Zip Archive API

Compress your files with the ZIP Archive API.

Integrate the Zip Archive API API with the Python API

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

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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Overview of Zip Archive API

The Zip Archive API allows you to manage zip archives programmatically. You can create, extract, and modify zip files, making it ideal for automating routine file management tasks. Integrating this API with Pipedream enables you to automate workflows that involve file compression or decompression, combine it with triggers from other apps, and process large batches of files efficiently, saving time and reducing manual effort.

Connect Zip Archive API

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    zip_archive_api: {
      type: "app",
      app: "zip_archive_api",
    }
  },
  async run({steps, $}) {
    const data = {
      "file": `https://www.learningcontainer.com/wp-content/uploads/2020/05/sample-zip-file.zip`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.archiveapi.com/extract`,
      headers: {
        "Accept": `text/plain`,
      },
      params: {
        secret: `${this.zip_archive_api.$auth.secret}`,
      },
      data,
    })
  },
})

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}}