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:mod:`decimal` --- Decimal fixed point and floating point arithmetic
====================================================================
.. module:: decimal
:synopsis: Implementation of the General Decimal Arithmetic Specification.
.. moduleauthor:: Eric Price <eprice at tjhsst.edu>
.. moduleauthor:: Facundo Batista <facundo at taniquetil.com.ar>
.. moduleauthor:: Raymond Hettinger <python at rcn.com>
.. moduleauthor:: Aahz <aahz at pobox.com>
.. moduleauthor:: Tim Peters <tim.one at comcast.net>
.. sectionauthor:: Raymond D. Hettinger <python at rcn.com>
.. versionadded:: 2.4
.. import modules for testing inline doctests with the Sphinx doctest builder
.. testsetup:: *
import decimal
import math
from decimal import *
# make sure each group gets a fresh context
setcontext(Context())
The :mod:`decimal` module provides support for decimal floating point
arithmetic. It offers several advantages over the :class:`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
:const:`1.1` and :const:`2.2` do not have an exact representations in binary
floating point. End users typically would not expect ``1.1 + 2.2`` to display
as :const:`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 :const:`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 :const:`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 :const:`1.56` while ``1.30 *
1.20`` gives :const:`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:
>>> 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
:const:`Infinity`, :const:`-Infinity`, and :const:`NaN`. The standard also
differentiates :const:`-0` from :const:`+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 :const:`ROUND_CEILING`, :const:`ROUND_DOWN`,
:const:`ROUND_FLOOR`, :const:`ROUND_HALF_DOWN`, :const:`ROUND_HALF_EVEN`,
:const:`ROUND_HALF_UP`, :const:`ROUND_UP`, and :const:`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: :const:`Clamped`, :const:`InvalidOperation`,
:const:`DivisionByZero`, :const:`Inexact`, :const:`Rounded`, :const:`Subnormal`,
:const:`Overflow`, and :const:`Underflow`.
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.
.. seealso::
* IBM's General Decimal Arithmetic Specification, `The General Decimal Arithmetic
Specification <http://speleotrove.com/decimal/>`_.
* IEEE standard 854-1987, `Unofficial IEEE 854 Text
<http://754r.ucbtest.org/standards/854.pdf>`_.
.. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. _decimal-tutorial:
Quick-start Tutorial
--------------------
The usual start to using decimals is importing the module, viewing the current
context with :func:`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=-999999999, Emax=999999999,
capitals=1, 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
:const:`NaN` which stands for "Not a number", positive and negative
:const:`Infinity`, and :const:`-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('1.41421356237')
>>> Decimal(2) ** Decimal('0.5')
Decimal('1.414213562373095048801688724')
>>> Decimal('NaN')
Decimal('NaN')
>>> Decimal('-Infinity')
Decimal('-Infinity')
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.
.. doctest:: newcontext
>>> 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')
Decimals interact well with much of the rest of Python. Here is a small decimal
floating point flying circus:
.. doctest::
:options: +NORMALIZE_WHITESPACE
>>> data = 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) # round() first converts to binary floating point
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 :meth:`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 :func:`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 :func:`setcontext`
function.
In accordance with the standard, the :mod:`Decimal` module provides two ready to
use standard contexts, :const:`BasicContext` and :const:`ExtendedContext`. The
former is especially useful for debugging because many of the traps are
enabled:
.. doctest:: newcontext
:options: +NORMALIZE_WHITESPACE
>>> 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=-999999999, Emax=999999999,
capitals=1, 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 :meth:`clear_flags` method. ::
>>> setcontext(ExtendedContext)
>>> getcontext().clear_flags()
>>> Decimal(355) / Decimal(113)
Decimal('3.14159292')
>>> getcontext()
Context(prec=9, rounding=ROUND_HALF_EVEN, Emin=-999999999, Emax=999999999,
capitals=1, flags=[Rounded, Inexact], traps=[])
The *flags* entry shows that the rational approximation to :const:`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 :attr:`traps` field of a
context:
.. doctest:: newcontext
>>> 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 :class:`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-decimal:
Decimal objects
---------------
.. class:: Decimal([value [, context]])
Construct a new :class:`Decimal` object based from *value*.
*value* can be an integer, string, tuple, :class:`float`, or another :class:`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 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
If *value* is a unicode string then 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
``u'\uff10'`` through ``u'\uff19'``.
If *value* is a :class:`tuple`, it should have three components, a sign
(:const:`0` for positive or :const:`1` for negative), a :class:`tuple` of
digits, and an integer exponent. For example, ``Decimal((0, (1, 4, 1, 4), -3))``
returns ``Decimal('1.414')``.
If *value* is a :class:`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 :const:`InvalidOperation`, an exception
is raised; otherwise, the constructor returns a new Decimal with the value of
:const:`NaN`.
Once constructed, :class:`Decimal` objects are immutable.
.. versionchanged:: 2.6
leading and trailing whitespace characters are permitted when
creating a Decimal instance from a string.
.. versionchanged:: 2.7
The argument to the constructor is now permitted to be a :class:`float` instance.
Decimal floating point objects share many properties with the other built-in
numeric types such as :class:`float` and :class:`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 :class:`float` or
:class:`long`).
Decimal objects cannot generally be combined with floats in
arithmetic operations: an attempt to add a :class:`Decimal` to a
:class:`float`, for example, will raise a :exc:`TypeError`.
There's one exception to this rule: it's possible to use Python's
comparison operators to compare a :class:`float` instance ``x``
with a :class:`Decimal` instance ``y``. Without this exception,
comparisons between :class:`Decimal` and :class:`float` instances
would follow the general rules for comparing objects of different
types described in the :ref:`expressions` section of the reference
manual, leading to confusing results.
.. versionchanged:: 2.7
A comparison between a :class:`float` instance ``x`` and a
:class:`Decimal` instance ``y`` now returns a result based on
the values of ``x`` and ``y``. In earlier versions ``x < y``
returned the same (arbitrary) result for any :class:`Decimal`
instance ``x`` and any :class:`float` instance ``y``.
In addition to the standard numeric properties, decimal floating point
objects also have a number of specialized methods:
.. method:: 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.
.. method:: as_tuple()
Return a :term:`named tuple` representation of the number:
``DecimalTuple(sign, digits, exponent)``.
.. versionchanged:: 2.6
Use a named tuple.
.. method:: canonical()
Return the canonical encoding of the argument. Currently, the encoding of
a :class:`Decimal` instance is always canonical, so this operation returns
its argument unchanged.
.. versionadded:: 2.6
.. method:: compare(other[, context])
Compare the values of two Decimal instances. This operation behaves in
the same way as the usual comparison method :meth:`__cmp__`, except that
:meth:`compare` returns a Decimal instance rather than an integer, 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')
.. method:: compare_signal(other[, context])
This operation is identical to the :meth:`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.
.. versionadded:: 2.6
.. method:: compare_total(other)
Compare two operands using their abstract representation rather than their
numerical value. Similar to the :meth:`compare` method, but the result
gives a total ordering on :class:`Decimal` instances. Two
:class:`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.
.. versionadded:: 2.6
.. method:: compare_total_mag(other)
Compare two operands using their abstract representation rather than their
value as in :meth:`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())``.
.. versionadded:: 2.6
.. method:: conjugate()
Just returns self, this method is only to comply with the Decimal
Specification.
.. versionadded:: 2.6
.. method:: 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.
.. versionadded:: 2.6
.. method:: 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.
.. versionadded:: 2.6
.. method:: copy_sign(other)
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 the context and is quiet: no flags are
changed and no rounding is performed.
.. versionadded:: 2.6
.. method:: exp([context])
Return the value of the (natural) exponential function ``e**x`` at the
given number. The result is correctly rounded using the
:const:`ROUND_HALF_EVEN` rounding mode.
>>> Decimal(1).exp()
Decimal('2.718281828459045235360287471')
>>> Decimal(321).exp()
Decimal('2.561702493119680037517373933E+139')
.. versionadded:: 2.6
.. method:: 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 2.7 onwards, a :class:`Decimal` instance
can also be constructed directly from a :class:`float`.
.. doctest::
>>> 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')
.. versionadded:: 2.7
.. method:: fma(other, third[, context])
Fused multiply-add. Return self*other+third with no rounding of the
intermediate product self*other.
>>> Decimal(2).fma(3, 5)
Decimal('11')
.. versionadded:: 2.6
.. method:: is_canonical()
Return :const:`True` if the argument is canonical and :const:`False`
otherwise. Currently, a :class:`Decimal` instance is always canonical, so
this operation always returns :const:`True`.
.. versionadded:: 2.6
.. method:: is_finite()
Return :const:`True` if the argument is a finite number, and
:const:`False` if the argument is an infinity or a NaN.
.. versionadded:: 2.6
.. method:: is_infinite()
Return :const:`True` if the argument is either positive or negative
infinity and :const:`False` otherwise.
.. versionadded:: 2.6
.. method:: is_nan()
Return :const:`True` if the argument is a (quiet or signaling) NaN and
:const:`False` otherwise.
.. versionadded:: 2.6
.. method:: is_normal()
Return :const:`True` if the argument is a *normal* finite non-zero
number with an adjusted exponent greater than or equal to *Emin*.
Return :const:`False` if the argument is zero, subnormal, infinite or a
NaN. Note, the term *normal* is used here in a different sense with
the :meth:`normalize` method which is used to create canonical values.
.. versionadded:: 2.6
.. method:: is_qnan()
Return :const:`True` if the argument is a quiet NaN, and
:const:`False` otherwise.
.. versionadded:: 2.6
.. method:: is_signed()
Return :const:`True` if the argument has a negative sign and
:const:`False` otherwise. Note that zeros and NaNs can both carry signs.
.. versionadded:: 2.6
.. method:: is_snan()
Return :const:`True` if the argument is a signaling NaN and :const:`False`
otherwise.
.. versionadded:: 2.6
.. method:: is_subnormal()
Return :const:`True` if the argument is subnormal, and :const:`False`
otherwise. A number is subnormal is if it is nonzero, finite, and has an
adjusted exponent less than *Emin*.
.. versionadded:: 2.6
.. method:: is_zero()
Return :const:`True` if the argument is a (positive or negative) zero and
:const:`False` otherwise.
.. versionadded:: 2.6
.. method:: ln([context])
Return the natural (base e) logarithm of the operand. The result is
correctly rounded using the :const:`ROUND_HALF_EVEN` rounding mode.
.. versionadded:: 2.6
.. method:: log10([context])
Return the base ten logarithm of the operand. The result is correctly
rounded using the :const:`ROUND_HALF_EVEN` rounding mode.
.. versionadded:: 2.6
.. method:: logb([context])
For a nonzero number, return the adjusted exponent of its operand as a
:class:`Decimal` instance. If the operand is a zero then
``Decimal('-Infinity')`` is returned and the :const:`DivisionByZero` flag
is raised. If the operand is an infinity then ``Decimal('Infinity')`` is
returned.
.. versionadded:: 2.6
.. method:: logical_and(other[, context])
:meth:`logical_and` is a logical operation which takes two *logical
operands* (see :ref:`logical_operands_label`). The result is the
digit-wise ``and`` of the two operands.
.. versionadded:: 2.6
.. method:: logical_invert([context])
:meth:`logical_invert` is a logical operation. The
result is the digit-wise inversion of the operand.
.. versionadded:: 2.6
.. method:: logical_or(other[, context])
:meth:`logical_or` is a logical operation which takes two *logical
operands* (see :ref:`logical_operands_label`). The result is the
digit-wise ``or`` of the two operands.
.. versionadded:: 2.6
.. method:: logical_xor(other[, context])
:meth:`logical_xor` is a logical operation which takes two *logical
operands* (see :ref:`logical_operands_label`). The result is the
digit-wise exclusive or of the two operands.
.. versionadded:: 2.6
.. method:: max(other[, context])
Like ``max(self, other)`` except that the context rounding rule is applied
before returning and that :const:`NaN` values are either signaled or
ignored (depending on the context and whether they are signaling or
quiet).
.. method:: max_mag(other[, context])
Similar to the :meth:`.max` method, but the comparison is done using the
absolute values of the operands.
.. versionadded:: 2.6
.. method:: min(other[, context])
Like ``min(self, other)`` except that the context rounding rule is applied
before returning and that :const:`NaN` values are either signaled or
ignored (depending on the context and whether they are signaling or
quiet).
.. method:: min_mag(other[, context])
Similar to the :meth:`.min` method, but the comparison is done using the
absolute values of the operands.
.. versionadded:: 2.6
.. method:: next_minus([context])
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.
.. versionadded:: 2.6
.. method:: next_plus([context])
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.
.. versionadded:: 2.6
.. method:: next_toward(other[, context])
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.
.. versionadded:: 2.6
.. method:: normalize([context])
Normalize the number by stripping the rightmost trailing zeros and
converting any result equal to :const:`Decimal('0')` to
:const:`Decimal('0e0')`. Used for producing canonical values for members
of an equivalence class. For example, ``Decimal('32.100')`` and
``Decimal('0.321000e+2')`` both normalize to the equivalent value
``Decimal('32.1')``.
.. method:: number_class([context])
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.
.. versionadded:: 2.6
.. method:: quantize(exp[, rounding[, context[, watchexp]]])
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
:const:`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.
If *watchexp* is set (default), then an error is returned whenever the
resulting exponent is greater than :attr:`Emax` or less than
:attr:`Etiny`.
.. method:: radix()
Return ``Decimal(10)``, the radix (base) in which the :class:`Decimal`
class does all its arithmetic. Included for compatibility with the
specification.
.. versionadded:: 2.6
.. method:: remainder_near(other[, context])
Compute the modulo as either a positive or negative value depending on
which is closest to zero. For instance, ``Decimal(10).remainder_near(6)``
returns ``Decimal('-2')`` which is closer to zero than ``Decimal('4')``.
If both are equally close, the one chosen will have the same sign as
*self*.
.. method:: rotate(other[, context])
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.
.. versionadded:: 2.6
.. method:: same_quantum(other[, context])
Test whether self and other have the same exponent or whether both are
:const:`NaN`.
.. method:: scaleb(other[, context])
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.
.. versionadded:: 2.6
.. method:: shift(other[, context])
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.
.. versionadded:: 2.6
.. method:: sqrt([context])
Return the square root of the argument to full precision.
.. method:: to_eng_string([context])
Convert to an engineering-type string.
Engineering notation has an exponent which is a multiple of 3, so there
are up to 3 digits left of the decimal place. For example, converts
``Decimal('123E+1')`` to ``Decimal('1.23E+3')``
.. method:: to_integral([rounding[, context]])
Identical to the :meth:`to_integral_value` method. The ``to_integral``
name has been kept for compatibility with older versions.
.. method:: to_integral_exact([rounding[, context]])
Round to the nearest integer, signaling :const:`Inexact` or
:const:`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.
.. versionadded:: 2.6
.. method:: to_integral_value([rounding[, context]])
Round to the nearest integer without signaling :const:`Inexact` or
:const:`Rounded`. If given, applies *rounding*; otherwise, uses the
rounding method in either the supplied *context* or the current context.
.. versionchanged:: 2.6
renamed from ``to_integral`` to ``to_integral_value``. The old name
remains valid for compatibility.
.. _logical_operands_label:
Logical operands
^^^^^^^^^^^^^^^^
The :meth:`logical_and`, :meth:`logical_invert`, :meth:`logical_or`,
and :meth:`logical_xor` methods expect their arguments to be *logical
operands*. A *logical operand* is a :class:`Decimal` instance whose
exponent and sign are both zero, and whose digits are all either
:const:`0` or :const:`1`.
.. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. _decimal-context:
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
:func:`getcontext` and :func:`setcontext` functions:
.. function:: getcontext()
Return the current context for the active thread.
.. function:: setcontext(c)
Set the current context for the active thread to *c*.
Beginning with Python 2.5, you can also use the :keyword:`with` statement and
the :func:`localcontext` function to temporarily change the active context.
.. function:: localcontext([c])
Return a context manager that will set the current context for the active thread
to a copy of *c* 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.
.. versionadded:: 2.5
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 :class:`Context` constructor
described below. In addition, the module provides three pre-made contexts:
.. class:: BasicContext
This is a standard context defined by the General Decimal Arithmetic
Specification. Precision is set to nine. Rounding is set to
:const:`ROUND_HALF_UP`. All flags are cleared. All traps are enabled (treated
as exceptions) except :const:`Inexact`, :const:`Rounded`, and
:const:`Subnormal`.
Because many of the traps are enabled, this context is useful for debugging.
.. class:: ExtendedContext
This is a standard context defined by the General Decimal Arithmetic
Specification. Precision is set to nine. Rounding is set to
:const:`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 :const:`NaN` or :const:`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:: DefaultContext
This context is used by the :class:`Context` constructor as a prototype for new
contexts. Changing a field (such a precision) has the effect of changing the
default for new contexts creating by the :class:`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 precision=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
:class:`Context` constructor.
.. class:: Context(prec=None, rounding=None, traps=None, flags=None, Emin=None, Emax=None, capitals=1)
Creates a new context. If a field is not specified or is :const:`None`, the
default values are copied from the :const:`DefaultContext`. If the *flags*
field is not specified or is :const:`None`, all flags are cleared.
The *prec* field is a positive integer that sets the precision for arithmetic
operations in the context.
The *rounding* option is one of:
* :const:`ROUND_CEILING` (towards :const:`Infinity`),
* :const:`ROUND_DOWN` (towards zero),
* :const:`ROUND_FLOOR` (towards :const:`-Infinity`),
* :const:`ROUND_HALF_DOWN` (to nearest with ties going towards zero),
* :const:`ROUND_HALF_EVEN` (to nearest with ties going to nearest even integer),
* :const:`ROUND_HALF_UP` (to nearest with ties going away from zero), or
* :const:`ROUND_UP` (away from zero).
* :const:`ROUND_05UP` (away from zero if last digit after rounding towards zero
would have been 0 or 5; otherwise towards zero)
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.
The *capitals* field is either :const:`0` or :const:`1` (the default). If set to
:const:`1`, exponents are printed with a capital :const:`E`; otherwise, a
lowercase :const:`e` is used: :const:`Decimal('6.02e+23')`.
.. versionchanged:: 2.6
The :const:`ROUND_05UP` rounding mode was added.
The :class:`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 :class:`Decimal` methods described above (with
the exception of the :meth:`adjusted` and :meth:`as_tuple` methods) there is
a corresponding :class:`Context` method. For example, for a :class:`Context`
instance ``C`` and :class:`Decimal` instance ``x``, ``C.exp(x)`` is
equivalent to ``x.exp(context=C)``. Each :class:`Context` method accepts a
Python integer (an instance of :class:`int` or :class:`long`) anywhere that a
Decimal instance is accepted.
.. method:: clear_flags()
Resets all of the flags to :const:`0`.
.. method:: copy()
Return a duplicate of the context.
.. method:: copy_decimal(num)
Return a copy of the Decimal instance num.
.. method:: create_decimal(num)
Creates a new Decimal instance from *num* but using *self* as
context. Unlike the :class:`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:
.. doctest:: newcontext
>>> 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 is
permitted.
.. method:: create_decimal_from_float(f)
Creates a new Decimal instance from a float *f* but rounding using *self*
as the context. Unlike the :meth:`Decimal.from_float` class method,
the context precision, rounding method, flags, and traps are applied to
the conversion.
.. doctest::
>>> 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):
...
Inexact: None
.. versionadded:: 2.7
.. method:: 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 :const:`Etiny`.
.. method:: Etop()
Returns a value equal to ``Emax - prec + 1``.
The usual approach to working with decimals is to create :class:`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 :class:`Decimal` class and are only briefly
recounted here.
.. method:: abs(x)
Returns the absolute value of *x*.
.. method:: add(x, y)
Return the sum of *x* and *y*.
.. method:: canonical(x)
Returns the same Decimal object *x*.
.. method:: compare(x, y)
Compares *x* and *y* numerically.
.. method:: compare_signal(x, y)
Compares the values of the two operands numerically.
.. method:: compare_total(x, y)
Compares two operands using their abstract representation.
.. method:: compare_total_mag(x, y)
Compares two operands using their abstract representation, ignoring sign.
.. method:: copy_abs(x)
Returns a copy of *x* with the sign set to 0.
.. method:: copy_negate(x)
Returns a copy of *x* with the sign inverted.
.. method:: copy_sign(x, y)
Copies the sign from *y* to *x*.
.. method:: divide(x, y)
Return *x* divided by *y*.
.. method:: divide_int(x, y)
Return *x* divided by *y*, truncated to an integer.
.. method:: divmod(x, y)
Divides two numbers and returns the integer part of the result.
.. method:: exp(x)
Returns `e ** x`.
.. method:: fma(x, y, z)
Returns *x* multiplied by *y*, plus *z*.
.. method:: is_canonical(x)
Returns True if *x* is canonical; otherwise returns False.
.. method:: is_finite(x)
Returns True if *x* is finite; otherwise returns False.
.. method:: is_infinite(x)
Returns True if *x* is infinite; otherwise returns False.
.. method:: is_nan(x)
Returns True if *x* is a qNaN or sNaN; otherwise returns False.
.. method:: is_normal(x)
Returns True if *x* is a normal number; otherwise returns False.
.. method:: is_qnan(x)
Returns True if *x* is a quiet NaN; otherwise returns False.
.. method:: is_signed(x)
Returns True if *x* is negative; otherwise returns False.
.. method:: is_snan(x)
Returns True if *x* is a signaling NaN; otherwise returns False.
.. method:: is_subnormal(x)
Returns True if *x* is subnormal; otherwise returns False.
.. method:: is_zero(x)
Returns True if *x* is a zero; otherwise returns False.
.. method:: ln(x)
Returns the natural (base e) logarithm of *x*.
.. method:: log10(x)
Returns the base 10 logarithm of *x*.
.. method:: logb(x)
Returns the exponent of the magnitude of the operand's MSD.
.. method:: logical_and(x, y)
Applies the logical operation *and* between each operand's digits.
.. method:: logical_invert(x)
Invert all the digits in *x*.
.. method:: logical_or(x, y)
Applies the logical operation *or* between each operand's digits.
.. method:: logical_xor(x, y)
Applies the logical operation *xor* between each operand's digits.
.. method:: max(x, y)
Compares two values numerically and returns the maximum.
.. method:: max_mag(x, y)
Compares the values numerically with their sign ignored.
.. method:: min(x, y)
Compares two values numerically and returns the minimum.
.. method:: min_mag(x, y)
Compares the values numerically with their sign ignored.
.. method:: minus(x)
Minus corresponds to the unary prefix minus operator in Python.
.. method:: multiply(x, y)
Return the product of *x* and *y*.
.. method:: next_minus(x)
Returns the largest representable number smaller than *x*.
.. method:: next_plus(x)
Returns the smallest representable number larger than *x*.
.. method:: next_toward(x, y)
Returns the number closest to *x*, in direction towards *y*.
.. method:: normalize(x)
Reduces *x* to its simplest form.
.. method:: number_class(x)
Returns an indication of the class of *x*.
.. method:: 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.
.. method:: power(x, y[, modulo])
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 result should always be correctly rounded, using the rounding mode of
the current thread's context.
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.
.. versionchanged:: 2.6
``y`` may now be nonintegral in ``x**y``.
Stricter requirements for the three-argument version.
.. method:: quantize(x, y)
Returns a value equal to *x* (rounded), having the exponent of *y*.
.. method:: radix()
Just returns 10, as this is Decimal, :)
.. method:: 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.
.. method:: 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*).
.. method:: rotate(x, y)
Returns a rotated copy of *x*, *y* times.
.. method:: same_quantum(x, y)
Returns True if the two operands have the same exponent.
.. method:: scaleb (x, y)
Returns the first operand after adding the second value its exp.
.. method:: shift(x, y)
Returns a shifted copy of *x*, *y* times.
.. method:: sqrt(x)
Square root of a non-negative number to context precision.
.. method:: subtract(x, y)
Return the difference between *x* and *y*.
.. method:: to_eng_string(x)
Converts a number to a string, using scientific notation.
.. method:: to_integral_exact(x)
Rounds to an integer.
.. method:: to_sci_string(x)
Converts a number to a string using scientific notation.
.. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. _decimal-signals:
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 :class:`DivisionByZero` trap
is set, then a :exc:`DivisionByZero` exception is raised upon encountering the
condition.
.. class:: Clamped
Altered an exponent to fit representation constraints.
Typically, clamping occurs when an exponent falls outside the context's
:attr:`Emin` and :attr:`Emax` limits. If possible, the exponent is reduced to
fit by adding zeros to the coefficient.
.. class:: DecimalException
Base class for other signals and a subclass of :exc:`ArithmeticError`.
.. class:: 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 :const:`Infinity` or
:const:`-Infinity` with the sign determined by the inputs to the calculation.
.. class:: 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:: InvalidOperation
An invalid operation was performed.
Indicates that an operation was requested that does not make sense. If not
trapped, returns :const:`NaN`. Possible causes include::
Infinity - Infinity
0 * Infinity
Infinity / Infinity
x % 0
Infinity % x
x._rescale( non-integer )
sqrt(-x) and x > 0
0 ** 0
x ** (non-integer)
x ** Infinity
.. class:: Overflow
Numerical overflow.
Indicates the exponent is larger than :attr:`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 :const:`Infinity`. In either case, :class:`Inexact` and :class:`Rounded`
are also signaled.
.. class:: Rounded
Rounding occurred though possibly no information was lost.
Signaled whenever rounding discards digits; even if those digits are zero
(such as rounding :const:`5.00` to :const:`5.0`). If not trapped, returns
the result unchanged. This signal is used to detect loss of significant
digits.
.. class:: Subnormal
Exponent was lower than :attr:`Emin` prior to rounding.
Occurs when an operation result is subnormal (the exponent is too small). If
not trapped, returns the result unchanged.
.. class:: Underflow
Numerical underflow with result rounded to zero.
Occurs when a subnormal result is pushed to zero by rounding. :class:`Inexact`
and :class:`Subnormal` are also signaled.
The following table summarizes the hierarchy of signals::
exceptions.ArithmeticError(exceptions.StandardError)
DecimalException
Clamped
DivisionByZero(DecimalException, exceptions.ZeroDivisionError)
Inexact
Overflow(Inexact, Rounded)
Underflow(Inexact, Rounded, Subnormal)
InvalidOperation
Rounded
Subnormal
.. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. _decimal-notes:
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 :const:`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:
.. doctest:: newcontext
# 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 :mod:`decimal` module makes it possible to restore the identities by
expanding the precision sufficiently to avoid loss of significance:
.. doctest:: newcontext
>>> 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 :mod:`decimal` module provides special values
including :const:`NaN`, :const:`sNaN`, :const:`-Infinity`, :const:`Infinity`,
and two zeros, :const:`+0` and :const:`-0`.
Infinities can be constructed directly with: ``Decimal('Infinity')``. Also,
they can arise from dividing by zero when the :exc:`DivisionByZero` signal is
not trapped. Likewise, when the :exc:`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 :const:`NaN`, or if the
:exc:`InvalidOperation` signal is trapped, raise an exception. For example,
``0/0`` returns :const:`NaN` which means "not a number". This variety of
:const:`NaN` is quiet and, once created, will flow through other computations
always resulting in another :const:`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 :const:`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
:const:`NaN` is involved. A test for equality where one of the operands is a
quiet or signaling :const:`NaN` always returns :const:`False` (even when doing
``Decimal('NaN')==Decimal('NaN')``), while a test for inequality always returns
:const:`True`. An attempt to compare two Decimals using any of the ``<``,
``<=``, ``>`` or ``>=`` operators will raise the :exc:`InvalidOperation` signal
if either operand is a :const:`NaN`, and return :const:`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 :const:`NaN` were taken from the IEEE 854 standard (see Table 3 in
section 5.7). To ensure strict standards-compliance, use the :meth:`compare`
and :meth:`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-1000000026')
.. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. _decimal-threads:
Working with threads
--------------------
The :func:`getcontext` function accesses a different :class:`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 :func:`setcontext` function automatically assigns its target to
the current thread.
If :func:`setcontext` has not been called before :func:`getcontext`, then
:func:`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 :func:`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()
. . .
.. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
.. _decimal-recipes:
Recipes
-------
Here are a few recipes that serve as utility functions and that demonstrate ways
to work with the :class:`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 = map(str, digits)
build, next = result.append, digits.pop
if sign:
build(trailneg)
for i in range(places):
build(next() if digits else '0')
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.
>>> 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.
>>> 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:
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 :meth:`quantize` method rounds to a fixed number of decimal places. If
the :const:`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 :meth:`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 :meth:`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 :const:`200`,
:const:`200.000`, :const:`2E2`, and :const:`.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 :meth:`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
:const:`5.0E+3` as :const:`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 zeros, losing significance, but keeping the
value unchanged::
def remove_exponent(d):
'''Remove exponent and trailing zeros.
>>> remove_exponent(Decimal('5E+3'))
Decimal('5000')
'''
return d.quantize(Decimal(1)) if d == d.to_integral() else d.normalize()
Q. Is there a way to convert a regular float to a :class:`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:
.. doctest::
>>> 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:
.. doctest:: newcontext
>>> 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:
.. doctest:: newcontext
>>> getcontext().prec = 3
>>> +Decimal('1.23456789') # unary plus triggers rounding
Decimal('1.23')
Alternatively, inputs can be rounded upon creation using the
:meth:`Context.create_decimal` method:
>>> Context(prec=5, rounding=ROUND_DOWN).create_decimal('1.2345678')
Decimal('1.2345')
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