String to datetime conversion with custom format

[tritemio]

Checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of Polars.

Reproducible example

import polars as pl
import pandas as pd

df = pl.DataFrame({'dt': "2024-06-03 20:02:48.6800000"})
dt_format = "%Y-%m-%d %H:%M:%S%.6f0". # NOTE: this format has a trailing 0
df['dt'].str.to_datetime(dt_format, time_unit='ns')

Log output

Traceback (most recent call last):
  File "/Users/anto/src/poste/sda-poste-logistics/script/polars_bug_datetime.py", line 7, in <module>
    df["dt"].str.to_datetime(dt_format, time_unit="ns")
  File "/Users/anto/src/poste/sda-poste-logistics/venv/lib/python3.11/site-packages/polars/series/utils.py", line 107, in wrapper
    return s.to_frame().select_seq(f(*args, **kwargs)).to_series()
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/anto/src/poste/sda-poste-logistics/venv/lib/python3.11/site-packages/polars/dataframe/frame.py", line 8524, in select_seq
    return self.lazy().select_seq(*exprs, **named_exprs).collect(_eager=True)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/anto/src/poste/sda-poste-logistics/venv/lib/python3.11/site-packages/polars/lazyframe/frame.py", line 1909, in collect
    return wrap_df(ldf.collect(callback))
                   ^^^^^^^^^^^^^^^^^^^^^
polars.exceptions.InvalidOperationError: conversion from `str` to `datetime[ns]` failed in column 'dt' for 1 out of 1 values: ["2024-06-03 20:02:48.6800000"]

You might want to try:
- setting `strict=False` to set values that cannot be converted to `null`
- using `str.strptime`, `str.to_date`, or `str.to_datetime` and providing a format string

Issue description

Converting from string to datetime with a format string should allow to decode custom formats.

In this example the input has 7 digits for fractional seconds after the decimal dot. However the last digit is always zero and should be ignored because there is a trailing 0 in the format string.

Instead, polars gives the above error during conversion.

Stripping the extra zero from the string before attempting the conversion works correctly in polars:

dt_format1 = "%Y-%m-%d %H:%M:%S%.6f"  # NOTE: no trailing 0 in the format
df['dt'].str.strip_suffix('0').str.to_datetime(dt_format1, time_unit='ns')

Pandas accepts the original format and convert the string correctly, as does python's datetime

x = pd.to_datetime(
    df["dt"].to_pandas(use_pyarrow_extension_array=True),
    format="%Y-%m-%d %H:%M:%S%.6f0",
)
df = df.with_columns(pl.from_pandas(x))

Expected behavior

The column should be converted to datetime without error, as done in pandas and datetime from python standard lib.

Installed versions

Details

--------Version info---------
Polars:               1.0.0-rc.2
Index type:           UInt32
Platform:             macOS-14.5-arm64-arm-64bit
Python:               3.11.3 (main, Sep  1 2023, 14:56:45) [Clang 14.0.3 (clang-1403.0.22.14.1)]

----Optional dependencies----
adbc_driver_manager:  1.0.0
cloudpickle:          3.0.0
connectorx:           0.3.3
deltalake:            <not installed>
fastexcel:            0.10.4
fsspec:               2023.12.2
gevent:               24.2.1
great_tables:         <not installed>
hvplot:               0.10.0
matplotlib:           3.8.4
nest_asyncio:         1.6.0
numpy:                1.26.4
openpyxl:             <not installed>
pandas:               2.2.2
pyarrow:              16.1.0
pydantic:             2.7.3
pyiceberg:            0.6.1
sqlalchemy:           2.0.30
torch:                <not installed>
xlsx2csv:             0.8.2
xlsxwriter:           3.2.0

[MarcoGorelli]

Thanks For the report, I'm surprised this didn't work, will check

[Julian-J-S]

This might be a "bug" or design decision by chrono (the rust parser) BUT

• "%Y-%m-%d %H:%M:%S%.6f0" 💥
  • this does NOT work in this case
  • this is usually supported.
• "%Y-%m-%d %H:%M:%S.%6f0" 🍀
  • this WORKS
  • Note: moved the dot . left
  • alternative way to make a literal dot instead of telling chrono to handle it itself as part of the fractional seconds

[MarcoGorelli]

To me this looks like it might be a bug in Chrono:

use chrono::NaiveDateTime;
fn main() {

    let result = NaiveDateTime::parse_from_str(
        "2024-06-03 20:02:48.6800000",
        "%Y-%m-%d %H:%M:%S%.6f0",
    );
    println!("{:?}", result);
    let result = NaiveDateTime::parse_from_str(
        "2024-06-03 20:02:48.680000",
        "%Y-%m-%d %H:%M:%S%.6f",
    );
    println!("{:?}", result);
}

prints out

Err(ParseError(TooShort))
Ok(2024-06-03T20:02:48.680)

[tritemio]

For reference I have created a pytest file that tests several format strings on datetime.strptime, pandas.to_datetime and polars to_datetime. Results shows the valid format string is different across the 3, with datetime and pandas being similar, while polars requires a different format.

I found that polars converts the string even without the trailing 0 in the format when using either %.f or %.6f. This should be the right format for chrono (although different from the python conventions).

Full results:

pytest file:

Details

from datetime import datetime

import pandas as pd
import polars as pl
import pytest

dt_string = "2024-06-03 20:02:48.6800000"


dt_formats = [
    "%Y-%m-%d %H:%M:%S%.f",
    "%Y-%m-%d %H:%M:%S%.6f",
    "%Y-%m-%d %H:%M:%S.%f",
    "%Y-%m-%d %H:%M:%S.%6f",
]
dt_formats = dt_formats + [f + "0" for f in dt_formats]


@pytest.fixture
def df():
    return pl.DataFrame({"dt": dt_string})


@pytest.mark.parametrize("format", dt_formats)
def test_polars(df, format, capsys):
    with capsys.disabled():
        print(format)
        print(df)

    t_ref = pl.Series(name="dt", values=[datetime(2024, 6, 3, 20, 2, 48, 680000)])
    df2 = df.with_columns(dt=pl.col("dt").str.to_datetime(format, time_unit="ns"))

    with capsys.disabled():
        print(df2)
    assert (df2["dt"] == t_ref).all()


@pytest.mark.parametrize("format", dt_formats)
def test_pandas(df, format, capsys):
    with capsys.disabled():
        print(format)
        print(df)

    t_ref = pd.Series(name="dt", data=[datetime(2024, 6, 3, 20, 2, 48, 680000)])
    t = pd.to_datetime(
        df["dt"].to_pandas(use_pyarrow_extension_array=True), format=format
    )

    with capsys.disabled():
        print(t)

    assert (t == t_ref).all()


@pytest.mark.parametrize("format", dt_formats)
def test_datetime(df, format, capsys):
    dt_ref = datetime(2024, 6, 3, 20, 2, 48, 680000)
    dt = datetime.strptime(dt_string, format)

    assert dt == dt_ref

[Julian-J-S]

@tritemio correct, python datetime and chrono have different behaviour for some details.

you can check out the documentation

• python
• chrono

python

chrono

Watch our for this (chrono)

date = "2020-01-01 10:00:00.1234"

• "%Y-%m-%d %H:%M:%S%.f" -> 2020-01-01 10:00:00.123400
• "%Y-%m-%d %H:%M:%S.%f" -> 2020-01-01 10:00:00.000001234