BUG: guess_datetime_format doesn't guess 2018-01-01T00:00:00.000

[MarcoGorelli]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

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

Reproducible Example

guess_datetime_format('2018-01-01T00:00:00.000')

Issue Description

This returns None, rather than %Y-%m-%dT%H:%M:%S.%f, which would work fine:

In [2]: dt.datetime.strptime('2018-01-01T00:00:00.000', '%Y-%m-%dT%H:%M:%S.%f')
Out[2]: datetime.datetime(2018, 1, 1, 0, 0)

Expected Behavior

that it return

%Y-%m-%dT%H:%M:%S.%f

Installed Versions

INSTALLED VERSIONS

commit : 822ce17
python : 3.8.13.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 : 1.6.0.dev0+329.g822ce171da.dirty
numpy : 1.23.3
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 59.8.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.3
hypothesis : 6.54.6
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 : 8.5.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.3
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.6.0
numba : 0.56.2
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.8
pyarrow : 9.0.0
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.9.1
snappy :
sqlalchemy : 1.4.41
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.9.0
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : 0.18.0
tzdata : None
None

[MarcoGorelli]

This would do the trick, though it'd be better to find a better way of writing it

diff --git a/pandas/_libs/tslibs/parsing.pyx b/pandas/_libs/tslibs/parsing.pyx
index 51bb21404e..7b3b0a63be 100644
--- a/pandas/_libs/tslibs/parsing.pyx
+++ b/pandas/_libs/tslibs/parsing.pyx
@@ -1048,7 +1048,13 @@ def guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:
 
         parsed_formatted = parsed_datetime.strftime(attr_format)
         for i, token_format in enumerate(format_guess):
-            token_filled = tokens[i].zfill(padding)
+            if '.' not in tokens[i]:
+                token_filled = tokens[i].zfill(padding)
+            else:
+                seconds, milliseconds = tokens[i].split('.')
+                seconds = seconds.zfill(2)
+                millisecond = milliseconds.zfill(6)
+                token_filled = f'{seconds}.{milliseconds}'
             if token_format is None and token_filled == parsed_formatted:
                 format_guess[i] = attr_format
                 tokens[i] = token_filled

[mroeschke]

Since to_datetime(..., format="..%f") was fixed to parse up to nanos should guess_datetime_format also allow %f to detect nanoseconds? #48820

[MarcoGorelli]

probably, kinda tricky though given that datetime.datetime.strftime is used

pandas/pandas/_libs/tslibs/parsing.pyx

Line 1049 in 32474d9

parsed_formatted = parsed_datetime.strftime(attr_format)

pandas/pandas/_libs/tslibs/parsing.pyx

Line 1088 in 32474d9

if parsed_datetime.strftime(guessed_format) == dt_str: