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        "author": "Soo Lee",
        "author_email": "duplexa@gmail.com",
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        "classifiers": [
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            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Bio-Informatics",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "The repo contains a benchmarking script for some of the CWL workflows used by 4DN-DCIC (https://github.com/4dn-dcic/pipelines-cwl), that returns total space, mem and CPUs required per given input size and a recommended AWS EC2 instance type.\n\n[![Build Status](https://travis-ci.org/SooLee/Benchmark.svg?branch=master)](https://travis-ci.org/SooLee/Benchmark)\n\n### Example usage of benchmarking script\n* importing the module\n```python\nfrom Benchmark import run as B\n```\n\n* md5\n```python\napp_name = 'md5'\ninput_json = {'input_size_in_bytes': {'input_file': 20000}}\nB.benchmark(app_name, input_json)\n```\n```\n{'aws': {'recommended_instance_type': 't2.xlarge', 'EBS_optimized': False, 'cost_in_usd': 0.188, 'EBS_optimization_surcharge': None, 'mem_in_gb': 16.0, 'cpu': 4}, 'total_size_in_GB': 14.855186462402344, 'total_mem_in_MB': 13142.84375, 'min_CPU': 4}\n```\n\n* fastqc-0-11-4-1\n```python\napp_name = 'fastqc-0-11-4-1'\ninput_json = {'input_size_in_bytes': {'input_fastq':20000},\n              'parameters': {'threads': 2}}\nB.benchmark(app_name, input_json)\n```\n```\n{'recommended_instance_type': 't2.nano', 'EBS_optimized': False, 'cost_in_usd': 0.006, 'EBS_optimization_surcharge': None, 'mem_in_gb': 0.5, 'cpu': 1}\n```\n\n* bwa-mem\n```python\napp_name = 'bwa-mem'\ninput_json = {'input_size_in_bytes': {'fastq1':93520000,\n                                      'fastq2':97604000,\n                                      'bwa_index':3364568000},\n              'parameters': {'nThreads': 4}}\nB.benchmark(app_name, input_json)\n```\n```\n{'aws': {'cost_in_usd': 0.188, 'EBS_optimization_surcharge': None, 'EBS_optimized': False, 'cpu': 4, 'mem_in_gb': 16.0, 'recommended_instance_type': 't2.xlarge'}, 'total_mem_in_MB': 12834.808349609375, 'total_size_in_GB': 15.502477258443832, 'min_CPU': 4}\n```\n\nTo use Benchmark in from other places, install it as below.\n```\npip install Benchmark-4dn\n```\nor\n```\npip install git+git://github.com/SooLee/Benchmark.git\n```\n\n\n---\n\nNote: From `0.5.3` we have a new function that takes in cpu and memory and returns a sorted list of instance dictionaries.\n```\nget_instance_types(cpu=1, mem_in_gb=0.5, instances=instance_list(), top=10, rank='cost_in_usd')\n```\n\nKeys in each instance dictionary:\n```\n'cost_in_usd', 'mem_in_gb', 'cpu', 'instance_type', 'EBS_optimized', 'EBS_optimization_surcharge'\n```\n\n\n",
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        "keywords": "benchmark,cwl,common workflow language,docker,tibanna,bioinformatics,4dn",
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        "summary": "Benchmark functions that returns total space, mem, cpu given                 input size and parameters for the CWL workflows",
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