Path A - Module 52: Framework Reliability & SMonitor#
Biological software is complex. When a calculation fails, you don’t just want to see a “ValueError”; you want to know which atom caused it and why.
MolSysMT uses the SMonitor framework to provide high-level diagnostics and traceability. In this module, you will learn to read the framework’s mind when things go wrong.
import molsysmt as msm
from molsysmt import systems
1. Triggering an Intelligent Error#
Let’s try to perform an operation that we know will fail. For example, trying to calculate the Radius of Gyration of an object that is not a molecular system.
try:
msm.structure.get_radius_of_gyration("Not a system")
except Exception as e:
# MolSysMT errors are informative
print(f"Caught an error: {type(e).__name__}")
print(f"Message: {e}")
2. The SMonitor Signals#
SMonitor records “Breadcrumbs” (migas de pan) of every step MolSysMT takes. If a conversion fails in a list of 10 items, SMonitor can tell you exactly which item was the problem.
# You can inspect the last signals if you are in a debug environment
from smonitor import get_last_signal
sig = get_last_signal()
if sig:
print(f"Last recorded signal tag: {sig.tags}")
3. Traceability of Attributes#
If you ask for atom_name and MolSysMT fails, it will tell you: “I tried to get it from the PDB file, then from the dictionary, and both failed because…”.
4. Reporting a Bug#
If you find a persistent error, MolSysMT provides tools to export the state of the framework so developers can reproduce it.
🏆 Path A Challenge: The Detective#
Intentionally break a
msm.convert()call by passing a wrongto_formname.Read the error message carefully. Does it suggest the correct form names?
Try to use
msm.where_is_attribute()on a system that is missing coordinates. Observe how MolSysMT reports the absence.
Reliability is what separates a script from a professional pipeline. In Module 53, we will learn about the Capability Matrix to know exactly what every file format can and cannot do.