Python argparse-如何使用kwargs或argv传递给方法

我一直在寻找将

**kwargs

或

*argv

与

argparse

一起使用的方法。我将从硬代码到动态代码

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

这是我的硬代码和一个我将如何使用它的示例

def get_parser():
    parser = argparse.ArgumentParser()
    parser.add_argument("-r",
                        "--range",
                        dest="r",
                        nargs=8,
                        help="AddRange Parameters")
    parser.add_argument("-p",
                        "--parameters",
                        dest="p",
                        nargs=8,
                        help="SetDefaults as Parameters")
    parser.add_argument("-r",
                    "--range",
                    dest="r",
                    nargs=8,
                    help="AddRange Parameters")
    return parser

"""Create a Template for a Job"""
def create_Template(temp3_,temp_tournsize,temp_popsize,temp0_,temp1_,temp_ngen,temp_run,tmpverb):
    #single GA job
    logging.basicConfig(level=logging.DEBUG)
    template = job.JobTemplate(runGASimple)
    print tmpverb
    template.setDefaults(temp3=temp3_, tournsize=temp_tournsize, popSize=temp_popsize, temp0=temp0_, temp1=temp1_, ngen=temp_ngen, number_of_runs=temp_run, verbose=tmpverb)
    return template

"""Run a simple Job"""
def ajob_run(template):
    ajob = job.Job(template)
    ajob.run()
    pass

    """change Default params with AddRange"""
def add_Range(var_temp0,var_start,var_end,var_stepSize,var_temp1,var_start2,var_end2,var_stepSize2,tmp_template):
    jobCreator = job.JobCreator()
    #jobCreator.addRange('temp0', start=0.0, end=1.0, stepSize=0.1)
    jobCreator.addRange(var_temp0, start= var_start, end=var_end, stepSize=var_stepSize)
    #jobCreator.addRange('temp1', start=0.0, end=1.0, stepSize=0.1)
    jobCreator.addRange(var_temp1, start=var_start2, end=var_end2, stepSize=var_stepSize2)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)

    return jobs

"""Create a Batchjob from Jobs"""
def batch_Job(tmp_jobs):
    batchJob = job.BatchJob(tmp_jobs, 5)

    return batchJob


if (__name__ == "__main__"):

    args = get_parser().parse_args()
    if (args.p and args.r):
        print 'AddRange with Parameters Input Start:'
        temp = create_Template(float(args.p[0]),int(args.p[1]),int(args.p[2]),float(args.p[3]),float(args.p[4]),int(args.p[5]),int(args.p[6]),ast.literal_eval(args.p[7]))
        tmpjobs = add_Range(args.r[0],float(args.r[1]),float(args.r[2]),float(args.r[3]),args.r[4],float(args.r[5]),float(args.r[6]),float(args.r[7]),temp)
        results = batch_Job(tmpjobs)


        print 'AddRange with Parameters Input Ende.'
    elif (args.p):
            print 'Parameters Input Start:'
        ajob_run(create_Template(
        float(args.p[0]),
        int(args.p[1]),
        int(args.p[2]),
        float(args.p[3]),
        float(args.p[4]),
        int(args.p[5]),
        int(args.p[6]),
        ast.literal_eval(args.p[7])))
        print 'Parameters Input Ende.'

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

然后是一个很长的输出，带有一个框架的结果

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

我的方法预料到了这一点。变量名将来可以更改

template.setDefaults(mux=0.8, tournsize=20, rangeSize=20, temp0=0.5, temp1=0.5, ngen=20, number_of_runs=1, verbose=False)

jobCreator.addRange('temp0', start=0.0, end=1.0, tournStep=0.1)

jobCreator.addRange('temp1', start=0.0, end=1.0, turns=4)

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

将按如下方式进行更改：

setDefaults(**kwargs)

addRange(paraName,**kwargs)

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

我期望：

CLI.py -p temp0=1 temp1=0.4 ....temp6=8 ... -r temp0 start=0 end=1 tournStep=0.1
or
CLI.py -p hn0=1 bn1=0.4 ....tp6=8 ... -r temp1 start=0 end=1 turns=4

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

然后将带有输入的变量名称转换为：

setDefaults()

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

及

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

但是我需要

argparse

，因为我将构建一个命令行界面

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

---

我忘记了其他方法的一些细节：

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

---

这是正确的方法吗？

在这里，

参数

参数将有一个8对的列表，例如：

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

CLI.py -p argname1=v1 ... argname8=v8

（显然，

argnameN

应该是所需函数的参数名）

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

然后，您可以轻松地将

args.p

（即

['argname1=v1'，…'argname8=v8']

）转换为字典：

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

def convert_value(v):
    try:
        return float(v) if '.' in v else int(v)
    except ValueError:
        # v is not a number
        return v

params = dict([convert_value(n) for n in pair.split('=')] for pair in args.p)

并将其传递给您的函数：

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

"""Create a Template for a Job"""
def create_Template(params):
    #single GA job
    logging.basicConfig(level=logging.DEBUG)
    template = job.JobTemplate(runGASimple)
    print tmpverb
    template.setDefaults(**params)
    return template

通过创建两个不同的范围参数，可以对范围参数执行相同的操作：

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

"""change Default params with AddRange"""
def add_Range(var_1, var_2, tmp_template):
    jobCreator = job.JobCreator()
    #jobCreator.addRange('temp0', start=0.0, end=1.0, stepSize=0.1)
    jobCreator.addRange(**var_1)
    #jobCreator.addRange('temp1', start=0.0, end=1.0, stepSize=0.1)
    jobCreator.addRange(**var_2)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)

---

请注意Gall的答案-它可能会大大简化您的代码。 关于动态“argparse”，请尝试以下方法：

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs

#!/usr/bin/env python

from __future__ import print_function
from __future__ import unicode_literals
import argparse


args_d = {
  '-r': {
    'flags': ['-r', '--range'],
    'nargs': 8,
    'help': 'AddRange Parameters',
    'dest': 'r'
  },
  '-p': {
    'flags': ['-p', '--parameters'],
    'nargs': 8,
    'help': 'SetDefaults as Parameters',
    'dest': 'p'
  }
}

def setup_parser(args_d):
    parser = argparse.ArgumentParser()

    for k,v in args_d.items():
        if 'flags' in v:
            flags = v['flags']
            del v['flags']
        parser.add_argument(*flags, **v)

    return parser

if __name__ == "__main__":

    args = setup_parser(args_d).parse_args()

    print(args)

---

您仍然需要动态生成字典。您可以尝试使用“inspect”模块来实现这一点……

看看

plac

插件（pypi源代码）。它可以从几个函数的参数签名创建一个解析器。非常感谢！！！我尝试了它，但我的程序有以下输出：AttributeError:'NoneType'对象没有属性'defaults'，我忘记了其他方法的一些细节：“使用AddSpecific”“更改默认参数”“def add_Specific（tmp_模板，paraName，*params）：jobCreator=job.jobCreator（）#jobCreator.AddSpecific（'temp0'，0.1,0.2,0.3,0.4，…，0.7，…）jobCreator.addRange（paraName，params）#所有其他参数将采用默认的jobs=jobCreator.generateJobs（tmp_模板）return jobs感谢大家的鼓励，我在两个月前开始编写python。

    """change Default params with AddSpecific"""
def add_Specific(tmp_template,paraName,*params):
    jobCreator = job.JobCreator()
    #jobCreator.addSpecific('temp0', 0.1,0.2,0.3,0.4,....,0.7,...)
    jobCreator.addRange(paraName, params)
    # all other params will take defaults
    jobs = jobCreator.generateJobs(tmp_template)
    return jobs