DEP: Enforce deprecation of date converters for csv

doc/source/whatsnew/v2.0.0.rst

@@ -144,6 +144,9 @@ Deprecations
 
 Removal of prior version deprecations/changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+- Removed Date parser functions :func:`~pandas.io.date_converters.parse_date_time`,
+  :func:`~pandas.io.date_converters.parse_date_fields`, :func:`~pandas.io.date_converters.parse_all_fields`
+  and :func:`~pandas.io.date_converters.generic_parser` (:issue:`24518`)
 - Remove argument ``squeeze`` from :meth:`DataFrame.groupby` and :meth:`Series.groupby` (:issue:`32380`)
 - Removed ``keep_tz`` argument in :meth:`DatetimeIndex.to_series` (:issue:`29731`)
 - Remove arguments ``names`` and ``dtype`` from :meth:`Index.copy` and ``levels`` and ``codes`` from :meth:`MultiIndex.copy` (:issue:`35853`, :issue:`36685`)

pandas/_libs/tslibs/parsing.pyi

@@ -27,14 +27,6 @@ def try_parse_dates(
     dayfirst: bool = ...,
     default: datetime | None = ...,
 ) -> npt.NDArray[np.object_]: ...
-def try_parse_date_and_time(
-    dates: npt.NDArray[np.object_],  # object[:]
-    times: npt.NDArray[np.object_],  # object[:]
-    date_parser=...,
-    time_parser=...,
-    dayfirst: bool = ...,
-    default: datetime | None = ...,
-) -> npt.NDArray[np.object_]: ...
 def try_parse_year_month_day(
     years: npt.NDArray[np.object_],  # object[:]
     months: npt.NDArray[np.object_],  # object[:]

pandas/_libs/tslibs/parsing.pyx

@@ -741,49 +741,6 @@ def try_parse_dates(
     return result.base  # .base to access underlying ndarray
 
 
-def try_parse_date_and_time(
-    object[:] dates,
-    object[:] times,
-    date_parser=None,
-    time_parser=None,
-    bint dayfirst=False,
-    default=None,
-) -> np.ndarray:
-    cdef:
-        Py_ssize_t i, n
-        object[::1] result
-
-    n = len(dates)
-    # TODO(cython3): Use len instead of `shape[0]`
-    if times.shape[0] != n:
-        raise ValueError('Length of dates and times must be equal')
-    result = np.empty(n, dtype='O')
-
-    if date_parser is None:
-        if default is None:  # GH2618
-            date = datetime.now()
-            default = datetime(date.year, date.month, 1)
-
-        parse_date = lambda x: du_parse(x, dayfirst=dayfirst, default=default)
-
-    else:
-        parse_date = date_parser
-
-    if time_parser is None:
-        parse_time = lambda x: du_parse(x)
-
-    else:
-        parse_time = time_parser
-
-    for i in range(n):
-        d = parse_date(str(dates[i]))
-        t = parse_time(str(times[i]))
-        result[i] = datetime(d.year, d.month, d.day,
-                             t.hour, t.minute, t.second)
-
-    return result.base  # .base to access underlying ndarray
-
-
 def try_parse_year_month_day(
     object[:] years, object[:] months, object[:] days
 ) -> np.ndarray:

pandas/io/parsers/base_parser.py

@@ -78,8 +78,6 @@
 from pandas.core.series import Series
 from pandas.core.tools import datetimes as tools
 
-from pandas.io.date_converters import generic_parser
-
 if TYPE_CHECKING:
     from pandas import DataFrame
 
@@ -1135,17 +1133,14 @@ def converter(*date_cols):
                     raise Exception("scalar parser")
                 return result
             except Exception:
-                try:
-                    return tools.to_datetime(
-                        parsing.try_parse_dates(
-                            parsing.concat_date_cols(date_cols),
-                            parser=date_parser,
-                            dayfirst=dayfirst,
-                        ),
-                        errors="ignore",
-                    )
-                except Exception:
-                    return generic_parser(date_parser, *date_cols)
+                return tools.to_datetime(
+                    parsing.try_parse_dates(
+                        parsing.concat_date_cols(date_cols),
+                        parser=date_parser,
+                        dayfirst=dayfirst,
+                    ),
+                    errors="ignore",
+                )
 
     return converter