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DataPipeline
DataPipeline
  • What is DataPipeline?
  • How to create a new DataPipeline project?
    • Input and Parameters
    • Scraping frequency
    • Notifications and Error Report
    • Running a manual job
    • Results and Output formats
  • DataPipeline Endpoints ✨
    • Endpoints and Parameters 🧩
    • How to use πŸ“š
  • Managing DataPipeline Jobs & Costs
    • Job status & Cancel a running job
    • Archiving DataPipeline Projects
    • Credit costs for DataPipeline
  • Documentation Overview
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DataPipeline Endpoints ✨

The DataPipeline endpoints allow the users to automate their interactions with the DataPipeline through a list of APIs, providing greater efficiency and flexibility. Here’s what you need to know:

Overview

With this new feature, users can set up, edit, and manage their projects via an API instead of using the dashboard. This automated approach is designed to streamline workflows and enhance productivity, particularly for users who manage multiple projects simultaneously.

Key benefits

  • βš™οΈAutomation: No need to log in or visit the dashboard to manage projects.

  • πŸš€Scheduling: Set up and edit projects programmatically, saving time and reducing manual effort.

  • πŸ’° Cost-Effective: Users pay per job, with a fast cost of 6 API credits, as with the existing DataPipeline.

Features

Beyond the core functionalities available in DataPipeline, the API endpoints also offer:

  • πŸ“Project Management: Besides creating and editing projects, the endpoints allow for archiving projects, giving you greater flexibility and control over your data management.

  • πŸ“ŠJob Management: Start, edit, and cancel running jobs effortlessly.

Last updated 11 months ago

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