Parsing Text file with irregular column width into Pandas

I need help in parsing below text into Pandas dataframe columns

(11/15/22 2:48:46 PM EST) 14:48:33.671 - 42300146: GWS: 2022-11-15 18:18:33.638 RESTQueue No request to signal.
(11/15/22 11:55:59 AM EST) 11:40:22.750 - 31009225: GWS: 2022-11-15 15:10:22.748  Message Type Received: Slots
(11/8/22 8:03:39 AM EST) 07:32:38.188 - 28624922: Timed out waiting for incoming connections, retry after couple of secs

Below is the expected output.

Note: The first and fourth column have different width.

I have tried to use read_fwf with specific width but didn't produce the output that I want. I couldn't use read_csv since there is no delimiter (other than whitespace) between columns.

Any help would be appreciated!

Thank you in advance.

You can use regular expression to parse the text (regex demo.)

text = """\
(11/15/22 2:48:46 PM EST) 14:48:33.671 - 42300146: GWS: 2022-11-15 18:18:33.638 RESTQueue No request to signal.
(11/15/22 11:55:59 AM EST) 11:40:22.750 - 31009225: GWS: 2022-11-15 15:10:22.748  Message Type Received: Slots
(11/8/22 8:03:39 AM EST) 07:32:38.188 - 28624922: Timed out waiting for incoming connections, retry after couple of secs"""

import re
import pandas as pd

pat = re.compile(r"(\(.*?\))\s+(\S+)\s+-\s+(\d+):\s+(.*)")

data = []
for line in text.splitlines():
    m = pat.search(line)
    if m:
        data.append(m.groups())

df = pd.DataFrame(
    data, columns=["Column 1", "Column 2", "Column 3", "Column 4"]
)
print(df)

Prints:

                     Column 1      Column 2  Column 3                                                                Column 4
0   (11/15/22 2:48:46 PM EST)  14:48:33.671  42300146            GWS: 2022-11-15 18:18:33.638 RESTQueue No request to signal.
1  (11/15/22 11:55:59 AM EST)  11:40:22.750  31009225              GWS: 2022-11-15 15:10:22.748  Message Type Received: Slots
2    (11/8/22 8:03:39 AM EST)  07:32:38.188  28624922  Timed out waiting for incoming connections, retry after couple of secs