It is numpy issue not yours.
There is no need to take a division in case of 'precision_time' has set to 'n' (nano second).
If division present, precision error may occur even the divisor is 1.
I advise to check 'n' is 1 to solve the issue with high readability:
[BEFORE]:
time = ((pd.to_datetime(dataframe.index).values.astype(np.int64) /
precision_factor).astype(np.int64).astype(str))
[AFTER]:
if precision_factor == 1.0:
time = ((pd.to_datetime(dataframe.index).values.astype(np.int64)).astype(str))
else:
time = ((pd.to_datetime(dataframe.index).values.astype(np.int64) /
precision_factor).astype(np.int64).astype(str))
https://github.com/influxdata/influxdb-python/blob/7b0367309b118e8be97bd85af4433b25129a4618/influxdb/_dataframe_client.py#L291
https://github.com/influxdata/influxdb-python/blob/7b0367309b118e8be97bd85af4433b25129a4618/influxdb/_dataframe_client.py#L305
https://github.com/influxdata/influxdb-python/blob/7b0367309b118e8be97bd85af4433b25129a4618/influxdb/_dataframe_client.py#L375
https://github.com/influxdata/influxdb-python/blob/7b0367309b118e8be97bd85af4433b25129a4618/influxdb/_dataframe_client.py#L378
It is numpy issue not yours. There is no need to take a division in case of 'precision_time' has set to 'n' (nano second). If division present, precision error may occur even the divisor is 1.
I advise to check 'n' is 1 to solve the issue with high readability:
[BEFORE]: time = ((pd.to_datetime(dataframe.index).values.astype(np.int64) / precision_factor).astype(np.int64).astype(str)) [AFTER]: