ScoreDetect

ScoreDetect allows you to easily create verification certificates for your digital content.

Integrate the ScoreDetect API with the Python API

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

Create Certificate from File with the ScoreDetect API

Creates a timestamped blockchain certificate using a provided file (local or URL). 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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Create Timestamped Blockchain Certificate with the ScoreDetect API

Creates a timestamped blockchain certificate using the provided text. See the documentation

 
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Overview of ScoreDetect

The ScoreDetect API provides real-time sports scores and stats, offering a treasure trove of data for sports enthusiasts, bettors, and developers building applications tied to sports events. With Pipedream, you can leverage this API to create serverless workflows that react to live sports data, integrating with countless other apps to automate notifications, update databases, sync with social media, or even trigger custom actions based on game events.

Connect ScoreDetect

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    scoredetect: {
      type: "app",
      app: "scoredetect",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.scoredetect.com/me`,
      headers: {
        Authorization: `Bearer ${this.scoredetect.$auth.api_key}`,
      },
    })
  },
})

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

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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}}