Skip to content

Latest commit

 

History

History
72 lines (50 loc) · 1.58 KB

readme.MD

File metadata and controls

72 lines (50 loc) · 1.58 KB

Run-Kit: Polyglot Analytics Pipeline

A real-world polyglot analytics pipeline demonstrating Rust → Python → R → JavaScript integration using run-kit.

Features

  • Generate synthetic customer data in Rust
  • Train a logistic regression model in Python (scikit-learn)
  • Fit a statistical GLM in R with robust standard errors
  • Generate an interactive HTML report with Plotly

Getting Started

1. Clone the repository

git clone https://github.com/esubalew/run-kit-analytics.git
cd kit

2. Set up Python virtual environment

# Create .venv folder
python3 -m venv .venv

# Activate the environment
# macOS/Linux
source .venv/bin/activate
# Windows
.venv\Scripts\activate

# Install dependencies
pip install pandas scikit-learn

3. Install R packages

Open R and run:

install.packages(c("jsonlite", "sandwich", "lmtest"))

4. Build and run the pipeline

cargo run

This will:

  1. Generate customer data (data/customers.csv)
  2. Train a Python logistic regression model
  3. Fit an R GLM model
  4. Produce report.html with interactive charts

5. View report

After running, open the generated report:

open report.html  # macOS
# or
xdg-open report.html  # Linux
# or double-click on Windows

References