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classmethod datetime.combine(date, time, tzinfo=self.tzinfo)
Return a new datetime object whose date components are equal to the given date object’s, and whose time components are equal to the given time object’s. If the tzinfo argument is provided, its value is used to set the tzinfo attribute of the result, otherwise the tzinfo attribute of the time argument is used. For any datetime object d, d == datetime.combine(d.date(), d.time(), d.tzinfo). If date is a datetime object, its time components and tzinfo attributes are ignored. Changed in version 3.6: Added the tzinfo argument. | python.library.datetime#datetime.datetime.combine |
datetime.ctime()
Return a string representing the date and time: >>> from datetime import datetime
>>> datetime(2002, 12, 4, 20, 30, 40).ctime()
'Wed Dec 4 20:30:40 2002'
The output string will not include time zone information, regardless of whether the input is aware or naive. d.ctime() is equivalent to: time.ctime(time.mktime(d.timetuple()))
on platforms where the native C ctime() function (which time.ctime() invokes, but which datetime.ctime() does not invoke) conforms to the C standard. | python.library.datetime#datetime.datetime.ctime |
datetime.date()
Return date object with same year, month and day. | python.library.datetime#datetime.datetime.date |
datetime.day
Between 1 and the number of days in the given month of the given year. | python.library.datetime#datetime.datetime.day |
datetime.dst()
If tzinfo is None, returns None, else returns self.tzinfo.dst(self), and raises an exception if the latter doesn’t return None or a timedelta object with magnitude less than one day. Changed in version 3.7: The DST offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.datetime.dst |
datetime.fold
In [0, 1]. Used to disambiguate wall times during a repeated interval. (A repeated interval occurs when clocks are rolled back at the end of daylight saving time or when the UTC offset for the current zone is decreased for political reasons.) The value 0 (1) represents the earlier (later) of the two moments with the same wall time representation. New in version 3.6. | python.library.datetime#datetime.datetime.fold |
classmethod datetime.fromisocalendar(year, week, day)
Return a datetime corresponding to the ISO calendar date specified by year, week and day. The non-date components of the datetime are populated with their normal default values. This is the inverse of the function datetime.isocalendar(). New in version 3.8. | python.library.datetime#datetime.datetime.fromisocalendar |
classmethod datetime.fromisoformat(date_string)
Return a datetime corresponding to a date_string in one of the formats emitted by date.isoformat() and datetime.isoformat(). Specifically, this function supports strings in the format: YYYY-MM-DD[*HH[:MM[:SS[.fff[fff]]]][+HH:MM[:SS[.ffffff]]]]
where * can match any single character. Caution This does not support parsing arbitrary ISO 8601 strings - it is only intended as the inverse operation of datetime.isoformat(). A more full-featured ISO 8601 parser, dateutil.parser.isoparse is available in the third-party package dateutil. Examples: >>> from datetime import datetime
>>> datetime.fromisoformat('2011-11-04')
datetime.datetime(2011, 11, 4, 0, 0)
>>> datetime.fromisoformat('2011-11-04T00:05:23')
datetime.datetime(2011, 11, 4, 0, 5, 23)
>>> datetime.fromisoformat('2011-11-04 00:05:23.283')
datetime.datetime(2011, 11, 4, 0, 5, 23, 283000)
>>> datetime.fromisoformat('2011-11-04 00:05:23.283+00:00')
datetime.datetime(2011, 11, 4, 0, 5, 23, 283000, tzinfo=datetime.timezone.utc)
>>> datetime.fromisoformat('2011-11-04T00:05:23+04:00')
datetime.datetime(2011, 11, 4, 0, 5, 23,
tzinfo=datetime.timezone(datetime.timedelta(seconds=14400)))
New in version 3.7. | python.library.datetime#datetime.datetime.fromisoformat |
classmethod datetime.fromordinal(ordinal)
Return the datetime corresponding to the proleptic Gregorian ordinal, where January 1 of year 1 has ordinal 1. ValueError is raised unless 1
<= ordinal <= datetime.max.toordinal(). The hour, minute, second and microsecond of the result are all 0, and tzinfo is None. | python.library.datetime#datetime.datetime.fromordinal |
classmethod datetime.fromtimestamp(timestamp, tz=None)
Return the local date and time corresponding to the POSIX timestamp, such as is returned by time.time(). If optional argument tz is None or not specified, the timestamp is converted to the platform’s local date and time, and the returned datetime object is naive. If tz is not None, it must be an instance of a tzinfo subclass, and the timestamp is converted to tz’s time zone. fromtimestamp() may raise OverflowError, if the timestamp is out of the range of values supported by the platform C localtime() or gmtime() functions, and OSError on localtime() or gmtime() failure. It’s common for this to be restricted to years in 1970 through 2038. Note that on non-POSIX systems that include leap seconds in their notion of a timestamp, leap seconds are ignored by fromtimestamp(), and then it’s possible to have two timestamps differing by a second that yield identical datetime objects. This method is preferred over utcfromtimestamp(). Changed in version 3.3: Raise OverflowError instead of ValueError if the timestamp is out of the range of values supported by the platform C localtime() or gmtime() functions. Raise OSError instead of ValueError on localtime() or gmtime() failure. Changed in version 3.6: fromtimestamp() may return instances with fold set to 1. | python.library.datetime#datetime.datetime.fromtimestamp |
datetime.hour
In range(24). | python.library.datetime#datetime.datetime.hour |
datetime.isocalendar()
Return a named tuple with three components: year, week and weekday. The same as self.date().isocalendar(). | python.library.datetime#datetime.datetime.isocalendar |
datetime.isoformat(sep='T', timespec='auto')
Return a string representing the date and time in ISO 8601 format:
YYYY-MM-DDTHH:MM:SS.ffffff, if microsecond is not 0
YYYY-MM-DDTHH:MM:SS, if microsecond is 0 If utcoffset() does not return None, a string is appended, giving the UTC offset:
YYYY-MM-DDTHH:MM:SS.ffffff+HH:MM[:SS[.ffffff]], if microsecond is not 0
YYYY-MM-DDTHH:MM:SS+HH:MM[:SS[.ffffff]], if microsecond is 0 Examples: >>> from datetime import datetime, timezone
>>> datetime(2019, 5, 18, 15, 17, 8, 132263).isoformat()
'2019-05-18T15:17:08.132263'
>>> datetime(2019, 5, 18, 15, 17, tzinfo=timezone.utc).isoformat()
'2019-05-18T15:17:00+00:00'
The optional argument sep (default 'T') is a one-character separator, placed between the date and time portions of the result. For example: >>> from datetime import tzinfo, timedelta, datetime
>>> class TZ(tzinfo):
... """A time zone with an arbitrary, constant -06:39 offset."""
... def utcoffset(self, dt):
... return timedelta(hours=-6, minutes=-39)
...
>>> datetime(2002, 12, 25, tzinfo=TZ()).isoformat(' ')
'2002-12-25 00:00:00-06:39'
>>> datetime(2009, 11, 27, microsecond=100, tzinfo=TZ()).isoformat()
'2009-11-27T00:00:00.000100-06:39'
The optional argument timespec specifies the number of additional components of the time to include (the default is 'auto'). It can be one of the following:
'auto': Same as 'seconds' if microsecond is 0, same as 'microseconds' otherwise.
'hours': Include the hour in the two-digit HH format.
'minutes': Include hour and minute in HH:MM format.
'seconds': Include hour, minute, and second in HH:MM:SS format.
'milliseconds': Include full time, but truncate fractional second part to milliseconds. HH:MM:SS.sss format.
'microseconds': Include full time in HH:MM:SS.ffffff format. Note Excluded time components are truncated, not rounded. ValueError will be raised on an invalid timespec argument: >>> from datetime import datetime
>>> datetime.now().isoformat(timespec='minutes')
'2002-12-25T00:00'
>>> dt = datetime(2015, 1, 1, 12, 30, 59, 0)
>>> dt.isoformat(timespec='microseconds')
'2015-01-01T12:30:59.000000'
New in version 3.6: Added the timespec argument. | python.library.datetime#datetime.datetime.isoformat |
datetime.isoweekday()
Return the day of the week as an integer, where Monday is 1 and Sunday is 7. The same as self.date().isoweekday(). See also weekday(), isocalendar(). | python.library.datetime#datetime.datetime.isoweekday |
datetime.max
The latest representable datetime, datetime(MAXYEAR, 12, 31, 23, 59,
59, 999999, tzinfo=None). | python.library.datetime#datetime.datetime.max |
datetime.microsecond
In range(1000000). | python.library.datetime#datetime.datetime.microsecond |
datetime.min
The earliest representable datetime, datetime(MINYEAR, 1, 1,
tzinfo=None). | python.library.datetime#datetime.datetime.min |
datetime.minute
In range(60). | python.library.datetime#datetime.datetime.minute |
datetime.month
Between 1 and 12 inclusive. | python.library.datetime#datetime.datetime.month |
classmethod datetime.now(tz=None)
Return the current local date and time. If optional argument tz is None or not specified, this is like today(), but, if possible, supplies more precision than can be gotten from going through a time.time() timestamp (for example, this may be possible on platforms supplying the C gettimeofday() function). If tz is not None, it must be an instance of a tzinfo subclass, and the current date and time are converted to tz’s time zone. This function is preferred over today() and utcnow(). | python.library.datetime#datetime.datetime.now |
datetime.replace(year=self.year, month=self.month, day=self.day, hour=self.hour, minute=self.minute, second=self.second, microsecond=self.microsecond, tzinfo=self.tzinfo, *, fold=0)
Return a datetime with the same attributes, except for those attributes given new values by whichever keyword arguments are specified. Note that tzinfo=None can be specified to create a naive datetime from an aware datetime with no conversion of date and time data. New in version 3.6: Added the fold argument. | python.library.datetime#datetime.datetime.replace |
datetime.resolution
The smallest possible difference between non-equal datetime objects, timedelta(microseconds=1). | python.library.datetime#datetime.datetime.resolution |
datetime.second
In range(60). | python.library.datetime#datetime.datetime.second |
datetime.strftime(format)
Return a string representing the date and time, controlled by an explicit format string. For a complete list of formatting directives, see strftime() and strptime() Behavior. | python.library.datetime#datetime.datetime.strftime |
classmethod datetime.strptime(date_string, format)
Return a datetime corresponding to date_string, parsed according to format. This is equivalent to: datetime(*(time.strptime(date_string, format)[0:6]))
ValueError is raised if the date_string and format can’t be parsed by time.strptime() or if it returns a value which isn’t a time tuple. For a complete list of formatting directives, see strftime() and strptime() Behavior. | python.library.datetime#datetime.datetime.strptime |
datetime.time()
Return time object with same hour, minute, second, microsecond and fold. tzinfo is None. See also method timetz(). Changed in version 3.6: The fold value is copied to the returned time object. | python.library.datetime#datetime.datetime.time |
datetime.timestamp()
Return POSIX timestamp corresponding to the datetime instance. The return value is a float similar to that returned by time.time(). Naive datetime instances are assumed to represent local time and this method relies on the platform C mktime() function to perform the conversion. Since datetime supports wider range of values than mktime() on many platforms, this method may raise OverflowError for times far in the past or far in the future. For aware datetime instances, the return value is computed as: (dt - datetime(1970, 1, 1, tzinfo=timezone.utc)).total_seconds()
New in version 3.3. Changed in version 3.6: The timestamp() method uses the fold attribute to disambiguate the times during a repeated interval. Note There is no method to obtain the POSIX timestamp directly from a naive datetime instance representing UTC time. If your application uses this convention and your system timezone is not set to UTC, you can obtain the POSIX timestamp by supplying tzinfo=timezone.utc: timestamp = dt.replace(tzinfo=timezone.utc).timestamp()
or by calculating the timestamp directly: timestamp = (dt - datetime(1970, 1, 1)) / timedelta(seconds=1) | python.library.datetime#datetime.datetime.timestamp |
datetime.timetuple()
Return a time.struct_time such as returned by time.localtime(). d.timetuple() is equivalent to: time.struct_time((d.year, d.month, d.day,
d.hour, d.minute, d.second,
d.weekday(), yday, dst))
where yday = d.toordinal() - date(d.year, 1, 1).toordinal() + 1 is the day number within the current year starting with 1 for January 1st. The tm_isdst flag of the result is set according to the dst() method: tzinfo is None or dst() returns None, tm_isdst is set to -1; else if dst() returns a non-zero value, tm_isdst is set to 1; else tm_isdst is set to 0. | python.library.datetime#datetime.datetime.timetuple |
datetime.timetz()
Return time object with same hour, minute, second, microsecond, fold, and tzinfo attributes. See also method time(). Changed in version 3.6: The fold value is copied to the returned time object. | python.library.datetime#datetime.datetime.timetz |
classmethod datetime.today()
Return the current local datetime, with tzinfo None. Equivalent to: datetime.fromtimestamp(time.time())
See also now(), fromtimestamp(). This method is functionally equivalent to now(), but without a tz parameter. | python.library.datetime#datetime.datetime.today |
datetime.toordinal()
Return the proleptic Gregorian ordinal of the date. The same as self.date().toordinal(). | python.library.datetime#datetime.datetime.toordinal |
datetime.tzinfo
The object passed as the tzinfo argument to the datetime constructor, or None if none was passed. | python.library.datetime#datetime.datetime.tzinfo |
datetime.tzname()
If tzinfo is None, returns None, else returns self.tzinfo.tzname(self), raises an exception if the latter doesn’t return None or a string object, | python.library.datetime#datetime.datetime.tzname |
classmethod datetime.utcfromtimestamp(timestamp)
Return the UTC datetime corresponding to the POSIX timestamp, with tzinfo None. (The resulting object is naive.) This may raise OverflowError, if the timestamp is out of the range of values supported by the platform C gmtime() function, and OSError on gmtime() failure. It’s common for this to be restricted to years in 1970 through 2038. To get an aware datetime object, call fromtimestamp(): datetime.fromtimestamp(timestamp, timezone.utc)
On the POSIX compliant platforms, it is equivalent to the following expression: datetime(1970, 1, 1, tzinfo=timezone.utc) + timedelta(seconds=timestamp)
except the latter formula always supports the full years range: between MINYEAR and MAXYEAR inclusive. Warning Because naive datetime objects are treated by many datetime methods as local times, it is preferred to use aware datetimes to represent times in UTC. As such, the recommended way to create an object representing a specific timestamp in UTC is by calling datetime.fromtimestamp(timestamp, tz=timezone.utc). Changed in version 3.3: Raise OverflowError instead of ValueError if the timestamp is out of the range of values supported by the platform C gmtime() function. Raise OSError instead of ValueError on gmtime() failure. | python.library.datetime#datetime.datetime.utcfromtimestamp |
classmethod datetime.utcnow()
Return the current UTC date and time, with tzinfo None. This is like now(), but returns the current UTC date and time, as a naive datetime object. An aware current UTC datetime can be obtained by calling datetime.now(timezone.utc). See also now(). Warning Because naive datetime objects are treated by many datetime methods as local times, it is preferred to use aware datetimes to represent times in UTC. As such, the recommended way to create an object representing the current time in UTC is by calling datetime.now(timezone.utc). | python.library.datetime#datetime.datetime.utcnow |
datetime.utcoffset()
If tzinfo is None, returns None, else returns self.tzinfo.utcoffset(self), and raises an exception if the latter doesn’t return None or a timedelta object with magnitude less than one day. Changed in version 3.7: The UTC offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.datetime.utcoffset |
datetime.utctimetuple()
If datetime instance d is naive, this is the same as d.timetuple() except that tm_isdst is forced to 0 regardless of what d.dst() returns. DST is never in effect for a UTC time. If d is aware, d is normalized to UTC time, by subtracting d.utcoffset(), and a time.struct_time for the normalized time is returned. tm_isdst is forced to 0. Note that an OverflowError may be raised if d.year was MINYEAR or MAXYEAR and UTC adjustment spills over a year boundary. Warning Because naive datetime objects are treated by many datetime methods as local times, it is preferred to use aware datetimes to represent times in UTC; as a result, using utcfromtimetuple may give misleading results. If you have a naive datetime representing UTC, use datetime.replace(tzinfo=timezone.utc) to make it aware, at which point you can use datetime.timetuple(). | python.library.datetime#datetime.datetime.utctimetuple |
datetime.weekday()
Return the day of the week as an integer, where Monday is 0 and Sunday is 6. The same as self.date().weekday(). See also isoweekday(). | python.library.datetime#datetime.datetime.weekday |
datetime.year
Between MINYEAR and MAXYEAR inclusive. | python.library.datetime#datetime.datetime.year |
datetime.__format__(format)
Same as datetime.strftime(). This makes it possible to specify a format string for a datetime object in formatted string literals and when using str.format(). For a complete list of formatting directives, see strftime() and strptime() Behavior. | python.library.datetime#datetime.datetime.__format__ |
datetime.__str__()
For a datetime instance d, str(d) is equivalent to d.isoformat(' '). | python.library.datetime#datetime.datetime.__str__ |
datetime.MAXYEAR
The largest year number allowed in a date or datetime object. MAXYEAR is 9999. | python.library.datetime#datetime.MAXYEAR |
datetime.MINYEAR
The smallest year number allowed in a date or datetime object. MINYEAR is 1. | python.library.datetime#datetime.MINYEAR |
class datetime.time(hour=0, minute=0, second=0, microsecond=0, tzinfo=None, *, fold=0)
All arguments are optional. tzinfo may be None, or an instance of a tzinfo subclass. The remaining arguments must be integers in the following ranges:
0 <= hour < 24,
0 <= minute < 60,
0 <= second < 60,
0 <= microsecond < 1000000,
fold in [0, 1]. If an argument outside those ranges is given, ValueError is raised. All default to 0 except tzinfo, which defaults to None. | python.library.datetime#datetime.time |
time.dst()
If tzinfo is None, returns None, else returns self.tzinfo.dst(None), and raises an exception if the latter doesn’t return None, or a timedelta object with magnitude less than one day. Changed in version 3.7: The DST offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.time.dst |
time.fold
In [0, 1]. Used to disambiguate wall times during a repeated interval. (A repeated interval occurs when clocks are rolled back at the end of daylight saving time or when the UTC offset for the current zone is decreased for political reasons.) The value 0 (1) represents the earlier (later) of the two moments with the same wall time representation. New in version 3.6. | python.library.datetime#datetime.time.fold |
classmethod time.fromisoformat(time_string)
Return a time corresponding to a time_string in one of the formats emitted by time.isoformat(). Specifically, this function supports strings in the format: HH[:MM[:SS[.fff[fff]]]][+HH:MM[:SS[.ffffff]]]
Caution This does not support parsing arbitrary ISO 8601 strings. It is only intended as the inverse operation of time.isoformat(). Examples: >>> from datetime import time
>>> time.fromisoformat('04:23:01')
datetime.time(4, 23, 1)
>>> time.fromisoformat('04:23:01.000384')
datetime.time(4, 23, 1, 384)
>>> time.fromisoformat('04:23:01+04:00')
datetime.time(4, 23, 1, tzinfo=datetime.timezone(datetime.timedelta(seconds=14400)))
New in version 3.7. | python.library.datetime#datetime.time.fromisoformat |
time.hour
In range(24). | python.library.datetime#datetime.time.hour |
time.isoformat(timespec='auto')
Return a string representing the time in ISO 8601 format, one of:
HH:MM:SS.ffffff, if microsecond is not 0
HH:MM:SS, if microsecond is 0
HH:MM:SS.ffffff+HH:MM[:SS[.ffffff]], if utcoffset() does not return None
HH:MM:SS+HH:MM[:SS[.ffffff]], if microsecond is 0 and utcoffset() does not return None
The optional argument timespec specifies the number of additional components of the time to include (the default is 'auto'). It can be one of the following:
'auto': Same as 'seconds' if microsecond is 0, same as 'microseconds' otherwise.
'hours': Include the hour in the two-digit HH format.
'minutes': Include hour and minute in HH:MM format.
'seconds': Include hour, minute, and second in HH:MM:SS format.
'milliseconds': Include full time, but truncate fractional second part to milliseconds. HH:MM:SS.sss format.
'microseconds': Include full time in HH:MM:SS.ffffff format. Note Excluded time components are truncated, not rounded. ValueError will be raised on an invalid timespec argument. Example: >>> from datetime import time
>>> time(hour=12, minute=34, second=56, microsecond=123456).isoformat(timespec='minutes')
'12:34'
>>> dt = time(hour=12, minute=34, second=56, microsecond=0)
>>> dt.isoformat(timespec='microseconds')
'12:34:56.000000'
>>> dt.isoformat(timespec='auto')
'12:34:56'
New in version 3.6: Added the timespec argument. | python.library.datetime#datetime.time.isoformat |
time.max
The latest representable time, time(23, 59, 59, 999999). | python.library.datetime#datetime.time.max |
time.microsecond
In range(1000000). | python.library.datetime#datetime.time.microsecond |
time.min
The earliest representable time, time(0, 0, 0, 0). | python.library.datetime#datetime.time.min |
time.minute
In range(60). | python.library.datetime#datetime.time.minute |
time.replace(hour=self.hour, minute=self.minute, second=self.second, microsecond=self.microsecond, tzinfo=self.tzinfo, *, fold=0)
Return a time with the same value, except for those attributes given new values by whichever keyword arguments are specified. Note that tzinfo=None can be specified to create a naive time from an aware time, without conversion of the time data. New in version 3.6: Added the fold argument. | python.library.datetime#datetime.time.replace |
time.resolution
The smallest possible difference between non-equal time objects, timedelta(microseconds=1), although note that arithmetic on time objects is not supported. | python.library.datetime#datetime.time.resolution |
time.second
In range(60). | python.library.datetime#datetime.time.second |
time.strftime(format)
Return a string representing the time, controlled by an explicit format string. For a complete list of formatting directives, see strftime() and strptime() Behavior. | python.library.datetime#datetime.time.strftime |
time.tzinfo
The object passed as the tzinfo argument to the time constructor, or None if none was passed. | python.library.datetime#datetime.time.tzinfo |
time.tzname()
If tzinfo is None, returns None, else returns self.tzinfo.tzname(None), or raises an exception if the latter doesn’t return None or a string object. | python.library.datetime#datetime.time.tzname |
time.utcoffset()
If tzinfo is None, returns None, else returns self.tzinfo.utcoffset(None), and raises an exception if the latter doesn’t return None or a timedelta object with magnitude less than one day. Changed in version 3.7: The UTC offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.time.utcoffset |
time.__format__(format)
Same as time.strftime(). This makes it possible to specify a format string for a time object in formatted string literals and when using str.format(). For a complete list of formatting directives, see strftime() and strptime() Behavior. | python.library.datetime#datetime.time.__format__ |
time.__str__()
For a time t, str(t) is equivalent to t.isoformat(). | python.library.datetime#datetime.time.__str__ |
class datetime.timedelta(days=0, seconds=0, microseconds=0, milliseconds=0, minutes=0, hours=0, weeks=0)
All arguments are optional and default to 0. Arguments may be integers or floats, and may be positive or negative. Only days, seconds and microseconds are stored internally. Arguments are converted to those units: A millisecond is converted to 1000 microseconds. A minute is converted to 60 seconds. An hour is converted to 3600 seconds. A week is converted to 7 days. and days, seconds and microseconds are then normalized so that the representation is unique, with 0 <= microseconds < 1000000
0 <= seconds < 3600*24 (the number of seconds in one day) -999999999 <= days <= 999999999 The following example illustrates how any arguments besides days, seconds and microseconds are “merged” and normalized into those three resulting attributes: >>> from datetime import timedelta
>>> delta = timedelta(
... days=50,
... seconds=27,
... microseconds=10,
... milliseconds=29000,
... minutes=5,
... hours=8,
... weeks=2
... )
>>> # Only days, seconds, and microseconds remain
>>> delta
datetime.timedelta(days=64, seconds=29156, microseconds=10)
If any argument is a float and there are fractional microseconds, the fractional microseconds left over from all arguments are combined and their sum is rounded to the nearest microsecond using round-half-to-even tiebreaker. If no argument is a float, the conversion and normalization processes are exact (no information is lost). If the normalized value of days lies outside the indicated range, OverflowError is raised. Note that normalization of negative values may be surprising at first. For example: >>> from datetime import timedelta
>>> d = timedelta(microseconds=-1)
>>> (d.days, d.seconds, d.microseconds)
(-1, 86399, 999999) | python.library.datetime#datetime.timedelta |
timedelta.max
The most positive timedelta object, timedelta(days=999999999,
hours=23, minutes=59, seconds=59, microseconds=999999). | python.library.datetime#datetime.timedelta.max |
timedelta.min
The most negative timedelta object, timedelta(-999999999). | python.library.datetime#datetime.timedelta.min |
timedelta.resolution
The smallest possible difference between non-equal timedelta objects, timedelta(microseconds=1). | python.library.datetime#datetime.timedelta.resolution |
timedelta.total_seconds()
Return the total number of seconds contained in the duration. Equivalent to td / timedelta(seconds=1). For interval units other than seconds, use the division form directly (e.g. td / timedelta(microseconds=1)). Note that for very large time intervals (greater than 270 years on most platforms) this method will lose microsecond accuracy. New in version 3.2. | python.library.datetime#datetime.timedelta.total_seconds |
class datetime.timezone(offset, name=None)
The offset argument must be specified as a timedelta object representing the difference between the local time and UTC. It must be strictly between -timedelta(hours=24) and timedelta(hours=24), otherwise ValueError is raised. The name argument is optional. If specified it must be a string that will be used as the value returned by the datetime.tzname() method. New in version 3.2. Changed in version 3.7: The UTC offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.timezone |
timezone.dst(dt)
Always returns None. | python.library.datetime#datetime.timezone.dst |
timezone.fromutc(dt)
Return dt + offset. The dt argument must be an aware datetime instance, with tzinfo set to self. | python.library.datetime#datetime.timezone.fromutc |
timezone.tzname(dt)
Return the fixed value specified when the timezone instance is constructed. If name is not provided in the constructor, the name returned by tzname(dt) is generated from the value of the offset as follows. If offset is timedelta(0), the name is “UTC”, otherwise it is a string in the format UTC±HH:MM, where ± is the sign of offset, HH and MM are two digits of offset.hours and offset.minutes respectively. Changed in version 3.6: Name generated from offset=timedelta(0) is now plain ‘UTC’, not 'UTC+00:00'. | python.library.datetime#datetime.timezone.tzname |
timezone.utc
The UTC timezone, timezone(timedelta(0)). | python.library.datetime#datetime.timezone.utc |
timezone.utcoffset(dt)
Return the fixed value specified when the timezone instance is constructed. The dt argument is ignored. The return value is a timedelta instance equal to the difference between the local time and UTC. Changed in version 3.7: The UTC offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.timezone.utcoffset |
class datetime.tzinfo
This is an abstract base class, meaning that this class should not be instantiated directly. Define a subclass of tzinfo to capture information about a particular time zone. An instance of (a concrete subclass of) tzinfo can be passed to the constructors for datetime and time objects. The latter objects view their attributes as being in local time, and the tzinfo object supports methods revealing offset of local time from UTC, the name of the time zone, and DST offset, all relative to a date or time object passed to them. You need to derive a concrete subclass, and (at least) supply implementations of the standard tzinfo methods needed by the datetime methods you use. The datetime module provides timezone, a simple concrete subclass of tzinfo which can represent timezones with fixed offset from UTC such as UTC itself or North American EST and EDT. Special requirement for pickling: A tzinfo subclass must have an __init__() method that can be called with no arguments, otherwise it can be pickled but possibly not unpickled again. This is a technical requirement that may be relaxed in the future. A concrete subclass of tzinfo may need to implement the following methods. Exactly which methods are needed depends on the uses made of aware datetime objects. If in doubt, simply implement all of them. | python.library.datetime#datetime.tzinfo |
tzinfo.dst(dt)
Return the daylight saving time (DST) adjustment, as a timedelta object or None if DST information isn’t known. Return timedelta(0) if DST is not in effect. If DST is in effect, return the offset as a timedelta object (see utcoffset() for details). Note that DST offset, if applicable, has already been added to the UTC offset returned by utcoffset(), so there’s no need to consult dst() unless you’re interested in obtaining DST info separately. For example, datetime.timetuple() calls its tzinfo attribute’s dst() method to determine how the tm_isdst flag should be set, and tzinfo.fromutc() calls dst() to account for DST changes when crossing time zones. An instance tz of a tzinfo subclass that models both standard and daylight times must be consistent in this sense: tz.utcoffset(dt) - tz.dst(dt) must return the same result for every datetime dt with dt.tzinfo ==
tz For sane tzinfo subclasses, this expression yields the time zone’s “standard offset”, which should not depend on the date or the time, but only on geographic location. The implementation of datetime.astimezone() relies on this, but cannot detect violations; it’s the programmer’s responsibility to ensure it. If a tzinfo subclass cannot guarantee this, it may be able to override the default implementation of tzinfo.fromutc() to work correctly with astimezone() regardless. Most implementations of dst() will probably look like one of these two: def dst(self, dt):
# a fixed-offset class: doesn't account for DST
return timedelta(0)
or: def dst(self, dt):
# Code to set dston and dstoff to the time zone's DST
# transition times based on the input dt.year, and expressed
# in standard local time.
if dston <= dt.replace(tzinfo=None) < dstoff:
return timedelta(hours=1)
else:
return timedelta(0)
The default implementation of dst() raises NotImplementedError. Changed in version 3.7: The DST offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.tzinfo.dst |
tzinfo.fromutc(dt)
This is called from the default datetime.astimezone() implementation. When called from that, dt.tzinfo is self, and dt’s date and time data are to be viewed as expressing a UTC time. The purpose of fromutc() is to adjust the date and time data, returning an equivalent datetime in self’s local time. Most tzinfo subclasses should be able to inherit the default fromutc() implementation without problems. It’s strong enough to handle fixed-offset time zones, and time zones accounting for both standard and daylight time, and the latter even if the DST transition times differ in different years. An example of a time zone the default fromutc() implementation may not handle correctly in all cases is one where the standard offset (from UTC) depends on the specific date and time passed, which can happen for political reasons. The default implementations of astimezone() and fromutc() may not produce the result you want if the result is one of the hours straddling the moment the standard offset changes. Skipping code for error cases, the default fromutc() implementation acts like: def fromutc(self, dt):
# raise ValueError error if dt.tzinfo is not self
dtoff = dt.utcoffset()
dtdst = dt.dst()
# raise ValueError if dtoff is None or dtdst is None
delta = dtoff - dtdst # this is self's standard offset
if delta:
dt += delta # convert to standard local time
dtdst = dt.dst()
# raise ValueError if dtdst is None
if dtdst:
return dt + dtdst
else:
return dt | python.library.datetime#datetime.tzinfo.fromutc |
tzinfo.tzname(dt)
Return the time zone name corresponding to the datetime object dt, as a string. Nothing about string names is defined by the datetime module, and there’s no requirement that it mean anything in particular. For example, “GMT”, “UTC”, “-500”, “-5:00”, “EDT”, “US/Eastern”, “America/New York” are all valid replies. Return None if a string name isn’t known. Note that this is a method rather than a fixed string primarily because some tzinfo subclasses will wish to return different names depending on the specific value of dt passed, especially if the tzinfo class is accounting for daylight time. The default implementation of tzname() raises NotImplementedError. | python.library.datetime#datetime.tzinfo.tzname |
tzinfo.utcoffset(dt)
Return offset of local time from UTC, as a timedelta object that is positive east of UTC. If local time is west of UTC, this should be negative. This represents the total offset from UTC; for example, if a tzinfo object represents both time zone and DST adjustments, utcoffset() should return their sum. If the UTC offset isn’t known, return None. Else the value returned must be a timedelta object strictly between -timedelta(hours=24) and timedelta(hours=24) (the magnitude of the offset must be less than one day). Most implementations of utcoffset() will probably look like one of these two: return CONSTANT # fixed-offset class
return CONSTANT + self.dst(dt) # daylight-aware class
If utcoffset() does not return None, dst() should not return None either. The default implementation of utcoffset() raises NotImplementedError. Changed in version 3.7: The UTC offset is not restricted to a whole number of minutes. | python.library.datetime#datetime.tzinfo.utcoffset |
dbm — Interfaces to Unix “databases” Source code: Lib/dbm/__init__.py dbm is a generic interface to variants of the DBM database — dbm.gnu or dbm.ndbm. If none of these modules is installed, the slow-but-simple implementation in module dbm.dumb will be used. There is a third party interface to the Oracle Berkeley DB.
exception dbm.error
A tuple containing the exceptions that can be raised by each of the supported modules, with a unique exception also named dbm.error as the first item — the latter is used when dbm.error is raised.
dbm.whichdb(filename)
This function attempts to guess which of the several simple database modules available — dbm.gnu, dbm.ndbm or dbm.dumb — should be used to open a given file. Returns one of the following values: None if the file can’t be opened because it’s unreadable or doesn’t exist; the empty string ('') if the file’s format can’t be guessed; or a string containing the required module name, such as 'dbm.ndbm' or 'dbm.gnu'.
dbm.open(file, flag='r', mode=0o666)
Open the database file file and return a corresponding object. If the database file already exists, the whichdb() function is used to determine its type and the appropriate module is used; if it does not exist, the first module listed above that can be imported is used. The optional flag argument can be:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask).
The object returned by open() supports the same basic functionality as dictionaries; keys and their corresponding values can be stored, retrieved, and deleted, and the in operator and the keys() method are available, as well as get() and setdefault(). Changed in version 3.2: get() and setdefault() are now available in all database modules. Changed in version 3.8: Deleting a key from a read-only database raises database module specific error instead of KeyError. Key and values are always stored as bytes. This means that when strings are used they are implicitly converted to the default encoding before being stored. These objects also support being used in a with statement, which will automatically close them when done. Changed in version 3.4: Added native support for the context management protocol to the objects returned by open(). The following example records some hostnames and a corresponding title, and then prints out the contents of the database: import dbm
# Open database, creating it if necessary.
with dbm.open('cache', 'c') as db:
# Record some values
db[b'hello'] = b'there'
db['www.python.org'] = 'Python Website'
db['www.cnn.com'] = 'Cable News Network'
# Note that the keys are considered bytes now.
assert db[b'www.python.org'] == b'Python Website'
# Notice how the value is now in bytes.
assert db['www.cnn.com'] == b'Cable News Network'
# Often-used methods of the dict interface work too.
print(db.get('python.org', b'not present'))
# Storing a non-string key or value will raise an exception (most
# likely a TypeError).
db['www.yahoo.com'] = 4
# db is automatically closed when leaving the with statement.
See also
Module shelve
Persistence module which stores non-string data. The individual submodules are described in the following sections. dbm.gnu — GNU’s reinterpretation of dbm Source code: Lib/dbm/gnu.py This module is quite similar to the dbm module, but uses the GNU library gdbm instead to provide some additional functionality. Please note that the file formats created by dbm.gnu and dbm.ndbm are incompatible. The dbm.gnu module provides an interface to the GNU DBM library. dbm.gnu.gdbm objects behave like mappings (dictionaries), except that keys and values are always converted to bytes before storing. Printing a gdbm object doesn’t print the keys and values, and the items() and values() methods are not supported.
exception dbm.gnu.error
Raised on dbm.gnu-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key.
dbm.gnu.open(filename[, flag[, mode]])
Open a gdbm database and return a gdbm object. The filename argument is the name of the database file. The optional flag argument can be:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The following additional characters may be appended to the flag to control how the database is opened:
Value Meaning
'f' Open the database in fast mode. Writes to the database will not be synchronized.
's' Synchronized mode. This will cause changes to the database to be immediately written to the file.
'u' Do not lock database. Not all flags are valid for all versions of gdbm. The module constant open_flags is a string of supported flag characters. The exception error is raised if an invalid flag is specified. The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666. In addition to the dictionary-like methods, gdbm objects have the following methods:
gdbm.firstkey()
It’s possible to loop over every key in the database using this method and the nextkey() method. The traversal is ordered by gdbm’s internal hash values, and won’t be sorted by the key values. This method returns the starting key.
gdbm.nextkey(key)
Returns the key that follows key in the traversal. The following code prints every key in the database db, without having to create a list in memory that contains them all: k = db.firstkey()
while k != None:
print(k)
k = db.nextkey(k)
gdbm.reorganize()
If you have carried out a lot of deletions and would like to shrink the space used by the gdbm file, this routine will reorganize the database. gdbm objects will not shorten the length of a database file except by using this reorganization; otherwise, deleted file space will be kept and reused as new (key, value) pairs are added.
gdbm.sync()
When the database has been opened in fast mode, this method forces any unwritten data to be written to the disk.
gdbm.close()
Close the gdbm database.
dbm.ndbm — Interface based on ndbm Source code: Lib/dbm/ndbm.py The dbm.ndbm module provides an interface to the Unix “(n)dbm” library. Dbm objects behave like mappings (dictionaries), except that keys and values are always stored as bytes. Printing a dbm object doesn’t print the keys and values, and the items() and values() methods are not supported. This module can be used with the “classic” ndbm interface or the GNU GDBM compatibility interface. On Unix, the configure script will attempt to locate the appropriate header file to simplify building this module.
exception dbm.ndbm.error
Raised on dbm.ndbm-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key.
dbm.ndbm.library
Name of the ndbm implementation library used.
dbm.ndbm.open(filename[, flag[, mode]])
Open a dbm database and return a ndbm object. The filename argument is the name of the database file (without the .dir or .pag extensions). The optional flag argument must be one of these values:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask). In addition to the dictionary-like methods, ndbm objects provide the following method:
ndbm.close()
Close the ndbm database.
dbm.dumb — Portable DBM implementation Source code: Lib/dbm/dumb.py Note The dbm.dumb module is intended as a last resort fallback for the dbm module when a more robust module is not available. The dbm.dumb module is not written for speed and is not nearly as heavily used as the other database modules. The dbm.dumb module provides a persistent dictionary-like interface which is written entirely in Python. Unlike other modules such as dbm.gnu no external library is required. As with other persistent mappings, the keys and values are always stored as bytes. The module defines the following:
exception dbm.dumb.error
Raised on dbm.dumb-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key.
dbm.dumb.open(filename[, flag[, mode]])
Open a dumbdbm database and return a dumbdbm object. The filename argument is the basename of the database file (without any specific extensions). When a dumbdbm database is created, files with .dat and .dir extensions are created. The optional flag argument can be:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask). Warning It is possible to crash the Python interpreter when loading a database with a sufficiently large/complex entry due to stack depth limitations in Python’s AST compiler. Changed in version 3.5: open() always creates a new database when the flag has the value 'n'. Changed in version 3.8: A database opened with flags 'r' is now read-only. Opening with flags 'r' and 'w' no longer creates a database if it does not exist. In addition to the methods provided by the collections.abc.MutableMapping class, dumbdbm objects provide the following methods:
dumbdbm.sync()
Synchronize the on-disk directory and data files. This method is called by the Shelve.sync() method.
dumbdbm.close()
Close the dumbdbm database. | python.library.dbm |
dumbdbm.close()
Close the dumbdbm database. | python.library.dbm#dbm.dumb.dumbdbm.close |
dumbdbm.sync()
Synchronize the on-disk directory and data files. This method is called by the Shelve.sync() method. | python.library.dbm#dbm.dumb.dumbdbm.sync |
exception dbm.dumb.error
Raised on dbm.dumb-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key. | python.library.dbm#dbm.dumb.error |
dbm.dumb.open(filename[, flag[, mode]])
Open a dumbdbm database and return a dumbdbm object. The filename argument is the basename of the database file (without any specific extensions). When a dumbdbm database is created, files with .dat and .dir extensions are created. The optional flag argument can be:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask). Warning It is possible to crash the Python interpreter when loading a database with a sufficiently large/complex entry due to stack depth limitations in Python’s AST compiler. Changed in version 3.5: open() always creates a new database when the flag has the value 'n'. Changed in version 3.8: A database opened with flags 'r' is now read-only. Opening with flags 'r' and 'w' no longer creates a database if it does not exist. In addition to the methods provided by the collections.abc.MutableMapping class, dumbdbm objects provide the following methods:
dumbdbm.sync()
Synchronize the on-disk directory and data files. This method is called by the Shelve.sync() method.
dumbdbm.close()
Close the dumbdbm database. | python.library.dbm#dbm.dumb.open |
exception dbm.error
A tuple containing the exceptions that can be raised by each of the supported modules, with a unique exception also named dbm.error as the first item — the latter is used when dbm.error is raised. | python.library.dbm#dbm.error |
exception dbm.gnu.error
Raised on dbm.gnu-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key. | python.library.dbm#dbm.gnu.error |
gdbm.close()
Close the gdbm database. | python.library.dbm#dbm.gnu.gdbm.close |
gdbm.firstkey()
It’s possible to loop over every key in the database using this method and the nextkey() method. The traversal is ordered by gdbm’s internal hash values, and won’t be sorted by the key values. This method returns the starting key. | python.library.dbm#dbm.gnu.gdbm.firstkey |
gdbm.nextkey(key)
Returns the key that follows key in the traversal. The following code prints every key in the database db, without having to create a list in memory that contains them all: k = db.firstkey()
while k != None:
print(k)
k = db.nextkey(k) | python.library.dbm#dbm.gnu.gdbm.nextkey |
gdbm.reorganize()
If you have carried out a lot of deletions and would like to shrink the space used by the gdbm file, this routine will reorganize the database. gdbm objects will not shorten the length of a database file except by using this reorganization; otherwise, deleted file space will be kept and reused as new (key, value) pairs are added. | python.library.dbm#dbm.gnu.gdbm.reorganize |
gdbm.sync()
When the database has been opened in fast mode, this method forces any unwritten data to be written to the disk. | python.library.dbm#dbm.gnu.gdbm.sync |
dbm.gnu.open(filename[, flag[, mode]])
Open a gdbm database and return a gdbm object. The filename argument is the name of the database file. The optional flag argument can be:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The following additional characters may be appended to the flag to control how the database is opened:
Value Meaning
'f' Open the database in fast mode. Writes to the database will not be synchronized.
's' Synchronized mode. This will cause changes to the database to be immediately written to the file.
'u' Do not lock database. Not all flags are valid for all versions of gdbm. The module constant open_flags is a string of supported flag characters. The exception error is raised if an invalid flag is specified. The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666. In addition to the dictionary-like methods, gdbm objects have the following methods:
gdbm.firstkey()
It’s possible to loop over every key in the database using this method and the nextkey() method. The traversal is ordered by gdbm’s internal hash values, and won’t be sorted by the key values. This method returns the starting key.
gdbm.nextkey(key)
Returns the key that follows key in the traversal. The following code prints every key in the database db, without having to create a list in memory that contains them all: k = db.firstkey()
while k != None:
print(k)
k = db.nextkey(k)
gdbm.reorganize()
If you have carried out a lot of deletions and would like to shrink the space used by the gdbm file, this routine will reorganize the database. gdbm objects will not shorten the length of a database file except by using this reorganization; otherwise, deleted file space will be kept and reused as new (key, value) pairs are added.
gdbm.sync()
When the database has been opened in fast mode, this method forces any unwritten data to be written to the disk.
gdbm.close()
Close the gdbm database. | python.library.dbm#dbm.gnu.open |
exception dbm.ndbm.error
Raised on dbm.ndbm-specific errors, such as I/O errors. KeyError is raised for general mapping errors like specifying an incorrect key. | python.library.dbm#dbm.ndbm.error |
dbm.ndbm.library
Name of the ndbm implementation library used. | python.library.dbm#dbm.ndbm.library |
ndbm.close()
Close the ndbm database. | python.library.dbm#dbm.ndbm.ndbm.close |
dbm.ndbm.open(filename[, flag[, mode]])
Open a dbm database and return a ndbm object. The filename argument is the name of the database file (without the .dir or .pag extensions). The optional flag argument must be one of these values:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask). In addition to the dictionary-like methods, ndbm objects provide the following method:
ndbm.close()
Close the ndbm database. | python.library.dbm#dbm.ndbm.open |
dbm.open(file, flag='r', mode=0o666)
Open the database file file and return a corresponding object. If the database file already exists, the whichdb() function is used to determine its type and the appropriate module is used; if it does not exist, the first module listed above that can be imported is used. The optional flag argument can be:
Value Meaning
'r' Open existing database for reading only (default)
'w' Open existing database for reading and writing
'c' Open database for reading and writing, creating it if it doesn’t exist
'n' Always create a new, empty database, open for reading and writing The optional mode argument is the Unix mode of the file, used only when the database has to be created. It defaults to octal 0o666 (and will be modified by the prevailing umask). | python.library.dbm#dbm.open |
dbm.whichdb(filename)
This function attempts to guess which of the several simple database modules available — dbm.gnu, dbm.ndbm or dbm.dumb — should be used to open a given file. Returns one of the following values: None if the file can’t be opened because it’s unreadable or doesn’t exist; the empty string ('') if the file’s format can’t be guessed; or a string containing the required module name, such as 'dbm.ndbm' or 'dbm.gnu'. | python.library.dbm#dbm.whichdb |
decimal — Decimal fixed point and floating point arithmetic Source code: Lib/decimal.py The decimal module provides support for fast correctly-rounded decimal floating point arithmetic. It offers several advantages over the float datatype: Decimal “is based on a floating-point model which was designed with people in mind, and necessarily has a paramount guiding principle – computers must provide an arithmetic that works in the same way as the arithmetic that people learn at school.” – excerpt from the decimal arithmetic specification. Decimal numbers can be represented exactly. In contrast, numbers like 1.1 and 2.2 do not have exact representations in binary floating point. End users typically would not expect 1.1 + 2.2 to display as 3.3000000000000003 as it does with binary floating point. The exactness carries over into arithmetic. In decimal floating point, 0.1
+ 0.1 + 0.1 - 0.3 is exactly equal to zero. In binary floating point, the result is 5.5511151231257827e-017. While near to zero, the differences prevent reliable equality testing and differences can accumulate. For this reason, decimal is preferred in accounting applications which have strict equality invariants. The decimal module incorporates a notion of significant places so that 1.30
+ 1.20 is 2.50. The trailing zero is kept to indicate significance. This is the customary presentation for monetary applications. For multiplication, the “schoolbook” approach uses all the figures in the multiplicands. For instance, 1.3 * 1.2 gives 1.56 while 1.30 *
1.20 gives 1.5600.
Unlike hardware based binary floating point, the decimal module has a user alterable precision (defaulting to 28 places) which can be as large as needed for a given problem: >>> from decimal import *
>>> getcontext().prec = 6
>>> Decimal(1) / Decimal(7)
Decimal('0.142857')
>>> getcontext().prec = 28
>>> Decimal(1) / Decimal(7)
Decimal('0.1428571428571428571428571429')
Both binary and decimal floating point are implemented in terms of published standards. While the built-in float type exposes only a modest portion of its capabilities, the decimal module exposes all required parts of the standard. When needed, the programmer has full control over rounding and signal handling. This includes an option to enforce exact arithmetic by using exceptions to block any inexact operations. The decimal module was designed to support “without prejudice, both exact unrounded decimal arithmetic (sometimes called fixed-point arithmetic) and rounded floating-point arithmetic.” – excerpt from the decimal arithmetic specification. The module design is centered around three concepts: the decimal number, the context for arithmetic, and signals. A decimal number is immutable. It has a sign, coefficient digits, and an exponent. To preserve significance, the coefficient digits do not truncate trailing zeros. Decimals also include special values such as Infinity, -Infinity, and NaN. The standard also differentiates -0 from +0. The context for arithmetic is an environment specifying precision, rounding rules, limits on exponents, flags indicating the results of operations, and trap enablers which determine whether signals are treated as exceptions. Rounding options include ROUND_CEILING, ROUND_DOWN, ROUND_FLOOR, ROUND_HALF_DOWN, ROUND_HALF_EVEN, ROUND_HALF_UP, ROUND_UP, and ROUND_05UP. Signals are groups of exceptional conditions arising during the course of computation. Depending on the needs of the application, signals may be ignored, considered as informational, or treated as exceptions. The signals in the decimal module are: Clamped, InvalidOperation, DivisionByZero, Inexact, Rounded, Subnormal, Overflow, Underflow and FloatOperation. For each signal there is a flag and a trap enabler. When a signal is encountered, its flag is set to one, then, if the trap enabler is set to one, an exception is raised. Flags are sticky, so the user needs to reset them before monitoring a calculation. See also IBM’s General Decimal Arithmetic Specification, The General Decimal Arithmetic Specification. Quick-start Tutorial The usual start to using decimals is importing the module, viewing the current context with getcontext() and, if necessary, setting new values for precision, rounding, or enabled traps: >>> from decimal import *
>>> getcontext()
Context(prec=28, rounding=ROUND_HALF_EVEN, Emin=-999999, Emax=999999,
capitals=1, clamp=0, flags=[], traps=[Overflow, DivisionByZero,
InvalidOperation])
>>> getcontext().prec = 7 # Set a new precision
Decimal instances can be constructed from integers, strings, floats, or tuples. Construction from an integer or a float performs an exact conversion of the value of that integer or float. Decimal numbers include special values such as NaN which stands for “Not a number”, positive and negative Infinity, and -0: >>> getcontext().prec = 28
>>> Decimal(10)
Decimal('10')
>>> Decimal('3.14')
Decimal('3.14')
>>> Decimal(3.14)
Decimal('3.140000000000000124344978758017532527446746826171875')
>>> Decimal((0, (3, 1, 4), -2))
Decimal('3.14')
>>> Decimal(str(2.0 ** 0.5))
Decimal('1.4142135623730951')
>>> Decimal(2) ** Decimal('0.5')
Decimal('1.414213562373095048801688724')
>>> Decimal('NaN')
Decimal('NaN')
>>> Decimal('-Infinity')
Decimal('-Infinity')
If the FloatOperation signal is trapped, accidental mixing of decimals and floats in constructors or ordering comparisons raises an exception: >>> c = getcontext()
>>> c.traps[FloatOperation] = True
>>> Decimal(3.14)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
decimal.FloatOperation: [<class 'decimal.FloatOperation'>]
>>> Decimal('3.5') < 3.7
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
decimal.FloatOperation: [<class 'decimal.FloatOperation'>]
>>> Decimal('3.5') == 3.5
True
New in version 3.3. The significance of a new Decimal is determined solely by the number of digits input. Context precision and rounding only come into play during arithmetic operations. >>> getcontext().prec = 6
>>> Decimal('3.0')
Decimal('3.0')
>>> Decimal('3.1415926535')
Decimal('3.1415926535')
>>> Decimal('3.1415926535') + Decimal('2.7182818285')
Decimal('5.85987')
>>> getcontext().rounding = ROUND_UP
>>> Decimal('3.1415926535') + Decimal('2.7182818285')
Decimal('5.85988')
If the internal limits of the C version are exceeded, constructing a decimal raises InvalidOperation: >>> Decimal("1e9999999999999999999")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
decimal.InvalidOperation: [<class 'decimal.InvalidOperation'>]
Changed in version 3.3. Decimals interact well with much of the rest of Python. Here is a small decimal floating point flying circus: >>> data = list(map(Decimal, '1.34 1.87 3.45 2.35 1.00 0.03 9.25'.split()))
>>> max(data)
Decimal('9.25')
>>> min(data)
Decimal('0.03')
>>> sorted(data)
[Decimal('0.03'), Decimal('1.00'), Decimal('1.34'), Decimal('1.87'),
Decimal('2.35'), Decimal('3.45'), Decimal('9.25')]
>>> sum(data)
Decimal('19.29')
>>> a,b,c = data[:3]
>>> str(a)
'1.34'
>>> float(a)
1.34
>>> round(a, 1)
Decimal('1.3')
>>> int(a)
1
>>> a * 5
Decimal('6.70')
>>> a * b
Decimal('2.5058')
>>> c % a
Decimal('0.77')
And some mathematical functions are also available to Decimal: >>> getcontext().prec = 28
>>> Decimal(2).sqrt()
Decimal('1.414213562373095048801688724')
>>> Decimal(1).exp()
Decimal('2.718281828459045235360287471')
>>> Decimal('10').ln()
Decimal('2.302585092994045684017991455')
>>> Decimal('10').log10()
Decimal('1')
The quantize() method rounds a number to a fixed exponent. This method is useful for monetary applications that often round results to a fixed number of places: >>> Decimal('7.325').quantize(Decimal('.01'), rounding=ROUND_DOWN)
Decimal('7.32')
>>> Decimal('7.325').quantize(Decimal('1.'), rounding=ROUND_UP)
Decimal('8')
As shown above, the getcontext() function accesses the current context and allows the settings to be changed. This approach meets the needs of most applications. For more advanced work, it may be useful to create alternate contexts using the Context() constructor. To make an alternate active, use the setcontext() function. In accordance with the standard, the decimal module provides two ready to use standard contexts, BasicContext and ExtendedContext. The former is especially useful for debugging because many of the traps are enabled: >>> myothercontext = Context(prec=60, rounding=ROUND_HALF_DOWN)
>>> setcontext(myothercontext)
>>> Decimal(1) / Decimal(7)
Decimal('0.142857142857142857142857142857142857142857142857142857142857')
>>> ExtendedContext
Context(prec=9, rounding=ROUND_HALF_EVEN, Emin=-999999, Emax=999999,
capitals=1, clamp=0, flags=[], traps=[])
>>> setcontext(ExtendedContext)
>>> Decimal(1) / Decimal(7)
Decimal('0.142857143')
>>> Decimal(42) / Decimal(0)
Decimal('Infinity')
>>> setcontext(BasicContext)
>>> Decimal(42) / Decimal(0)
Traceback (most recent call last):
File "<pyshell#143>", line 1, in -toplevel-
Decimal(42) / Decimal(0)
DivisionByZero: x / 0
Contexts also have signal flags for monitoring exceptional conditions encountered during computations. The flags remain set until explicitly cleared, so it is best to clear the flags before each set of monitored computations by using the clear_flags() method. >>> setcontext(ExtendedContext)
>>> getcontext().clear_flags()
>>> Decimal(355) / Decimal(113)
Decimal('3.14159292')
>>> getcontext()
Context(prec=9, rounding=ROUND_HALF_EVEN, Emin=-999999, Emax=999999,
capitals=1, clamp=0, flags=[Inexact, Rounded], traps=[])
The flags entry shows that the rational approximation to Pi was rounded (digits beyond the context precision were thrown away) and that the result is inexact (some of the discarded digits were non-zero). Individual traps are set using the dictionary in the traps field of a context: >>> setcontext(ExtendedContext)
>>> Decimal(1) / Decimal(0)
Decimal('Infinity')
>>> getcontext().traps[DivisionByZero] = 1
>>> Decimal(1) / Decimal(0)
Traceback (most recent call last):
File "<pyshell#112>", line 1, in -toplevel-
Decimal(1) / Decimal(0)
DivisionByZero: x / 0
Most programs adjust the current context only once, at the beginning of the program. And, in many applications, data is converted to Decimal with a single cast inside a loop. With context set and decimals created, the bulk of the program manipulates the data no differently than with other Python numeric types. Decimal objects
class decimal.Decimal(value="0", context=None)
Construct a new Decimal object based from value. value can be an integer, string, tuple, float, or another Decimal object. If no value is given, returns Decimal('0'). If value is a string, it should conform to the decimal numeric string syntax after leading and trailing whitespace characters, as well as underscores throughout, are removed: sign ::= '+' | '-'
digit ::= '0' | '1' | '2' | '3' | '4' | '5' | '6' | '7' | '8' | '9'
indicator ::= 'e' | 'E'
digits ::= digit [digit]...
decimal-part ::= digits '.' [digits] | ['.'] digits
exponent-part ::= indicator [sign] digits
infinity ::= 'Infinity' | 'Inf'
nan ::= 'NaN' [digits] | 'sNaN' [digits]
numeric-value ::= decimal-part [exponent-part] | infinity
numeric-string ::= [sign] numeric-value | [sign] nan
Other Unicode decimal digits are also permitted where digit appears above. These include decimal digits from various other alphabets (for example, Arabic-Indic and Devanāgarī digits) along with the fullwidth digits '\uff10' through '\uff19'. If value is a tuple, it should have three components, a sign (0 for positive or 1 for negative), a tuple of digits, and an integer exponent. For example, Decimal((0, (1, 4, 1, 4), -3)) returns Decimal('1.414'). If value is a float, the binary floating point value is losslessly converted to its exact decimal equivalent. This conversion can often require 53 or more digits of precision. For example, Decimal(float('1.1')) converts to Decimal('1.100000000000000088817841970012523233890533447265625'). The context precision does not affect how many digits are stored. That is determined exclusively by the number of digits in value. For example, Decimal('3.00000') records all five zeros even if the context precision is only three. The purpose of the context argument is determining what to do if value is a malformed string. If the context traps InvalidOperation, an exception is raised; otherwise, the constructor returns a new Decimal with the value of NaN. Once constructed, Decimal objects are immutable. Changed in version 3.2: The argument to the constructor is now permitted to be a float instance. Changed in version 3.3: float arguments raise an exception if the FloatOperation trap is set. By default the trap is off. Changed in version 3.6: Underscores are allowed for grouping, as with integral and floating-point literals in code. Decimal floating point objects share many properties with the other built-in numeric types such as float and int. All of the usual math operations and special methods apply. Likewise, decimal objects can be copied, pickled, printed, used as dictionary keys, used as set elements, compared, sorted, and coerced to another type (such as float or int). There are some small differences between arithmetic on Decimal objects and arithmetic on integers and floats. When the remainder operator % is applied to Decimal objects, the sign of the result is the sign of the dividend rather than the sign of the divisor: >>> (-7) % 4
1
>>> Decimal(-7) % Decimal(4)
Decimal('-3')
The integer division operator // behaves analogously, returning the integer part of the true quotient (truncating towards zero) rather than its floor, so as to preserve the usual identity x == (x // y) * y + x % y: >>> -7 // 4
-2
>>> Decimal(-7) // Decimal(4)
Decimal('-1')
The % and // operators implement the remainder and divide-integer operations (respectively) as described in the specification. Decimal objects cannot generally be combined with floats or instances of fractions.Fraction in arithmetic operations: an attempt to add a Decimal to a float, for example, will raise a TypeError. However, it is possible to use Python’s comparison operators to compare a Decimal instance x with another number y. This avoids confusing results when doing equality comparisons between numbers of different types. Changed in version 3.2: Mixed-type comparisons between Decimal instances and other numeric types are now fully supported. In addition to the standard numeric properties, decimal floating point objects also have a number of specialized methods:
adjusted()
Return the adjusted exponent after shifting out the coefficient’s rightmost digits until only the lead digit remains: Decimal('321e+5').adjusted() returns seven. Used for determining the position of the most significant digit with respect to the decimal point.
as_integer_ratio()
Return a pair (n, d) of integers that represent the given Decimal instance as a fraction, in lowest terms and with a positive denominator: >>> Decimal('-3.14').as_integer_ratio()
(-157, 50)
The conversion is exact. Raise OverflowError on infinities and ValueError on NaNs.
New in version 3.6.
as_tuple()
Return a named tuple representation of the number: DecimalTuple(sign, digits, exponent).
canonical()
Return the canonical encoding of the argument. Currently, the encoding of a Decimal instance is always canonical, so this operation returns its argument unchanged.
compare(other, context=None)
Compare the values of two Decimal instances. compare() returns a Decimal instance, and if either operand is a NaN then the result is a NaN: a or b is a NaN ==> Decimal('NaN')
a < b ==> Decimal('-1')
a == b ==> Decimal('0')
a > b ==> Decimal('1')
compare_signal(other, context=None)
This operation is identical to the compare() method, except that all NaNs signal. That is, if neither operand is a signaling NaN then any quiet NaN operand is treated as though it were a signaling NaN.
compare_total(other, context=None)
Compare two operands using their abstract representation rather than their numerical value. Similar to the compare() method, but the result gives a total ordering on Decimal instances. Two Decimal instances with the same numeric value but different representations compare unequal in this ordering: >>> Decimal('12.0').compare_total(Decimal('12'))
Decimal('-1')
Quiet and signaling NaNs are also included in the total ordering. The result of this function is Decimal('0') if both operands have the same representation, Decimal('-1') if the first operand is lower in the total order than the second, and Decimal('1') if the first operand is higher in the total order than the second operand. See the specification for details of the total order. This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.
compare_total_mag(other, context=None)
Compare two operands using their abstract representation rather than their value as in compare_total(), but ignoring the sign of each operand. x.compare_total_mag(y) is equivalent to x.copy_abs().compare_total(y.copy_abs()). This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.
conjugate()
Just returns self, this method is only to comply with the Decimal Specification.
copy_abs()
Return the absolute value of the argument. This operation is unaffected by the context and is quiet: no flags are changed and no rounding is performed.
copy_negate()
Return the negation of the argument. This operation is unaffected by the context and is quiet: no flags are changed and no rounding is performed.
copy_sign(other, context=None)
Return a copy of the first operand with the sign set to be the same as the sign of the second operand. For example: >>> Decimal('2.3').copy_sign(Decimal('-1.5'))
Decimal('-2.3')
This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.
exp(context=None)
Return the value of the (natural) exponential function e**x at the given number. The result is correctly rounded using the ROUND_HALF_EVEN rounding mode. >>> Decimal(1).exp()
Decimal('2.718281828459045235360287471')
>>> Decimal(321).exp()
Decimal('2.561702493119680037517373933E+139')
from_float(f)
Classmethod that converts a float to a decimal number, exactly. Note Decimal.from_float(0.1) is not the same as Decimal(‘0.1’). Since 0.1 is not exactly representable in binary floating point, the value is stored as the nearest representable value which is 0x1.999999999999ap-4. That equivalent value in decimal is 0.1000000000000000055511151231257827021181583404541015625. Note From Python 3.2 onwards, a Decimal instance can also be constructed directly from a float. >>> Decimal.from_float(0.1)
Decimal('0.1000000000000000055511151231257827021181583404541015625')
>>> Decimal.from_float(float('nan'))
Decimal('NaN')
>>> Decimal.from_float(float('inf'))
Decimal('Infinity')
>>> Decimal.from_float(float('-inf'))
Decimal('-Infinity')
New in version 3.1.
fma(other, third, context=None)
Fused multiply-add. Return self*other+third with no rounding of the intermediate product self*other. >>> Decimal(2).fma(3, 5)
Decimal('11')
is_canonical()
Return True if the argument is canonical and False otherwise. Currently, a Decimal instance is always canonical, so this operation always returns True.
is_finite()
Return True if the argument is a finite number, and False if the argument is an infinity or a NaN.
is_infinite()
Return True if the argument is either positive or negative infinity and False otherwise.
is_nan()
Return True if the argument is a (quiet or signaling) NaN and False otherwise.
is_normal(context=None)
Return True if the argument is a normal finite number. Return False if the argument is zero, subnormal, infinite or a NaN.
is_qnan()
Return True if the argument is a quiet NaN, and False otherwise.
is_signed()
Return True if the argument has a negative sign and False otherwise. Note that zeros and NaNs can both carry signs.
is_snan()
Return True if the argument is a signaling NaN and False otherwise.
is_subnormal(context=None)
Return True if the argument is subnormal, and False otherwise.
is_zero()
Return True if the argument is a (positive or negative) zero and False otherwise.
ln(context=None)
Return the natural (base e) logarithm of the operand. The result is correctly rounded using the ROUND_HALF_EVEN rounding mode.
log10(context=None)
Return the base ten logarithm of the operand. The result is correctly rounded using the ROUND_HALF_EVEN rounding mode.
logb(context=None)
For a nonzero number, return the adjusted exponent of its operand as a Decimal instance. If the operand is a zero then Decimal('-Infinity') is returned and the DivisionByZero flag is raised. If the operand is an infinity then Decimal('Infinity') is returned.
logical_and(other, context=None)
logical_and() is a logical operation which takes two logical operands (see Logical operands). The result is the digit-wise and of the two operands.
logical_invert(context=None)
logical_invert() is a logical operation. The result is the digit-wise inversion of the operand.
logical_or(other, context=None)
logical_or() is a logical operation which takes two logical operands (see Logical operands). The result is the digit-wise or of the two operands.
logical_xor(other, context=None)
logical_xor() is a logical operation which takes two logical operands (see Logical operands). The result is the digit-wise exclusive or of the two operands.
max(other, context=None)
Like max(self, other) except that the context rounding rule is applied before returning and that NaN values are either signaled or ignored (depending on the context and whether they are signaling or quiet).
max_mag(other, context=None)
Similar to the max() method, but the comparison is done using the absolute values of the operands.
min(other, context=None)
Like min(self, other) except that the context rounding rule is applied before returning and that NaN values are either signaled or ignored (depending on the context and whether they are signaling or quiet).
min_mag(other, context=None)
Similar to the min() method, but the comparison is done using the absolute values of the operands.
next_minus(context=None)
Return the largest number representable in the given context (or in the current thread’s context if no context is given) that is smaller than the given operand.
next_plus(context=None)
Return the smallest number representable in the given context (or in the current thread’s context if no context is given) that is larger than the given operand.
next_toward(other, context=None)
If the two operands are unequal, return the number closest to the first operand in the direction of the second operand. If both operands are numerically equal, return a copy of the first operand with the sign set to be the same as the sign of the second operand.
normalize(context=None)
Normalize the number by stripping the rightmost trailing zeros and converting any result equal to Decimal('0') to Decimal('0e0'). Used for producing canonical values for attributes of an equivalence class. For example, Decimal('32.100') and Decimal('0.321000e+2') both normalize to the equivalent value Decimal('32.1').
number_class(context=None)
Return a string describing the class of the operand. The returned value is one of the following ten strings.
"-Infinity", indicating that the operand is negative infinity.
"-Normal", indicating that the operand is a negative normal number.
"-Subnormal", indicating that the operand is negative and subnormal.
"-Zero", indicating that the operand is a negative zero.
"+Zero", indicating that the operand is a positive zero.
"+Subnormal", indicating that the operand is positive and subnormal.
"+Normal", indicating that the operand is a positive normal number.
"+Infinity", indicating that the operand is positive infinity.
"NaN", indicating that the operand is a quiet NaN (Not a Number).
"sNaN", indicating that the operand is a signaling NaN.
quantize(exp, rounding=None, context=None)
Return a value equal to the first operand after rounding and having the exponent of the second operand. >>> Decimal('1.41421356').quantize(Decimal('1.000'))
Decimal('1.414')
Unlike other operations, if the length of the coefficient after the quantize operation would be greater than precision, then an InvalidOperation is signaled. This guarantees that, unless there is an error condition, the quantized exponent is always equal to that of the right-hand operand. Also unlike other operations, quantize never signals Underflow, even if the result is subnormal and inexact. If the exponent of the second operand is larger than that of the first then rounding may be necessary. In this case, the rounding mode is determined by the rounding argument if given, else by the given context argument; if neither argument is given the rounding mode of the current thread’s context is used. An error is returned whenever the resulting exponent is greater than Emax or less than Etiny.
radix()
Return Decimal(10), the radix (base) in which the Decimal class does all its arithmetic. Included for compatibility with the specification.
remainder_near(other, context=None)
Return the remainder from dividing self by other. This differs from self % other in that the sign of the remainder is chosen so as to minimize its absolute value. More precisely, the return value is self - n * other where n is the integer nearest to the exact value of self / other, and if two integers are equally near then the even one is chosen. If the result is zero then its sign will be the sign of self. >>> Decimal(18).remainder_near(Decimal(10))
Decimal('-2')
>>> Decimal(25).remainder_near(Decimal(10))
Decimal('5')
>>> Decimal(35).remainder_near(Decimal(10))
Decimal('-5')
rotate(other, context=None)
Return the result of rotating the digits of the first operand by an amount specified by the second operand. The second operand must be an integer in the range -precision through precision. The absolute value of the second operand gives the number of places to rotate. If the second operand is positive then rotation is to the left; otherwise rotation is to the right. The coefficient of the first operand is padded on the left with zeros to length precision if necessary. The sign and exponent of the first operand are unchanged.
same_quantum(other, context=None)
Test whether self and other have the same exponent or whether both are NaN. This operation is unaffected by context and is quiet: no flags are changed and no rounding is performed. As an exception, the C version may raise InvalidOperation if the second operand cannot be converted exactly.
scaleb(other, context=None)
Return the first operand with exponent adjusted by the second. Equivalently, return the first operand multiplied by 10**other. The second operand must be an integer.
shift(other, context=None)
Return the result of shifting the digits of the first operand by an amount specified by the second operand. The second operand must be an integer in the range -precision through precision. The absolute value of the second operand gives the number of places to shift. If the second operand is positive then the shift is to the left; otherwise the shift is to the right. Digits shifted into the coefficient are zeros. The sign and exponent of the first operand are unchanged.
sqrt(context=None)
Return the square root of the argument to full precision.
to_eng_string(context=None)
Convert to a string, using engineering notation if an exponent is needed. Engineering notation has an exponent which is a multiple of 3. This can leave up to 3 digits to the left of the decimal place and may require the addition of either one or two trailing zeros. For example, this converts Decimal('123E+1') to Decimal('1.23E+3').
to_integral(rounding=None, context=None)
Identical to the to_integral_value() method. The to_integral name has been kept for compatibility with older versions.
to_integral_exact(rounding=None, context=None)
Round to the nearest integer, signaling Inexact or Rounded as appropriate if rounding occurs. The rounding mode is determined by the rounding parameter if given, else by the given context. If neither parameter is given then the rounding mode of the current context is used.
to_integral_value(rounding=None, context=None)
Round to the nearest integer without signaling Inexact or Rounded. If given, applies rounding; otherwise, uses the rounding method in either the supplied context or the current context.
Logical operands The logical_and(), logical_invert(), logical_or(), and logical_xor() methods expect their arguments to be logical operands. A logical operand is a Decimal instance whose exponent and sign are both zero, and whose digits are all either 0 or 1. Context objects Contexts are environments for arithmetic operations. They govern precision, set rules for rounding, determine which signals are treated as exceptions, and limit the range for exponents. Each thread has its own current context which is accessed or changed using the getcontext() and setcontext() functions:
decimal.getcontext()
Return the current context for the active thread.
decimal.setcontext(c)
Set the current context for the active thread to c.
You can also use the with statement and the localcontext() function to temporarily change the active context.
decimal.localcontext(ctx=None)
Return a context manager that will set the current context for the active thread to a copy of ctx on entry to the with-statement and restore the previous context when exiting the with-statement. If no context is specified, a copy of the current context is used. For example, the following code sets the current decimal precision to 42 places, performs a calculation, and then automatically restores the previous context: from decimal import localcontext
with localcontext() as ctx:
ctx.prec = 42 # Perform a high precision calculation
s = calculate_something()
s = +s # Round the final result back to the default precision
New contexts can also be created using the Context constructor described below. In addition, the module provides three pre-made contexts:
class decimal.BasicContext
This is a standard context defined by the General Decimal Arithmetic Specification. Precision is set to nine. Rounding is set to ROUND_HALF_UP. All flags are cleared. All traps are enabled (treated as exceptions) except Inexact, Rounded, and Subnormal. Because many of the traps are enabled, this context is useful for debugging.
class decimal.ExtendedContext
This is a standard context defined by the General Decimal Arithmetic Specification. Precision is set to nine. Rounding is set to ROUND_HALF_EVEN. All flags are cleared. No traps are enabled (so that exceptions are not raised during computations). Because the traps are disabled, this context is useful for applications that prefer to have result value of NaN or Infinity instead of raising exceptions. This allows an application to complete a run in the presence of conditions that would otherwise halt the program.
class decimal.DefaultContext
This context is used by the Context constructor as a prototype for new contexts. Changing a field (such a precision) has the effect of changing the default for new contexts created by the Context constructor. This context is most useful in multi-threaded environments. Changing one of the fields before threads are started has the effect of setting system-wide defaults. Changing the fields after threads have started is not recommended as it would require thread synchronization to prevent race conditions. In single threaded environments, it is preferable to not use this context at all. Instead, simply create contexts explicitly as described below. The default values are prec=28, rounding=ROUND_HALF_EVEN, and enabled traps for Overflow, InvalidOperation, and DivisionByZero.
In addition to the three supplied contexts, new contexts can be created with the Context constructor.
class decimal.Context(prec=None, rounding=None, Emin=None, Emax=None, capitals=None, clamp=None, flags=None, traps=None)
Creates a new context. If a field is not specified or is None, the default values are copied from the DefaultContext. If the flags field is not specified or is None, all flags are cleared. prec is an integer in the range [1, MAX_PREC] that sets the precision for arithmetic operations in the context. The rounding option is one of the constants listed in the section Rounding Modes. The traps and flags fields list any signals to be set. Generally, new contexts should only set traps and leave the flags clear. The Emin and Emax fields are integers specifying the outer limits allowable for exponents. Emin must be in the range [MIN_EMIN, 0], Emax in the range [0, MAX_EMAX]. The capitals field is either 0 or 1 (the default). If set to 1, exponents are printed with a capital E; otherwise, a lowercase e is used: Decimal('6.02e+23'). The clamp field is either 0 (the default) or 1. If set to 1, the exponent e of a Decimal instance representable in this context is strictly limited to the range Emin - prec + 1 <= e <= Emax - prec + 1. If clamp is 0 then a weaker condition holds: the adjusted exponent of the Decimal instance is at most Emax. When clamp is 1, a large normal number will, where possible, have its exponent reduced and a corresponding number of zeros added to its coefficient, in order to fit the exponent constraints; this preserves the value of the number but loses information about significant trailing zeros. For example: >>> Context(prec=6, Emax=999, clamp=1).create_decimal('1.23e999')
Decimal('1.23000E+999')
A clamp value of 1 allows compatibility with the fixed-width decimal interchange formats specified in IEEE 754. The Context class defines several general purpose methods as well as a large number of methods for doing arithmetic directly in a given context. In addition, for each of the Decimal methods described above (with the exception of the adjusted() and as_tuple() methods) there is a corresponding Context method. For example, for a Context instance C and Decimal instance x, C.exp(x) is equivalent to x.exp(context=C). Each Context method accepts a Python integer (an instance of int) anywhere that a Decimal instance is accepted.
clear_flags()
Resets all of the flags to 0.
clear_traps()
Resets all of the traps to 0. New in version 3.3.
copy()
Return a duplicate of the context.
copy_decimal(num)
Return a copy of the Decimal instance num.
create_decimal(num)
Creates a new Decimal instance from num but using self as context. Unlike the Decimal constructor, the context precision, rounding method, flags, and traps are applied to the conversion. This is useful because constants are often given to a greater precision than is needed by the application. Another benefit is that rounding immediately eliminates unintended effects from digits beyond the current precision. In the following example, using unrounded inputs means that adding zero to a sum can change the result: >>> getcontext().prec = 3
>>> Decimal('3.4445') + Decimal('1.0023')
Decimal('4.45')
>>> Decimal('3.4445') + Decimal(0) + Decimal('1.0023')
Decimal('4.44')
This method implements the to-number operation of the IBM specification. If the argument is a string, no leading or trailing whitespace or underscores are permitted.
create_decimal_from_float(f)
Creates a new Decimal instance from a float f but rounding using self as the context. Unlike the Decimal.from_float() class method, the context precision, rounding method, flags, and traps are applied to the conversion. >>> context = Context(prec=5, rounding=ROUND_DOWN)
>>> context.create_decimal_from_float(math.pi)
Decimal('3.1415')
>>> context = Context(prec=5, traps=[Inexact])
>>> context.create_decimal_from_float(math.pi)
Traceback (most recent call last):
...
decimal.Inexact: None
New in version 3.1.
Etiny()
Returns a value equal to Emin - prec + 1 which is the minimum exponent value for subnormal results. When underflow occurs, the exponent is set to Etiny.
Etop()
Returns a value equal to Emax - prec + 1.
The usual approach to working with decimals is to create Decimal instances and then apply arithmetic operations which take place within the current context for the active thread. An alternative approach is to use context methods for calculating within a specific context. The methods are similar to those for the Decimal class and are only briefly recounted here.
abs(x)
Returns the absolute value of x.
add(x, y)
Return the sum of x and y.
canonical(x)
Returns the same Decimal object x.
compare(x, y)
Compares x and y numerically.
compare_signal(x, y)
Compares the values of the two operands numerically.
compare_total(x, y)
Compares two operands using their abstract representation.
compare_total_mag(x, y)
Compares two operands using their abstract representation, ignoring sign.
copy_abs(x)
Returns a copy of x with the sign set to 0.
copy_negate(x)
Returns a copy of x with the sign inverted.
copy_sign(x, y)
Copies the sign from y to x.
divide(x, y)
Return x divided by y.
divide_int(x, y)
Return x divided by y, truncated to an integer.
divmod(x, y)
Divides two numbers and returns the integer part of the result.
exp(x)
Returns e ** x.
fma(x, y, z)
Returns x multiplied by y, plus z.
is_canonical(x)
Returns True if x is canonical; otherwise returns False.
is_finite(x)
Returns True if x is finite; otherwise returns False.
is_infinite(x)
Returns True if x is infinite; otherwise returns False.
is_nan(x)
Returns True if x is a qNaN or sNaN; otherwise returns False.
is_normal(x)
Returns True if x is a normal number; otherwise returns False.
is_qnan(x)
Returns True if x is a quiet NaN; otherwise returns False.
is_signed(x)
Returns True if x is negative; otherwise returns False.
is_snan(x)
Returns True if x is a signaling NaN; otherwise returns False.
is_subnormal(x)
Returns True if x is subnormal; otherwise returns False.
is_zero(x)
Returns True if x is a zero; otherwise returns False.
ln(x)
Returns the natural (base e) logarithm of x.
log10(x)
Returns the base 10 logarithm of x.
logb(x)
Returns the exponent of the magnitude of the operand’s MSD.
logical_and(x, y)
Applies the logical operation and between each operand’s digits.
logical_invert(x)
Invert all the digits in x.
logical_or(x, y)
Applies the logical operation or between each operand’s digits.
logical_xor(x, y)
Applies the logical operation xor between each operand’s digits.
max(x, y)
Compares two values numerically and returns the maximum.
max_mag(x, y)
Compares the values numerically with their sign ignored.
min(x, y)
Compares two values numerically and returns the minimum.
min_mag(x, y)
Compares the values numerically with their sign ignored.
minus(x)
Minus corresponds to the unary prefix minus operator in Python.
multiply(x, y)
Return the product of x and y.
next_minus(x)
Returns the largest representable number smaller than x.
next_plus(x)
Returns the smallest representable number larger than x.
next_toward(x, y)
Returns the number closest to x, in direction towards y.
normalize(x)
Reduces x to its simplest form.
number_class(x)
Returns an indication of the class of x.
plus(x)
Plus corresponds to the unary prefix plus operator in Python. This operation applies the context precision and rounding, so it is not an identity operation.
power(x, y, modulo=None)
Return x to the power of y, reduced modulo modulo if given. With two arguments, compute x**y. If x is negative then y must be integral. The result will be inexact unless y is integral and the result is finite and can be expressed exactly in ‘precision’ digits. The rounding mode of the context is used. Results are always correctly-rounded in the Python version. Decimal(0) ** Decimal(0) results in InvalidOperation, and if InvalidOperation is not trapped, then results in Decimal('NaN'). Changed in version 3.3: The C module computes power() in terms of the correctly-rounded exp() and ln() functions. The result is well-defined but only “almost always correctly-rounded”. With three arguments, compute (x**y) % modulo. For the three argument form, the following restrictions on the arguments hold: all three arguments must be integral
y must be nonnegative at least one of x or y must be nonzero
modulo must be nonzero and have at most ‘precision’ digits The value resulting from Context.power(x, y, modulo) is equal to the value that would be obtained by computing (x**y)
% modulo with unbounded precision, but is computed more efficiently. The exponent of the result is zero, regardless of the exponents of x, y and modulo. The result is always exact.
quantize(x, y)
Returns a value equal to x (rounded), having the exponent of y.
radix()
Just returns 10, as this is Decimal, :)
remainder(x, y)
Returns the remainder from integer division. The sign of the result, if non-zero, is the same as that of the original dividend.
remainder_near(x, y)
Returns x - y * n, where n is the integer nearest the exact value of x / y (if the result is 0 then its sign will be the sign of x).
rotate(x, y)
Returns a rotated copy of x, y times.
same_quantum(x, y)
Returns True if the two operands have the same exponent.
scaleb(x, y)
Returns the first operand after adding the second value its exp.
shift(x, y)
Returns a shifted copy of x, y times.
sqrt(x)
Square root of a non-negative number to context precision.
subtract(x, y)
Return the difference between x and y.
to_eng_string(x)
Convert to a string, using engineering notation if an exponent is needed. Engineering notation has an exponent which is a multiple of 3. This can leave up to 3 digits to the left of the decimal place and may require the addition of either one or two trailing zeros.
to_integral_exact(x)
Rounds to an integer.
to_sci_string(x)
Converts a number to a string using scientific notation.
Constants The constants in this section are only relevant for the C module. They are also included in the pure Python version for compatibility.
32-bit 64-bit
decimal.MAX_PREC
425000000 999999999999999999
decimal.MAX_EMAX
425000000 999999999999999999
decimal.MIN_EMIN
-425000000 -999999999999999999
decimal.MIN_ETINY
-849999999 -1999999999999999997
decimal.HAVE_THREADS
The value is True. Deprecated, because Python now always has threads.
Deprecated since version 3.9.
decimal.HAVE_CONTEXTVAR
The default value is True. If Python is compiled --without-decimal-contextvar, the C version uses a thread-local rather than a coroutine-local context and the value is False. This is slightly faster in some nested context scenarios.
New in version 3.9: backported to 3.7 and 3.8. Rounding modes
decimal.ROUND_CEILING
Round towards Infinity.
decimal.ROUND_DOWN
Round towards zero.
decimal.ROUND_FLOOR
Round towards -Infinity.
decimal.ROUND_HALF_DOWN
Round to nearest with ties going towards zero.
decimal.ROUND_HALF_EVEN
Round to nearest with ties going to nearest even integer.
decimal.ROUND_HALF_UP
Round to nearest with ties going away from zero.
decimal.ROUND_UP
Round away from zero.
decimal.ROUND_05UP
Round away from zero if last digit after rounding towards zero would have been 0 or 5; otherwise round towards zero.
Signals Signals represent conditions that arise during computation. Each corresponds to one context flag and one context trap enabler. The context flag is set whenever the condition is encountered. After the computation, flags may be checked for informational purposes (for instance, to determine whether a computation was exact). After checking the flags, be sure to clear all flags before starting the next computation. If the context’s trap enabler is set for the signal, then the condition causes a Python exception to be raised. For example, if the DivisionByZero trap is set, then a DivisionByZero exception is raised upon encountering the condition.
class decimal.Clamped
Altered an exponent to fit representation constraints. Typically, clamping occurs when an exponent falls outside the context’s Emin and Emax limits. If possible, the exponent is reduced to fit by adding zeros to the coefficient.
class decimal.DecimalException
Base class for other signals and a subclass of ArithmeticError.
class decimal.DivisionByZero
Signals the division of a non-infinite number by zero. Can occur with division, modulo division, or when raising a number to a negative power. If this signal is not trapped, returns Infinity or -Infinity with the sign determined by the inputs to the calculation.
class decimal.Inexact
Indicates that rounding occurred and the result is not exact. Signals when non-zero digits were discarded during rounding. The rounded result is returned. The signal flag or trap is used to detect when results are inexact.
class decimal.InvalidOperation
An invalid operation was performed. Indicates that an operation was requested that does not make sense. If not trapped, returns NaN. Possible causes include: Infinity - Infinity
0 * Infinity
Infinity / Infinity
x % 0
Infinity % x
sqrt(-x) and x > 0
0 ** 0
x ** (non-integer)
x ** Infinity
class decimal.Overflow
Numerical overflow. Indicates the exponent is larger than Emax after rounding has occurred. If not trapped, the result depends on the rounding mode, either pulling inward to the largest representable finite number or rounding outward to Infinity. In either case, Inexact and Rounded are also signaled.
class decimal.Rounded
Rounding occurred though possibly no information was lost. Signaled whenever rounding discards digits; even if those digits are zero (such as rounding 5.00 to 5.0). If not trapped, returns the result unchanged. This signal is used to detect loss of significant digits.
class decimal.Subnormal
Exponent was lower than Emin prior to rounding. Occurs when an operation result is subnormal (the exponent is too small). If not trapped, returns the result unchanged.
class decimal.Underflow
Numerical underflow with result rounded to zero. Occurs when a subnormal result is pushed to zero by rounding. Inexact and Subnormal are also signaled.
class decimal.FloatOperation
Enable stricter semantics for mixing floats and Decimals. If the signal is not trapped (default), mixing floats and Decimals is permitted in the Decimal constructor, create_decimal() and all comparison operators. Both conversion and comparisons are exact. Any occurrence of a mixed operation is silently recorded by setting FloatOperation in the context flags. Explicit conversions with from_float() or create_decimal_from_float() do not set the flag. Otherwise (the signal is trapped), only equality comparisons and explicit conversions are silent. All other mixed operations raise FloatOperation.
The following table summarizes the hierarchy of signals: exceptions.ArithmeticError(exceptions.Exception)
DecimalException
Clamped
DivisionByZero(DecimalException, exceptions.ZeroDivisionError)
Inexact
Overflow(Inexact, Rounded)
Underflow(Inexact, Rounded, Subnormal)
InvalidOperation
Rounded
Subnormal
FloatOperation(DecimalException, exceptions.TypeError)
Floating Point Notes Mitigating round-off error with increased precision The use of decimal floating point eliminates decimal representation error (making it possible to represent 0.1 exactly); however, some operations can still incur round-off error when non-zero digits exceed the fixed precision. The effects of round-off error can be amplified by the addition or subtraction of nearly offsetting quantities resulting in loss of significance. Knuth provides two instructive examples where rounded floating point arithmetic with insufficient precision causes the breakdown of the associative and distributive properties of addition: # Examples from Seminumerical Algorithms, Section 4.2.2.
>>> from decimal import Decimal, getcontext
>>> getcontext().prec = 8
>>> u, v, w = Decimal(11111113), Decimal(-11111111), Decimal('7.51111111')
>>> (u + v) + w
Decimal('9.5111111')
>>> u + (v + w)
Decimal('10')
>>> u, v, w = Decimal(20000), Decimal(-6), Decimal('6.0000003')
>>> (u*v) + (u*w)
Decimal('0.01')
>>> u * (v+w)
Decimal('0.0060000')
The decimal module makes it possible to restore the identities by expanding the precision sufficiently to avoid loss of significance: >>> getcontext().prec = 20
>>> u, v, w = Decimal(11111113), Decimal(-11111111), Decimal('7.51111111')
>>> (u + v) + w
Decimal('9.51111111')
>>> u + (v + w)
Decimal('9.51111111')
>>>
>>> u, v, w = Decimal(20000), Decimal(-6), Decimal('6.0000003')
>>> (u*v) + (u*w)
Decimal('0.0060000')
>>> u * (v+w)
Decimal('0.0060000')
Special values The number system for the decimal module provides special values including NaN, sNaN, -Infinity, Infinity, and two zeros, +0 and -0. Infinities can be constructed directly with: Decimal('Infinity'). Also, they can arise from dividing by zero when the DivisionByZero signal is not trapped. Likewise, when the Overflow signal is not trapped, infinity can result from rounding beyond the limits of the largest representable number. The infinities are signed (affine) and can be used in arithmetic operations where they get treated as very large, indeterminate numbers. For instance, adding a constant to infinity gives another infinite result. Some operations are indeterminate and return NaN, or if the InvalidOperation signal is trapped, raise an exception. For example, 0/0 returns NaN which means “not a number”. This variety of NaN is quiet and, once created, will flow through other computations always resulting in another NaN. This behavior can be useful for a series of computations that occasionally have missing inputs — it allows the calculation to proceed while flagging specific results as invalid. A variant is sNaN which signals rather than remaining quiet after every operation. This is a useful return value when an invalid result needs to interrupt a calculation for special handling. The behavior of Python’s comparison operators can be a little surprising where a NaN is involved. A test for equality where one of the operands is a quiet or signaling NaN always returns False (even when doing Decimal('NaN')==Decimal('NaN')), while a test for inequality always returns True. An attempt to compare two Decimals using any of the <, <=, > or >= operators will raise the InvalidOperation signal if either operand is a NaN, and return False if this signal is not trapped. Note that the General Decimal Arithmetic specification does not specify the behavior of direct comparisons; these rules for comparisons involving a NaN were taken from the IEEE 854 standard (see Table 3 in section 5.7). To ensure strict standards-compliance, use the compare() and compare-signal() methods instead. The signed zeros can result from calculations that underflow. They keep the sign that would have resulted if the calculation had been carried out to greater precision. Since their magnitude is zero, both positive and negative zeros are treated as equal and their sign is informational. In addition to the two signed zeros which are distinct yet equal, there are various representations of zero with differing precisions yet equivalent in value. This takes a bit of getting used to. For an eye accustomed to normalized floating point representations, it is not immediately obvious that the following calculation returns a value equal to zero: >>> 1 / Decimal('Infinity')
Decimal('0E-1000026')
Working with threads The getcontext() function accesses a different Context object for each thread. Having separate thread contexts means that threads may make changes (such as getcontext().prec=10) without interfering with other threads. Likewise, the setcontext() function automatically assigns its target to the current thread. If setcontext() has not been called before getcontext(), then getcontext() will automatically create a new context for use in the current thread. The new context is copied from a prototype context called DefaultContext. To control the defaults so that each thread will use the same values throughout the application, directly modify the DefaultContext object. This should be done before any threads are started so that there won’t be a race condition between threads calling getcontext(). For example: # Set applicationwide defaults for all threads about to be launched
DefaultContext.prec = 12
DefaultContext.rounding = ROUND_DOWN
DefaultContext.traps = ExtendedContext.traps.copy()
DefaultContext.traps[InvalidOperation] = 1
setcontext(DefaultContext)
# Afterwards, the threads can be started
t1.start()
t2.start()
t3.start()
. . .
Recipes Here are a few recipes that serve as utility functions and that demonstrate ways to work with the Decimal class: def moneyfmt(value, places=2, curr='', sep=',', dp='.',
pos='', neg='-', trailneg=''):
"""Convert Decimal to a money formatted string.
places: required number of places after the decimal point
curr: optional currency symbol before the sign (may be blank)
sep: optional grouping separator (comma, period, space, or blank)
dp: decimal point indicator (comma or period)
only specify as blank when places is zero
pos: optional sign for positive numbers: '+', space or blank
neg: optional sign for negative numbers: '-', '(', space or blank
trailneg:optional trailing minus indicator: '-', ')', space or blank
>>> d = Decimal('-1234567.8901')
>>> moneyfmt(d, curr='$')
'-$1,234,567.89'
>>> moneyfmt(d, places=0, sep='.', dp='', neg='', trailneg='-')
'1.234.568-'
>>> moneyfmt(d, curr='$', neg='(', trailneg=')')
'($1,234,567.89)'
>>> moneyfmt(Decimal(123456789), sep=' ')
'123 456 789.00'
>>> moneyfmt(Decimal('-0.02'), neg='<', trailneg='>')
'<0.02>'
"""
q = Decimal(10) ** -places # 2 places --> '0.01'
sign, digits, exp = value.quantize(q).as_tuple()
result = []
digits = list(map(str, digits))
build, next = result.append, digits.pop
if sign:
build(trailneg)
for i in range(places):
build(next() if digits else '0')
if places:
build(dp)
if not digits:
build('0')
i = 0
while digits:
build(next())
i += 1
if i == 3 and digits:
i = 0
build(sep)
build(curr)
build(neg if sign else pos)
return ''.join(reversed(result))
def pi():
"""Compute Pi to the current precision.
>>> print(pi())
3.141592653589793238462643383
"""
getcontext().prec += 2 # extra digits for intermediate steps
three = Decimal(3) # substitute "three=3.0" for regular floats
lasts, t, s, n, na, d, da = 0, three, 3, 1, 0, 0, 24
while s != lasts:
lasts = s
n, na = n+na, na+8
d, da = d+da, da+32
t = (t * n) / d
s += t
getcontext().prec -= 2
return +s # unary plus applies the new precision
def exp(x):
"""Return e raised to the power of x. Result type matches input type.
>>> print(exp(Decimal(1)))
2.718281828459045235360287471
>>> print(exp(Decimal(2)))
7.389056098930650227230427461
>>> print(exp(2.0))
7.38905609893
>>> print(exp(2+0j))
(7.38905609893+0j)
"""
getcontext().prec += 2
i, lasts, s, fact, num = 0, 0, 1, 1, 1
while s != lasts:
lasts = s
i += 1
fact *= i
num *= x
s += num / fact
getcontext().prec -= 2
return +s
def cos(x):
"""Return the cosine of x as measured in radians.
The Taylor series approximation works best for a small value of x.
For larger values, first compute x = x % (2 * pi).
>>> print(cos(Decimal('0.5')))
0.8775825618903727161162815826
>>> print(cos(0.5))
0.87758256189
>>> print(cos(0.5+0j))
(0.87758256189+0j)
"""
getcontext().prec += 2
i, lasts, s, fact, num, sign = 0, 0, 1, 1, 1, 1
while s != lasts:
lasts = s
i += 2
fact *= i * (i-1)
num *= x * x
sign *= -1
s += num / fact * sign
getcontext().prec -= 2
return +s
def sin(x):
"""Return the sine of x as measured in radians.
The Taylor series approximation works best for a small value of x.
For larger values, first compute x = x % (2 * pi).
>>> print(sin(Decimal('0.5')))
0.4794255386042030002732879352
>>> print(sin(0.5))
0.479425538604
>>> print(sin(0.5+0j))
(0.479425538604+0j)
"""
getcontext().prec += 2
i, lasts, s, fact, num, sign = 1, 0, x, 1, x, 1
while s != lasts:
lasts = s
i += 2
fact *= i * (i-1)
num *= x * x
sign *= -1
s += num / fact * sign
getcontext().prec -= 2
return +s
Decimal FAQ Q. It is cumbersome to type decimal.Decimal('1234.5'). Is there a way to minimize typing when using the interactive interpreter? A. Some users abbreviate the constructor to just a single letter: >>> D = decimal.Decimal
>>> D('1.23') + D('3.45')
Decimal('4.68')
Q. In a fixed-point application with two decimal places, some inputs have many places and need to be rounded. Others are not supposed to have excess digits and need to be validated. What methods should be used? A. The quantize() method rounds to a fixed number of decimal places. If the Inexact trap is set, it is also useful for validation: >>> TWOPLACES = Decimal(10) ** -2 # same as Decimal('0.01')
>>> # Round to two places
>>> Decimal('3.214').quantize(TWOPLACES)
Decimal('3.21')
>>> # Validate that a number does not exceed two places
>>> Decimal('3.21').quantize(TWOPLACES, context=Context(traps=[Inexact]))
Decimal('3.21')
>>> Decimal('3.214').quantize(TWOPLACES, context=Context(traps=[Inexact]))
Traceback (most recent call last):
...
Inexact: None
Q. Once I have valid two place inputs, how do I maintain that invariant throughout an application? A. Some operations like addition, subtraction, and multiplication by an integer will automatically preserve fixed point. Others operations, like division and non-integer multiplication, will change the number of decimal places and need to be followed-up with a quantize() step: >>> a = Decimal('102.72') # Initial fixed-point values
>>> b = Decimal('3.17')
>>> a + b # Addition preserves fixed-point
Decimal('105.89')
>>> a - b
Decimal('99.55')
>>> a * 42 # So does integer multiplication
Decimal('4314.24')
>>> (a * b).quantize(TWOPLACES) # Must quantize non-integer multiplication
Decimal('325.62')
>>> (b / a).quantize(TWOPLACES) # And quantize division
Decimal('0.03')
In developing fixed-point applications, it is convenient to define functions to handle the quantize() step: >>> def mul(x, y, fp=TWOPLACES):
... return (x * y).quantize(fp)
>>> def div(x, y, fp=TWOPLACES):
... return (x / y).quantize(fp)
>>> mul(a, b) # Automatically preserve fixed-point
Decimal('325.62')
>>> div(b, a)
Decimal('0.03')
Q. There are many ways to express the same value. The numbers 200, 200.000, 2E2, and 02E+4 all have the same value at various precisions. Is there a way to transform them to a single recognizable canonical value? A. The normalize() method maps all equivalent values to a single representative: >>> values = map(Decimal, '200 200.000 2E2 .02E+4'.split())
>>> [v.normalize() for v in values]
[Decimal('2E+2'), Decimal('2E+2'), Decimal('2E+2'), Decimal('2E+2')]
Q. Some decimal values always print with exponential notation. Is there a way to get a non-exponential representation? A. For some values, exponential notation is the only way to express the number of significant places in the coefficient. For example, expressing 5.0E+3 as 5000 keeps the value constant but cannot show the original’s two-place significance. If an application does not care about tracking significance, it is easy to remove the exponent and trailing zeroes, losing significance, but keeping the value unchanged: >>> def remove_exponent(d):
... return d.quantize(Decimal(1)) if d == d.to_integral() else d.normalize()
>>> remove_exponent(Decimal('5E+3'))
Decimal('5000')
Q. Is there a way to convert a regular float to a Decimal? A. Yes, any binary floating point number can be exactly expressed as a Decimal though an exact conversion may take more precision than intuition would suggest: >>> Decimal(math.pi)
Decimal('3.141592653589793115997963468544185161590576171875')
Q. Within a complex calculation, how can I make sure that I haven’t gotten a spurious result because of insufficient precision or rounding anomalies. A. The decimal module makes it easy to test results. A best practice is to re-run calculations using greater precision and with various rounding modes. Widely differing results indicate insufficient precision, rounding mode issues, ill-conditioned inputs, or a numerically unstable algorithm. Q. I noticed that context precision is applied to the results of operations but not to the inputs. Is there anything to watch out for when mixing values of different precisions? A. Yes. The principle is that all values are considered to be exact and so is the arithmetic on those values. Only the results are rounded. The advantage for inputs is that “what you type is what you get”. A disadvantage is that the results can look odd if you forget that the inputs haven’t been rounded: >>> getcontext().prec = 3
>>> Decimal('3.104') + Decimal('2.104')
Decimal('5.21')
>>> Decimal('3.104') + Decimal('0.000') + Decimal('2.104')
Decimal('5.20')
The solution is either to increase precision or to force rounding of inputs using the unary plus operation: >>> getcontext().prec = 3
>>> +Decimal('1.23456789') # unary plus triggers rounding
Decimal('1.23')
Alternatively, inputs can be rounded upon creation using the Context.create_decimal() method: >>> Context(prec=5, rounding=ROUND_DOWN).create_decimal('1.2345678')
Decimal('1.2345')
Q. Is the CPython implementation fast for large numbers? A. Yes. In the CPython and PyPy3 implementations, the C/CFFI versions of the decimal module integrate the high speed libmpdec library for arbitrary precision correctly-rounded decimal floating point arithmetic 1. libmpdec uses Karatsuba multiplication for medium-sized numbers and the Number Theoretic Transform for very large numbers. The context must be adapted for exact arbitrary precision arithmetic. Emin and Emax should always be set to the maximum values, clamp should always be 0 (the default). Setting prec requires some care. The easiest approach for trying out bignum arithmetic is to use the maximum value for prec as well 2: >>> setcontext(Context(prec=MAX_PREC, Emax=MAX_EMAX, Emin=MIN_EMIN))
>>> x = Decimal(2) ** 256
>>> x / 128
Decimal('904625697166532776746648320380374280103671755200316906558262375061821325312')
For inexact results, MAX_PREC is far too large on 64-bit platforms and the available memory will be insufficient: >>> Decimal(1) / 3
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
MemoryError
On systems with overallocation (e.g. Linux), a more sophisticated approach is to adjust prec to the amount of available RAM. Suppose that you have 8GB of RAM and expect 10 simultaneous operands using a maximum of 500MB each: >>> import sys
>>>
>>> # Maximum number of digits for a single operand using 500MB in 8-byte words
>>> # with 19 digits per word (4-byte and 9 digits for the 32-bit build):
>>> maxdigits = 19 * ((500 * 1024**2) // 8)
>>>
>>> # Check that this works:
>>> c = Context(prec=maxdigits, Emax=MAX_EMAX, Emin=MIN_EMIN)
>>> c.traps[Inexact] = True
>>> setcontext(c)
>>>
>>> # Fill the available precision with nines:
>>> x = Decimal(0).logical_invert() * 9
>>> sys.getsizeof(x)
524288112
>>> x + 2
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
decimal.Inexact: [<class 'decimal.Inexact'>]
In general (and especially on systems without overallocation), it is recommended to estimate even tighter bounds and set the Inexact trap if all calculations are expected to be exact.
1
New in version 3.3.
2
Changed in version 3.9: This approach now works for all exact results except for non-integer powers. | python.library.decimal |
class decimal.BasicContext
This is a standard context defined by the General Decimal Arithmetic Specification. Precision is set to nine. Rounding is set to ROUND_HALF_UP. All flags are cleared. All traps are enabled (treated as exceptions) except Inexact, Rounded, and Subnormal. Because many of the traps are enabled, this context is useful for debugging. | python.library.decimal#decimal.BasicContext |
class decimal.Clamped
Altered an exponent to fit representation constraints. Typically, clamping occurs when an exponent falls outside the context’s Emin and Emax limits. If possible, the exponent is reduced to fit by adding zeros to the coefficient. | python.library.decimal#decimal.Clamped |
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