knime-extension-template

cookiecutter knime extension template

Installation

Install cookiecutter if you don't have it already:

pip install cookiecutter

Then run the following command to create a new extension:

cookiecutter https://github.com/spatial-data-lab/knime-extension-template

Package Organization and Best Practices

General suggestions

• Create one repository per Python node extension
• If the extension contains several nodes create a file for each node group e.g., IO, analysis, views

Proposed File Structure

The following shows the proposed file structure for a KNIME Extension with several nodes grouped into different categories and written in Python:

my_extension
+-- icons
    +-- my_node.svg
+-- src
    +--  my_extension.py
    +-- nodes
        +-- category1.py
        +-- category2.py
    +-- util
        +-- general_helper.py
+-- test
    +-- test_my_extension.py
+-- knime.yml
+-- LICENSE.TXT
+-- my_conda_env.yml

Working with file paths

Importing Nodes

All nodes in the nodes folder need to be imported into the my_extension.py file like the following:

import nodes.category1 etc.

Referencing Icons

When referencing icons the root path is my_extension (the folder of the extension_module parameter in the knime.yml file). So to reference node1_icon.png the path is icons/node1_icon.png.

Local development

For local development create a config.yml file in the parent folder of the my_extension folder. In the file use the following lines:

my.group: # {group\_id}.{name} from the knime.yml_
  src: C:\DEV\Python\my\_git\_repo # Path to folder containing knime.yml file_
  conda_env_path: C:\Users\XYZ\.conda\envs\my\_python\_env # Path to the local Python env to use_
  debug_mode: true # Optional line, if set to true, it will always use the latest changes of execute/configure, when that method is used within the KNIME Analytics Platform_

The config.yml file can contain list several repositories below each other.

To add the Python extension in my_extension to your KNIME Analytics Platform add the following line to the knime.ini file:

-Dknime.python.extension.config=C:\DEV\Python\config.yml

Local Debugging

To debug your Python code in Visual Studio Code (VSCode) even though it is executed from KNIME, perform the following steps:

1. In the Python environment that you use for running the tests, install debugpy using pip install debugpy or Anaconda or similar
2. Open the Python file you want to edit, e.g., my_node_.py_ (by pressing Ctrl+P and start typing the file name)
3. Inject the following lines of code in your Python file from where you want to start debugging e.g. in the execute method of your node:

   import debugpy
   import logging
   LOGGER = logging.getLogger(__name__)
   debugpy.listen(5678)
   LOGGER.error("Waiting for debugger attach")
   debugpy.wait_for_client()
   debugpy.breakpoint()

4. Start KNIME Analytics Platform and execute the Python node you want to debug
5. Once you see "Waiting for debugger attach" in the KNIME Analytics Platform console, go to VSCode and open the Run & Debug view (Ctrl+Shift+D), click Run and Debug , choose Remote Attach , localhost (should be default), and Port 5678 (default). (If you do not have a Python file open while clicking here, it will not show the Python debugging options!)

Contribute

We are very happy about every contributor.