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Python portable plugin example

The following is the introduction and packaging process of the pysam plugin example. The pysam plugin can be downloaded and tested through this link python sdk example.

Deployment requirements

To use the Python portable plugin, Python3 environment is required.

  • Required if you install NeuronEX through the installation package

    1. Manually install the python 3.x environment.
    2. Install the ekuiper and pynng libraries through pip
    shell
    pip install ekuiper pynng
  • If you install NeuronEX through docker, please use the NeuronEX image of type neuronex:3.x.x-python, which is already included Python3 environment, as well as some related function libraries.

Overall introduction of pysam plugin

The directory of the pysam plugin contains the following files:

  • pysam.json: required, plugin metadata file, used to describe the metadata information of the plugin.
  • pysam.py: required, plugin main program executable file.
  • pyjson.py: optional, a data source Source plugin in the plugin.
  • sources folder, pyjson.json, pyjson.yaml: Optional, the configuration information of the data source Source plugin pyjson.py in the plugin.
  • print.py: optional, an action Sink plugin in the plugin.
  • sinks folder, print.json: Optional, the configuration information of the action Sink plugin print.py in the plugin.
  • revert.py: optional, a function plugin in the plugin.
  • functions folder, revert.json: Optional, the configuration information of the function plugin revert.py in the plugin.
pysam

tip

A plugin can contain one or more data source Source, action Sink and function plugins. In the pysam example, it includes a data source Source plugin pyjson, an action Sink plugin print and a function plugin revert.

Introduction to plugin metadata files

The pysam.json file is the metadata file of the plugin, which is used to describe the metadata information of the plugin. The following is an introduction to the key information in the metadata file:

  • language: This field specifies the language implemented by the plugin. The plugin must be implemented in a single language. For python type plugins, fill in python.
  • executable: The field needs to specify the name of the plugin main program executable file. In this case the pysam.py file.

Tips

This pysam.py file name does not need to have the same name as the plugin's metadata file pysam.json. For example, you can fill in main.py in the executable field, or rename pysam.py to main.py.

  • sources: This field is in array format and contains all data source Source plugin information in the plugin.
  • sinks: This field is in array format and contains all action sink plugin information in the plugin.
  • functions: This field is in array format and contains all Function plugin information in the plugin.
json
{
   "version": "v1.0.0",
   "language": "python",
   "executable": "pysam.py",
   "sources": [
     "pyjson"
   ],
   "sinks": [
     "print"
   ],
   "functions": [
     "revert"
   ]
}

Tips

The pysam.json file is the metadata file of the plugin. The file name pysam must be the same as the Data Processing -> Extension -> Portable plugin tab on the NeuronEX Dashboard, click The plugin name filled in when creating a portable plugin is the same.

Introduction to the plugin main program

In this example, the pysam.py file is the main program executable file of the plugin. This file contains the main program logic of the plugin, and configures and registers the specific data source Source, action Sink and function plugin.

python
from ekuiper import plugin, PluginConfig
from print import PrintSink
from pyjson import PyJson
from revert import revertIns

if __name__ == '__main__':
     c = PluginConfig("pysam", {"pyjson": lambda: PyJson()}, {"print": lambda: PrintSink()},
                      {"revert": lambda: revertIns})
     plugin.start(c)

Specific plugin implementation introduction

In this example, the pyjson.py file is a data source Source plugin in the plugin, the print.py file is an action Sink plugin in the plugin, and the revert.py file is a Function plugin in the plugin. . Taking the Function plugin revert.py as an example, customized functional requirements can be achieved through the exec function in the revert.py file.

python

from typing import Any, List
from ekuiper import Function, Context

class RevertFunc(Function):

     def __init__(self):
         pass

     def validate(self, args: List[Any]):
         return ""

     def exec(self, args: List[Any], ctx: Context):
         return args[0][::-1]

     def is_aggregate(self):
         return False

revertIns = RevertFunc()

plugin packaging and installation

After completing the plugin development, we need to package the results into a zip for installation. In the directory of the same level as pysam.json, execute the following command to package:

shell
zip -r pysam.zip ./*

Through the above command, the pysam.zip file will be generated in the current directory. This file is the plugin package we need to install. On the Portable plugin tab, click Create Portable plugin. Enter the plugin name pysam in the pop-up window and upload the plugin pysam.zip to complete the plugin installation.

After the plugin is installed, the detailed information of the plugin will be displayed in the plugin list, as follows: pysam

tip

After installing the plugin, NeuronEX does not need to be restarted to use the plugin function normally.

plugin usage example

Use the plugin in the data source Source

On the Source page, click Create Stream to select the pysam plugin to use as a custom data source.

Using plugins in SQL

On the Rules page, click Create Rule to directly call the custom function revert in the rule SQL. In this example, the revert function obtains device_name from the demoStream stream. The value of the field, and implements the function of string reversal and outputs it to the result field.

sql
SELECT revert(device_name) as result FROM demoStream

Assume that the input data in the demoStream stream is as follows:

json
{
   "device_name": "abcdefg"
}

Then, the rule output data is as follows:

json
{
   "result": "gfedcba"
}

Using plugins in action sinks

On the Add Action page, you can select the print plugin to use as a custom action.

other

Other plugin options

Users can add the install.sh file and the requirements.txt file in the plugin directory. When the plugin is installed, the install.sh script will be automatically executed to install the dependent libraries required by the plugin.

An example of the install.sh file is as follows:

shell
cur=$(dirname "$0")
echo "Base path $cur"
pip install -r $cur/requirements.txt
echo "Done"

An example of the requirements.txt file is as follows:

shell
numpy==1.22.3
scipy==1.8.0

tip

Users can add corresponding algorithm model files, such as model.pkl files, in the plugin directory, and the model file can be directly called in the plugin python code.