代码可在 Anaconda 上运行，但不能通过 cmd 在 Python 上运行

Question

我有运行超过 7000 列数据集的代码，大约有 250k 条记录

当我使用 Anaconda Spyder 时它工作正常

但现在我想根据任务计划运行此代码

因此我想在 cmd 命令提示符中执行代码作为

Python "c:\myfolder\predservice.py"

它不能作为任务计划工作

我通过在 cmd 中在 Python 上运行脚本来开始跟踪问题

我遇到了这个错误，这是我在运行 Spyder 时没有遇到的

我怎样才能避免这样的错误

我以为是内存的原因。 当我选择数据集的一个子集时它运行良好但是当我运行整个数据集时我收到此错误

>>> df =pd.concat([df.drop('PreviousDRGs', 1), pd.get_dummies(df['PreviousDRGs'] .str.split(",", expand=True), prefix
 = 'PreviousDRGs').max(level=0, axis=1).asty pe(np.int8)], axis=1)


 Traceback (most recent call last):   File "<stdin>", line 1, in
 <module>   File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\generic.py",
 line 11616, in stat_func return self._agg_by_level(name, axis=axis,
 level=level, skipna=skipna)   


 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\generic.py",
 line 10440, in _agg_by_level grouped = self.groupby(level=level,
 axis=axis, sort=False)   


 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\generic.py",
 line 7894, in groupby **kwargs   



 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\groupby\groupby.py",
 line 2522, in groupby return klass(obj, by, **kwds)   



 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\groupby\groupby.py",
 line 363, in __init__ obj._consolidate_inplace()   



 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\generic.py",
 line 5252, in _consolidate_inplace self._protect_consolidate(f)   



 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\generic.py",
 line 5241, in _protect_consolidate result = f()   




 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\generic.py",
 line 5250, in f self._data = self._data.consolidate()   



 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\internals\managers.py",
 line 932, in consolidate bm._consolidate_inplace()   





 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\internals\managers.py",
 line 937, in _consolidate_inplace self.blocks =
 tuple(_consolidate(self.blocks))   




 File
 "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\internals\managers.py",
 line 1913, in _consolidate list(group_blocks), dtype=dtype,
 _can_consolidate=_can_consolidate   



 File "C:\Users\decisionsupport\AppData\Local\Programs\Python\Python37-32\lib\site-packages\pandas\core\internals\blocks.py",
 line 3323, in _merge_blocks new_values = new_values[argsort]   
 numpy.core._exceptions.MemoryError: Unable to allocate array with
 shape (4524, 1 38299) and data type uint8
>>> 

Answer 1

看起来Anaconda可能正在使用64位python。 您的错误回溯表明您的任务计划程序正在使用32位python运行.py脚本。 要么

1. 用64位版本替换您的32位python
2. 或安装一个单独的64位python，并告诉Task Scheduler使用它来运行.py文件。

Answer 2

我认为您需要在调用脚本之前在 cmd 中激活您的 conda base

call <path>\anaconda\Scripts\activate base
<path>\anaconda\python.exe <path>\scriptname.py