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Timesheet Helper

Timesheet Helper is a collection of Python scripts designed to process text-based timesheets copied from Microsoft Word. The scripts can remove time spans, calculate the duration of time spans, and format the timesheet for either email or timesheet entry purposes.

Table of Contents

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Ensure you have Python installed on your machine. The scripts are written in Python 3.

# Check Python version
python --version

Installation

Clone the repository to your local machine.

# Clone the repository
git clone https://github.com/Christopher-C-Robinson/Timesheet_Helper.git

Usage

  1. Copy your bulleted timesheet from Microsoft Word.
  2. Paste it within the timesheet.py script.
  3. Run the timesheet.py script.
# Run the script
python timesheet.py

Scripts

remove_times.py

This script defines a function remove_timespans that removes time spans from the text.

timesheet_helper.py

This script defines a function replace_with_duration that replaces time spans in the text with their corresponding durations.

timesheet.py

This script imports functions from the other two scripts and processes a text-based timesheet.

azureDevopsAPI.py

This script fetches information about a specific test case from Azure DevOps using the Azure DevOps API.

Usage

  1. Ensure you have the required environment variables set in a .env file:

    • API_VERSION
    • ORGANIZATION
    • PERSONAL_ACCESS_TOKEN
  2. Run the script:

python azureDevopsAPI.py

extract_failed_tests_from_xml.py

This script extracts the names of all failed test cases from multiple XML files and copies the formatted list to the clipboard.

Usage

  1. Ensure you have the required directories and file paths set in the script.
  2. Run the script:
python extract_failed_tests_from_xml.py

Contributing

If you would like to contribute to the Timesheet Helper project, please feel free to fork the repository, create a feature branch, and submit a pull request.

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