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Introduction

The tower-examples repository in GitHub contains a collection of sample applications that can be run on Tower.

Getting started is easy. First, run the following command to clone the repository locally.

git clone https://github.com/tower/tower-examples

Next, go through the Quickstart guide to learn how to use these examples. The Quickstart focuses on the "Hello, World!" example to get you started.

Overview of Examples

Tower examples are organized around integrations with tools such as dltHub and Tower concepts such as orchestration and tables.

Hello, World!​

Tower's most basic example demonstrates the use of app parameters. You will create and deploy an app that has a few parameters and prints a message.

Using dltHub​

Tower can be used as a runner for dltHub pipelines.

Implementing an ELT pipeline​

This example implements a typical ELT pipeline. You will read CSV files on S3 and populate a Snowflake data warehouse.

Working with DLT Plus​

This example uses dlt plus and adds transformations to extraction and loading tasks.

Working with Tables​

You can use Tower-supplied or self-managed Apache Iceberg tables to store and process data in a lakehouse. Tower will integrate with the REST catalog of your choice.

Writing to an Iceberg table​

In this example you will download a JSON file containing stock ticker data for a specified date from S3 and write its contents into an Iceberg table.

Highlights the use of: Iceberg, PyArrow

Analyzing data in an Iceberg table​

This example reads stock ticker data from an Iceberg table populated in the previous example, calculates stats such as moving averages and volatility using Polars, and uses the DeepSeek R1 LLM to make recommendations on buying or selling stocks.

Highlights the use of: Iceberg, Polars, Local Inference, Together.ai, DeepSeek R1

Working with Models​

In this example you will use the DeepSeek R1 LLM in both local and serverless modes to summarize a GitHub issue.

Highlights the use of: ollama, DeepSeek R1, Hugging Face Hub, Together.ai, dltHub

Scheduling and Orchestrating Apps​

Setting up a schedule for an app​

In this example we will set up a recurring schedule to instantiate an app and run it in Tower.

Highlights the use of: dltHub

Imlementing a Control Flow​

This example demonstrates the calling of a Tower app from another app and waiting for its completion, effectively creating a control flow.