A molecular modeling task often starts as a sequence of small actions: prepare a structure, adjust settings, run an operation, inspect the result, and repeat. The first time, this is manageable. The tenth time, manual repetition becomes a source of friction—and small differences between runs can make results harder to compare or reproduce.
SAMSON’s scripting and extension workflows offer two ways to reduce that friction: automate tasks with Python, or add capabilities through extensions. The useful first question is not “What can I automate?” but “Which part of my work do I repeat, and what would I want someone else to be able to understand or repeat later?”
Start with the recurring task
Look for a workflow that you perform more than once, especially one involving a consistent sequence of actions or a predictable analysis. Write down the sequence in plain language before turning it into a script. This helps separate the scientific choices you want to make from the routine steps that could be automated.
For example, note what information the workflow starts with, what decisions you make along the way, and what outcome you need to inspect. This is not a substitute for checking the scientific validity of a method. It is a way to make the workflow easier to follow and to identify where repeated manual work is happening.
Use Python when the task is a workflow
If your goal is automation inside SAMSON, the Scripting guide is the recommended starting point. It covers the integrated Python environment, package management, running scripts, and embedding scripts or apps in documents.
Embedding a script in a document can be useful when the document is part of the workflow itself. Instead of keeping the steps separate from the molecular work, you can package scripted work with the document and make the process easier to revisit or share. That can help reduce the “How did I get this result?” problem: the workflow is closer to the context in which it was used.
Automation does not mean every decision should be removed. A script can handle repeatable operations while a modeler still reviews inputs, checks outputs, and decides whether the result is appropriate. Keep those review points visible in your workflow, particularly when a result will inform later modeling or analysis.
Use extensions when you need capabilities
Sometimes the problem is not repeated execution of an existing workflow; it is that you need additional functionality. In that case, the relevant path is Extending SAMSON. It covers adding or removing extensions and introduces the SDK and extension distribution path for developers.
A practical distinction: choose scripting when you want SAMSON to carry out a repeatable sequence of work; explore extensions when you want to install or develop capabilities. The two paths can complement each other, but they address different needs. If you are unsure where to begin, follow the documentation’s recommended order: scripting first, then extending SAMSON if your goal calls for it.
Make the workflow useful to your future self
Before sharing or reusing an automated workflow, make its purpose clear. Record what it is intended to do, what inputs it expects, and which parts still require your judgment. Keep the workflow focused: a small, understandable automation is often easier to review than a large script that attempts to handle every possible case.
When your next step involves modeling or analysis, continue to Simulate and analyze. If you want to distribute scripted documents or work with others, see Share and collaborate.
For the complete overview and links to both learning paths, see Automate and extend.
Note: SAMSON and all SAMSON Extensions are free for non-commercial use. Get SAMSON.