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batch-and-cli

batch-and-cli

Use hailtop.batch DAGs and packaged hailctl commands for Hail Batch, cloud configuration, authentication, cluster helpers, and file description workflows.

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Skill-Dokumentation

GitHub

name: batch-and-cli description: "Use hailtop.batch DAGs and packaged hailctl commands for Hail Batch, cloud configuration, authentication, cluster helpers, and file description workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

Batch and CLI

Use this sub-skill when the task mentions Hail Batch, hailtop.batch, Batch, LocalBackend, ServiceBackend, new_job, resource files, Docker/resource settings, hailctl batch, hailctl config, hailctl auth, hailctl dataproc, hailctl hdinsight, hailctl describe, billing projects, requester-pays, regions, or remote_tmpdir.

Route First

  • Read references/batch-workflows.md for Python hailtop.batch DAG construction, local/service backend choice, dependencies, input/output files, resource groups, Docker images, resource requests, and scatter/gather planning.
  • Read references/cloud-and-cli.md for packaged hailctl command families, Batch service configuration, auth, Dataproc, HDInsight, describe, and cloud side-effect boundaries.
  • Read references/troubleshooting.md for LocalBackend/Docker/tmp failures, ServiceBackend auth/billing/remote tmpdir errors, requester-pays access, command interpolation mistakes, and cloud skip conditions.
  • Run scripts/batch_local_smoke.py --help first; use scripts/batch_local_smoke.py --dry-run for a no-execution template or scripts/batch_local_smoke.py --run for a local-only smoke when hailtop.batch is importable.

Boundaries

  • For Hail query backend selection, hl.init, hl.init_batch, Spark/local setup, package import failures, or generated runtime asset issues, route to ../setup-and-backends/SKILL.md unless the task is specifically about hailtop.batch DAG execution.
  • For Table or MatrixTable analysis code, route to ../tables-and-expressions/SKILL.md or ../genomics-analysis/SKILL.md; use this sub-skill only to package those scripts as Batch jobs.
  • For sparse VariantDataset or GVCF combiner workflows, route data-processing logic to ../variant-datasets/SKILL.md; keep this sub-skill focused on orchestration.
  • Do not recommend private development, service-maintenance, or deployment commands as public user workflows. Prefer packaged hailctl commands visible in installed help.

Verified Entry Points

  • Python API: hailtop.batch.Batch, LocalBackend, ServiceBackend, Batch.new_job, Batch.new_python_job, Batch.read_input, Batch.read_input_group, Batch.write_output, Job.depends_on, BashJob.command, BashJob.declare_resource_group, BashJob.image, Job.cpu, Job.memory, Job.storage, and Job.regions.
  • Installed signatures include Batch(name=None, backend=None, attributes=None, requester_pays_project=None, default_image=None, default_memory=None, default_cpu=None, default_storage=None, default_regions=None, default_timeout=None, default_shell=None, default_python_image=None, default_spot=None, project=None, cancel_after_n_failures=None).
  • Installed signatures include LocalBackend(tmp_dir='/tmp/', gsa_key_file=None, extra_docker_run_flags=None) and ServiceBackend(*args, billing_project=None, bucket=None, remote_tmpdir=None, google_project=None, token=None, regions=None, gcs_requester_pays_configuration=None, gcs_bucket_allow_list=None).
  • Verified CLI help covers hailctl --help, hailctl auth --help, hailctl batch --help, hailctl config --help, hailctl dataproc --help, hailctl describe --help, hailctl hdinsight --help, and python -m hailtop.hailctl --help.

Safety Defaults

  • Start with LocalBackend for examples, smoke tests, and DAG debugging; it avoids Batch Service credentials and cloud billing.
  • Treat ServiceBackend, hailctl batch submit, hailctl batch init, hailctl dataproc start, hailctl dataproc stop, hailctl dataproc modify, hailctl hdinsight start, and hailctl hdinsight stop as cloud-mutating or billing-impacting.
  • Use placeholders for billing projects, buckets, tokens, and remote tmpdirs; do not store credentials in scripts, skills, prompts, or logs.
  • Close explicit backend objects after use with backend.close() or the async close pattern used by the surrounding application.
Gespeicherte Skills