The Square Kilometre Array (SKA) project employs the TANGO Controls framework to manage its telescopes. Within SKA MID, the Dish Local Monitoring and Control (LMC) software integrates dish sub-components into the overall control system. Because hardware availability is often limited, Dish LMC development and validation are heavily based on software simulators derived from Interface Control Documents (ICDs) and system-level requirements. These simulators emulate the behaviour of the respective devices for requirement verification. Their use has enabled iterative testing in both staging and integration environments, accelerated development, and reduced risks ahead of hardware integration. This paper presents the design and implementation of Dish LMC simulators, their role in supporting system-level validation and advancing software maturity.

Precise control of photon beam properties is essential for modern synchrotron beamlines, particularly those utilizing APPLE-II type undulators. This paper presents the control system architecture developed at MAX-IV by using IcePAP drivers and TANGO control system, to achieve advanced polarization and energy manipulation. The system implements the BLUES (Beamline Universal Polarization Mode) framework, allowing dynamic control of both helical and inclined polarization states through synchronized phase motor settings. Central to this approach is the use of parametric lookup tables to define non-linear motion trajectories for the undulator’s gap and phase axes. This system enables linear energy ramps, supporting constant eV/s scans crucial for high-resolution spectroscopy and imaging techniques, taking full advantage of the high flux provided by fourth-generation light sources and improving data collection efficiency without compromising the stability or quality of the photon beam. Integration between the beamline and accelerator control systems allows for the complex coordination required to manage polarization settings. To ensure electron beam stability during undulator motion, the control system integrates feedforward correction loops that compensate for orbit and optics distortions induced by gap and phase changes. This approach offers a scalable and precise method for enhancing beamline capabilities, tailored specifically for the challenges posed by APPLE-II undulators.

Ten years ago, the PandABox platform was first introduced in Melbourne during the MOCRAF workshop. Originally developed through a collaboration between Synchrotron SOLEIL and Diamond Light Source, PandABox was designed to support multi-technique scanning and feedback applications. Since then, the platform has been widely adopted across synchrotron facilities worldwide—including SOLEIL, DIAMOND, MAX IV, and DESY in Europe; NSLS-II in the United States; HEPS in Asia; and SESAME in Middle-East. With the fourth-generation light sources, there is an increasing need for high-performance, multi-channel encoder processing to enable synchronized data acquisition and motion control during continuous scanning experiments—now a critical feature for automation. In response to these evolving demands, and following discussions within the LEAPS-INNOV WP5.3 project, the opportunity to jointly develop a new state-of-the-art equipment became evident. This effort has since expanded into a broader collaboration that now includes MAX IV, ALBA, and DESY alongside the original partners. This paper presents the new generation of the PandABox platform, offering a comprehensive overview of its integration within EPICS and TANGO control systems. It also outlines future functionalities and the framework of the ongoing international collaboration driving its development.

Test flakiness—when a test intermittently passes or fails without changes to the code—poses a significant challenge in the validation of distributed control systems. This paper presents an investigation into test flakiness in CSP.LMC (Local Monitoring and Control for the Central Signal Processor), a key subsystem of the SKA (Square Kilometre Array) telescope. CSP.LMC is a Python application built on the TANGO framework, that is tested using a multi-level testing approach combining unit, component, and integration tests. To achieve scalable and reproducible deployment, the entire SKA control software runs within a Kubernetes environment. We systematically collect test outcomes and execution benchmarks to monitor system stability over time. A data mining approach is applied to uncover correlations and hidden patterns associated with test instability. Our analysis aims to uncover subtle software issues that are not easily detected through standard test evaluation. Furthermore, we aim to explore how the complexity of both the software architecture and its deployment may introduce sources of non-determinism that can lead to flaky tests. We discuss the impact of flakiness on the reliability of SKA control software and propose practical strategies to benchmark, detect, and mitigate flaky tests in complex distributed environments.

At MAX IV, we have developed a high-performance data acquisition (DAQ) system to handle the high rate detectors exploiting the brightness of the fourth-generation source. This system integrates multiple detector types, including photon counting and charge integrating detectors as well as sCMOS cameras, into a unified DAQ framework. Data are streamed to a central Kubernetes cluster which mounts an IBM Storage Scale (GPFS) storage, with control provided via Tango. The system provides live feedback from the detectors/cameras and is furthermore extended to provide on-the-fly data reduction via the "Dranspose" framework, a horizontally scalable, distributed data analysis pipeline. We present an overview of the diverse detector suite at MAX IV and describe the components of our DAQ and processing framework, highlighting its performance for live data streaming and on-the-fly reduction with reference to several applications.

The National Synchrotron Radiation Centre SOLARIS*, a 3rd Generation Synchrotron Light Source, stands as the most advanced research infrastructure in Poland. Since its commencement of operation in 2015, SOLARIS has undergone significant expansions. Initially, system upgrades were straightforward to implement. However, as the facility matured, new beamlines were created, and the number of equipment increased significantly. This led to a rise in the complexity of upgrades, prompting the SOLARIS team to focus on creating automation tools for deployments and maintaining up-to-date libraries and software. During this period, many versions of libraries, such as Python and PyQt, as well as the CentOS operating system, became obsolete, leading to increased maintenance costs. To address these challenges, a comprehensive strategy was developed. This strategy includes transitioning from CentOS 6 and 7 to AlmaLinux 9, upgrading older versions of Python to version 3.9, and updating automation tools such as Ansible and GitLab CI/CD. This paper presents the methodology employed for the control system upgrade, detailing the architecture of the new system, the upgrade process, and the challenges encountered.

The Tango HDB++ project is a high-performance, event-driven archiving system that stores data with microsecond resolution timestamps. HDB++ supports various backend databases to accommodate any infrastructure choice, with Timescale as the default option. Timescale, an extension of PostgreSQL, is selected for its exceptional performance, reliability, and open-source license. After more than five years of using the system in production at major facilities such as the ESRF, MAX IV and SKAO, this paper presents the insights gained from operating HDB++ with Timescale in a large research facility. Results are presented considering various perspectives. From a performance standpoint, the paper examines how the scalability features have maintained low query response times despite the continuous growth in data volume over the years. From the system administration perspective, findings show that standardized and proven technologies have consistently supported high-quality service delivery. Lastly, from the user perspective, we analyze how users can query data stored from the inception of the project up to last week within seconds, either from the python API or from clients like grafana. This capability is also enabled by the successful migration and integration of archived data from older or different systems into the database in full compliance with HDB++ standards.

Elettra, the Italian Synchrotron in Trieste, is about to undergo a major upgrade of the facility. To effectively exploit such improvement, data acquisition and processing are being integrated into single automated pipelines, subject to a facility-wide standard and yet flexible enough to accommodate the specific usage at each beamline. The entire procedure of data acquisition and processing spans a vast ecosystem of different structures and frameworks, which are being standardized across the whole facility: the GeCo control system, handling the safety and the operation of the beamlines; the TANGO Controls framework, that allows distributed control of the data acquisition process; the architecture of data storage and processing, whose accessibility is mediated by VUO, the Elettra unified portal; a modular adaptive processing infrastructure (MAPI) for analysis workflows; and an overview of the data lake data@Elettra. The intertwining of all these components results in the integrated pipeline experienced by the users. The acquisition/processing sequence presently in place at SYRMEP, the microtomography beamline, is presented as a case study of the standard structure that is being designed. Beamline and acquisition control, on-the-fly and post-acquisition processing are described in the light of the general landscape proposed for Elettra 2.0, the upgraded facility.

Integration of MicroTCA systems into TANGO using ChimeraTK at SOLEIL Twenty years ago, standard electronic systems such as cPCI, motion controllers, and the S7 300 PLC were chosen to build the SOLEIL control system. Although fully operational since 2006, many of these technologies are now obsolete. As SOLEIL undergoes a major upgrade with the SOLEIL II project—aimed at constructing a 4th-generation synchrotron light source—modernizing the control system with state-of-the-art technologies has become essential. SOLEIL has adopted the MicroTCA (MTCA) platform as one of the new standard baselines for applications requiring high-speed control and data acquisition. This poster presents ongoing efforts to standardize the integration of MicroTCA systems and applications into the TANGO control system. It outlines SOLEIL’s MTCA integration strategy, including the development of a connector bridging TANGO to the ChimeraTK and FWK frameworks developed at DESY via OPC UA. This communication layer facilitates interoperability and modular integration within the SOLEIL control architecture. The approach is illustrated through two current MTCA-based projects—low-level RF and fast orbit feedback—highlighting technology choices, system development, installation, and preliminary results.

Since last status update in 2023, the Tango Controls collaboration has undertaken a major effort to add new features to cppTango, the core of Tango Controls, and two other official language bindings, JTango and PyTango. Significant development efforts have been dedicated to the implementation and prototyping of community-requested features. Observability is a trending topic in software development, and we have listened to our community adding OpenTelemetry support. Continuing with cppTango refactoring, we switched to C++17 and catch2 as the new testing framework to improve code quality and test coverage. PyTango has undergone a major overhaul by switching from boost-python to pybind11, which has been a welcome modernization of the code base and has allowed us to remove obsolete APIs. Special Interest Group (SIG) meetings continued to be a great success. Several have been held, among them one that addressed and is still addressing the request of our users for a much improved documentation. Encryption has also been a SIG topic, and a prototype for complete end-to-end encryption of all communication in Tango Controls has been developed. CI/CD has again received major updates and gained more computing power to run more tests in less time, thanks to the Gitlab runner contributions of the collaboration members. Thanks to the continuous community effort on keeping a modern and well maintained core, the future road map of Tango Controls looks promising and achievable.

Distributed software systems are complex and the interactions across multiple machines can be difficult to debug and monitor. Log messages are not enough for observability. We need more information about the communication between applications, how each one is executing, and its internal state. In practice, applications can be made more observable using software frameworks such as OpenTelemetry. The Tango Controls framework has built-in support for OpenTelemetry in C++ and Python since version 10.0.0. We are using it operationally at the MAX IV synchrotron. We provide examples of the traces, trends, and other data available when running at scale on a beamline with hundreds of devices. We report on the compute and performance impact for client and server software applications, as well as practical issues. For the backend servers that ingest and query the telemetry data (running Grafana Tempo for traces and Grafana Loki for logs) we report on the compute resources required.

It is 2025 and the SKA Telescope Control System has come a long way since the start of construction. The outline of the software architecture and some key technology decisions (including the choice of Tango) were made early. To keep the geographically distributed teams engaged, and avoid creating silos and fragmentation, development of virtually all the software components started in parallel; often while the detailed designs for the custom hardware was still evolving and before the COTS equipment was selected. The deployment strategy was adjusted to align with the industry trends. From designing a software system for hardware that does not exist we arrived at the point where we can prove that the software can actually work with the hardware. However, the software design and implementation meeting reality uncovered some issues, forcing us to make changes (ska-tango-base) and learn hard lessons (naive implementation of event callbacks). Are we ready to deliver a large distributed control system? We realize that scalability will be a challenge. This paper provides an honest overview of what works and what did not work so well, and how we address issues.

Sardana* and Taurus\*\* are community-driven, open-source SCADA solutions that have been used for over a decade in scientific facilities, including synchrotrons (ALBA, DESY, MAX IV, SOLARIS) and laser laboratories (MBI-Berlin). Taurus is a Python framework for building both graphical and command-line user interfaces that support multiple control systems or data sources. Sardana, is an experiment orchestration tool that provides a high-level hardware abstraction and a sequence engine. It follows a client-server architecture built on top of the TANGO control system\*\*\*. In the last two years, significant developments have been made in both projects. Sardana focused on enhancing continuous scans, introducing multiple synchronization descriptions to support passive elements (e.g. shutters) and detectors reporting at different rates. The configuration tool has also been extended, following the roadmap defined by the community\*\*\*\*. Taurus has seen substantial performance gains, particularly in GUI startup times, as part of an optimization effort that started nearly three years ago. Latest improvements take profit of new TANGO event subscription asynchronous modes\*\*\*\*\*. Continuous codebase modernization is underway, and support for Qt6 is planned for the July 2025 release. This presentation will overview these recent advancements in both Sardana and Taurus and outline their current development roadmap.

The future of synchrotron beamline operations is poised for a transformative leap with advancements in artificial intelligence (AI) and machine learning (ML). While SOLARIS National Synchrotron Radiation Centre* has yet to integrate these technologies, their potential to revolutionize experiments, data analysis, and user interactions is immense. AI-driven automation promises real-time assistance in optimizing beamline experiments, minimizing manual intervention while enhancing precision. Machine learning algorithms will unlock deeper insights from complex datasets, facilitating faster, more accurate interpretations. Additionally, intelligent virtual agents could redefine how researchers interact with beamline controls, offering predictive guidance and adaptive optimization. As SOLARIS expands its capabilities, embracing AI and ML will position it at the forefront of scientific innovation, ensuring seamless, efficient, and accessible synchrotron research for future generations.

Operational since 2008, SOLEIL [1] offers users access to a wide array of experimental techniques through its 29 beamlines, covering a broad energy spectrum from THz to hard X-rays. In response to evolving scientific and societal needs, SOLEIL is undergoing a major upgrade through the SOLEIL II project. This transformative initiative includes the development of a new Diffraction Limited Storage Ring (DLSR) [2], designed to dramatically increase brilliance, coherence, and flux. The upgrade also encompasses the modernization of beamlines to support state-of-the-art experimental techniques, along with a comprehensive digital transformation centered on data and user-oriented workflows. This poster presents the current status of the digital transformation efforts within the SOLEIL II framework. It outlines the project's overall progress, with a particular focus on advancements in computing and data management. A central element of this transformation is the implementation of a unified Data Platform. Key developments include the deployment of a data catalog, upgrades to the IT infrastructure, user interface (UI) research, and the integration of robotics. The platform leverages shared infrastructure and software patterns to support both beamline and accelerator teams. Additionally, ongoing evaluations of data streaming technologies—such as ASAPO, LIMA2, and Dranspose—aim to enhance real-time data acquisition and processing capabilities.

The AlarmHandler system is a key component for ensuring operational safety and efficiency in complex control systems. Key updates include improved support for array data types within the alarm evaluation logic, enabling more sophisticated and flexible condition definitions directly involving array or matrix data. Furthermore new tools, designed to extend the AlarmHandler's reach and usability, are now available. A dedicated notification service allows for configurable, multi-channel alerting, such as email and messaging platforms, facilitating timely operator awareness and response. Complementing this, new management utilities have been created to streamline the configuration, deployment, and maintenance of alarm definitions across distributed systems, significantly simplifying administrative tasks. This contribution details the architectural changes, implementation specifics, and the benefits these advancements bring in terms of system robustness, operator efficiency, and overall monitoring capability.

Libera instruments have been used with various control systems for several years. In line with the latest security and functionality upgrades, Libera control system interfaces have also been upgraded. EPICS interface in Libera instruments has been upgraded to support the latest EPICS BASE version 7.0.9, which enables users to use the PVA protocol and retrieve more signal data in a single call. Group PVs, allowing atomic access to all signal components, were also added. Furthermore, similar parameters, such as sensors, can be grouped on the Libera side already and provided to PVA clients in a single PV. The TANGO interface has been upgraded to version 9.5. It supports flexible configuration where DeviceClasses can be configured for each board type individually. The interface has also been extended with TANGO alarm and logging functionalities. Both interfaces, EPICS and TANGO, can run on the Libera instrument or they can now be compiled and run from an external server station. This network architecture enables easier maintenance and upgrades. This paper details all recent updates and improvements to the Libera control system interfaces and presents possible use cases.

SKA-Low is the low frequency radio telescope currently under construction in Western Australia. At its final extent, it will consist of 512 stations up to 74 km apart, each containing 256 antennas which can be used in different combinations to digitally “point” the telescope. The Monitoring, Control and Calibration Subsystem (MCCS) is responsible for performing calibration and providing local monitoring and control of all of the LFAA (Low Frequency Aperture Array) hardware components. This includes managing the allocation of resources for an observation, and the aggregation of health status. SKAO has adopted the Tango control system framework, and the MCCS software comprises upwards of 18 different Tango devices, some of which are replicated dozens of times for a single station. This complexity poses a significant challenge to computing resources and reliability when considering how to scale up the system, first to the 16 stations to be constructed and integrated by January 2026, then 68 stations at the end of 2026, and targeting 307 stations by mid-2028. This paper will describe the MCCS architecture, report on our latest performance profiling, and discuss how we are preparing for the AA 2 construction milestone which will need to support 68 stations.

We present a web-based application that significantly simplifies and accelerates the development of Tango Controls device servers by integrating large language models (LLMs) into the code generation process. The tool allows users to define device attributes, commands, and properties through an intuitive graphical interface, and optionally upload device documentation in PDF format. Using retrieval-augmented generation, the system extracts relevant content from the documentation and generates Python code for Tango device servers, tailored to the specific device functionality. The backend leverages FastAPI and LangChain to interface with various LLMs such as GPT, Claude, and Gemini. Tests on devices like power supplies and teslameters show that the generated code often requires limited manual adjustments. While the application improves development efficiency and accuracy, it also highlights certain limitations, including occasional command mismatches and the need for better retrieval strategies. Future enhancements include automated test code generation, improved document parsing, support for additional programming languages, and integration of open-source models for broader applicability.

The Balder beamline at MAX IV Laboratory, a state-of-the-art 4th generation synchrotron, is designed for X-ray absorption and emission spectroscopy. Delivering a high photon flux (10¹³ ph/s), it supports in situ experiments, which require fast, high-quality data acquisition and support for sequential multi-technique measurements. This work presents a data acquisition (DAQ) system that combines X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD) within a single, synchronized experiment. At the core of the system is a Double Crystal Monochromator, operated by ACS SPiiPlusEC motion controller. This controller enables stable and rapid energy scanning via programmable motion trajectories, allowing sequential acquisition of energy spectra and diffraction patterns. Experiment synchronization is achieved via FPGA-based PandABox, which generates TTL signals based on the real-time motor position, enabling technique-specific pulse trains to be sent to the respective XAS and XRD detectors, precisely gated to the energy scan. The entire experiment workflow is orchestrated using Sardana through dedicated macros and controllers. User interaction is streamlined through a Taurus GUI, providing an intuitive drag-and-drop interface for sequencing and configuring each technique. This contribution outlines the system architecture, integration challenges, and benchmarking results, highlighting the enhanced experimental capabilities made possible by this advanced DAQ system at MAX IV.

The ALBA Synchrotron (Barcelona, Spain) has been operating as a 3 GeV facility for over 10 years and is now preparing its transition to ALBA II, a fourth-generation light source. As part of this planned upgrade, we are evaluating state-of-the-art technologies that could shape the future of our Tango Control System. In particular, we investigate how asynchronous programming can enhance system responsiveness while reducing latency and resource usage. This study focuses on applying asynchronous communication paradigms at all levels between our Taurus SCADA UIs, Tango Control System and PLC-based systems — used for Equipment (EPS) and Personnel (PSS) Protection as well as automation. In this context, we explore the adoption of OPC Unified Architecture (OPC UA), a self-descriptive industrial standard for secure, platform-independent communication, alongside asyncio, the Python standard library for coroutine-based asynchronous programming, as supported by the FreeOpcUa library and "green" modes of PyTango, the Python binding for Tango Controls. Our goal is to demonstrate a modern, flexible, vendor-independent and high-performance control strategy for ALBA II Control System. We provide a comprehensive comparison and benchmark between the proposed solution and existing PyPLC Tango Device Servers.

At the Square Kilometre Array Observatory (SKAO), monitoring data is ingested from distributed subsystems via the Tango Controls archiver, with attribute data stored in the Engineering Data Archive (EDA). The EDA uses a PostgreSQL database with the TimescaleDB extension, offering a performant solution for time-series storage. However, as SKAO infrastructure scales, PostgreSQL becomes impractical for long-term retention due to cost and operational complexity. This paper outlines a long-term storage strategy based on S3-compatible object storage. The solution decouples operational and archival storage by exporting and serializing Tango attribute data into efficient formats like Apache Parquet for storage in S3. Metadata indexing ensures the data remains discoverable and retrievable over time. The approach draws from the MeerKAT telescope's experience, a precursor to SKAO operated by SARAO. MeerKAT faced similar challenges archiving large volumes of telemetry data and adopted a database and long term storage model. We also describe supporting tools and processes for managing data lifecycle transitions. The paper concludes with open challenges and future directions for integrating this approach into observatory-wide data access frameworks, ensuring engineering telemetry remains accessible throughout the SKAO system lifecycle.

Graphical user interfaces (GUIs) play a critical role in the operation and maintenance of large-scale distributed control systems. In this work, we present a synoptic-based visualization for the Central Signal Processor (CSP) of the SKA (Square Kilometre Array) telescope, developed using Taranta, a web-based visualization tool for TANGO systems. The synoptic view provides an intuitive, multi-level representation of CSP, from the upper-level control managed by CSP.LMC down to individual data processing subsystems, including CBF, PSS, and PST devices. The synoptic diagrams are created using Inkscape and exported as SVG files, enabling flexible and straightforward integration with Taranta. A key focus of this work is the collaboration between different subsystem teams, which was essential to accurately model and visualize the full CSP hierarchy. We also define a strategy to validate the effectiveness and the usability of the GUI, ensuring it delivers tangible value in improving the monitoring and troubleshooting capabilities of complex control systems such as SKA.

BL31-FaXToR is the only hard-X-ray micro-tomography and radiography beamline at the third-generation ALBA synchrotron * **. It enables 3D imaging with sub-second temporal resolution under either monochromatic or white-beam conditions. The beamline features a dual-detection system enabling high speed or high resolution acquisitions. For high speed data acquisitions of the detector utilizes multiple frame grabbers and an IBM Storage Scale clustered file system. The goal of the high speed detector is to provide live reconstructions during scans with minimal latency ***. The Detectors are managed through a REST client or LImA device server. The control system is based on Tango and Sardana, providing an efficient, distributed Python environment with full user access to hardware via both graphical and command-line interfaces. The synchronization elements also include a voice coil actuated fast shutter capable of 10 ms openings and a periodic chopper, which introduced new challenges for Sardana requiring the implementation of multiple synchronizations in time and position domain. The experimental GUI was developed using Taurus and LavuE. This paper outlines the BL31-FaXToR control system architecture, presents implementation examples, and discusses upcoming planned features.

IC@MS (Integrated Cloud Alarm Management Software) is a modular, web-based platform designed to unify and modernize alarm handling in scientific and industrial control environments. Initially developed for facilities using the Tango Controls framework, IC@MS provides seamless integration with PyAlarm, AlarmHandler, PyTangoArchiving, and TangoGraphQL to enable real-time monitoring, alarm grouping, historical analysis, and device interaction. Its backend, based on Flask and MongoDB, and frontend built with React, offer a responsive user interface for defining alarms, assigning severities, and configuring notifications via email or SMS. Through Dockerized deployment and REST/GraphQL APIs, IC@MS ensures flexibility, scalability, and extensibility across varied infrastructure landscapes. The software has been successfully deployed in particle accelerators and synchrotron light sources, supporting thousands of concurrent alarms and enabling data-driven decisions through structured alarm history and snapshot analysis. IC@MS represents a shift toward interoperable, cloud-ready alarm systems designed to meet the performance, reliability, and compliance needs of complex research facilities.

Modern control systems increasingly require intuitive and platform-independent tools to manage distributed infrastructures. We present Polka, a lightweight web-based management tool for TANGO Controls. Polka offers a user-friendly interface to administer multiple TANGO databases, device servers (Starters), branches, and pooling configurations including pooling Manager, Pooling Profiler, and Pool Threads Manager. Built with React and WebSocket-based communication, it delivers a responsive, real-time interface accessible from any browser. Unlike Astor, the long-established desktop-based TANGO Manager, Polka requires no client-side installation and supports platform-independent access for both administrators and operators. While Astor remains effective for quick diagnostics and device server control via its Java GUI, Polka offers a modernized approach to the same core functionalities, reintroducing multi-database support, Starter editing, and branch migration. It also brings refreshing tools for pooling configuration profiling with visualizations and delivers updated statistics dashboards. This paper will present Polka’s architecture, key features, and operational benefits in scientific infrastructures. The comparison with Astor highlights how Polka preserves core TANGO management capabilities while introducing scalable, web-based enhancements that address the needs of modern distributed control systems.

Pycumbia is a Python binding to the high-performance C++ cumbia framework, designed to simplify the development of control system applications without sacrificing responsiveness or scalability. It offers a user-friendly interface while maintaining the speed, concurrency, and low memory footprint of its C++ backend. By releasing Python’s GIL, pycumbia ensures that GUI applications and data workflows remain smooth and responsive even under heavy load, a key requirement in control system environments. From a user experience perspective, pycumbia significantly reduces the complexity typically associated with integrating control systems into custom applications. Developers can build advanced data visualization tools and synoptic panels with just a few lines of Python code, without dealing with polling logic, event dispatching, or thread management. Pycumbia also ships with PYI stubs for full IDE code completion. A key architectural advantage is its flexibility in deployment: pycumbia can run inside an isolated *miniconda* environment, allowing developers to use up-to-date Qt and Python packages independently of the operating system, or system-wide, provided the base OS supports a recent enough software stack. This enables modern Qt-based graphical applications to be developed and run consistently across platforms, bypassing limitations of outdated system packages. Pycumbia in real-world control system applications improves both the developer experience and application performance.