Python 错误'；日期时间'；导入模块时未定义

python初学者，遇到日期时间错误。不知道为什么。任何帮助都将不胜感激

我在同一目录中有2个.py文件，model.py和func2.py。运行model.py时，我正在尝试导入func.py。我得到的错误是name错误：未定义名称“datetime”

model.py:

import numpy as np
import pandas as pd
import datetime
from xlsxwriter.utility import xl_rowcol_to_cell
import func2

def data_upload(xls):
    demand_df=pd.read_excel(xls,'Historical Demand',encoding = "ISO-8859-1",parse_dates=['Transaction Date'],converters={'Part Number':str})
    po_df=pd.read_excel(xls,'Historical PO',encoding = "ISO-8859-1",parse_dates=['Date Order Placed', 'Date Order Received'],converters={'Part Number':str, 'Unit Cost':float,'Total Spend':float})
    snapshot_df=pd.read_excel(xls,'Snapshot Summary',converters={'Part Number':str},)
    other_df=pd.read_excel(xls,'Other Data',converters={'Part Number':str})
    return demand_df, po_df, snapshot_df, snapshot_df, other_df

xls = pd.ExcelFile('/Users/Desktop/Input Raw Data Template.xlsx')

demand_df, po_df, snapshot_df, snapshot_df, other_df = data_upload(xls)

input_scope = 365
input_leadtime_max = 140

model_input_df = func2.scoping_analysis(demand_df,po_df,input_scope)

import numpy as np
import pandas as pd
import datetime

def scoping_analysis(demand_df,po_df,input_scope):
    demand_scope = []
    demand_timeframe = demand_df['Transaction Date']> demand_df['Transaction Date'].max() - datetime.timedelta(days=input_scope)
    demand_df = demand_df[demand_timeframe].groupby('Part Number').sum().astype(int)
    demand_df = demand_df[demand_df['Transaction Quantity']>0].sort_values('Transaction Quantity',ascending=False)
    demand_df.reset_index(inplace=True)
    demand_scope = demand_df['Part Number'].values

    po_scope = []
    po_timeframe = po_df['Date Order Placed']> po_df['Date Order Placed'].max() - datetime.timedelta(days=input_scope)  
    po_df = po_df[po_timeframe].groupby('Part Number').sum().astype(int)
    po_df = po_df[po_df['Total Spend']>0].sort_values('Total Spend',ascending=False)
    po_df.reset_index(inplace=True)
    po_scope = po_df['Part Number'].values

    inscope_items = list(set(demand_scope).intersection(po_scope))

    model_input_df = pd.DataFrame(data = inscope_items, columns=['Part Number'])

    return model_input_df

func2.py:

import numpy as np
import pandas as pd
import datetime
from xlsxwriter.utility import xl_rowcol_to_cell
import func2

def data_upload(xls):
    demand_df=pd.read_excel(xls,'Historical Demand',encoding = "ISO-8859-1",parse_dates=['Transaction Date'],converters={'Part Number':str})
    po_df=pd.read_excel(xls,'Historical PO',encoding = "ISO-8859-1",parse_dates=['Date Order Placed', 'Date Order Received'],converters={'Part Number':str, 'Unit Cost':float,'Total Spend':float})
    snapshot_df=pd.read_excel(xls,'Snapshot Summary',converters={'Part Number':str},)
    other_df=pd.read_excel(xls,'Other Data',converters={'Part Number':str})
    return demand_df, po_df, snapshot_df, snapshot_df, other_df

xls = pd.ExcelFile('/Users/Desktop/Input Raw Data Template.xlsx')

demand_df, po_df, snapshot_df, snapshot_df, other_df = data_upload(xls)

input_scope = 365
input_leadtime_max = 140

model_input_df = func2.scoping_analysis(demand_df,po_df,input_scope)

import numpy as np
import pandas as pd
import datetime

def scoping_analysis(demand_df,po_df,input_scope):
    demand_scope = []
    demand_timeframe = demand_df['Transaction Date']> demand_df['Transaction Date'].max() - datetime.timedelta(days=input_scope)
    demand_df = demand_df[demand_timeframe].groupby('Part Number').sum().astype(int)
    demand_df = demand_df[demand_df['Transaction Quantity']>0].sort_values('Transaction Quantity',ascending=False)
    demand_df.reset_index(inplace=True)
    demand_scope = demand_df['Part Number'].values

    po_scope = []
    po_timeframe = po_df['Date Order Placed']> po_df['Date Order Placed'].max() - datetime.timedelta(days=input_scope)  
    po_df = po_df[po_timeframe].groupby('Part Number').sum().astype(int)
    po_df = po_df[po_df['Total Spend']>0].sort_values('Total Spend',ascending=False)
    po_df.reset_index(inplace=True)
    po_scope = po_df['Part Number'].values

    inscope_items = list(set(demand_scope).intersection(po_scope))

    model_input_df = pd.DataFrame(data = inscope_items, columns=['Part Number'])

    return model_input_df

回溯：

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-38-3db20f4cbfba> in <module>()
----> 1 model_input_df = func2.scoping_analysis(demand_df,po_df,input_scope)
      2 


~/Desktop/Programming/Code/SPO/func2.py in scoping_analysis(demand_df, po_df, input_scope)
      1 import numpy as np
      2 import pandas as pd
----> 3 import datetime
      4 
      5 def scoping_analysis(demand_df,po_df,input_scope):

NameError: name 'datetime' is not defined

---------------------------------------------------------------------------
NameError回溯（最近一次呼叫上次）
在（）
---->1模型输入函数=函数2.范围分析（需求函数、采购函数、输入函数范围）
2.
范围分析中的~/Desktop/Programming/Code/SPO/func2.py（需求、采购、输入范围）
1作为np导入numpy
2进口熊猫作为pd
---->3导入日期时间
4.
5定义范围分析（需求定义、采购定义、输入范围）：
NameError:未定义名称“datetime”

你能在问题中包含完整的回溯吗？我想说，它是在read\u excel中提出的，因为“解析日期”。请包括stacktrace。@glibdud traceback addtry重新启动ipython内核

datetime

是标准库的一部分，因此我的第一个怀疑是，您过去曾在iPython中意外地隐藏了该名称。我不确定它是如何给出那个特定的错误的，但这些问题可以通过iPython以非直观的方式表现出来。@roganjosh重启内核就做到了。谢谢大家的意见