Integrate the Columns Ai API with the Python API

Setup the Columns Ai API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Columns Ai and Python remarkably fast. Free for developers.

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Popular Columns Ai and Python Actions#

Build Graph From Scratch with the Columns Ai API

Builds a graph object from scratch and publishes it. See the documentation

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Build Graph From Template with the Columns Ai API

Builds a graph object from a template and publishes it. See the documentation.

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Connect Columns Ai#

import { ChartType } from 'columns-graph-model';
import { Columns } from 'columns-sdk';

export default defineComponent({
  props: {
    columns_ai: {
      type: "app",
      app: "columns_ai",
    }
  },
  async run({steps, $}) {    
    const rows = [{
        "value": 312,
        "state": "WA",
        "parent": "US"
      }];// rows is an example data set where you should organize your data in a similar way.

    //Instantiates a Columns SDK object with your API Key.  
    const columns = new Columns(this.columns_ai.$auth.api_key);
    const data = columns.data(['state'], ['value'], rows);
    const graph = columns.graph(data);

    // switch to different chart types: BAR, PIE, DOUGHGUT, LINE, AREA, SCATTER, etc.
    graph.type = ChartType.COLUMN;

    // customise the graph (lots of options in its data model)
    graph.settings.general.palette = ['#ff0000', '#00ff00', '#0000ff'];
    graph.settings.general.background = '#00000002';
    
    return graph;          
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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