Python Project Template

Workflow Guide

1. Initial Setup

First, clone the repository and navigate to the project directory:

git clone <repository-url>
cd Python_Project_Template

2. Virtual Environment Setup

Create and activate a virtual environment:

# Create virtual environment
make venv

# Activate virtual environment (shown after running make venv)
source venv/bin/activate  # For Unix/MacOS
# or
.\venv\Scripts\activate  # For Windows

3. Install Dependencies

Install required packages:

make install

4. GitHub Integration

Initialize repository and push to GitHub:

# Set your GitHub username and repo name in Makefile
# Then run:
make init

# For subsequent pushes:
make push

5. Sync with GitHub

To pull latest changes and update packages:

make sync

6. Sample Analysis

The project includes a raw dataset (raw_data/boston.txt) and configuration (src/config/config.yaml) for running a random forest regression. The configuration file allows you to adjust model hyperparameters without changing the code.

To run the analysis:

1. Activate your virtual environment.
2. Preprocess the raw data to prepare the dataset:

   python src/00_rawdata_process.py

3. Execute the regression analysis script:

   python src/01_regression.py

4. Visualize the results using the visualization script:

   python src/02_visualization.py

Example configuration in config.yaml:

model:
  type: "random_forest"
  parameters:
    n_estimators: 100
    max_depth: 10
  test_size: 0.2
  scoring: "roc_auc"