share paths and fix bugs

Author: MarcoGorelli

doc/source/whatsnew/v2.0.0.rst

@@ -768,6 +768,7 @@ Performance improvements
 - Performance improvement in :func:`merge` when not merging on the index - the new index will now be :class:`RangeIndex` instead of :class:`Int64Index` (:issue:`49478`)
 - Performance improvement in :meth:`DataFrame.to_dict` and :meth:`Series.to_dict` when using any non-object dtypes (:issue:`46470`)
 - Performance improvement in :func:`read_html` when there are multiple tables (:issue:`49929`)
+- Performance improvement in :func:`to_datetime` when using ``'%Y%m%d'`` format (:issue:`17410`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_200.bug_fixes:
@@ -794,6 +795,13 @@ Datetimelike
 - Bug in :func:`to_datetime` was raising ``ValueError`` when parsing empty string and non-ISO8601 format was passed. Now, empty strings will be parsed as :class:`NaT`, for compatibility with how is done for ISO8601 formats (:issue:`50251`)
 - Bug in :class:`Timestamp` was showing ``UserWarning``, which was not actionable by users, when parsing non-ISO8601 delimited date strings (:issue:`50232`)
 - Bug in :func:`to_datetime` was showing misleading ``ValueError`` when parsing dates with format containing ISO week directive and ISO weekday directive (:issue:`50308`)
+- Bug in :func:`to_datetime` was not raising ``ValueError`` when parsing string with decimal date with format ``'%Y%m%d'`` (:issue:`50051`)
+- Bug in :func:`to_datetime` was not converting ``None`` to ``NaT`` when parsing mixed-offset date strings with ISO8601 format (:issue:`50071`)
+- Bug in :func:`to_datetime` was not returning input when parsing out-of-bounds date string with ``errors='ignore'`` and ``format='%Y%m%d'`` (:issue:`14487`)
+- Bug in :func:`to_datetime` was converting timezone-naive ``datetime.datetime`` to timezone-aware when parsing with timezone-aware strings, ISO8601 format, and ``utc=False`` (:issue:`50254`)
+- Bug in :func:`to_datetime` was throwing ``ValueError`` when parsing dates with ISO8601 format where some values were not zero-padded (:issue:`21422`)
+- Bug in :func:`to_datetime` was giving incorrect results when using ``format='%Y%m%d'`` and ``errors='ignore'`` (:issue:`26493`)
+- Bug in :func:`to_datetime` was failing to parse date strings ``'today'`` and ``'now'`` if ``format`` was not ISO8601 (:issue:`50359`)
 -
 
 Timedelta

pandas/_libs/tslib.pyi

@@ -23,9 +23,6 @@ def array_to_datetime(
     dayfirst: bool = ...,
     yearfirst: bool = ...,
     utc: bool = ...,
-    require_iso8601: bool = ...,
-    format: str | None = ...,
-    exact: bool = ...,
 ) -> tuple[np.ndarray, tzinfo | None]: ...
 
 # returned ndarray may be object dtype or datetime64[ns]

pandas/_libs/tslib.pyx

@@ -38,6 +38,7 @@ from pandas._libs.tslibs.np_datetime cimport (
     pydatetime_to_dt64,
     string_to_dts,
 )
+from pandas._libs.tslibs.strptime cimport parse_today_now
 from pandas._libs.util cimport (
     is_datetime64_object,
     is_float_object,
@@ -409,9 +410,6 @@ cpdef array_to_datetime(
     bint dayfirst=False,
     bint yearfirst=False,
     bint utc=False,
-    bint require_iso8601=False,
-    format: str | None=None,
-    bint exact=True,
 ):
     """
     Converts a 1D array of date-like values to a numpy array of either:
@@ -438,8 +436,6 @@ cpdef array_to_datetime(
          yearfirst parsing behavior when encountering datetime strings
     utc : bool, default False
          indicator whether the dates should be UTC
-    require_iso8601 : bool, default False
-         indicator whether the datetime string should be iso8601
 
     Returns
     -------
@@ -510,16 +506,6 @@ cpdef array_to_datetime(
                     iresult[i] = get_datetime64_nanos(val, NPY_FR_ns)
 
                 elif is_integer_object(val) or is_float_object(val):
-                    if require_iso8601:
-                        if is_coerce:
-                            iresult[i] = NPY_NAT
-                            continue
-                        elif is_raise:
-                            raise ValueError(
-                                f"time data \"{val}\" at position {i} doesn't "
-                                f"match format \"{format}\""
-                            )
-                        return values, tz_out
                     # these must be ns unit by-definition
                     seen_integer = True
 
@@ -550,25 +536,13 @@ cpdef array_to_datetime(
 
                     string_to_dts_failed = string_to_dts(
                         val, &dts, &out_bestunit, &out_local,
-                        &out_tzoffset, False, format, exact
+                        &out_tzoffset, False, None, False
                     )
                     if string_to_dts_failed:
                         # An error at this point is a _parsing_ error
                         # specifically _not_ OutOfBoundsDatetime
-                        if _parse_today_now(val, &iresult[i], utc):
+                        if parse_today_now(val, &iresult[i], utc):
                             continue
-                        elif require_iso8601:
-                            # if requiring iso8601 strings, skip trying
-                            # other formats
-                            if is_coerce:
-                                iresult[i] = NPY_NAT
-                                continue
-                            elif is_raise:
-                                raise ValueError(
-                                    f"time data \"{val}\" at position {i} doesn't "
-                                    f"match format \"{format}\""
-                                )
-                            return values, tz_out
 
                         try:
                             py_dt = parse_datetime_string(val,
@@ -631,18 +605,6 @@ cpdef array_to_datetime(
                 if is_coerce:
                     iresult[i] = NPY_NAT
                     continue
-                elif require_iso8601 and isinstance(val, str):
-                    # GH#19382 for just-barely-OutOfBounds falling back to
-                    # dateutil parser will return incorrect result because
-                    # it will ignore nanoseconds
-                    if is_raise:
-
-                        # Still raise OutOfBoundsDatetime,
-                        # as error message is informative.
-                        raise
-
-                    assert is_ignore
-                    return values, tz_out
                 raise
 
     except OutOfBoundsDatetime:
@@ -801,26 +763,6 @@ cdef _array_to_datetime_object(
     return oresult, None
 
 
-cdef bint _parse_today_now(str val, int64_t* iresult, bint utc):
-    # We delay this check for as long as possible
-    # because it catches relatively rare cases
-
-    # Multiply by 1000 to convert to nanos, since these methods naturally have
-    #  microsecond resolution
-    if val == "now":
-        if utc:
-            iresult[0] = Timestamp.utcnow().value * 1000
-        else:
-            # GH#18705 make sure to_datetime("now") matches Timestamp("now")
-            # Note using Timestamp.now() is faster than Timestamp("now")
-            iresult[0] = Timestamp.now().value * 1000
-        return True
-    elif val == "today":
-        iresult[0] = Timestamp.today().value * 1000
-        return True
-    return False
-
-
 def array_to_datetime_with_tz(ndarray values, tzinfo tz):
     """
     Vectorized analogue to pd.Timestamp(value, tz=tz)

pandas/_libs/tslibs/parsing.pyx

@@ -846,7 +846,7 @@ def format_is_iso(f: str) -> bint:
     but must be consistent.  Leading 0s in dates and times are optional.
     """
     iso_template = "%Y{date_sep}%m{date_sep}%d{time_sep}%H:%M:%S{micro_or_tz}".format
-    excluded_formats = ["%Y%m%d", "%Y%m", "%Y"]
+    excluded_formats = ["%Y%m"]
 
     for date_sep in [" ", "/", "\\", "-", ".", ""]:
         for time_sep in [" ", "T"]:

pandas/_libs/tslibs/strptime.pxd

@@ -0,0 +1,4 @@
+from numpy cimport int64_t
+
+
+cdef bint parse_today_now(str val, int64_t* iresult, bint utc)

pandas/_libs/tslibs/strptime.pyx

@@ -34,22 +34,43 @@ from pandas._libs.tslibs.nattype cimport (
     c_nat_strings as nat_strings,
 )
 from pandas._libs.tslibs.np_datetime cimport (
+    NPY_DATETIMEUNIT,
     NPY_FR_ns,
     check_dts_bounds,
     npy_datetimestruct,
     npy_datetimestruct_to_datetime,
     pydate_to_dt64,
     pydatetime_to_dt64,
+    string_to_dts,
 )
 from pandas._libs.tslibs.timestamps cimport _Timestamp
 from pandas._libs.util cimport (
     is_datetime64_object,
     is_float_object,
     is_integer_object,
 )
+from pandas._libs.tslibs.timestamps import Timestamp
 
 cnp.import_array()
 
+cdef bint parse_today_now(str val, int64_t* iresult, bint utc):
+    # We delay this check for as long as possible
+    # because it catches relatively rare cases
+
+    # Multiply by 1000 to convert to nanos, since these methods naturally have
+    #  microsecond resolution
+    if val == "now":
+        if utc:
+            iresult[0] = Timestamp.utcnow().value * 1000
+        else:
+            # GH#18705 make sure to_datetime("now") matches Timestamp("now")
+            # Note using Timestamp.now() is faster than Timestamp("now")
+            iresult[0] = Timestamp.now().value * 1000
+        return True
+    elif val == "today":
+        iresult[0] = Timestamp.today().value * 1000
+        return True
+    return False
 
 cdef dict _parse_code_table = {"y": 0,
                                "Y": 1,
@@ -93,6 +114,7 @@ def array_strptime(
     exact : matches must be exact if True, search if False
     errors : string specifying error handling, {'raise', 'ignore', 'coerce'}
     """
+    from pandas._libs.tslibs.parsing import format_is_iso
 
     cdef:
         Py_ssize_t i, n = len(values)
@@ -110,6 +132,9 @@ def array_strptime(
         bint found_naive = False
         bint found_tz = False
         tzinfo tz_out = None
+        bint iso_format = fmt is not None and format_is_iso(fmt)
+        NPY_DATETIMEUNIT out_bestunit
+        int out_local = 0, out_tzoffset = 0
 
     assert is_raise or is_ignore or is_coerce
 
@@ -230,6 +255,40 @@ def array_strptime(
         else:
             val = str(val)
 
+        if iso_format:
+            string_to_dts_failed = string_to_dts(
+                val, &dts, &out_bestunit, &out_local,
+                &out_tzoffset, False, fmt, exact
+            )
+            if not string_to_dts_failed:
+                # No error reported by string_to_dts, pick back up
+                # where we left off
+                value = npy_datetimestruct_to_datetime(NPY_FR_ns, &dts)
+                if out_local == 1:
+                    # Store the out_tzoffset in seconds
+                    # since we store the total_seconds of
+                    # dateutil.tz.tzoffset objects
+                    tz = timezone(timedelta(minutes=out_tzoffset))
+                    result_timezone[i] = tz
+                    out_local = 0
+                    out_tzoffset = 0
+                iresult[i] = value
+                try:
+                    check_dts_bounds(&dts)
+                except ValueError:
+                    if is_coerce:
+                        iresult[i] = NPY_NAT
+                        continue
+                    raise
+                continue
+
+        if parse_today_now(val, &iresult[i], utc):
+            continue
+
+        # Some ISO formats can't be parsed by string_to_dts
+        # For example, 6-digit YYYYMD. So, if there's an error,
+        # try the string-matching code below.
+
         # exact matching
         if exact:
             found = format_regex.match(val)

pandas/core/arrays/datetimes.py

@@ -2118,10 +2118,7 @@ def objects_to_datetime64ns(
     yearfirst,
     utc: bool = False,
     errors: DateTimeErrorChoices = "raise",
-    require_iso8601: bool = False,
     allow_object: bool = False,
-    format: str | None = None,
-    exact: bool = True,
 ):
     """
     Convert data to array of timestamps.
@@ -2134,7 +2131,6 @@ def objects_to_datetime64ns(
     utc : bool, default False
         Whether to convert/localize timestamps to UTC.
     errors : {'raise', 'ignore', 'coerce'}
-    require_iso8601 : bool, default False
     allow_object : bool
         Whether to return an object-dtype ndarray instead of raising if the
         data contains more than one timezone.
@@ -2165,9 +2161,6 @@ def objects_to_datetime64ns(
             utc=utc,
             dayfirst=dayfirst,
             yearfirst=yearfirst,
-            require_iso8601=require_iso8601,
-            format=format,
-            exact=exact,
         )
         result = result.reshape(data.shape, order=order)
     except OverflowError as err: