从所有具有特定主题行的 Outlook 电子邮件中提取可变数据，然后从正文中获取日期

Question

我每天都会收到一封电子邮件，其中包含当天销售的水果数量。虽然我现在想出了一些代码来记录相关数据向前发展，但我无法向后做。

数据像这样存储在电子邮件正文中：

Date of report:,01-Jan-2020
Apples,8
Pears,5
Lemons,7
Oranges,9
Tomatoes,6
Melons,3
Bananas,0
Grapes,4
Grapefruit,8
Cucumber,2
Satsuma,1

我想让代码做的是首先搜索我的电子邮件并找到与特定主题匹配的电子邮件，逐行迭代并找到我正在搜索的变量，然后将它们登录在日期列中记录“报告日期”并转换为以下格式的数据框：“%m-%d-%Y”。

我想我可以通过对我编写的代码进行一些修改来实现这一点，以便跟踪它的进展：

# change for the fruit you're looking for
Fruit_1 = "Apples"
Fruit_2 = "Pears"

outlook = win32com.client.Dispatch("Outlook.Application").GetNamespace("MAPI")
inbox = outlook.GetDefaultFolder(6) 
messages = inbox.Items
messages.Sort("[ReceivedTime]", True)

# find data email
for message in messages:
    if message.subject == 'FRUIT QUANTITIES':
        if Fruit_1 and Fruit_2 in message.body: 
            data = str(message.body)
            break
        else:
            print('No data for', Fruit_1, 'or', Fruit_2, 'was found')
            break

fruitd = open("fruitd.txt", "w") # copy the contents of the latest email into a .txt file
fruitd.write(data)
fruitd.close()

def get_vals(filename: str, searches: list) -> dict:
    #Searches file for search terms and returns the values
    dct = {}
    with open(filename) as file:
        for line in file:
            term, *value = line.strip().split(',')
            if term in searches:
                dct[term] = float(value[0]) # Unpack value 
    # if terms are not found update the dictionary w remaining and set value to None
    if len(dct.keys()) != len(searches):
        dct.update({x: None for x in search_terms if x not in dct})
    return dct


searchf = [
    Fruit_1, 
    Fruit_2
] # the list of search terms the function searches for

result = get_vals("fruitd.txt", searchf) # search for terms 
print(result)

# create new dataframe with the values from the dictionary
d = {**{'date':today}, **result}
fruit_vals = pd.DataFrame([d]).rename(columns=lambda z: z.upper())
fruit_vals['DATE'] = pd.to_datetime(fruit_vals['DATE'], format='%d-%m-%Y')
print(fruit_vals)

我正在创建一个名为 'fruitd' 的 .txt，因为我不确定如何以任何其他方式遍历电子邮件正文。不幸的是，我认为为过去的每封电子邮件创建一个 .txt 并不是真正可行的，我想知道是否有更好的方法？

非常欢迎任何建议或指示。

**EDIT 理想情况下希望获得搜索列表中的所有变量；所以 Fruit_1 & Fruit_2 有空间将其扩展为 Fruit_3 + Fruit_4 （等），如有必要。

Answer 1

#PREP THE STUFF
Fruit_1 = "Apples"
Fruit_2 = "Pears"
SEARCHF = [
    Fruit_1, 
    Fruit_2
]

#DEF THE STUFF
# modified to take a list of list of strs as `report` arg
# apparently IDK how to type-hint; type-hinting removed
def get_report_vals(report, searches):
    dct = {}
    for line in report:
        term, *value = line
        # `str.casefold` is similar to `str.lower`, arguably better form
        # if there might ever be a possibility of dealing with non-Latin chars
        if term.casefold().startswith('date'):
            #FIXED (now takes `date` str out of list)
            dct['date'] = pd.to_datetime(value[0])
        elif term in searches:
            dct[term] = float(value[0])
    if len(dct.keys()) != len(searches):
        # corrected (?) `search_terms` to `searches`
        dct.update({x: None for x in searches if x not in dct})
    return dct


#DO THE STUFF
outlook = win32com.client.Dispatch("Outlook.Application").GetNamespace("MAPI")
inbox = outlook.GetDefaultFolder(6) 
messages = inbox.Items
messages.Sort("[ReceivedTime]", True)

results = []

for message in messages:
    if message.subject == 'FRUIT QUANTITIES':
        # are you looking for:
        #  Fruit_1 /and/ Fruit_2
        # or:
        #  Fruit_1 /or/  Fruit_2
        if Fruit_1 in message.body and Fruit_2 in message.body:
            # FIXED
            data = [line.strip().split(",") for line in message.body.split('\n')]
            results.append(get_report_vals(data, SEARCHF))
        else:
            pass

fruit_vals = pd.DataFrame(results)
fruit_vals.columns = map(str.upper, fruit_vals.columns)

从所有具有特定主题行的 Outlook 电子邮件中提取可变数据，然后从正文中获取日期

Pull variable data from all outlook emails that have a particular subject line then take date from the body

python

outlook

numpy

pandas