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| """Parsing functions for datetime and datetime-like strings."""import reimport timeimport warningsfrom pandas.util._exceptions import find_stack_levelcimport cythonfrom cpython.datetime cimport (    datetime,    datetime_new,    import_datetime,    timedelta,    tzinfo,)from datetime import timezonefrom cpython.object cimport PyObject_Strfrom cython cimport Py_ssize_tfrom libc.string cimport strchrimport_datetime()import numpy as npcimport numpy as cnpfrom numpy cimport (    PyArray_GETITEM,    PyArray_ITER_DATA,    PyArray_ITER_NEXT,    PyArray_IterNew,    flatiter,    float64_t,)cnp.import_array()# dateutil compatfrom decimal import InvalidOperationfrom dateutil.parser import (    DEFAULTPARSER,    parse as du_parse,)from dateutil.relativedelta import relativedeltafrom dateutil.tz import (    tzlocal as _dateutil_tzlocal,    tzoffset,    tzutc as _dateutil_tzutc,)from pandas._config import get_optionfrom pandas._libs.tslibs.ccalendar cimport c_MONTH_NUMBERSfrom pandas._libs.tslibs.dtypes cimport (    attrname_to_npy_unit,    npy_unit_to_attrname,)from pandas._libs.tslibs.nattype cimport (    c_NaT as NaT,    c_nat_strings as nat_strings,)from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetimefrom pandas._libs.tslibs.np_datetime cimport (    NPY_DATETIMEUNIT,    npy_datetimestruct,    string_to_dts,)from pandas._libs.tslibs.strptime import array_strptimefrom pandas._libs.tslibs.util cimport (    get_c_string_buf_and_size,    is_array,)cdef extern from "../src/headers/portable.h":    int getdigit_ascii(char c, int default) nogilcdef extern from "../src/parser/tokenizer.h":    double xstrtod(const char *p, char **q, char decimal, char sci, char tsep,                   int skip_trailing, int *error, int *maybe_int)# ----------------------------------------------------------------------# Constantsclass DateParseError(ValueError):    pass_DEFAULT_DATETIME = datetime(1, 1, 1).replace(hour=0, minute=0,                                              second=0, microsecond=0)cdef:    set _not_datelike_strings = {"a", "A", "m", "M", "p", "P", "t", "T"}    # _timestamp_units -> units that we round to nanos    set _timestamp_units = {        NPY_DATETIMEUNIT.NPY_FR_ns,        NPY_DATETIMEUNIT.NPY_FR_ps,        NPY_DATETIMEUNIT.NPY_FR_fs,        NPY_DATETIMEUNIT.NPY_FR_as,    }# ----------------------------------------------------------------------cdef:    const char* delimiters = " /-."    int MAX_DAYS_IN_MONTH = 31, MAX_MONTH = 12cdef bint _is_delimiter(const char ch):    return strchr(delimiters, ch) != NULLcdef int _parse_1digit(const char* s):    cdef int result = 0    result += getdigit_ascii(s[0], -10) * 1    return resultcdef int _parse_2digit(const char* s):    cdef int result = 0    result += getdigit_ascii(s[0], -10) * 10    result += getdigit_ascii(s[1], -100) * 1    return resultcdef int _parse_4digit(const char* s):    cdef int result = 0    result += getdigit_ascii(s[0], -10) * 1000    result += getdigit_ascii(s[1], -100) * 100    result += getdigit_ascii(s[2], -1000) * 10    result += getdigit_ascii(s[3], -10000) * 1    return resultcdef datetime _parse_delimited_date(    str date_string, bint dayfirst, NPY_DATETIMEUNIT* out_bestunit):    """    Parse special cases of dates: MM/DD/YYYY, DD/MM/YYYY, MM/YYYY.    At the beginning function tries to parse date in MM/DD/YYYY format, but    if month > 12 - in DD/MM/YYYY (`dayfirst == False`).    With `dayfirst == True` function makes an attempt to parse date in    DD/MM/YYYY, if an attempt is wrong - in DD/MM/YYYY    For MM/DD/YYYY, DD/MM/YYYY: delimiter can be a space or one of /-.    For MM/YYYY: delimiter can be a space or one of /-    If `date_string` can't be converted to date, then function returns    None, None    Parameters    ----------    date_string : str    dayfirst : bool    out_bestunit : NPY_DATETIMEUNIT*        For specifying identified resolution.    Returns:    --------    datetime or None    """    cdef:        const char* buf        Py_ssize_t length        int day = 1, month = 1, year        bint can_swap = 0    buf = get_c_string_buf_and_size(date_string, &length)    if length == 10 and _is_delimiter(buf[2]) and _is_delimiter(buf[5]):        # parsing MM?DD?YYYY and DD?MM?YYYY dates        month = _parse_2digit(buf)        day = _parse_2digit(buf + 3)        year = _parse_4digit(buf + 6)        out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_D        can_swap = 1    elif length == 9 and _is_delimiter(buf[1]) and _is_delimiter(buf[4]):        # parsing M?DD?YYYY and D?MM?YYYY dates        month = _parse_1digit(buf)        day = _parse_2digit(buf + 2)        year = _parse_4digit(buf + 5)        out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_D        can_swap = 1    elif length == 9 and _is_delimiter(buf[2]) and _is_delimiter(buf[4]):        # parsing MM?D?YYYY and DD?M?YYYY dates        month = _parse_2digit(buf)        day = _parse_1digit(buf + 3)        year = _parse_4digit(buf + 5)        out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_D        can_swap = 1    elif length == 8 and _is_delimiter(buf[1]) and _is_delimiter(buf[3]):        # parsing M?D?YYYY and D?M?YYYY dates        month = _parse_1digit(buf)        day = _parse_1digit(buf + 2)        year = _parse_4digit(buf + 4)        out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_D        can_swap = 1    elif length == 7 and _is_delimiter(buf[2]):        # parsing MM?YYYY dates        if buf[2] == b".":            # we cannot reliably tell whether e.g. 10.2010 is a float            # or a date, thus we refuse to parse it here            return None        month = _parse_2digit(buf)        year = _parse_4digit(buf + 3)        out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_M    else:        return None    if month < 0 or day < 0 or year < 1000:        # some part is not an integer, so        # date_string can't be converted to date, above format        return None    if 1 <= month <= MAX_DAYS_IN_MONTH and 1 <= day <= MAX_DAYS_IN_MONTH \            and (month <= MAX_MONTH or day <= MAX_MONTH):        if (month > MAX_MONTH or (day <= MAX_MONTH and dayfirst)) and can_swap:            day, month = month, day        # In Python <= 3.6.0 there is no range checking for invalid dates        # in C api, thus we call faster C version for 3.6.1 or newer        return datetime_new(year, month, day, 0, 0, 0, 0, None)    raise DateParseError(f"Invalid date specified ({month}/{day})")cdef bint _does_string_look_like_time(str parse_string):    """    Checks whether given string is a time: it has to start either from    H:MM or from HH:MM, and hour and minute values must be valid.    Parameters    ----------    parse_string : str    Returns:    --------    bool        Whether given string is potentially a time.    """    cdef:        const char* buf        Py_ssize_t length        int hour = -1, minute = -1    buf = get_c_string_buf_and_size(parse_string, &length)    if length >= 4:        if buf[1] == b":":            # h:MM format            hour = getdigit_ascii(buf[0], -1)            minute = _parse_2digit(buf + 2)        elif buf[2] == b":":            # HH:MM format            hour = _parse_2digit(buf)            minute = _parse_2digit(buf + 3)    return 0 <= hour <= 23 and 0 <= minute <= 59def py_parse_datetime_string(    str date_string, bint dayfirst=False, bint yearfirst=False):    # Python-accessible version for testing (we can't just make    #  parse_datetime_string cpdef bc it has a pointer argument)    cdef:        NPY_DATETIMEUNIT out_bestunit    return parse_datetime_string(date_string, dayfirst, yearfirst, &out_bestunit)cdef datetime parse_datetime_string(    # NB: This will break with np.str_ (GH#32264) even though    #  isinstance(npstrobj, str) evaluates to True, so caller must ensure    #  the argument is *exactly* 'str'    str date_string,    bint dayfirst,    bint yearfirst,    NPY_DATETIMEUNIT* out_bestunit):    """    Parse datetime string, only returns datetime.    Also cares special handling matching time patterns.    Returns    -------    datetime    Notes    -----    Does not handle "today" or "now", which caller is responsible for handling.    """    cdef:        datetime dt        bint is_quarter = 0    if not _does_string_look_like_datetime(date_string):        raise ValueError(f'Given date string "{date_string}" not likely a datetime')    if _does_string_look_like_time(date_string):        # use current datetime as default, not pass _DEFAULT_DATETIME        dt = du_parse(date_string, dayfirst=dayfirst,                      yearfirst=yearfirst)        return dt    dt = _parse_delimited_date(date_string, dayfirst, out_bestunit)    if dt is not None:        return dt    try:        dt = _parse_dateabbr_string(            date_string, _DEFAULT_DATETIME, None, out_bestunit, &is_quarter        )        return dt    except DateParseError:        raise    except ValueError:        pass    dt = dateutil_parse(date_string, default=_DEFAULT_DATETIME,                        dayfirst=dayfirst, yearfirst=yearfirst,                        ignoretz=False, out_bestunit=out_bestunit)    return dtdef parse_datetime_string_with_reso(    str date_string, str freq=None, dayfirst=None, yearfirst=None):    # NB: This will break with np.str_ (GH#45580) even though    #  isinstance(npstrobj, str) evaluates to True, so caller must ensure    #  the argument is *exactly* 'str'    """    Try hard to parse datetime string, leveraging dateutil plus some extra    goodies like quarter recognition.    Parameters    ----------    date_string : str    freq : str or None, default None        Helps with interpreting time string if supplied        Corresponds to `offset.rule_code`    dayfirst : bool, default None        If None uses default from print_config    yearfirst : bool, default None        If None uses default from print_config    Returns    -------    datetime    str        Describing resolution of parsed string.    Raises    ------    ValueError : preliminary check suggests string is not datetime    DateParseError : error within dateutil    """    if dayfirst is None:        dayfirst = get_option("display.date_dayfirst")    if yearfirst is None:        yearfirst = get_option("display.date_yearfirst")    cdef:        datetime parsed        str reso        bint string_to_dts_failed        npy_datetimestruct dts        NPY_DATETIMEUNIT out_bestunit        int out_local = 0        int out_tzoffset        tzinfo tz        bint is_quarter = 0    if not _does_string_look_like_datetime(date_string):        raise ValueError(f'Given date string "{date_string}" not likely a datetime')    # Try iso8601 first, as it handles nanoseconds    string_to_dts_failed = string_to_dts(        date_string, &dts, &out_bestunit, &out_local,        &out_tzoffset, False    )    if not string_to_dts_failed:        # Match Timestamp and drop picoseconds, femtoseconds, attoseconds        # The new resolution will just be nano        # GH#50417        if out_bestunit in _timestamp_units:            out_bestunit = NPY_DATETIMEUNIT.NPY_FR_ns        if out_bestunit == NPY_DATETIMEUNIT.NPY_FR_ns:            # TODO: avoid circular import            from pandas import Timestamp            parsed = Timestamp(date_string)        else:            if out_local:                tz = timezone(timedelta(minutes=out_tzoffset))            else:                tz = None            parsed = datetime_new(                dts.year, dts.month, dts.day, dts.hour, dts.min, dts.sec, dts.us, tz            )        reso = npy_unit_to_attrname[out_bestunit]        return parsed, reso    parsed = _parse_delimited_date(date_string, dayfirst, &out_bestunit)    if parsed is not None:        reso = npy_unit_to_attrname[out_bestunit]        return parsed, reso    try:        parsed = _parse_dateabbr_string(            date_string, _DEFAULT_DATETIME, freq, &out_bestunit, &is_quarter        )    except DateParseError:        raise    except ValueError:        pass    else:        if is_quarter:            reso = "quarter"        else:            reso = npy_unit_to_attrname[out_bestunit]        return parsed, reso    parsed = dateutil_parse(date_string, _DEFAULT_DATETIME,                            dayfirst=dayfirst, yearfirst=yearfirst,                            ignoretz=False, out_bestunit=&out_bestunit)    reso = npy_unit_to_attrname[out_bestunit]    return parsed, resocpdef bint _does_string_look_like_datetime(str py_string):    """    Checks whether given string is a datetime: it has to start with '0' or    be greater than 1000.    Parameters    ----------    py_string: str    Returns    -------    bool        Whether given string is potentially a datetime.    """    cdef:        const char *buf        char *endptr = NULL        Py_ssize_t length = -1        double converted_date        char first        int error = 0    buf = get_c_string_buf_and_size(py_string, &length)    if length >= 1:        first = buf[0]        if first == b"0":            # Strings starting with 0 are more consistent with a            # date-like string than a number            return True        elif py_string in _not_datelike_strings:            return False        else:            # xstrtod with such parameters copies behavior of python `float`            # cast; for example, " 35.e-1 " is valid string for this cast so,            # for correctly xstrtod call necessary to pass these params:            # b'.' - a dot is used as separator, b'e' - an exponential form of            # a float number can be used, b'\0' - not to use a thousand            # separator, 1 - skip extra spaces before and after,            converted_date = xstrtod(buf, &endptr,                                     b".", b"e", b"\0", 1, &error, NULL)            # if there were no errors and the whole line was parsed, then ...            if error == 0 and endptr == buf + length:                return converted_date >= 1000    return Truecdef datetime _parse_dateabbr_string(str date_string, datetime default,                                     str freq, NPY_DATETIMEUNIT* out_bestunit,                                     bint* is_quarter):    # special handling for possibilities eg, 2Q2005, 2Q05, 2005Q1, 05Q1    cdef:        datetime ret        # year initialized to prevent compiler warnings        int year = -1, quarter = -1, month        Py_ssize_t date_len        const char* buf    if date_string in nat_strings:        # default to nanos, could also reasonably do NPY_FR_GENERIC        out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_ns        return NaT    date_string = date_string.upper()    date_len = len(date_string)    if date_len == 4:        # parse year only like 2000        try:            ret = default.replace(year=int(date_string))            out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_Y            return ret        except ValueError:            pass    if 4 <= date_len <= 7:        buf = get_c_string_buf_and_size(date_string, &date_len)        try:            i = date_string.index("Q", 1, 6)            if i == 1:                quarter = _parse_1digit(buf)  # i.e. int(date_string[0])                if date_len == 4 or (date_len == 5                                     and date_string[i + 1] == "-"):                    # r'(\d)Q-?(\d\d)')                    year = 2000 + int(date_string[-2:])                elif date_len == 6 or (date_len == 7                                       and date_string[i + 1] == "-"):                    # r'(\d)Q-?(\d\d\d\d)')                    year = int(date_string[-4:])                else:                    raise ValueError            elif i == 2 or i == 3:                # r'(\d\d)-?Q(\d)'                if date_len == 4 or (date_len == 5                                     and date_string[i - 1] == "-"):                    # i.e. quarter = int(date_string[-1])                    quarter = _parse_1digit(buf + date_len - 1)                    year = 2000 + int(date_string[:2])                else:                    raise ValueError            elif i == 4 or i == 5:                if date_len == 6 or (date_len == 7                                     and date_string[i - 1] == "-"):                    # r'(\d\d\d\d)-?Q(\d)'                    # i.e. quarter = int(date_string[-1])                    quarter = _parse_1digit(buf + date_len - 1)                    year = int(date_string[:4])                else:                    raise ValueError            if not (1 <= quarter <= 4):                raise DateParseError(f"Incorrect quarterly string is given, "                                     f"quarter must be "                                     f"between 1 and 4: {date_string}")            try:                # GH#1228                year, month = quarter_to_myear(year, quarter, freq)            except KeyError:                raise DateParseError("Unable to retrieve month "                                     "information from given "                                     f"freq: {freq}")            ret = default.replace(year=year, month=month)            # Monthly is as close as we can get to a non-existent NPY_FR_Q            out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_M            is_quarter[0] = 1            return ret        except DateParseError:            raise        except ValueError:            # e.g. if "Q" is not in date_string and .index raised            pass    if date_len == 6 and freq == "M":        year = int(date_string[:4])        month = int(date_string[4:6])        try:            ret = default.replace(year=year, month=month)            out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_M            return ret        except ValueError as err:            # We can infer that none of the patterns below will match            raise ValueError(f"Unable to parse {date_string}") from err    for pat in ["%Y-%m", "%b %Y", "%b-%Y"]:        try:            ret = datetime.strptime(date_string, pat)            out_bestunit[0] = NPY_DATETIMEUNIT.NPY_FR_M            return ret        except ValueError:            pass    raise ValueError(f"Unable to parse {date_string}")cpdef quarter_to_myear(int year, int quarter, str freq):    """    A quarterly frequency defines a "year" which may not coincide with    the calendar-year.  Find the calendar-year and calendar-month associated    with the given year and quarter under the `freq`-derived calendar.    Parameters    ----------    year : int    quarter : int    freq : str or None    Returns    -------    year : int    month : int    See Also    --------    Period.qyear    """    if quarter <= 0 or quarter > 4:        raise ValueError("Quarter must be 1 <= q <= 4")    if freq is not None:        mnum = c_MONTH_NUMBERS[get_rule_month(freq)] + 1        month = (mnum + (quarter - 1) * 3) % 12 + 1        if month > mnum:            year -= 1    else:        month = (quarter - 1) * 3 + 1    return year, monthcdef datetime dateutil_parse(    str timestr,    datetime default,    bint ignoretz,    bint dayfirst,    bint yearfirst,    NPY_DATETIMEUNIT* out_bestunit):    """ lifted from dateutil to get resolution"""    cdef:        str attr        datetime ret        object res        str reso = None        dict repl = {}    try:        res, _ = DEFAULTPARSER._parse(timestr, dayfirst=dayfirst, yearfirst=yearfirst)    except InvalidOperation:        # GH#51157 dateutil can raise decimal.InvalidOperation        res = None    if res is None:        raise DateParseError(            f"Unknown datetime string format, unable to parse: {timestr}"        )    for attr in ["year", "month", "day", "hour",                 "minute", "second", "microsecond"]:        value = getattr(res, attr)        if value is not None:            repl[attr] = value            reso = attr    if reso is None:        raise DateParseError(f"Unable to parse datetime string: {timestr}")    if reso == "microsecond":        if repl["microsecond"] == 0:            reso = "second"        elif repl["microsecond"] % 1000 == 0:            reso = "millisecond"    try:        ret = default.replace(**repl)    except ValueError as err:        # e.g. "day is out of range for month"        # we re-raise to match dateutil's exception message        raise DateParseError(str(err) + ": " + timestr) from err    except OverflowError as err:        # with e.g. "08335394550" dateutil raises when trying to pass        #  year=8335394550 to datetime.replace        raise OutOfBoundsDatetime(            f'Parsing "{timestr}" to datetime overflows'        ) from err    if res.weekday is not None and not res.day:        ret = ret + relativedelta.relativedelta(weekday=res.weekday)    if not ignoretz:        if res.tzname and res.tzname in time.tzname:            # GH#50791            if res.tzname != "UTC":                # If the system is localized in UTC (as many CI runs are)                #  we get tzlocal, once the deprecation is enforced will get                #  timezone.utc, not raise.                warnings.warn(                    "Parsing '{res.tzname}' as tzlocal (dependent on system timezone) "                    "is deprecated and will raise in a future version. Pass the 'tz' "                    "keyword or call tz_localize after construction instead",                    FutureWarning,                    stacklevel=find_stack_level()                )            ret = ret.replace(tzinfo=_dateutil_tzlocal())        elif res.tzoffset == 0:            ret = ret.replace(tzinfo=_dateutil_tzutc())        elif res.tzoffset:            ret = ret.replace(tzinfo=tzoffset(res.tzname, res.tzoffset))            # dateutil can return a datetime with a tzoffset outside of (-24H, 24H)            #  bounds, which is invalid (can be constructed, but raises if we call            #  str(ret)).  Check that and raise here if necessary.            try:                ret.utcoffset()            except ValueError as err:                # offset must be a timedelta strictly between -timedelta(hours=24)                #  and timedelta(hours=24)                raise ValueError(                    f'Parsed string "{timestr}" gives an invalid tzoffset, '                    "which must be between -timedelta(hours=24) and timedelta(hours=24)"                )    out_bestunit[0] = attrname_to_npy_unit[reso]    return ret# ----------------------------------------------------------------------# Parsing for type-inferencedef try_parse_dates(object[:] values, parser) -> np.ndarray:    cdef:        Py_ssize_t i, n        object[::1] result    n = len(values)    result = np.empty(n, dtype="O")    for i in range(n):        if values[i] == "":            result[i] = np.nan        else:            result[i] = parser(values[i])    return result.base  # .base to access underlying ndarraydef try_parse_year_month_day(    object[:] years, object[:] months, object[:] days) -> np.ndarray:    cdef:        Py_ssize_t i, n        object[::1] result    n = len(years)    # TODO(cython3): Use len instead of `shape[0]`    if months.shape[0] != n or days.shape[0] != n:        raise ValueError("Length of years/months/days must all be equal")    result = np.empty(n, dtype="O")    for i in range(n):        result[i] = datetime(int(years[i]), int(months[i]), int(days[i]))    return result.base  # .base to access underlying ndarray# ----------------------------------------------------------------------# Miscellaneous# Class copied verbatim from https://github.com/dateutil/dateutil/pull/732## We use this class to parse and tokenize date strings. However, as it is# a private class in the dateutil library, relying on backwards compatibility# is not practical. In fact, using this class issues warnings (xref gh-21322).# Thus, we port the class over so that both issues are resolved.## Copyright (c) 2017 - dateutil contributorsclass _timelex:    def __init__(self, instream):        if getattr(instream, "decode", None) is not None:            instream = instream.decode()        if isinstance(instream, str):            self.stream = instream        elif getattr(instream, "read", None) is None:            raise TypeError(                "Parser must be a string or character stream, not "                f"{type(instream).__name__}")        else:            self.stream = instream.read()    def get_tokens(self):        """        This function breaks the time string into lexical units (tokens), which        can be parsed by the parser. Lexical units are demarcated by changes in        the character set, so any continuous string of letters is considered        one unit, any continuous string of numbers is considered one unit.        The main complication arises from the fact that dots ('.') can be used        both as separators (e.g. "Sep.20.2009") or decimal points (e.g.        "4:30:21.447"). As such, it is necessary to read the full context of        any dot-separated strings before breaking it into tokens; as such, this        function maintains a "token stack", for when the ambiguous context        demands that multiple tokens be parsed at once.        """        cdef:            Py_ssize_t n        stream = self.stream.replace("\x00", "")        # TODO: Change \s --> \s+ (this doesn't match existing behavior)        # TODO: change the punctuation block to punc+ (does not match existing)        # TODO: can we merge the two digit patterns?        tokens = re.findall(r"\s|"                            r"(?<![\.\d])\d+\.\d+(?![\.\d])"                            r"|\d+"                            r"|[a-zA-Z]+"                            r"|[\./:]+"                            r"|[^\da-zA-Z\./:\s]+", stream)        # Re-combine token tuples of the form ["59", ",", "456"] because        # in this context the "," is treated as a decimal        # (e.g. in python's default logging format)        for n, token in enumerate(tokens[:-2]):            # Kludge to match ,-decimal behavior; it'd be better to do this            # later in the process and have a simpler tokenization            if (token is not None and token.isdigit() and                    tokens[n + 1] == "," and tokens[n + 2].isdigit()):                # Have to check None b/c it might be replaced during the loop                # TODO: I _really_ don't faking the value here                tokens[n] = token + "." + tokens[n + 2]                tokens[n + 1] = None                tokens[n + 2] = None        tokens = [x for x in tokens if x is not None]        return tokens    @classmethod    def split(cls, s):        return cls(s).get_tokens()_DATEUTIL_LEXER_SPLIT = _timelex.splitdef guess_datetime_format(dt_str: str, bint dayfirst=False) -> str | None:    """    Guess the datetime format of a given datetime string.    Parameters    ----------    dt_str : str        Datetime string to guess the format of.    dayfirst : bool, default False        If True parses dates with the day first, eg 20/01/2005        Warning: dayfirst=True is not strict, but will prefer to parse        with day first (this is a known bug).    Returns    -------    str or None : ret        datetime format string (for `strftime` or `strptime`),        or None if it can't be guessed.    """    day_attribute_and_format = (("day",), "%d", 2)    # attr name, format, padding (if any)    datetime_attrs_to_format = [        (("year", "month", "day", "hour", "minute", "second"), "%Y%m%d%H%M%S", 0),        (("year", "month", "day", "hour", "minute"), "%Y%m%d%H%M", 0),        (("year", "month", "day", "hour"), "%Y%m%d%H", 0),        (("year", "month", "day"), "%Y%m%d", 0),        (("hour", "minute", "second"), "%H%M%S", 0),        (("hour", "minute"), "%H%M", 0),        (("year",), "%Y", 0),        (("month",), "%B", 0),        (("month",), "%b", 0),        (("month",), "%m", 2),        day_attribute_and_format,        (("hour",), "%H", 2),        (("minute",), "%M", 2),        (("second",), "%S", 2),        (("second", "microsecond"), "%S.%f", 0),        (("tzinfo",), "%z", 0),        (("tzinfo",), "%Z", 0),        (("day_of_week",), "%a", 0),        (("day_of_week",), "%A", 0),        (("meridiem",), "%p", 0),    ]    if dayfirst:        datetime_attrs_to_format.remove(day_attribute_and_format)        datetime_attrs_to_format.insert(0, day_attribute_and_format)    try:        parsed_datetime = du_parse(dt_str, dayfirst=dayfirst)    except (ValueError, OverflowError, InvalidOperation):        # In case the datetime can't be parsed, its format cannot be guessed        return None    if parsed_datetime is None:        return None    # _DATEUTIL_LEXER_SPLIT from dateutil will never raise here    tokens = _DATEUTIL_LEXER_SPLIT(dt_str)    # Normalize offset part of tokens.    # There are multiple formats for the timezone offset.    # To pass the comparison condition between the output of `strftime` and    # joined tokens, which is carried out at the final step of the function,    # the offset part of the tokens must match the '%z' format like '+0900'    # instead of ‘+09:00’.    if parsed_datetime.tzinfo is not None:        offset_index = None        if len(tokens) > 0 and tokens[-1] == "Z":            # the last 'Z' means zero offset            offset_index = -1        elif len(tokens) > 1 and tokens[-2] in ("+", "-"):            # ex. [..., '+', '0900']            offset_index = -2        elif len(tokens) > 3 and tokens[-4] in ("+", "-"):            # ex. [..., '+', '09', ':', '00']            offset_index = -4        if offset_index is not None:            # If the input string has a timezone offset like '+0900',            # the offset is separated into two tokens, ex. ['+', '0900’].            # This separation will prevent subsequent processing            # from correctly parsing the time zone format.            # So in addition to the format nomalization, we rejoin them here.            try:                tokens[offset_index] = parsed_datetime.strftime("%z")            except ValueError:                # Invalid offset might not have raised in du_parse                # https://github.com/dateutil/dateutil/issues/188                return None            tokens = tokens[:offset_index + 1 or None]    format_guess = [None] * len(tokens)    found_attrs = set()    for attrs, attr_format, padding in datetime_attrs_to_format:        # If a given attribute has been placed in the format string, skip        # over other formats for that same underlying attribute (IE, month        # can be represented in multiple different ways)        if set(attrs) & found_attrs:            continue        if parsed_datetime.tzinfo is None and attr_format in ("%Z", "%z"):            continue        parsed_formatted = parsed_datetime.strftime(attr_format)        for i, token_format in enumerate(format_guess):            token_filled = _fill_token(tokens[i], padding)            if token_format is None and token_filled == parsed_formatted:                format_guess[i] = attr_format                tokens[i] = token_filled                found_attrs.update(attrs)                break    # Only consider it a valid guess if we have a year, month and day.    # We make exceptions for %Y and %Y-%m (only with the `-` separator)    # as they conform with ISO8601.    if (        len({"year", "month", "day"} & found_attrs) != 3        and format_guess != ["%Y"]        and not (            format_guess == ["%Y", None, "%m"] and tokens[1] == "-"        )    ):        return None    output_format = []    for i, guess in enumerate(format_guess):        if guess is not None:            # Either fill in the format placeholder (like %Y)            output_format.append(guess)        else:            # Or just the token separate (IE, the dashes in "01-01-2013")            try:                # If the token is numeric, then we likely didn't parse it                # properly, so our guess is wrong                float(tokens[i])                return None            except ValueError:                pass            output_format.append(tokens[i])    # if am/pm token present, replace 24-hour %H, with 12-hour %I    if "%p" in output_format and "%H" in output_format:        i = output_format.index("%H")        output_format[i] = "%I"    guessed_format = "".join(output_format)    try:        array_strptime(np.asarray([dt_str], dtype=object), guessed_format)    except ValueError:        # Doesn't parse, so this can't be the correct format.        return None    # rebuild string, capturing any inferred padding    dt_str = "".join(tokens)    if parsed_datetime.strftime(guessed_format) == dt_str:        _maybe_warn_about_dayfirst(guessed_format, dayfirst)        return guessed_format    else:        return Nonecdef str _fill_token(token: str, padding: int):    cdef str token_filled    if re.search(r"\d+\.\d+", token) is None:        # For example: 98        token_filled = token.zfill(padding)    else:        # For example: 00.123        seconds, nanoseconds = token.split(".")        seconds = f"{int(seconds):02d}"        # right-pad so we get nanoseconds, then only take        # first 6 digits (microseconds) as stdlib datetime        # doesn't support nanoseconds        nanoseconds = nanoseconds.ljust(9, "0")[:6]        token_filled = f"{seconds}.{nanoseconds}"    return token_filledcdef void _maybe_warn_about_dayfirst(format: str, bint dayfirst):    """Warn if guessed datetime format doesn't respect dayfirst argument."""    cdef:        int day_index = format.find("%d")        int month_index = format.find("%m")    if (day_index != -1) and (month_index != -1):        if (day_index > month_index) and dayfirst:            warnings.warn(                f"Parsing dates in {format} format when dayfirst=True was specified. "                "Pass `dayfirst=False` or specify a format to silence this warning.",                UserWarning,                stacklevel=find_stack_level(),            )        if (day_index < month_index) and not dayfirst:            warnings.warn(                f"Parsing dates in {format} format when dayfirst=False (the default) "                "was specified. "                "Pass `dayfirst=True` or specify a format to silence this warning.",                UserWarning,                stacklevel=find_stack_level(),            )@cython.wraparound(False)@cython.boundscheck(False)cdef object convert_to_unicode(object item, bint keep_trivial_numbers):    """    Convert `item` to str.    Parameters    ----------    item : object    keep_trivial_numbers : bool        if True, then conversion (to string from integer/float zero)        is not performed    Returns    -------    str or int or float    """    cdef:        float64_t float_item    if keep_trivial_numbers:        if isinstance(item, int):            if <int>item == 0:                return item        elif isinstance(item, float):            float_item = item            if float_item == 0.0 or float_item != float_item:                return item    if not isinstance(item, str):        item = PyObject_Str(item)    return item@cython.wraparound(False)@cython.boundscheck(False)def concat_date_cols(tuple date_cols) -> np.ndarray:    """    Concatenates elements from numpy arrays in `date_cols` into strings.    Parameters    ----------    date_cols : tuple[ndarray]    Returns    -------    arr_of_rows : ndarray[object]    Examples    --------    >>> dates=np.array(['3/31/2019', '4/31/2019'], dtype=object)    >>> times=np.array(['11:20', '10:45'], dtype=object)    >>> result = concat_date_cols((dates, times))    >>> result    array(['3/31/2019 11:20', '4/31/2019 10:45'], dtype=object)    """    cdef:        Py_ssize_t rows_count = 0, col_count = len(date_cols)        Py_ssize_t col_idx, row_idx        list list_to_join        cnp.ndarray[object] iters        object[::1] iters_view        flatiter it        cnp.ndarray[object] result        object[::1] result_view    if col_count == 0:        return np.zeros(0, dtype=object)    if not all(is_array(array) for array in date_cols):        raise ValueError("not all elements from date_cols are numpy arrays")    rows_count = min(len(array) for array in date_cols)    result = np.zeros(rows_count, dtype=object)    result_view = result    if col_count == 1:        array = date_cols[0]        it = <flatiter>PyArray_IterNew(array)        for row_idx in range(rows_count):            item = PyArray_GETITEM(array, PyArray_ITER_DATA(it))            result_view[row_idx] = convert_to_unicode(item, True)            PyArray_ITER_NEXT(it)    else:        # create fixed size list - more efficient memory allocation        list_to_join = [None] * col_count        iters = np.zeros(col_count, dtype=object)        # create memoryview of iters ndarray, that will contain some        # flatiter's for each array in `date_cols` - more efficient indexing        iters_view = iters        for col_idx, array in enumerate(date_cols):            iters_view[col_idx] = PyArray_IterNew(array)        # array elements that are on the same line are converted to one string        for row_idx in range(rows_count):            for col_idx, array in enumerate(date_cols):                # this cast is needed, because we did not find a way                # to efficiently store `flatiter` type objects in ndarray                it = <flatiter>iters_view[col_idx]                item = PyArray_GETITEM(array, PyArray_ITER_DATA(it))                list_to_join[col_idx] = convert_to_unicode(item, False)                PyArray_ITER_NEXT(it)            result_view[row_idx] = " ".join(list_to_join)    return resultcpdef str get_rule_month(str source):    """    Return starting month of given freq, default is December.    Parameters    ----------    source : str        Derived from `freq.rule_code` or `freq.freqstr`.    Returns    -------    rule_month: str    Examples    --------    >>> get_rule_month('D')    'DEC'    >>> get_rule_month('A-JAN')    'JAN'    """    source = source.upper()    if "-" not in source:        return "DEC"    else:        return source.split("-")[1]
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