Why the BMS Industry Should Embrace Python for Control Programming
For decades, Building Management Systems (BMS) have run the backbone of commercial buildings — from HVAC and lighting to energy management and alarms. Yet behind the scenes, most BMS controllers are still programmed using proprietary, decades-old languages that very few people outside the industry understand.
Meanwhile, the rest of the software world has moved forward with modern, open, and powerful programming languages like Python — which dominates AI, data science, cloud, and edge computing.
This begs the question:
Why hasn’t the BMS industry embraced Python for control logic programming?
And more importantly: Should it?
The short answer is: yes — and the advantages are enormous.
1. A Larger Talent Pool = Faster Innovation
Ask any BMS company how easy it is to hire technicians who know Johnson Controls’ GPL, Siemens Desigo block programming, or Delta’s GCL+. The answer: not very. These languages are niche, outdated, and often trapped inside closed vendor ecosystems.
On the other hand, Python is one of the most popular programming languages in the world. Millions of developers, data scientists, and engineers already know it.
By adopting Python for controller programming, the BMS industry could tap into a global talent pool, dramatically lowering training costs and onboarding times. New engineers wouldn’t need months to learn proprietary tools — they’d be productive almost immediately.
2. Modern Software Engineering Practices
Most current BMS programming environments don’t support version control, unit testing, modular code, or collaboration workflows. Sequences live inside closed GUIs, making them hard to share, review, or debug.
Python changes that.
With Python, control logic can be stored in Git repositories, tested automatically, reviewed like modern software, and deployed through structured pipelines. This isn’t just cleaner — it’s a paradigm shift from “programming by drawing blocks in a 1990s interface” to true software engineering.
3. Seamless Integration with Analytics, AI, and the Cloud
Today’s buildings are becoming smarter — with layers of energy optimization, AI-driven fault detection, and cloud-based analytics. Python is already the language of choice in these domains.
If control logic lived in Python too, integration would be seamless:
- Predictive control using machine learning models
- Real-time optimization using MPC algorithms
- Native communication over BACnet, MQTT, REST, and Modbus through existing Python libraries
- On-the-fly adaptation of sequences based on live data
Instead of bolting these features on top, Python could natively blend control and intelligence.
4. Open Ecosystem and Vendor Agnosticism
Proprietary languages keep customers locked in. You can’t easily take your Siemens sequences and port them to Honeywell or Johnson Controls. This lack of portability slows innovation and inflates project costs.
A Python-based control ecosystem would be open and vendor-neutral. Integrators could build reusable libraries, share best practices, and innovate on top of a common foundation.
Just like open-source transformed the web, an open control programming ecosystem could transform buildings.
So Why Haven’t Manufacturers Done It Yet?
The big players — Siemens, JCI, Schneider, Honeywell, Trane, Delta, Distech — haven’t adopted Python at the controller level. Here’s why:
- Real-time performance: Traditional controllers run on limited hardware and require deterministic behavior. Historically, Python wasn’t ideal for real-time loops. (But that’s changing fast with modern edge devices and MicroPython.)
- Certification & Safety: BMS controllers need UL, BTL, CE certifications. Manufacturers are risk-averse and slow to adopt new languages.
- Legacy Installed Base: Entire product lines are built on proprietary environments. Rewriting them in Python would be a massive undertaking.
- Business Lock-in: Proprietary tools keep customers tied to a vendor. Open languages would reduce that stickiness — which doesn’t align with their short-term interests.
Where the Shift Will Start
The transition to Python for BMS control likely won’t come from the big vendors first. It will come from innovators, integrators, and edge-based architectures, such as:
- Open-source platforms like Eclipse VOLTTRON, which already use Python agents to control building systems.
- Custom edge controllers (Raspberry Pi, industrial Linux boxes) running Python control loops and communicating via BACnet or MQTT.
- Research institutions and smart campuses pioneering Python-native supervisory control strategies.
These early adopters will prove that Python can meet the performance, reliability, and flexibility requirements of modern building systems — and force the rest of the industry to catch up.
A Strategic Opportunity
For companies willing to lead, this is a once-in-a-generation opportunity:
- Build your own Python-based control framework.
- Run it on edge devices and connect via standard protocols.
- Develop faster, integrate better, and scale smarter.
- Attract top software talent into an industry that desperately needs it.
- Position yourself as the modern alternative to legacy BMS vendors.
Final Thoughts
The BMS industry has spent decades perfecting mechanical reliability — but it’s still programming like it’s 1995.
Embracing Python for control programming isn’t just about changing a language. It’s about unlocking innovation, democratizing building controls, and bridging the gap between mechanical systems and modern software.
The companies that recognize this early will shape the next era of smart buildings.