Batch processing patterns
Run Biotite over many sequence or structure files — a timestamped run folder, xargs parallelism, per-file JSON outputs, retries that skip finished files.
Batch processing lets you run Biotite over many sequence or structure files in one reproducible run. A clean run layout, per-file outputs, and frequent checkpointing are what most affect whether a large batch finishes cleanly and stays easy to audit.
Where this code runs
You cannot open a shell on the platform yourself. The scripts on this page are plain Biotite Python and shell: ask Ivy in chat to run them in the chat's code workspace, which ships Biotite, or run them on your own machine.
Recommended run layout
Use a unique run-<timestamp>/ for each submission to avoid overwriting
results.
Streaming batches
- Tune
-Pfor concurrency. - Keep per-file outputs to isolate failures.
Minimal sequence parser (example)
Checkpointing and retries
- Write partial outputs frequently; avoid holding results in memory.
- Keep a
logs/run.logwith start/end timestamps per file. - On retry, skip outputs that already exist unless a
--forceflag is passed.
Packaging outputs
Include a SUMMARY.json (counts, skipped files, errors) for downstream
auditing.
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