more complex setups, you can also customize the Python environment for each code location by adding an

executable_path

key to specify a custom Python executable, which can be useful if you have different Python environments for different code locations. Please refer to the Dagster documentation for more detailed information and examples on configuring

workspace.yaml

for multiple code locations.

I have workspaces.yaml as:

load_from:
  - python_file:
      relative_path: my_dagster_project/jobs.py
  - python_file:
      relative_path: my_dagster_project_v2/jobs.py

But only

my_dagster_project

is being picked up. why is that @Scout

If only one of your code locations specified in

workspace.yaml

is being picked up, there could be several reasons for this behavior: 1. File Path Issues: Ensure that the

relative_path

for each

python_file

is correct and that the files actually exist at those locations relative to the

workspace.yaml

file. 2. Syntax Errors or Typos: Check for any syntax errors or typos in the

workspace.yaml

file that might be causing the second code location to be ignored. 3. Errors in Code: If there are any errors in the Python file specified in the second code location (

my_dagster_project_v2/jobs.py

), it might prevent Dagster from successfully loading it. Check the logs for any error messages that might indicate what went wrong. 4. Duplicate Definitions: If there are duplicate definitions (e.g., jobs with the same name) across the two code locations, it might cause conflicts. Ensure that all definitions are uniquely named. 5. Workspace Loading Issues: There might be issues with how the workspace is being loaded by Dagster. You can try running Dagster with increased verbosity or logging to get more information about what's happening when the workspace is loaded. 6. File Permissions: Ensure that the file permissions for

my_dagster_project_v2/jobs.py

allow the user running Dagster to read the file. 7. Dagster Version: If you are using an older version of Dagster, there might be a bug or limitation that has since been addressed. Consider upgrading to the latest version of Dagster. To debug this issue, you can start by checking the logs when you run Dagster to see if there are any error messages related to loading the second code location. If the logs don't provide enough information, you can increase the verbosity of the logs to get more detailed output. If you continue to face issues, you can also validate the structure of your

workspace.yaml

file against the documentation to ensure it aligns with the expected format and that there are no missing or incorrect configurations. If none of these steps resolve the issue, it may be helpful to consult the Dagster community or support channels with specific details about your setup and the behavior you're observing.

what is the difference between

dagit

and

dagster dev

@Scout

dagit

and

dagster dev

are two different commands used in the context of Dagster, each serving a distinct purpose: 1.

dagit

: This is the command used to run the Dagit web interface, which is Dagster's graphical user interface (GUI). Dagit allows you to visualize and interact with your Dagster instance, including viewing pipelines (now called jobs), assets, schedules, sensors, and runs. It's a tool for development, introspection, and monitoring of your data workflows. When you run

dagit

, it expects that your Dagster instance is already running or that you have a

workspace.yaml

file that Dagit can use to load your repository or repositories. Usage example:

shell    dagit -f my_pipeline.py -p 3000

This command will start the Dagit server, loading the repository defined in

my_pipeline.py

and making the Dagit UI available at

<http://localhost:3000>

. 2.

dagster dev

: This is a newer command introduced to streamline local development workflows. It's designed to provide a simplified interface for running Dagster in a development environment. The

dagster dev

command starts up a development-focused instance of Dagster, which includes both the Dagit UI and the Dagster daemon. This command is particularly useful because it sets up everything you need for local development without requiring separate commands or additional setup. Usage example:

shell    dagster dev

This command will start the Dagit UI and the Dagster daemon in development mode, allowing you to develop and test your data workflows locally. In summary,

dagit

is specifically for running the Dagit UI, while

dagster dev

is a more comprehensive command that sets up a local development environment with both the Dagit UI and the Dagster daemon running. The

dagster dev

command simplifies the process of getting started with local development by reducing the need for separate commands and configuration.

it seems like my workspaces.yaml is being ignored, and only my_dagster_project is being picked up @Scout

If your

workspace.yaml

file seems to be ignored and only one of your code locations is being picked up, here are a few steps you can take to troubleshoot the issue: 1. Check the

workspace.yaml

File Name and Location: Ensure that the file is named

workspace.yaml

(not

workspaces.yaml

) and is located in the directory from which you are running the

dagit

or

dagster dev

command. If it's in a different directory, you need to specify the path to the

workspace.yaml

file using the

-w

or

--workspace

flag when starting

dagit

or

dagster dev

. 2. Validate YAML Syntax: Verify that the

workspace.yaml

file is correctly formatted and follows the YAML syntax. YAML is sensitive to indentation and formatting, so even small mistakes can lead to the file being read incorrectly. 3. Check for Errors in the Second Code Location: If there are errors in the Python file specified in the second code location (

my_dagster_project_v2/jobs.py

), Dagster might not be able to load it. Look for any error messages in the terminal or the Dagit UI that might indicate a problem with loading the code location. 4. Ensure Unique Names: If you have jobs or assets with the same name in different code locations, it might cause conflicts. Make sure that all your jobs and assets have unique names across code locations. 5. Check File Paths: Ensure that the paths specified in the

workspace.yaml

file are correct and that the files exist at those paths. Relative paths are relative to the location of the

workspace.yaml

file. 6. Review Dagster Logs: Increase the logging level when running

dagit

or

dagster dev

to get more detailed output, which might provide insights into why the second code location is not being picked up. 7. Check Dagster Version: Ensure that you are using a version of Dagster that supports the features and syntax you are using in your

workspace.yaml

file. If necessary, update to the latest version. 8. Consult the Documentation: Review the [workspace file documentation](https://docs.dagster.io/concepts/code-locations/workspace-files) to ensure that your

workspace.yaml

file is configured correctly. If after trying these steps you still encounter issues, you may want to reach out to the Dagster community or support channels with specific details about your setup and the behavior you're observing for further assistance.

how do i load code locations from multiple modules @Scout

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Speed up the answer, baby @Scout

To load code locations from multiple modules, define them in your

workspace.yaml

file using the

python_module

key like this:

yaml load_from:   - python_module:       module_name: your_first_module_name   - python_module:       module_name: your_second_module_name

Replace

your_first_module_name

and

your_second_module_name

with the actual names of your Python modules. Each module should contain Dagster definitions such as assets and jobs. Make sure the modules are importable in your Python environment.

workspace.yaml isn’t being picked up although it’s in the same folder that im executing dagster dev from. Unless i add the -w flag it doesnt work.

agster dev -w workspace.yaml

Why is that? @Scout

If your

workspace.yaml

file is not being picked up when you run

dagster dev

without the

-w

flag, even though it is in the same directory from which you are executing the command, it could be due to a few reasons: 1. Environment Variable: If the

DAGSTER_HOME

environment variable is set, Dagster will look for the

workspace.yaml

file in the

DAGSTER_HOME

directory rather than the current working directory. Make sure that

DAGSTER_HOME

is either not set or is set to the directory where your

workspace.yaml

file is located. 2. File Naming: Ensure that the file is named exactly

workspace.yaml

. If the file has a different name or extension, it won't be recognized by default. 3. Dagster Version: There might be a version-specific issue with Dagster that is causing it to not recognize the

workspace.yaml

file. Ensure that you are using a version of Dagster that supports the features and syntax you are using. 4. Unexpected Behavior: It's possible that there is a bug or unexpected behavior in the version of Dagster you are using. You can check the Dagster GitHub issues to see if others have reported similar problems or if there's an ongoing discussion about this issue. If none of these reasons apply and you're still experiencing the issue, it might be worth reaching out to the Dagster community or filing an issue on the Dagster GitHub repository with details of your setup and the behavior you're observing for further assistance.