This code below gets us the messages count for every 30 days from the time period of message sent.
This code gets us:(In-detail)
1.Amazon first mail to my mail with a particular phase(here first order).
2.Convert that epoch format into time date and using timedelta And getting count of mails sent in the interval of 30 days.
The output for this code will be like this:
Amazon first order:
1534476682000
Amazon total orders between 2018-08-01 and 2018-09-01: 20
Amazon total orders between 2018-09-01 and 2018-10-01: 11
Amazon total orders between 2018-10-01 and 2018-11-01: 15
Amazon total orders between 2018-11-01 and 2018-12-01: 7
Amazon total orders between 2018-12-01 and 2019-01-01: 19
Amazon total orders between 2019-01-01 and 2019-02-01: 23
Amazon total orders between 2019-02-01 and 2019-03-01: 12
Code:
#amazonfirstorder
from googleapiclient.discovery import build
from httplib2 import Http
from oauth2client import file, client, tools
from dateutil.relativedelta import relativedelta
from datetime import datetime
SCOPES = 'https://www.googleapis.com/auth/gmail.readonly'
def main():
store = file.Storage('token.json')
creds = store.get()
if not creds or creds.invalid:
flow = client.flow_from_clientsecrets('credentials.json', SCOPES)
creds = tools.run_flow(flow, store)
service = build('gmail', 'v1', http=creds.authorize(Http()))
results = service.users().messages().list(userId='me', q='from:[email protected] subject:(your amazon.in order of )',labelIds = ['INBOX']).execute()
messages = results.get('messages', [])
print('\nFilpkart first order:')
if not messages:
print (" ")
else:
print (" ")
msg = service.users().messages().get(userId='me', id=messages[-1]['id']).execute()
#print(msg['snippet'])
a=(msg['internalDate'])
ts = int(a)
ts /= 1000
year=int(datetime.utcfromtimestamp(ts).strftime('%Y'))
month=int(datetime.utcfromtimestamp(ts).strftime('%m'))
#print(year)
#print(month)
print(msg['internalDate'])
log_results = []
start_date = datetime(year,month,1)
#start_date = datetime(2016,1,1)
end_date = datetime.today()
increment = relativedelta(months=1)
target_date = start_date + increment
while target_date <= end_date:
timestamp_after = int(start_date.timestamp()) # timestamp of start day
timestamp_before = int(target_date.timestamp()) # timestamp of start day + 30 days
query = f'from:([email protected]) subject:(your amazon.in order of ) after:{timestamp_after} before:{timestamp_before}'
results = service.users().messages().list(userId='me', q=query, labelIds=['INBOX']).execute()
messages = results.get('messages', [])
orders = len(messages)
start_date_str = start_date.strftime('%Y-%m-%d')
target_date_str = target_date.strftime('%Y-%m-%d')
print(f"\nFlipkart total orders between {start_date.strftime('%Y-%m-%d')} and {target_date.strftime('%Y-%m-%d')}: {orders}")
log_results.append(dict(start=start_date_str, end=target_date_str, orders=orders))
# update interval
start_date += increment
target_date += increment
return log_results
if __name__ == '__main__':
log_results = main()
Now i have two problems :
First
How to save the output of that code into csv file.
Second:
The above code gets us 30 days mails count,What i need is i need the count of mails i received before 12.00 PM in month-wise and after 12 PM in month-wise and save them in csv.
OUTPUT i need for 2nd Problem :
Amazon total orders between 2018-09-01 and 2018-10-01 before 12:00 PM : 11
Amazon total orders between 2018-10-01 and 2018-11-01 before 12:00 PM : 15
Amazon total orders between 2018-11-01 and 2018-12-01 before 12:00 PM : 7
Amazon total orders between 2018-12-01 and 2019-01-01 before 12:00 PM : 19
Amazon total orders between 2018-09-01 and 2018-10-01 after 12:00 PM : 3
Amazon total orders between 2018-10-01 and 2018-11-01 after 12:00 PM : 6
Amazon total orders between 2018-11-01 and 2018-12-01 after 12:00 PM : 88
Amazon total orders between 2018-12-01 and 2019-01-01 after 12:00 PM : 26
Similar to what already proposed, but in this case you would calculate the increment as exactly one month instead of 30 days (see the use of relativedelta instead of timedelta):
from googleapiclient.discovery import build
from httplib2 import Http
from oauth2client import file, client, tools
from dateutil.relativedelta import relativedelta
from datetime import datetime
SCOPES = 'https://www.googleapis.com/auth/gmail.readonly'
def main():
store = file.Storage('token.json')
creds = store.get()
if not creds or creds.invalid:
flow = client.flow_from_clientsecrets('credentials.json', SCOPES)
creds = tools.run_flow(flow, store)
service = build('gmail', 'v1', http=creds.authorize(Http()))
log_results = []
start_date = datetime(2016, 1, 1)
end_date = datetime.today()
increment = relativedelta(months=1)
target_date = start_date + increment
while target_date <= end_date:
timestamp_after = int(start_date.timestamp()) # timestamp of start day
timestamp_before = int(target_date.timestamp()) # timestamp of start day + 30 days
query = f'from:([email protected]) subject:(your amazon.in order of ) after:{timestamp_after} before:{timestamp_before}'
results = service.users().messages().list(userId='me', q=query, labelIds=['INBOX']).execute()
messages = results.get('messages', [])
orders = len(messages)
start_date_str = start_date.strftime('%Y-%m-%d')
target_date_str = target_date.strftime('%Y-%m-%d')
print(f"\nAmazon total orders between {start_date.strftime('%Y-%m-%d')} and {target_date.strftime('%Y-%m-%d')}: {orders}")
log_results.append(dict(start=start_date_str, end=target_date_str, orders=orders))
# update interval
start_date += increment
target_date += increment
return log_results
if __name__ == '__main__':
log_results = main()
# Write to csv
import pandas as pd
df = pd.DataFrame(log_results)
df.to_csv('orders.csv')