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Automated Clockify Monthly Report Backup to GitHub

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Automated workflow for Clockify that schedules and backs up detailed monthly reports to GitHub, ensuring no data is lost. It extracts time entries, compares datasets, and updates or creates files in GitHub, streamlining data management and enhancing report accessibility.

Workflow Overview

Automated workflow for Clockify that schedules and backs up detailed monthly reports to GitHub, ensuring no data is lost. It extracts time entries, compares datasets, and updates or creates files in GitHub, streamlining data management and enhancing report accessibility.

  • Project Managers: To automate the backup of time tracking data from Clockify.
  • Developers: To integrate Clockify data with GitHub for version control.
  • Data Analysts: To analyze time entry data over specific months.
  • Small Business Owners: To keep track of time spent on projects and ensure accurate billing.
  • Automation Enthusiasts: To streamline workflows and reduce manual data handling.

This workflow automates the process of backing up detailed monthly reports from Clockify to GitHub. It addresses the challenge of manually tracking and storing time entries, ensuring that data is consistently updated and available for analysis or reference. By automating these tasks, users save time and reduce the risk of errors associated with manual processes.

  • Schedule Trigger: Initiates the workflow daily at 5 AM.
  • Get First Workspace: Fetches the first available Clockify workspace ID to use in subsequent API calls.
  • Set Month Indexes: Defines the last 3 months for which reports will be generated.
  • Split Out Indexes: Breaks down the month indexes into separate entries for processing.
  • Set Intervals: Calculates the start and end dates for each month based on the current date, formatting them for API requests.
  • Get Detailed Monthly Report: Sends a request to Clockify's API to retrieve time entries for each specified month.
  • Check if File Exists in GitHub: Verifies if a report file for the month already exists in the specified GitHub repository.
  • Point to New Data: Prepares the retrieved time entries for further processing.
  • Skip Empty Reports: Filters out any months that do not have time entries, preventing unnecessary file creation.
  • Update/Create File in GitHub: Depending on whether the file exists, it either updates the existing report or creates a new one, ensuring that all relevant data is stored in GitHub.

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Quick Info

Categories
Schedule Triggered
Complex Workflow
+2
Complexity
complex

Tags

advanced
api
integration
logic
conditional
complex
sticky note
files
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