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Command Line Interface¤

Command-line tools for running and benchmarking Datarax pipelines without writing Python code.

Commands¤

Command Purpose Example
datarax run Execute pipeline datarax run config.yaml
datarax benchmark Measure performance datarax benchmark pipeline.yaml

★ Insight ─────────────────────────────────────

  • CLI is useful for quick experiments and CI/CD
  • Config files define pipelines declaratively
  • Benchmark command includes warmup automatically
  • Use Python API for complex workflows

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Quick Start¤

# Run a pipeline from config
datarax run config.yaml

# Benchmark pipeline performance
datarax benchmark config.yaml --batches 100

# Get help
datarax --help

Modules¤

  • main - Main CLI entry point and commands
  • benchmark - CLI benchmark tool for performance testing

Config File Format¤

# config.yaml
source:
  type: hf
  name: mnist
  split: train

pipeline:
  batch_size: 32
  transforms:
    - type: normalize
    - type: augment
      probability: 0.5

output:
  format: tfrecord
  path: ./output

Benchmark Output¤

$ datarax benchmark config.yaml --batches 100

Pipeline Benchmark Results
==========================
Warmup batches: 10
Measured batches: 100

Throughput: 1234.56 samples/sec
Latency (mean): 25.6 ms
Latency (p99): 32.1 ms

See Also¤