尝试缓存结果时 Joblib UserWarning

我得到以下内容UserWarning当尝试使用 joblib 缓存结果时：

import numpy
from tempfile import mkdtemp
cachedir = mkdtemp()
from joblib import Memory
memory = Memory(cachedir=cachedir, verbose=0)

@memory.cache
def get_nc_var3d(path_nc, var, year):
    """
    Get value from netcdf for variable var for year
    :param path_nc:
    :param var:
    :param year:
    :return:
    """
    try:
        hndl_nc = open_or_die(path_nc)
        val = hndl_nc.variables[var][int(year), :, :]
    except:
        val = numpy.nan
        logger.info('Error in getting var ' + var + ' for year ' + str(year) + ' from netcdf ')
    
    hndl_nc.close()
    return val

使用参数调用此函数时收到以下警告：

UserWarning: Persisting input arguments took 0.58s to run.
If this happens often in your code, it can cause performance problems 
(results will be correct in all cases). 
The reason for this is probably some large input arguments for a wrapped function (e.g. large strings).
THIS IS A JOBLIB ISSUE. If you can, kindly provide the joblib's team with an example so that they can fix the problem.

输入参数：C:/Users/rit/Documents/PhD/Projects/\GLA/Input/LUWH/\LUWLAN_v1.0h\transit_model.nc range_to_large 1150

我如何摆脱警告？既然输入参数不太长，为什么会发生这种情况？

对于“为什么这不起作用？”我没有答案。问题的一部分。但是，要简单地忽略警告，您可以使用warnings.catch_warnings with warnings.simplefilter正如所见here https://docs.python.org/3/library/warnings.html#temporarily-suppressing-warnings.

import warnings

with warnings.catch_warnings():
  warnings.simplefilter("ignore")
  your_code()

显然，我不建议忽略警告，除非你确定它无害，但如果你打算这样做，这种方式只会抑制上下文管理器内的警告，并且直接来自 python 文档