Nixtla Blog Code

This repository contains the code and examples for blog articles published on nixtla.io.

Environment Setup

This project uses uv for Python package management. To set up the environment:

1. Install uv if you haven't already:

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Create and activate a virtual environment:

uv venv
source .venv/bin/activate  # On Unix/macOS
# or
.venv\Scripts\activate  # On Windows

3. Install dependencies:

uv sync
pre-commit install

Project Structure

• notebooks/: Contains Jupyter notebooks for each blog post
• README.md: This file

Each blog post's code is organized in its own notebook, named according to the blog post title.

Available Notebooks

• Anomaly Detection (anomaly_detection.ipynb) - Learn how to detect anomalies in time series data using TimeGPT
• Baseline Forecasts (baseline_forecasts.ipynb) - Explore baseline forecasting methods and their effectiveness
• Intermittent Forecasting (intermittent_forecasting.ipynb) - Explore demand forecasting techniques for intermittent time series

Running Notebooks Locally

The notebooks are standard Jupyter notebooks that can be run in any Jupyter environment.

To run the notebooks locally, you can use:

# Start Jupyter Lab
uv run jupyter lab

# Or start Jupyter Notebook  
uv run jupyter notebook

This will start a local server where you can interact with the notebooks in your browser.

Contributing

We welcome contributions to improve the code examples and documentation. Please see CONTRIBUTION.md for detailed guidelines on:

• Style and structure of blog posts
• Development workflow