Run Python Code with Python API on New Evidence for Control Added from Drata API

Pipedream makes it easy to connect APIs for Python, Drata and 2,400+ other apps remarkably fast.

Trigger workflow on

New Evidence for Control Added from the Drata API

Next, do this

Run Python Code with the Python API

No credit card required

▶

Watch us build a workflow

8 min

Watch now ➜

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

Getting Started#

This integration creates a workflow with a Drata trigger and Python action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Evidence for Control Added trigger
1. Connect your Drata account
2. Configure timer
3. Select a Control ID
Configure the Run Python Code action
1. Connect your Python account
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

New Evidence for Control Added on Drata

Description:Emit a new event for every new evidence for a control. [See the documentation](https://developers.drata.com/docs/openapi/reference/operation/GRCPublicController_getMappedExternalEvidence/#tag/Controls/operation/GRCPublicController_getMappedExternalEvidence).

Version:0.0.3

Key:drata-new-evidence-added

View on GitHub

Drata Overview#

Drata is a compliance automation platform. Drata’s platform is built by compliance and security experts so you don’t have to be one. With 75+ native integrations, you can easily connect your tech stack and automate evidence collection and testing.

Pipedream customers get 25% off Drata, with implementation fees waived. Visit https://drata.com/partner/pipedream for more information.

Trigger Code#

import drata from "../../drata.app.mjs";
import constants from "../../common/constants.mjs";
import { DEFAULT_POLLING_SOURCE_TIMER_INTERVAL } from "@pipedream/platform";

const docsLink = "https://developers.drata.com/docs/openapi/reference/operation/GRCPublicController_getMappedExternalEvidence/#tag/Controls/operation/GRCPublicController_getMappedExternalEvidence";

export default {
  key: "drata-new-evidence-added",
  name: "New Evidence for Control Added",
  description: `Emit a new event for every new evidence for a control. [See the documentation](${docsLink}).`,
  type: "source",
  version: "0.0.3",
  dedupe: "unique",
  props: {
    drata,
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
    controlId: {
      propDefinition: [
        drata,
        "controlId",
      ],
    },
  },
  hooks: {
    async deploy() {
      console.log(this.controlId);
      const response = await this.drata.listEvidencesForControl({
        controlId: this.controlId,
        paginate: true,
        // this endpoint does not support custom sorting. It sorts by name
        params: {
          limit: constants.DEPLOY_LIMIT,
        },
      });

      this._setVisitedIds(response.data.map((evidence) => evidence.id));
      for (const evidence of response.data.slice(-constants.DEPLOY_LIMIT)) {
        this.$emit(evidence, {
          id: evidence.id,
          summary: `Historical evidence added event: ${evidence.name}`,
          ts: new Date(),
        });
      }
    },
  },
  methods: {
    _getVisitedIds() {
      return new Set(this.db.get("visitedIds"));
    },
    _setVisitedIds(visitedIds) {
      this.db.set("visitedIds", Array.from(visitedIds));
    },
  },
  async run() {
    const visitedIds = this._getVisitedIds();

    const response = await this.drata.listEvidencesForControl({
      controlId: this.controlId,
      paginate: true,
      params: {
        limit: constants.PAGINATION_LIMIT,
      },
    });

    for (const evidence of response.data) {
      if (!visitedIds.has(evidence.id)) {
        visitedIds.add(evidence.id);
        this.$emit(evidence, {
          id: evidence.id,
          summary: `New evidence added: ${evidence.name}`,
          ts: new Date(),
        });
      }
    }

    this._setVisitedIds(visitedIds);
  },
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
Drata	`drata`	`app`	This component uses the Drata app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Control ID	`controlId`	`integer`	Select a value from the drop down menu.

Trigger Authentication#

Drata uses API keys for authentication. When you connect your Drata account, Pipedream securely stores the keys so you can easily authenticate to Drata APIs in both code and no-code steps.

Make sure you're logged into the Drata UI, then see these docs to create a Drata API key. Enter it below.

About Drata#

Drata automates your compliance journey from start to audit-ready and beyond and provides support from the security and compliance experts who built it.

Action#

Run Python Code on Python

Description:Write Python and use any of the 350k+ PyPi packages available. Refer to the [Pipedream Python docs](https://pipedream.com/docs/code/python) to learn more.

Version:0.0.2

Key:python-run-python-code

View on GitHub

Python Overview#

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:

Action Code#

import python from "../../python.app.mjs";

export default {
  name: "Run Python Code",
  version: "0.0.2",
  key: "python-run-python-code",
  description: "Write Python and use any of the 350k+ PyPi packages available. Refer to the [Pipedream Python docs](https://pipedream.com/docs/code/python) to learn more.",
  props: {
    python,
  },
  type: "action",
  methods: {},
  async run({
    steps, $,
  }) {
    // Placeholder action for Python code app
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
Python	`python`	`app`	This component uses the Python app.

Run Python Code with Python API on New Evidence for Control Added from Drata API

Pipedream makes it easy to connect APIs for Python, Drata and 2,400+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

1-24of2,400+apps by most popular

1
-
24
of
2,400+
apps by most popular