I'm writing a Python script. I need to return lines that contain latest 'timestamp': field from a text file. For example, in the below text file example:
{'uid': 3167, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 10, 18, 7, 13), 'status': 1, 'punch': 1}, {'uid': 3168, 'user_id': '198', 'timestamp': datetime.datetime(2021, 3, 10, 18, 10, 42), 'status': 2, 'punch': 1}, {'uid': 3169, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 10, 18, 13, 53), 'status': 1, 'punch': 1}, {'uid': 3170, 'user_id': '13', 'timestamp': datetime.datetime(2021, 3, 10, 18, 22, 2), 'status': 1, 'punch': 1}, {'uid': 3171, 'user_id': '9', 'timestamp': datetime.datetime(2021, 3, 10, 18, 22, 43), 'status': 1, 'punch': 1}, {'uid': 3172, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 10, 18, 32, 30), 'status': 2, 'punch': 1}, {'uid': 3173, 'user_id': '4', 'timestamp': datetime.datetime(2021, 3, 10, 19, 42, 26), 'status': 1, 'punch': 1}, {'uid': 3174, 'user_id': '1', 'timestamp': datetime.datetime(2021, 3, 10, 19, 42, 34), 'status': 1, 'punch': 1}, {'uid': 3175, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 11, 8, 48, 6), 'status': 1, 'punch': 1}, {'uid': 3176, 'user_id': '7', 'timestamp': datetime.datetime(2021, 3, 11, 9, 2, 30), 'status': 2, 'punch': 1}, {'uid': 3177, 'user_id': '5', 'timestamp': datetime.datetime(2021, 3, 11, 9, 12, 40), 'status': 1, 'punch': 1}, {'uid': 3178, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 11, 9, 40, 47), 'status': 1, 'punch': 1}, {'uid': 3179, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 11, 9, 49, 59), 'status': 2, 'punch': 1},
Return Text File 'today's date 11/3/2021' ex:
{'uid': 3175, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 11, 8, 48, 6), 'status': 1, 'punch': 1}, {'uid': 3176, 'user_id': '7', 'timestamp': datetime.datetime(2021, 3, 11, 9, 2, 30), 'status': 2, 'punch': 1}, {'uid': 3177, 'user_id': '5', 'timestamp': datetime.datetime(2021, 3, 11, 9, 12, 40), 'status': 1, 'punch': 1}, {'uid': 3178, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 11, 9, 40, 47), 'status': 1, 'punch': 1}, {'uid': 3179, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 11, 9, 49, 59), 'status': 2, 'punch': 1},
It seems you're dealing with tabular data and pandas is very natural for that.
import datetime
import pandas as pd
df = pd.DataFrame([{'uid': 3167, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 10, 18, 7, 13), 'status': 1, 'punch': 1}, {'uid': 3168, 'user_id': '198', 'timestamp': datetime.datetime(2021, 3, 10, 18, 10, 42), 'status': 2, 'punch': 1}, {'uid': 3169, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 10, 18, 13, 53), 'status': 1, 'punch': 1}, {'uid': 3170, 'user_id': '13', 'timestamp': datetime.datetime(2021, 3, 10, 18, 22, 2), 'status': 1, 'punch': 1}, {'uid': 3171, 'user_id': '9', 'timestamp': datetime.datetime(2021, 3, 10, 18, 22, 43), 'status': 1, 'punch': 1}, {'uid': 3172, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 10, 18, 32, 30), 'status': 2, 'punch': 1}, {'uid': 3173, 'user_id': '4', 'timestamp': datetime.datetime(2021, 3, 10, 19, 42, 26), 'status': 1, 'punch': 1}, {'uid': 3174, 'user_id': '1', 'timestamp': datetime.datetime(2021, 3, 10, 19, 42, 34), 'status': 1, 'punch': 1}, {'uid': 3175, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 11, 8, 48, 6), 'status': 1, 'punch': 1}, {'uid': 3176, 'user_id': '7', 'timestamp': datetime.datetime(2021, 3, 11, 9, 2, 30), 'status': 2, 'punch': 1}, {'uid': 3177, 'user_id': '5', 'timestamp': datetime.datetime(2021, 3, 11, 9, 12, 40), 'status': 1, 'punch': 1}, {'uid': 3178, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 11, 9, 40, 47), 'status': 1, 'punch': 1}, {'uid': 3179, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 11, 9, 49, 59), 'status': 2, 'punch': 1},])
today = pd.to_datetime('today').normalize()
rows = df[df['timestamp'] >= today]
Which gives
uid user_id timestamp status punch
8 3175 3 2021-03-11 08:48:06 1 1
9 3176 7 2021-03-11 09:02:30 2 1
10 3177 5 2021-03-11 09:12:40 1 1
11 3178 6 2021-03-11 09:40:47 1 1
12 3179 15 2021-03-11 09:49:59 2 1
If you want the result in a list of dicts, you can then do rows.to_dict('records').
Without pandas it'd be a similar approach of getting today's datetime and iterating over your data to filter them.
lines = [{'uid': 3167, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 10, 18, 7, 13), 'status': 1, 'punch': 1}, {'uid': 3168, 'user_id': '198', 'timestamp': datetime.datetime(2021, 3, 10, 18, 10, 42), 'status': 2, 'punch': 1}, {'uid': 3169, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 10, 18, 13, 53), 'status': 1, 'punch': 1}, {'uid': 3170, 'user_id': '13', 'timestamp': datetime.datetime(2021, 3, 10, 18, 22, 2), 'status': 1, 'punch': 1}, {'uid': 3171, 'user_id': '9', 'timestamp': datetime.datetime(2021, 3, 10, 18, 22, 43), 'status': 1, 'punch': 1}, {'uid': 3172, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 10, 18, 32, 30), 'status': 2, 'punch': 1}, {'uid': 3173, 'user_id': '4', 'timestamp': datetime.datetime(2021, 3, 10, 19, 42, 26), 'status': 1, 'punch': 1}, {'uid': 3174, 'user_id': '1', 'timestamp': datetime.datetime(2021, 3, 10, 19, 42, 34), 'status': 1, 'punch': 1}, {'uid': 3175, 'user_id': '3', 'timestamp': datetime.datetime(2021, 3, 11, 8, 48, 6), 'status': 1, 'punch': 1}, {'uid': 3176, 'user_id': '7', 'timestamp': datetime.datetime(2021, 3, 11, 9, 2, 30), 'status': 2, 'punch': 1}, {'uid': 3177, 'user_id': '5', 'timestamp': datetime.datetime(2021, 3, 11, 9, 12, 40), 'status': 1, 'punch': 1}, {'uid': 3178, 'user_id': '6', 'timestamp': datetime.datetime(2021, 3, 11, 9, 40, 47), 'status': 1, 'punch': 1}, {'uid': 3179, 'user_id': '15', 'timestamp': datetime.datetime(2021, 3, 11, 9, 49, 59), 'status': 2, 'punch': 1},]
today = datetime.date.today()
today = datetime.datetime(today.year, today.month, today.day)
result = [line for line in lines if line['timestamp'] >= today]