---

name: engines-configuration description: "Configure Modin engines, backends, resources, diagnostics, and backend switching." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Modin engines and configuration

Use this sub-skill when a task needs execution-engine selection, modin.config, resource limits, backend movement, logging, metrics, progress bars, range partitioning, or Ray/Dask startup troubleshooting.

Start here

1. Read references/engine-selection.md to distinguish Engine, StorageFormat, Backend, and per-object backend movement, and to choose Ray, Dask, Python, Native/Pandas, or optional Unidist/MPI.
2. Read references/configuration-reference.md for exact environment variables, modin.config API usage, CLI export, progress/logging/metrics controls, async reads, and range partitioning.
3. Read references/troubleshooting.md for Ray/Dask install/start failures, multiprocessing safe-main guard issues, MPI prerequisites, backend-switch errors, logging/progress/metrics problems, and range-partitioning surprises.
4. Run scripts/backend_smoke.py to test a tiny DataFrame operation under Ray, Dask, Python, or Native execution.
5. Run scripts/export_config_help.py to export the installed Modin config catalog to CSV without using a source checkout.

Routing boundaries

This sub-skill owns:

• Install extras for modin[ray], modin[dask], modin[all], and optional modin[mpi] with external MPI prerequisites.
• MODIN_ENGINE, MODIN_BACKEND, MODIN_STORAGE_FORMAT, MODIN_CPUS, MODIN_NPARTITIONS, MODIN_MEMORY, MODIN_PROGRESS_BAR, MODIN_RANGE_PARTITIONING, MODIN_ASYNC_READ_MODE, MODIN_LOG_MODE, MODIN_METRICS_MODE, MODIN_BACKEND_SWITCH_PROGRESS, MODIN_AUTO_SWITCH_BACKENDS, MODIN_DASK_THREADS_PER_WORKER, MODIN_NATIVE_MAX_ROWS, MODIN_NATIVE_MAX_XFER_ROWS, MODIN_NATIVE_DEEP_COPY, MODIN_BACKEND_MERGE_CAST_IN_PLACE, MODIN_BACKEND_JOIN_CONSIDER_ALL_BACKENDS, MODIN_RAY_INIT_CUSTOM_RESOURCES, and MODIN_RAY_TASK_CUSTOM_RESOURCES.
• python -m modin --versions, python -m modin.config, and python -m modin.config --export-path <csv>.
• DataFrame.set_backend, Series.set_backend, move_to, get_backend, and backend-transfer progress control.
• Logging (LogMode, LogMemoryInterval, LogFileSize), metrics, and Dask/Ray main-guard guidance.

Route ordinary DataFrame recipes to ../core-pandas-api/SKILL.md, reader/writer and conversion work to ../io-interoperability/SKILL.md, and experimental APIs to ../advanced-extensions/SKILL.md.

Default operating pattern

1. Choose global execution before importing modin.pandas or before the first Modin operation.
2. Prefer MODIN_BACKEND=<Ray|Dask|Pandas|Python_Test|Unidist> for a complete global backend alias. Use MODIN_ENGINE only when you understand the storage-format pairing.
3. For native local pandas execution, set MODIN_BACKEND=Pandas rather than trying to force MODIN_ENGINE=Native alone.
4. Set MODIN_CPUS, MODIN_NPARTITIONS, and MODIN_MEMORY before the engine starts.
5. In .py files that run Ray or Dask work, put executable Modin work under if __name__ == "__main__":.
6. Use df.set_backend(...) / df.move_to(...) for one object only; it does not change the global default backend and may materialize large data locally.
7. Verify with the bundled smoke script and the config-export helper before diagnosing higher-level pandas or I/O behavior.