PERF:cythonize _return_parsed_timezone_results?

[MarcoGorelli]

Pandas version checks

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• I have confirmed this issue exists on the main branch of pandas.

Reproducible Example

I made a file

import pandas as pd

dates = pd.date_range('1900', '2000').tz_localize('+01:00').strftime('%Y-%d-%m %H:%M:%S%z').tolist()
dates.append('2020-01-01 00:00:00+02:00')

pd.to_datetime(dates, format='%Y-%d-%m %H:%M:%S%z')

I then ran

python -m cProfile  -o out.prof perf.py
snakeviz out.prof --server

I can then see that, of the 0.329 seconds spent in to_datetime, a whole 0.248 are spent in _return_parsed_timezone_results. That's a whole 75%!

This function is a pair of Python for-loops

pandas/pandas/core/tools/datetimes.py

Lines 316 to 328 in 0cebd75

	tz_results = np.array(
	[Timestamp(res).tz_localize(zone) for res, zone in zip(result, timezones)]
	)
	if utc:
	# Convert to the same tz
	tz_results = np.array(
	[
	tz_result.tz_convert("utc")
	if tz_result.tzinfo is not None
	else tz_result.tz_localize("utc")
	for tz_result in tz_results
	]
	)

Would this be a good candidate for Cython to speed it up?

cc @lukemanley

Installed Versions

INSTALLED VERSIONS

commit : e93ee07
python : 3.8.15.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 2.0.0.dev0+863.ge93ee07729
numpy : 1.23.5
pytz : 2022.6
dateutil : 2.8.2
setuptools : 65.5.1
pip : 22.3.1
Cython : 0.29.32
pytest : 7.2.0
hypothesis : 6.59.0
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.7.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 2022.11.0
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.6.2
numba : 0.56.4
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.9
pyarrow : 9.0.0
pyreadstat : 1.2.0
pyxlsb : 1.0.10
s3fs : 2021.11.0
scipy : 1.9.3
snappy :
sqlalchemy : 1.4.44
tables : 3.7.0
tabulate : 0.9.0
xarray : 2022.11.0
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : None
qtpy : None
pyqt5 : None
None

Prior Performance

No response