""" Parsing functions for datetime and datetime-like strings. """ import re import time import warnings from pandas.util._exceptions import find_stack_level cimport cython from cpython.datetime cimport ( datetime, datetime_new, import_datetime, timedelta, tzinfo, ) from datetime import timezone from cpython.object cimport PyObject_Str from cython cimport Py_ssize_t from libc.string cimport strchr import_datetime() import numpy as np cimport numpy as cnp from numpy cimport ( PyArray_GETITEM, PyArray_ITER_DATA, PyArray_ITER_NEXT, PyArray_IterNew, flatiter, float64_t, ) cnp.import_array() # dateutil compat from decimal import InvalidOperation from dateutil.parser import ( DEFAULTPARSER, parse as du_parse, ) from dateutil.relativedelta import relativedelta from dateutil.tz import ( tzlocal as _dateutil_tzlocal, tzoffset, tzutc as _dateutil_tzutc, ) from pandas._config import get_option from pandas._libs.tslibs.ccalendar cimport c_MONTH_NUMBERS from 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 OutOfBoundsDatetime from pandas._libs.tslibs.np_datetime cimport ( NPY_DATETIMEUNIT, npy_datetimestruct, string_to_dts, ) from pandas._libs.tslibs.strptime import array_strptime from 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) nogil cdef 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) # ---------------------------------------------------------------------- # Constants class 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 = 12 cdef bint _is_delimiter(const char ch): return strchr(delimiters, ch) != NULL cdef int _parse_1digit(const char* s): cdef int result = 0 result += getdigit_ascii(s[0], -10) * 1 return result cdef 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 result cdef 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 result cdef 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 <= 59 def 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 dt def 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, reso cpdef 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 True cdef 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, month cdef 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-inference def 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 ndarray def 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 contributors class _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"(? 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 None cdef 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_filled cdef 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 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 = 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 = 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 result cpdef 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]