"Run Kedro pipelines, choose runners, configure execution flags,
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill runners-and-execution --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Runners And Execution?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-runners-and-execution)More formats (shields.io, HTML) on the badges page.
---
name: runners-and-execution
description: "Run Kedro pipelines, choose runners, configure execution flags,
resume missing outputs, load versions, and troubleshoot runner failures."
disable-model-invocation: true
metadata:
disco-role: operating
license: Apache 2.0
---
# Runners and Execution
Use this sub-skill when a task is about executing Kedro pipelines with `kedro run`, `KedroSession.run()`, `AbstractRunner`, `SequentialRunner`, `ThreadRunner`, `ParallelRunner`, async load/save, run slicing, load versions, or missing-output resume behavior.
## Route Here
- Choose between `SequentialRunner`, `ThreadRunner`, `ParallelRunner`, or a custom `AbstractRunner` subclass.
- Build a `kedro run` command with `--runner`, `--async`, `--tags`, `--nodes`, `--from-nodes`, `--to-nodes`, `--from-inputs`, `--to-outputs`, `--load-versions`, `--pipelines`, `--namespaces`, `--params`, `--config`, `--conf-source`, or `--only-missing-outputs`.
- Use `KedroSession.run()` programmatically after a project has already been bootstrapped or opened through a session.
- Diagnose execution-time failures from missing inputs, empty slices, wrong runner instances, multiprocessing serialization, async I/O, resume suggestions, hook behavior, or persistent-output skipping.
## Route Elsewhere
- Pipeline graph construction, `node()`, `Pipeline`, `pipeline()`, tags, namespaces, and slice semantics before execution: read [`../pipelines-and-nodes/SKILL.md`](../pipelines-and-nodes/SKILL.md).
- `DataCatalog`, catalog YAML, credentials, dataset versioning, `OmegaConfigLoader`, and dataset optional dependencies: read [`../data-catalog-and-config/SKILL.md`](../data-catalog-and-config/SKILL.md).
- Project creation, project detection, `kedro new`, `KedroSession.create()`, `bootstrap_project()`, and CLI command availability: read [`../project-cli-and-sessions/SKILL.md`](../project-cli-and-sessions/SKILL.md).
- Hook implementation, plugin hooks, custom CLI commands, custom datasets, and custom runner design beyond selection/use: read [`../hooks-and-extensions/SKILL.md`](../hooks-and-extensions/SKILL.md).
- Package-wide installation, optional extras, and root routing: read [`../../SKILL.md`](../../SKILL.md).
## Current Facts
- Kedro version target: `1.4.0`; distribution and import name: `kedro`; Python requirement: `>=3.10`.
- Runner constructors: `SequentialRunner(is_async=False)`, `ThreadRunner(max_workers=None, is_async=False)`, and `ParallelRunner(max_workers=None, is_async=False)`.
- `KedroSession.run()` accepts `pipeline_name=None`, `pipeline_names=None`, `tags=None`, `runner=None`, `node_names=None`, `from_nodes=None`, `to_nodes=None`, `from_inputs=None`, `to_outputs=None`, `load_versions=None`, `namespaces=None`, and `only_missing_outputs=False`.
- `kedro run` defaults to `SequentialRunner` and supports the execution flags documented in [`references/run-options.md`](references/run-options.md).
- `ParallelRunner` uses multiprocessing, requires serializable nodes/datasets, uses `SharedMemoryDataCatalog` through the CLI/session path, and does not execute node/dataset hooks in worker processes.
- `ThreadRunner` uses threads, does not support async load/save, and is the recommended concurrent runner for Spark-style workflows sharing one Spark session.
## Reference Map
- Read [`references/run-options.md`](references/run-options.md) to construct safe CLI and `KedroSession.run()` calls, including slicing, load versions, runtime params, config files, and only-missing-output runs.
- Read [`references/runner-selection.md`](references/runner-selection.md) to choose a runner, configure `max_workers`, use `KEDRO_MP_CONTEXT`, handle async I/O, and understand programmatic output objects.
- Read [`references/troubleshooting.md`](references/troubleshooting.md) when a run fails, skips unexpected nodes, cannot find inputs, cannot serialize for multiprocessing, ignores hooks, or rejects CLI/session arguments.
## Fast Patterns
- Safe default run: `KEDRO_DISABLE_TELEMETRY=1 kedro run`.
- Explicit concurrent run for thread-safe work: `KEDRO_DISABLE_TELEMETRY=1 kedro run --runner=ThreadRunner`.
- Multiprocessing run when nodes and datasets are serializable: `KEDRO_DISABLE_TELEMETRY=1 KEDRO_MP_CONTEXT=spawn kedro run --runner=ParallelRunner`.
- Resume only missing persistent outputs: `KEDRO_DISABLE_TELEMETRY=1 kedro run --only-missing-outputs`.
- Load a versioned input: `KEDRO_DISABLE_TELEMETRY=1 kedro run --load-versions=raw_data:2024-01-01T00.00.00.000Z`.
- Programmatic run: create a new `KedroSession` for each successful run, pass a runner instance such as `SequentialRunner()`, and load returned output datasets from the catalog or dataset objects.
## Safety Notes
- `kedro run` executes user pipeline code and can read/write configured datasets; do not treat it as a dry-run command.
- For automation or privacy-sensitive checks, set `KEDRO_DISABLE_TELEMETRY=1` or `DO_NOT_TRACK=1` before CLI probes or runs.
- `--conf-source` may point at local or remote configuration; confirm trust and credentials handling before using remote configuration sources.
- `--params` values may override runtime parameters used by nodes; avoid echoing secrets and route parameter/config validation to [`../data-catalog-and-config/SKILL.md`](../data-catalog-and-config/SKILL.md).
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!