[Python] Timestamp - out of bounds for nanoseconds

[MarioShuuya]

Describe the bug, including details regarding any error messages, version, and platform.

Environment
OS: Windows/Linux
Python: 3.11.2
Pyarrow: 17.0.0
Pandas: 2.2.2

Description
When trying to read a timestamp value, below the pandas min. value of 1677-09-21 00:12:43.145224193, from a datetime object into a pyarrow table, the result is an out of bounds for nanoseconds exception.

I have found problems that might relate but did not solve the issue here

• ARROW-5359
• ARROW-3448

Example Code

import pyarrow as pa
import datetime

schema = pa.schema([])
schema = schema.append(pa.field("CreateAt", pa.timestamp(unit="ns")))

ts = datetime.datetime(1677, 9, 21, 1)  # OK
arrays = [[ts]]
print(arrays)
table = pa.Table.from_arrays(arrays, schema=schema)
print(table)

ts = datetime.datetime(1, 1, 1, 1)  # NoK
arrays = [[ts]]
print(arrays)
table = pa.Table.from_arrays(arrays, schema=schema)
print(table)

Use Case
I am reading data from a database, where one column has ns precision timestamps. Instead of null values, it uses 0001-01-01 00:00:00.0000000. The goal is to store the result of the database read, which is an array containing datetime objects, into a Pyarrow table to then store it as parquet. This works well, until i hit a timestamp too big or small for pandas.

Component(s)

Python