Productivity Tracker Plugin

The Productivity Tracker Plugin is a VSCode extension designed to monitor and analyze programming productivity. It tracks coding activity, trains a machine learning model, and provides insights into productivity trends.

Features

• Tracks characters added to files during coding sessions.
• Saves activity logs to productivity_log.json in the user's workspace.
• Uses a Decision Tree model to predict productivity trends based on day and time.
• Displays productivity insights and time series analysis in VSCode.
• Provides options to retrain the model and generate insights via the Command Palette.

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Installation Instructions

1. Clone the Repository

Clone the project to your local machine:

git clone <repository-url>
cd productivity-tracker-plugin

2. Install Dependencies

Ensure Node.js and npm are installed on your system.

Install the required dependencies for the extension:

npm install

Install the Python libraries required for the ML scripts:

pip install -r requirements.txt

3. Open in VSCode

• Open the project folder in VSCode.
• Open the productivitytrackerplugin workspace.

4. Run the Extension

• Press F5 in VSCode to run the extension in a new Extension Development Host window.

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Usage

Logging Productivity

1. Open a folder in VSCode. The extension automatically tracks coding activity and saves it to productivity_log.json in the folder.

Generating Insights

1. Open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P on Mac).
2. Search for and select "ProductivityTracker: Generate Insights".
3. Insights are displayed in VSCode, and a time series plot is saved as productivity_plot.png in the workspace folder.

Model Training

• The model is retrained automatically when insights are generated.

Viewing Logs

• The raw productivity logs are saved as productivity_log.json in the workspace.

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Project Structure

• extension.js: Main file for the VSCode extension.
• train_model.py: Python script for training the Decision Tree model.
• generate_insights.py: Python script for generating productivity insights and plots.
• requirements.txt: Python dependencies.
• test_productivity_log.json: Sample log data for testing.

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Requirements

Software

• Node.js (16.x or higher)
• Python (3.8 or higher)
• VSCode

Python Libraries

• scikit-learn
• pandas
• matplotlib

Install all required Python libraries using:

pip install -r requirements.txt

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Troubleshooting

Common Issues

1. No Productivity Log Found: Ensure you have a folder open in VSCode before using the extension.
2. Python Script Errors: Ensure all Python dependencies are installed and the paths to the scripts are correct.
3. Empty Plot: Ensure there is sufficient data in the productivity_log.json file.

Debugging

• Use the VSCode Output tab to check for logs.
• Check the console logs in the Extension Development Host window.