@Scout I Installed dagster_graphql, dagster latest version even im geeting this error

from dagster_graphql import DagsterGraphQLClient

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Cell In[2], line 1
----> 1 from dagster_graphql import DagsterGraphQLClient

File ~/anaconda3/envs/everstage/lib/python3.10/site-packages/dagster_graphql/__init__.py:1
----> 1 from dagster._core.libraries import DagsterLibraryRegistry
      3 from .client import (
      4     DagsterGraphQLClient as DagsterGraphQLClient,
      5     DagsterGraphQLClientError as DagsterGraphQLClientError,
   (...)
     10     ShutdownRepositoryLocationStatus as ShutdownRepositoryLocationStatus,
     11 )
     12 from .version import __version__ as __version__

ModuleNotFoundError: No module named 'dagster._core'

The error message you're encountering indicates that Python cannot find the

dagster._core

module, which is expected to be part of the

dagster

package. This could be due to several reasons, such as an incomplete or corrupted installation of the

dagster

package, or a version mismatch where the

dagster_graphql

package expects a different structure of the

dagster

package than what is installed. Here are some steps you can take to troubleshoot this issue: 1. Ensure that Dagster is installed: Verify that you have

dagster

installed in your environment. You can do this by running

pip list

and checking for

dagster

in the list of installed packages. 2. Check for multiple installations: Sometimes, having multiple versions of the same package installed, or having the package installed both globally and within a virtual environment, can cause conflicts. Ensure that you're working within a clean Python environment and that

dagster

is installed only once. 3. Reinstall Dagster: If the installation is corrupted, you may need to reinstall

dagster

. You can do this by running

pip uninstall dagster

followed by

pip install dagster

. 4. Check for version compatibility: Ensure that the versions of

dagster

and

dagster_graphql

are compatible with each other. You can check the release notes or the documentation for

dagster_graphql

to find out which versions are expected to work together. 5. Use a virtual environment: If you're not already doing so, consider using a virtual environment to manage your Python packages. This can help avoid conflicts with system-wide packages and makes it easier to manage dependencies. 6. Check the import path: The error message suggests that the import path

dagster._core

might not be correct. It's possible that the structure of the

dagster

package has changed in recent versions, or that there's an issue with the

dagster_graphql

package's expectations. You can check the source code of the

dagster

package to see if the module structure matches what

dagster_graphql

is trying to import. If you've tried these steps and are still encountering issues, you may want to look for similar issues reported by other users in the Dagster GitHub issues or ask for help in the Dagster community channels. It's also possible that there's a bug or a regression in the packages themselves, in which case reporting the issue to the maintainers could be helpful.

@Scout is there a way to trigger a pipeline dagster from rest end point

Yes, you can trigger a Dagster pipeline (job) from a REST endpoint by using Dagster's GraphQL API. Dagster provides a GraphQL endpoint that can be used to interact with your Dagster instance, including triggering pipeline runs. To trigger a pipeline from a REST endpoint, you would typically set up a web server that exposes a REST API. When this API is called, it would then send a GraphQL request to the Dagster instance to start a pipeline run. Here's a high-level overview of the steps you would take: 1. Set up a web server: Use a web server framework like Flask or FastAPI to create a REST endpoint. This server would handle incoming HTTP requests to trigger pipeline runs. 2. Send a GraphQL request: When the REST endpoint is called, have it send a GraphQL mutation to Dagster's GraphQL endpoint to start the pipeline run. The mutation would look something like this:

graphql
mutation {
  launchPipelineExecution(
    executionParams: {
      selector: {
        pipelineName: "your_pipeline_name"
      },
      runConfigData: {
        # Your pipeline run configuration goes here
      }
    }
  ) {
    run {
      runId
    }
  }
}

3. Handle the response: Process the response from Dagster's GraphQL API and return an appropriate response from your REST endpoint. Here's an example of how you might set up a simple Flask app to trigger a Dagster pipeline:

python
from flask import Flask, request, jsonify
import requests

app = Flask(__name__)

DAGSTER_GRAPHQL_ENDPOINT = '<http://localhost:3000/graphql>'

@app.route('/trigger_pipeline', methods=['POST'])
def trigger_pipeline():
    pipeline_name = request.json.get('pipeline_name')
    run_config = request.json.get('run_config')

    query = '''
    mutation($pipelineName: String!, $runConfig: RunConfigData) {
      launchPipelineExecution(
        executionParams: {
          selector: {
            pipelineName: $pipelineName
          },
          runConfigData: $runConfig
        }
      ) {
        run {
          runId
        }
      }
    }
    '''

    variables = {
        'pipelineName': pipeline_name,
        'runConfig': run_config
    }

    response = <http://requests.post|requests.post>(
        DAGSTER_GRAPHQL_ENDPOINT,
        json={'query': query, 'variables': variables}
    )

    return jsonify(response.json())

if __name__ == '__main__':
    app.run(debug=True)

In this example, you would send a POST request to

/trigger_pipeline

with a JSON body containing the

pipeline_name

and

run_config

. The Flask app would then send the GraphQL mutation to Dagster's GraphQL endpoint to start the pipeline run. Please note that you should secure your REST endpoint and Dagster's GraphQL endpoint appropriately to prevent unauthorized access. This might involve setting up authentication and usin