Agent skill

orcaflex-batch-manager

Manage large-scale OrcaFlex batch processing with parallel execution, adaptive worker scaling, memory optimization, and progress tracking for efficient simulation campaigns.

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Forks 4

Install this agent skill to your Project

npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/engineering/marine-offshore/orcaflex/batch-manager

SKILL.md

Orcaflex Batch Manager

When to Use

  • Running large simulation campaigns (100+ cases)
  • Parallel processing of multiple OrcaFlex models
  • Sensitivity studies with many parameter combinations
  • Operability matrices covering many sea states
  • Multi-seed Monte Carlo simulations
  • Overnight batch processing with monitoring

Python API

Basic Batch Processing

python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path

def run_batch(input_dir: str, output_dir: str, max_workers: int = 20):
    """
    Run batch processing on OrcaFlex models.

    Args:
        input_dir: Directory containing model files

*See sub-skills for full details.*
### Adaptive Parallel Processing

```python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
import psutil

class AdaptiveBatchProcessor(BatchProcessor):
    """Batch processor with adaptive resource management."""

    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)

*See sub-skills for full details.*
### Chunk-Based Processing

```python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
import time

def process_in_chunks(
    input_dir: str,
    output_dir: str,
    chunk_size: int = 50,
    pause_seconds: int = 5

*See sub-skills for full details.*
### Progress Tracking and Checkpoints

```python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
import json
import time

class CheckpointBatchProcessor(BatchProcessor):
    """Batch processor with checkpoint save/restore."""

    def __init__(self, checkpoint_file: str = "batch_checkpoint.json", **kwargs):

*See sub-skills for full details.*
### File Size Optimization

```python
from pathlib import Path
import os

def sort_by_file_size(files: list, reverse: bool = True) -> list:
    """
    Sort files by size for optimal processing order.

    Processing large files first with fewer workers,
    then small files with more workers.

*See sub-skills for full details.*
### Performance Metrics

```python
from dataclasses import dataclass, field
from typing import Dict, List
import time
import json

@dataclass
class BatchMetrics:
    """Track batch processing performance metrics."""


*See sub-skills for full details.*

## Related Skills

- [orcaflex-modeling](../orcaflex-modeling/SKILL.md) - Run OrcaFlex simulations
- [orcaflex-operability](../orcaflex-operability/SKILL.md) - Multi-sea-state campaigns
- [orcaflex-post-processing](../orcaflex-post-processing/SKILL.md) - Extract results
- [orcaflex-results-comparison](../orcaflex-results-comparison/SKILL.md) - Compare results

## References

- Python concurrent.futures documentation
- psutil system monitoring
- Source: `src/digitalmodel/modules/orcaflex/universal/batch_processor.py`
- Source: `src/digitalmodel/modules/orcaflex/orcaflex_parallel_analysis.py`

## Sub-Skills

- [Basic Batch Configuration (+1)](basic-batch-configuration/SKILL.md)
- [Resource Management (+2)](resource-management/SKILL.md)

## Sub-Skills

- [Error Handling](error-handling/SKILL.md)

## Sub-Skills

- [Version Metadata](version-metadata/SKILL.md)
- [[1.0.0] - 2026-01-17](100-2026-01-17/SKILL.md)
- [Parallel Execution (+1)](parallel-execution/SKILL.md)
- [Batch Results JSON (+1)](batch-results-json/SKILL.md)

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