---
id: tower
version: "0.3.70"
license: unclear
license_treatment: permissive
maintenance: active
---

# tower — Tower CLI and runtime environment for Tower.

License: permissive · Maintenance: active · Downloads: 128.8K/mo

## What it is and what it does

Tower is a code-first deployment platform that bridges the gap between writing Python scripts and running them reliably in production. It handles orchestration of data pipelines and AI agents, provides a consistent execution environment across serverless and self-hosted compute, and includes built-in analytical storage (Iceberg) and multi-tenant APIs. You write Python code with a Towerfile entrypoint, deploy via CLI or through AI assistants (Claude, Cursor) using the Tower MCP server, and Tower manages secrets, observability, and execution across environments.

The platform depends on attrs, httpx, pydantic, pydantic-core, and python-dateutil for its runtime. It targets developers shipping Python to production who want to avoid building custom orchestration, API layers, and storage infrastructure. Tower is actively maintained, supports Python 3.12–3.14, and has no known security vulnerabilities.

Use it for:

- Deploy ELT pipelines and dbt workflows without managing Airflow infrastructure.
- Expose Python functions as multi-tenant APIs with built-in user and tenant management.
- Run AI agents with fresh, company-specific data stored in a managed lakehouse.
- Build interactive apps (Marimo notebooks, FastAPI endpoints) and deploy them in under 30 seconds.
- Keep sensitive data in your own environment using self-hosted runners while using Tower's control plane.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Tower is a CLI and Python runtime for deploying Python data apps, pipelines, and AI agents to production with built-in orchestration, analytical storage, and multi-tenant APIs.

Yes, if you are shipping Python code to production and want to avoid the complexity of Airflow + custom APIs + storage infrastructure. Tower is actively maintained, has no known vulnerabilities, and offers a cohesive platform for orchestration, APIs, and analytical storage. The MIT license is permissive. Install friction is moderate due to compiled dependencies, but wheels are available for all modern Python versions (3.12–3.14) and platforms. Requires Python 3.12 or later and authentication before first use.

## Install

pip install tower
uv add tower
poetry add tower

## Installing tower

Before you install: Medium install friction due to compiled wheels for multiple Python versions (3.12–3.14) and platforms. Actively maintained with a release 15 days ago. Requires Python 3.12 or later.

License in practice: MIT license (permissive); you can use, modify, and distribute Tower freely with minimal restrictions.

Quickstart:

pip install -U tower
tower login
tower deploy
tower run

Requires Python 3.12 or later. You must authenticate via `tower login` before deploying apps.

Verify before relying:

- Whether Tower's serverless compute is included in the free tier or requires a paid plan.
- Exact cost model for analytical storage (Iceberg) and multi-tenant API usage.
- Performance characteristics and latency for typical data pipeline workloads.
- Data residency and compliance certifications for sensitive workloads.
- Whether self-hosted runners work offline or require periodic control-plane connectivity.

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 128.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python app deployment platform, orchestration for data pipelines, serverless python runtime, ai agent deployment, production python code runner, multi-tenant api platform, lakehouse storage integration, cli deployment tool, orchestration, deployment, ai-agents

[View on SkillFed](https://skillfed.io/packages/tower) · [View on PyPI](https://pypi.org/project/tower/)