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With PCAN-Explorer 7, we have enhanced our professional Windows software for CAN, CAN FD, and CAN XL by adding a key feature for automated development and testing workflows: Python scripting. In addition to VBScript, this provides a modern scripting language that allows users to access the PCAN-Explorer 7 object model and automate repetitive tasks in CAN environments. For engineers, this means that PCAN-Explorer 7 is no longer merely a tool for the manual analysis of CAN communication; it becomes a scriptable platform for diagnostics, test automation, logging, reporting, and prototype testing procedures. This article presents the Python feature in detail, highlights practical examples, and explains how it might be further developed in the future.
From the perspective of our software developers, integrating Python is a logical step. For one thing, Python is well-established across many technical fields today – including test systems, automation, CI/CD environments, data analysis and communication, and automotive development. For another, the existing scripting technology, VBScript, is not a future-proof long-term solution; Microsoft has announced plans to phase it out. Consequently, Python provides PCAN-Explorer 7 with a future-oriented foundation for custom scripting and automation – directly within the program environment. Python was selected because the language offers clear syntax, high readability, and an extensive standard library. This is particularly relevant for PCAN-Explorer 7, as many automation tasks can be implemented via concise, easily maintainable scripts – ranging from loading a project and recording a trace to analyzing CAN data.
Image 1: Official Python Logo.
Python is an interpreted scripting language. Unlike traditional compiled languages, its code is not translated into an executable program beforehand but is executed directly. This offers a clear advantage for technical users: scripts can be quickly written, tested, modified, and re-run. At the same time, Python supports structured programming using variables, functions, loops, conditional statements, lists, dictionaries, and file operations. For PCAN-Explorer 7 users, this means that CAN communication can not only be monitored but processes can also be controlled in a targeted manner. Examples include opening projects, starting and stopping trace recordings, reading raw CAN data, processing signals, writing CSV or Excel files, and controlling visualizations via the Instruments Panel or the Plotter.
This feature is particularly suitable for engineers, test developers, application engineers, and power users who possess basic knowledge of CAN, CAN FD, or CAN XL, as well as a solid foundation in Python. While you do not need to be a software developer, you should understand variables, functions, loops, conditional statements, lists, dictionaries, and file operations. A basic understanding of the PCAN API structure is also helpful.
The primary advantage is automation. Recurring tasks can be executed consistently: loading a project, establishing a connection, starting a trace, sending specific messages, evaluating responses, and logging results. This reduces manual effort while making test procedures more comparable. A second advantage is extensibility. Python features an extensive standard library and – depending on the specific Python installation – can be extended with external modules for analysis, logging, or reporting. PCAN-Explorer 7 currently includes Python 3.13 (as of 2026). Additionally, a custom Python installation can be used, enabling the use of further modules and libraries. Third, Python improves the maintainability of technical automation processes. Compared to VBScript, Python offers better readability and a more extensive ecosystem of libraries.
Image 2: The PCAN-Explorer 7 interface with the Python window.
Common applications for Python scripting in PCAN-Explorer 7 include custom automation tasks related to CAN communication, analysis, and testing. These include checksum and CRC checks, signal visualization, logging to CSV or Excel files, simple restbus simulations, test automation, and diagnostic sequences. Additionally, system information such as time or date can be transmitted, simple high-layer protocols with handshake logic implemented, or state machines created – for instance, to flash custom devices or ECUs. Furthermore, Python can extend the use of existing features – such as the CAN Tracer and the Instrument Panel add-in – and tailor them more closely to project-specific requirements.
A classic use case is automated logging. A Python script can start a trace, run it for a defined period, and subsequently check whether specific CAN IDs, signals, or error patterns occurred. This is useful for endurance tests, commissioning, or regression testing. The benefit lies in reproducibility: every test run follows the same logic. Measurement data can be automatically named and saved for later comparison.
Image 3: Schematic example of automated logging via a Python script.
Another use case is signal-based analysis. In development projects, simply examining data bytes is often insufficient; physical signals – such as temperature, rotational speed, voltage, or status values – are crucial. CAN messages can be analyzed semantically using symbol or data descriptions, thereby transforming a manual visual inspection into an automated plausibility check. The value of such checks is particularly high for CAN FD and CAN XL, which feature larger data fields.
Image 4: Python example for signal-based analysis.
CSV logging and reporting are also among the common use cases. Python is ideally suited for writing measurement data to files in a structured format. This allows CAN data from PCAN-Explorer 7 to be prepared directly for analysis, test reports, or external tools. This is particularly useful when measurement results need to be documented or compared with other test runs, rather than simply viewed.
Image 5: CSV logging and reporting as a Python script.
PCAN-Explorer 7 not only allows users to create their own Python scripts, but also provides specific programming examples directly through the software help. The “Automating Tasks in PCAN-Explorer” section offers an overview of all available objects in the PCAN-Explorer object model (see figure).
Image 6: Overview of available objects that can be used via Python in PCAN-Explorer 7.
These examples demonstrate how to use scripts to interact with the software's functions – such as accessing projects, connections, messages, signals, or automation sequences. The examples are available for both VBScript and Python. This is supplemented by a complete reference of the available objects, including diagrams of the PCAN-Explorer object model as well as add-ins such as the Instruments Panel and Plotter. This overview is accessible in PE7 via the help section of the respective add-in being used, for example in the Instruments Panel under “Instruments Panel Object Model” and “Diagram of the Instruments Panel Object Model”.
Image 7: Overview of the object model in the PE7 add-in Instruments Panel.
Image 8: Overview of the object model in the PE7-Plotter add-in.
Python scripting makes PCAN-Explorer 7 better suited for modern development processes. Even today, manual CAN analyses can be converted into automated workflows. While specific enhancements are not yet available at this time, there are numerous ideas in the pipeline. Possible topics include the retrofitting of PCAN-Explorer events for Python – which are not yet available as they are in VBScript – as well as a debug functionality in a later version. The most important point, however, is already clear: Python expands PCAN-Explorer 7 from a powerful CAN analysis tool into a flexible automation platform for professional users.
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