Actions364
- Continuous Activity Actions
- Dataset Actions
- Get Last Metric Values
- Get Metadata
- Get Schema
- Get Single Metric History
- List Datasets
- List Partitions
- Compute Metrics
- Create Dataset
- Create Managed Dataset
- Delete Data
- Delete Dataset
- Execute Tables Import
- Get Column Lineage
- Get Data
- Get Data - Alternative Version
- Get Dataset Settings
- Get Full Info
- List Tables
- List Tables Schemas
- Prepare Tables Import
- Run Checks
- Set Metadata
- Set Schema
- Synchronize Hive Metastore
- Update Dataset Settings
- Update From Hive Metastore
- API Service Actions
- Bundles Automation-Side Actions
- Bundles Design-Side Actions
- Connection Actions
- Dashboard Actions
- Data Collection Actions
- Data Quality Actions
- Compute Rules on Specific Partition
- Create Data Quality Rules Configuration
- Delete Rule
- Get Data Quality Project Current Status
- Get Data Quality Project Timeline
- Get Data Quality Rules Configuration
- Get Dataset Current Status
- Get Dataset Current Status per Partition
- Get Last Outcome on Specific Partition
- Get Last Rule Results
- Get Rule History
- Update Rule Configuration
- DSS Administration Actions
- Job Actions
- Library Actions
- Dataset Statistic Actions
- Discussion Actions
- Flow Documentation Actions
- Insight Actions
- Internal Metric Actions
- LLM Mesh Actions
- Machine Learning - Lab Actions
- Delete Visual Analysis
- Deploy Trained Model to Flow
- Download Model Documentation of Trained Model
- Generate Model Documentation From Custom Template
- Start Training ML Task
- Update User Metadata for Trained Model
- Update Visual Analysis
- Adjust Forecasting Parameters and Algorithm
- Compute Partial Dependencies of Trained Model
- Compute Subpopulation Analysis of Trained Model
- Create ML Task
- Create Visual Analysis
- Create Visual Analysis and ML Task
- Generate Model Documentation From Default Template
- Generate Model Documentation From File Template
- Get ML Task Settings
- Get ML Task Status
- Get Model Snippet
- Get Partial Dependencies of Trained Model
- Get Scoring Jar of Trained Model
- Get Scoring PMML of Trained Model
- Get Subpopulation Analysis of Trained Model
- Get Trained Model Details
- Get Visual Analysis
- List ML Tasks of Project
- List ML Tasks of Visual Analyses
- List Visual Analyses
- Reguess ML Task
- Machine Learning - Saved Model Actions
- Compute Partial Dependencies of Version
- Get Version Scoring PMML
- Get Version Snippet
- Import MLflow Version From File or Path
- List Saved Models
- List Versions
- Set Version Active
- Compute Subpopulation Analysis of Version
- Create Saved Model
- Delete Version
- Download Model Documentation of Version
- Evaluate MLflow Model Version
- Generate Model Documentation From Custom Template
- Generate Model Documentation From Default Template
- Generate Model Documentation From File Template
- Get MLflow Model Version Metadata
- Get Partial Dependencies of Version
- Get Saved Model
- Get Subpopulation Analysis of Version
- Get Version Details
- Get Version Scoring Jar
- Set Version User Meta
- Update Saved Model
- Long Task Actions
- Machine Learning - Experiment Tracking Actions
- Macro Actions
- Plugin Actions
- Download Plugin
- Fetch From Git Remote
- Get File Detail From Plugin
- Get Git Remote Info
- Get Plugin Settings
- Install Plugin From Git
- Install Plugin From Store
- List Files in Plugin
- List Git Branches
- List Plugin Usages
- Move File or Folder in Plugin
- Add Folder to Plugin
- Create Development Plugin
- Create Plugin Code Env
- Delete File From Plugin
- Delete Git Remote Info
- Delete Plugin
- Download File From Plugin
- Move Plugin to Dev Environment
- Pull From Git Remote
- Push to Git Remote
- Rename File or Folder in Plugin
- Reset to Local Head State
- Reset to Remote Head State
- Set Git Remote Info
- Set Plugin Settings
- Update Plugin Code Env
- Update Plugin From Git
- Update Plugin From Store
- Update Plugin From Zip Archive
- Upload File to Plugin
- Upload Plugin
- Project Deployer Actions
- Get Deployment Settings
- Get Deployment Status
- Create Deployment
- Create Infra
- Create Project
- Delete Bundle
- Delete Deployment
- Delete Infra
- Delete Project
- Get Deployment
- Get Deployment Governance Status
- Get Infra
- Get Infra Settings
- Get Project
- Get Project Settings
- Save Deployment Settings
- Save Infra Settings
- Save Project Settings
- Update Deployment
- Upload Bundle
- SQL Query Actions
- Wiki Actions
- Managed Folder Actions
- Meaning Actions
- Model Comparison Actions
- Notebook Actions
- Project Actions
- Project Folder Actions
- Recipe Actions
- Scenario Actions
- Security Actions
- Streaming Endpoint Actions
- Webapp Actions
- Workspace Actions
Overview
This node integrates with the Dataiku DSS API, enabling users to perform a wide range of operations on various Dataiku DSS resources. Specifically for the Plugin resource and the Pull From Git Remote operation, it allows pulling (and rebasing) the content of a plugin from a previously-declared git remote repository. This is useful for synchronizing local plugin code with the latest changes from a remote Git repository, facilitating collaborative development and version control of plugins within Dataiku DSS.
Common scenarios include:
- Keeping a plugin up-to-date with the latest code changes pushed by team members.
- Automating plugin updates as part of CI/CD pipelines.
- Managing plugin versions and ensuring consistency between local and remote repositories.
Example use case:
- A developer wants to update a plugin in Dataiku DSS with the latest commits from its Git remote. Using this node operation, they can pull and rebase the plugin's content automatically without manual intervention.
Properties
| Name | Meaning |
|---|---|
| Plugin ID | The unique identifier of the plugin to operate on. Required for all plugin-related actions. |
Note: The provided input properties JSON only includes "Plugin ID" relevant to the Plugin resource operations.
Output
The node outputs data in JSON format or binary data depending on the operation:
- For the Pull From Git Remote operation, the output will be JSON containing the response from the Dataiku DSS API about the pull operation status or result.
- If the operation involves downloading files (not applicable here), the node would output binary data representing the downloaded file.
- In case of textual responses like logs, the output JSON contains a
logsfield with the log content.
The output structure generally reflects the raw API response from Dataiku DSS, which may include details such as success status, messages, or error information.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Needs valid credentials including the DSS server URL and a user API key for authentication.
- The node uses HTTP requests to communicate with the Dataiku DSS REST API.
- No additional external services are required beyond the Dataiku DSS API access.
Troubleshooting
- Missing Credentials Error: The node throws an error if the Dataiku DSS API credentials are not set or invalid. Ensure that the API key and server URL are correctly configured.
- Required Parameter Missing: The node validates required parameters such as Plugin ID for plugin operations. Missing these will cause errors. Provide all mandatory fields.
- API Request Failures: Network issues, incorrect URLs, or insufficient permissions can cause API call failures. Check network connectivity, API endpoint correctness, and user permissions in Dataiku DSS.
- Unexpected Response Format: If the API returns unexpected data, parsing errors might occur. Verify the API version compatibility and response formats.
- Operation Not Supported: Using an unsupported operation or resource combination will throw an error indicating unknown resource or operation.
Links and References
This summary focuses on the Plugin resource and the Pull From Git Remote operation as requested, based on static analysis of the provided source code and property definitions.