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9. Numeric and Mathematical Modules »

9.4. <tt class="xref py py-mod docutils literal">decimal</tt> — Decimal fixed point and floating point arithmetic¶

The <tt class="xref py py-mod docutils literal">decimal</tt> module provides support for fast correctly-rounded
decimal floating point arithmetic. It offers several advantages over the
<tt class="xref py py-class docutils literal">float</tt> 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
<tt class="xref py py-const docutils literal">1.1</tt> and <tt class="xref py py-const docutils literal">2.2</tt> do not have exact representations in binary
floating point. End users typically would not expect <tt class="docutils literal">1.1 + 2.2</tt> to display
as <tt class="xref py py-const docutils literal">3.3000000000000003</tt> as it does with binary floating point.

The exactness carries over into arithmetic.  In decimal floating point, <tt class="docutils literal">0.1
+ 0.1 + 0.1 - 0.3</tt> is exactly equal to zero.  In binary floating point, the result
is <tt class="xref py py-const docutils literal">5.5511151231257827e-017</tt>.  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 <tt class="docutils literal">1.30
+ 1.20</tt> is <tt class="xref py py-const docutils literal">2.50</tt>.  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, <tt class="docutils literal">1.3 * 1.2</tt> gives <tt class="xref py py-const docutils literal">1.56</tt> while <tt class="docutils literal">1.30 *
1.20</tt> gives <tt class="xref py py-const docutils literal">1.5600</tt>.

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
<tt class="xref py py-const docutils literal">Infinity</tt>, <tt class="xref py py-const docutils literal">-Infinity</tt>, and <tt class="xref py py-const docutils literal">NaN</tt>.  The standard also
differentiates <tt class="xref py py-const docutils literal">-0</tt> from <tt class="xref py py-const docutils literal">+0</tt>.

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 <tt class="xref py py-const docutils literal">ROUND_CEILING</tt>, <tt class="xref py py-const docutils literal">ROUND_DOWN</tt>,
<tt class="xref py py-const docutils literal">ROUND_FLOOR</tt>, <tt class="xref py py-const docutils literal">ROUND_HALF_DOWN</tt>, <tt class="xref py py-const docutils literal">ROUND_HALF_EVEN</tt>,
<tt class="xref py py-const docutils literal">ROUND_HALF_UP</tt>, <tt class="xref py py-const docutils literal">ROUND_UP</tt>, and <tt class="xref py py-const docutils literal">ROUND_05UP</tt>.

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: <tt class="xref py py-const docutils literal">Clamped</tt>, <tt class="xref py py-const docutils literal">InvalidOperation</tt>,
<tt class="xref py py-const docutils literal">DivisionByZero</tt>, <tt class="xref py py-const docutils literal">Inexact</tt>, <tt class="xref py py-const docutils literal">Rounded</tt>, <tt class="xref py py-const docutils literal">Subnormal</tt>,
<tt class="xref py py-const docutils literal">Overflow</tt>, <tt class="xref py py-const docutils literal">Underflow</tt> and <tt class="xref py py-const docutils literal">FloatOperation</tt>.

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.

IEEE standard 854-1987, Unofficial IEEE 854 Text.

9.4.1. Quick-start Tutorial¶

The usual start to using decimals is importing the module, viewing the current
context with <tt class="xref py py-func docutils literal">getcontext()</tt> 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
<tt class="xref py py-const docutils literal">NaN</tt> which stands for “Not a number”, positive and negative
<tt class="xref py py-const docutils literal">Infinity</tt>, and <tt class="xref py py-const docutils literal">-0</tt>:

>>> 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 <tt class="xref py py-exc docutils literal">FloatOperation</tt> 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 <tt class="xref py py-class docutils literal">InvalidOperation</tt>:

>>> 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 <tt class="xref py py-meth docutils literal">quantize()</tt> 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 <tt class="xref py py-func docutils literal">getcontext()</tt> 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 <tt class="xref py py-func docutils literal">setcontext()</tt>
function.

In accordance with the standard, the <tt class="xref py py-mod docutils literal">Decimal</tt> module provides two ready to
use standard contexts, <tt class="xref py py-const docutils literal">BasicContext</tt> and <tt class="xref py py-const docutils literal">ExtendedContext</tt>. 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 <tt class="xref py py-meth docutils literal">clear_flags()</tt> 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 <tt class="xref py py-const docutils literal">Pi</tt> 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 <tt class="xref py py-attr docutils literal">traps</tt> 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 <tt class="xref py py-class docutils literal">Decimal</tt> 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.

9.4.2. Decimal objects¶

class <tt class="descclassname">decimal.</tt><tt class="descname">Decimal</tt><big>(</big>value="0", context=None<big>)</big>¶

Construct a new <tt class="xref py py-class docutils literal">Decimal</tt> object based from value.

value can be an integer, string, tuple, <tt class="xref py py-class docutils literal">float</tt>, or another <tt class="xref py py-class docutils literal">Decimal</tt>
object. If no value is given, returns <tt class="docutils literal">Decimal('0')</tt>.  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

Other Unicode decimal digits are also permitted where <tt class="docutils literal">digit</tt>
appears above.  These include decimal digits from various other
alphabets (for example, Arabic-Indic and Devanāgarī digits) along
with the fullwidth digits <tt class="docutils literal">'\uff10'</tt> through <tt class="docutils literal">'\uff19'</tt>.

If value is a <tt class="xref py py-class docutils literal">tuple</tt>, it should have three components, a sign
(<tt class="xref py py-const docutils literal">0</tt> for positive or <tt class="xref py py-const docutils literal">1</tt> for negative), a <tt class="xref py py-class docutils literal">tuple</tt> of
digits, and an integer exponent. For example, <tt class="docutils literal">Decimal((0, (1, 4, 1, 4), -3))</tt>
returns <tt class="docutils literal">Decimal('1.414')</tt>.

If value is a <tt class="xref py py-class docutils literal">float</tt>, 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, <tt class="docutils literal">Decimal(float('1.1'))</tt>
converts to
<tt class="docutils literal">Decimal('1.100000000000000088817841970012523233890533447265625')</tt>.

The context precision does not affect how many digits are stored. That is
determined exclusively by the number of digits in value. For example,
<tt class="docutils literal">Decimal('3.00000')</tt> 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 <tt class="xref py py-const docutils literal">InvalidOperation</tt>, an exception
is raised; otherwise, the constructor returns a new Decimal with the value of
<tt class="xref py py-const docutils literal">NaN</tt>.

Once constructed, <tt class="xref py py-class docutils literal">Decimal</tt> objects are immutable.

Changed in version 3.2: The argument to the constructor is now permitted to be a <tt class="xref py py-class docutils literal">float</tt>
instance.

Changed in version 3.3: <tt class="xref py py-class docutils literal">float</tt> arguments raise an exception if the <tt class="xref py py-exc docutils literal">FloatOperation</tt>
trap is set. By default the trap is off.

Decimal floating point objects share many properties with the other built-in
numeric types such as <tt class="xref py py-class docutils literal">float</tt> and <tt class="xref py py-class docutils literal">int</tt>.  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 <tt class="xref py py-class docutils literal">float</tt> or
<tt class="xref py py-class docutils literal">int</tt>).

There are some small differences between arithmetic on Decimal objects and
arithmetic on integers and floats.  When the remainder operator <tt class="docutils literal">%</tt> 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 <tt class="docutils literal">//</tt> behaves analogously, returning the
integer part of the true quotient (truncating towards zero) rather than its
floor, so as to preserve the usual identity <tt class="docutils literal">x == (x // y) * y + x % y</tt>:

>>> -7 // 4
-2
>>> Decimal(-7) // Decimal(4)
Decimal('-1')

The <tt class="docutils literal">%</tt> and <tt class="docutils literal">//</tt> operators implement the <tt class="docutils literal">remainder</tt> and
<tt class="docutils literal">divide-integer</tt> operations (respectively) as described in the
specification.

Decimal objects cannot generally be combined with floats or
instances of <tt class="xref py py-class docutils literal">fractions.Fraction</tt> in arithmetic operations:
an attempt to add a <tt class="xref py py-class docutils literal">Decimal</tt> to a <tt class="xref py py-class docutils literal">float</tt>, for
example, will raise a <tt class="xref py py-exc docutils literal">TypeError</tt>.  However, it is possible to
use Python’s comparison operators to compare a <tt class="xref py py-class docutils literal">Decimal</tt>
instance <tt class="docutils literal">x</tt> with another number <tt class="docutils literal">y</tt>.  This avoids confusing results
when doing equality comparisons between numbers of different types.

Changed in version 3.2: Mixed-type comparisons between <tt class="xref py py-class docutils literal">Decimal</tt> 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:

<tt class="descname">adjusted</tt><big>(</big><big>)</big>¶

Return the adjusted exponent after shifting out the coefficient’s
rightmost digits until only the lead digit remains:
<tt class="docutils literal">Decimal('321e+5').adjusted()</tt> returns seven.  Used for determining the
position of the most significant digit with respect to the decimal point.

<tt class="descname">as_tuple</tt><big>(</big><big>)</big>¶

Return a named tuple representation of the number:
<tt class="docutils literal">DecimalTuple(sign, digits, exponent)</tt>.

<tt class="descname">canonical</tt><big>(</big><big>)</big>¶

Return the canonical encoding of the argument.  Currently, the encoding of
a <tt class="xref py py-class docutils literal">Decimal</tt> instance is always canonical, so this operation returns
its argument unchanged.

<tt class="descname">compare</tt><big>(</big>other, context=None<big>)</big>¶

Compare the values of two Decimal instances.  <tt class="xref py py-meth docutils literal">compare()</tt> 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')

<tt class="descname">compare_signal</tt><big>(</big>other, context=None<big>)</big>¶

This operation is identical to the <tt class="xref py py-meth docutils literal">compare()</tt> 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.

<tt class="descname">compare_total</tt><big>(</big>other, context=None<big>)</big>¶

Compare two operands using their abstract representation rather than their
numerical value.  Similar to the <tt class="xref py py-meth docutils literal">compare()</tt> method, but the result
gives a total ordering on <tt class="xref py py-class docutils literal">Decimal</tt> instances.  Two
<tt class="xref py py-class docutils literal">Decimal</tt> 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 <tt class="docutils literal">Decimal('0')</tt> if both operands have the same
representation, <tt class="docutils literal">Decimal('-1')</tt> if the first operand is lower in the
total order than the second, and <tt class="docutils literal">Decimal('1')</tt> 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.

<tt class="descname">compare_total_mag</tt><big>(</big>other, context=None<big>)</big>¶

Compare two operands using their abstract representation rather than their
value as in <tt class="xref py py-meth docutils literal">compare_total()</tt>, but ignoring the sign of each operand.
<tt class="docutils literal">x.compare_total_mag(y)</tt> is equivalent to
<tt class="docutils literal">x.copy_abs().compare_total(y.copy_abs())</tt>.

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.

<tt class="descname">conjugate</tt><big>(</big><big>)</big>¶

Just returns self, this method is only to comply with the Decimal
Specification.

<tt class="descname">copy_abs</tt><big>(</big><big>)</big>¶

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.

<tt class="descname">copy_negate</tt><big>(</big><big>)</big>¶

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.

<tt class="descname">copy_sign</tt><big>(</big>other, context=None<big>)</big>¶

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.

<tt class="descname">exp</tt><big>(</big>context=None<big>)</big>¶

Return the value of the (natural) exponential function <tt class="docutils literal">e**x</tt> at the
given number.  The result is correctly rounded using the
<tt class="xref py py-const docutils literal">ROUND_HALF_EVEN</tt> rounding mode.

>>> Decimal(1).exp()
Decimal('2.718281828459045235360287471')
>>> Decimal(321).exp()
Decimal('2.561702493119680037517373933E+139')

<tt class="descname">from_float</tt><big>(</big>f<big>)</big>¶

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 <tt class="xref py py-class docutils literal">Decimal</tt> instance
can also be constructed directly from a <tt class="xref py py-class docutils literal">float</tt>.

>>> 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.

<tt class="descname">fma</tt><big>(</big>other, third, context=None<big>)</big>¶

Fused multiply-add.  Return self*other+third with no rounding of the
intermediate product self*other.

>>> Decimal(2).fma(3, 5)
Decimal('11')

<tt class="descname">is_canonical</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is canonical and <tt class="xref py py-const docutils literal">False</tt>
otherwise.  Currently, a <tt class="xref py py-class docutils literal">Decimal</tt> instance is always canonical, so
this operation always returns <tt class="xref py py-const docutils literal">True</tt>.

<tt class="descname">is_finite</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is a finite number, and
<tt class="xref py py-const docutils literal">False</tt> if the argument is an infinity or a NaN.

<tt class="descname">is_infinite</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is either positive or negative
infinity and <tt class="xref py py-const docutils literal">False</tt> otherwise.

<tt class="descname">is_nan</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is a (quiet or signaling) NaN and
<tt class="xref py py-const docutils literal">False</tt> otherwise.

<tt class="descname">is_normal</tt><big>(</big>context=None<big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is a normal finite number.  Return
<tt class="xref py py-const docutils literal">False</tt> if the argument is zero, subnormal, infinite or a NaN.

<tt class="descname">is_qnan</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is a quiet NaN, and
<tt class="xref py py-const docutils literal">False</tt> otherwise.

<tt class="descname">is_signed</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument has a negative sign and
<tt class="xref py py-const docutils literal">False</tt> otherwise.  Note that zeros and NaNs can both carry signs.

<tt class="descname">is_snan</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is a signaling NaN and <tt class="xref py py-const docutils literal">False</tt>
otherwise.

<tt class="descname">is_subnormal</tt><big>(</big>context=None<big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is subnormal, and <tt class="xref py py-const docutils literal">False</tt>
otherwise.

<tt class="descname">is_zero</tt><big>(</big><big>)</big>¶

Return <tt class="xref py py-const docutils literal">True</tt> if the argument is a (positive or negative) zero and
<tt class="xref py py-const docutils literal">False</tt> otherwise.

<tt class="descname">ln</tt><big>(</big>context=None<big>)</big>¶

Return the natural (base e) logarithm of the operand.  The result is
correctly rounded using the <tt class="xref py py-const docutils literal">ROUND_HALF_EVEN</tt> rounding mode.

<tt class="descname">log10</tt><big>(</big>context=None<big>)</big>¶

Return the base ten logarithm of the operand.  The result is correctly
rounded using the <tt class="xref py py-const docutils literal">ROUND_HALF_EVEN</tt> rounding mode.

<tt class="descname">logb</tt><big>(</big>context=None<big>)</big>¶

For a nonzero number, return the adjusted exponent of its operand as a
<tt class="xref py py-class docutils literal">Decimal</tt> instance.  If the operand is a zero then
<tt class="docutils literal">Decimal('-Infinity')</tt> is returned and the <tt class="xref py py-const docutils literal">DivisionByZero</tt> flag
is raised.  If the operand is an infinity then <tt class="docutils literal">Decimal('Infinity')</tt> is
returned.

<tt class="descname">logical_and</tt><big>(</big>other, context=None<big>)</big>¶

<tt class="xref py py-meth docutils literal">logical_and()</tt> is a logical operation which takes two logical
operands (see Logical operands).  The result is the
digit-wise <tt class="docutils literal">and</tt> of the two operands.

<tt class="descname">logical_invert</tt><big>(</big>context=None<big>)</big>¶

<tt class="xref py py-meth docutils literal">logical_invert()</tt> is a logical operation.  The
result is the digit-wise inversion of the operand.

<tt class="descname">logical_or</tt><big>(</big>other, context=None<big>)</big>¶

<tt class="xref py py-meth docutils literal">logical_or()</tt> is a logical operation which takes two logical
operands (see Logical operands).  The result is the
digit-wise <tt class="docutils literal">or</tt> of the two operands.

<tt class="descname">logical_xor</tt><big>(</big>other, context=None<big>)</big>¶

<tt class="xref py py-meth docutils literal">logical_xor()</tt> is a logical operation which takes two logical
operands (see Logical operands).  The result is the
digit-wise exclusive or of the two operands.

<tt class="descname">max</tt><big>(</big>other, context=None<big>)</big>¶

Like <tt class="docutils literal">max(self, other)</tt> except that the context rounding rule is applied
before returning and that <tt class="xref py py-const docutils literal">NaN</tt> values are either signaled or
ignored (depending on the context and whether they are signaling or
quiet).

<tt class="descname">max_mag</tt><big>(</big>other, context=None<big>)</big>¶

Similar to the <tt class="xref py py-meth docutils literal">max()</tt> method, but the comparison is done using the
absolute values of the operands.

<tt class="descname">min</tt><big>(</big>other, context=None<big>)</big>¶

Like <tt class="docutils literal">min(self, other)</tt> except that the context rounding rule is applied
before returning and that <tt class="xref py py-const docutils literal">NaN</tt> values are either signaled or
ignored (depending on the context and whether they are signaling or
quiet).

<tt class="descname">min_mag</tt><big>(</big>other, context=None<big>)</big>¶

Similar to the <tt class="xref py py-meth docutils literal">min()</tt> method, but the comparison is done using the
absolute values of the operands.

<tt class="descname">next_minus</tt><big>(</big>context=None<big>)</big>¶

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.

<tt class="descname">next_plus</tt><big>(</big>context=None<big>)</big>¶

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.

<tt class="descname">next_toward</tt><big>(</big>other, context=None<big>)</big>¶

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.

<tt class="descname">normalize</tt><big>(</big>context=None<big>)</big>¶

Normalize the number by stripping the rightmost trailing zeros and
converting any result equal to <tt class="xref py py-const docutils literal">Decimal('0')</tt> to
<tt class="xref py py-const docutils literal">Decimal('0e0')</tt>. Used for producing canonical values for attributes
of an equivalence class. For example, <tt class="docutils literal">Decimal('32.100')</tt> and
<tt class="docutils literal">Decimal('0.321000e+2')</tt> both normalize to the equivalent value
<tt class="docutils literal">Decimal('32.1')</tt>.

<tt class="descname">number_class</tt><big>(</big>context=None<big>)</big>¶

Return a string describing the class of the operand.  The returned value
is one of the following ten strings.

<tt class="docutils literal">"-Infinity"</tt>, indicating that the operand is negative infinity.

<tt class="docutils literal">"-Normal"</tt>, indicating that the operand is a negative normal number.

<tt class="docutils literal">"-Subnormal"</tt>, indicating that the operand is negative and subnormal.

<tt class="docutils literal">"-Zero"</tt>, indicating that the operand is a negative zero.

<tt class="docutils literal">"+Zero"</tt>, indicating that the operand is a positive zero.

<tt class="docutils literal">"+Subnormal"</tt>, indicating that the operand is positive and subnormal.

<tt class="docutils literal">"+Normal"</tt>, indicating that the operand is a positive normal number.

<tt class="docutils literal">"+Infinity"</tt>, indicating that the operand is positive infinity.

<tt class="docutils literal">"NaN"</tt>, indicating that the operand is a quiet NaN (Not a Number).

<tt class="docutils literal">"sNaN"</tt>, indicating that the operand is a signaling NaN.

<tt class="descname">quantize</tt><big>(</big>exp, rounding=None, context=None, watchexp=True<big>)</big>¶

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
<tt class="xref py py-const docutils literal">InvalidOperation</tt> 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 <tt class="docutils literal">rounding</tt> argument if given, else by the given
<tt class="docutils literal">context</tt> 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 <tt class="xref py py-attr docutils literal">Emax</tt> or less than
<tt class="xref py py-attr docutils literal">Etiny</tt>.

Deprecated since version 3.3: watchexp is an implementation detail from the pure Python version
and is not present in the C version. It will be removed in version
3.4, where it defaults to <tt class="docutils literal">True</tt>.

<tt class="descname">radix</tt><big>(</big><big>)</big>¶

Return <tt class="docutils literal">Decimal(10)</tt>, the radix (base) in which the <tt class="xref py py-class docutils literal">Decimal</tt>
class does all its arithmetic.  Included for compatibility with the
specification.

<tt class="descname">remainder_near</tt><big>(</big>other, context=None<big>)</big>¶

Return the remainder from dividing self by other.  This differs from
<tt class="docutils literal">self % other</tt> in that the sign of the remainder is chosen so as to
minimize its absolute value.  More precisely, the return value is
<tt class="docutils literal">self - n * other</tt> where <tt class="docutils literal">n</tt> is the integer nearest to the exact
value of <tt class="docutils literal">self / other</tt>, 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')

<tt class="descname">rotate</tt><big>(</big>other, context=None<big>)</big>¶

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.

<tt class="descname">same_quantum</tt><big>(</big>other, context=None<big>)</big>¶

Test whether self and other have the same exponent or whether both are
<tt class="xref py py-const docutils literal">NaN</tt>.

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.

<tt class="descname">scaleb</tt><big>(</big>other, context=None<big>)</big>¶

Return the first operand with exponent adjusted by the second.
Equivalently, return the first operand multiplied by <tt class="docutils literal">10**other</tt>.  The
second operand must be an integer.

<tt class="descname">shift</tt><big>(</big>other, context=None<big>)</big>¶

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.

<tt class="descname">sqrt</tt><big>(</big>context=None<big>)</big>¶

Return the square root of the argument to full precision.

<tt class="descname">to_eng_string</tt><big>(</big>context=None<big>)</big>¶

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
<tt class="docutils literal">Decimal('123E+1')</tt> to <tt class="docutils literal">Decimal('1.23E+3')</tt>

<tt class="descname">to_integral</tt><big>(</big>rounding=None, context=None<big>)</big>¶

Identical to the <tt class="xref py py-meth docutils literal">to_integral_value()</tt> method.  The <tt class="docutils literal">to_integral</tt>
name has been kept for compatibility with older versions.

<tt class="descname">to_integral_exact</tt><big>(</big>rounding=None, context=None<big>)</big>¶

Round to the nearest integer, signaling <tt class="xref py py-const docutils literal">Inexact</tt> or
<tt class="xref py py-const docutils literal">Rounded</tt> as appropriate if rounding occurs.  The rounding mode is
determined by the <tt class="docutils literal">rounding</tt> parameter if given, else by the given
<tt class="docutils literal">context</tt>.  If neither parameter is given then the rounding mode of the
current context is used.

<tt class="descname">to_integral_value</tt><big>(</big>rounding=None, context=None<big>)</big>¶

Round to the nearest integer without signaling <tt class="xref py py-const docutils literal">Inexact</tt> or
<tt class="xref py py-const docutils literal">Rounded</tt>.  If given, applies rounding; otherwise, uses the
rounding method in either the supplied context or the current context.

9.4.2.1. Logical operands¶

The <tt class="xref py py-meth docutils literal">logical_and()</tt>, <tt class="xref py py-meth docutils literal">logical_invert()</tt>, <tt class="xref py py-meth docutils literal">logical_or()</tt>,
and <tt class="xref py py-meth docutils literal">logical_xor()</tt> methods expect their arguments to be logical
operands.  A logical operand is a <tt class="xref py py-class docutils literal">Decimal</tt> instance whose
exponent and sign are both zero, and whose digits are all either
<tt class="xref py py-const docutils literal">0</tt> or <tt class="xref py py-const docutils literal">1</tt>.

9.4.3. 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
<tt class="xref py py-func docutils literal">getcontext()</tt> and <tt class="xref py py-func docutils literal">setcontext()</tt> functions:

<tt class="descclassname">decimal.</tt><tt class="descname">getcontext</tt><big>(</big><big>)</big>¶

Return the current context for the active thread.

<tt class="descclassname">decimal.</tt><tt class="descname">setcontext</tt><big>(</big>c<big>)</big>¶

Set the current context for the active thread to c.

You can also use the <tt class="xref std std-keyword docutils literal">with</tt> statement and the <tt class="xref py py-func docutils literal">localcontext()</tt>
function to temporarily change the active context.

<tt class="descclassname">decimal.</tt><tt class="descname">localcontext</tt><big>(</big>ctx=None<big>)</big>¶

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 <tt class="xref py py-class docutils literal">Context</tt> constructor
described below. In addition, the module provides three pre-made contexts:

class <tt class="descclassname">decimal.</tt><tt class="descname">BasicContext</tt>¶

This is a standard context defined by the General Decimal Arithmetic
Specification.  Precision is set to nine.  Rounding is set to
<tt class="xref py py-const docutils literal">ROUND_HALF_UP</tt>.  All flags are cleared.  All traps are enabled (treated
as exceptions) except <tt class="xref py py-const docutils literal">Inexact</tt>, <tt class="xref py py-const docutils literal">Rounded</tt>, and
<tt class="xref py py-const docutils literal">Subnormal</tt>.

Because many of the traps are enabled, this context is useful for debugging.

class <tt class="descclassname">decimal.</tt><tt class="descname">ExtendedContext</tt>¶

This is a standard context defined by the General Decimal Arithmetic
Specification.  Precision is set to nine.  Rounding is set to
<tt class="xref py py-const docutils literal">ROUND_HALF_EVEN</tt>.  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 <tt class="xref py py-const docutils literal">NaN</tt> or <tt class="xref py py-const docutils literal">Infinity</tt> instead of
raising exceptions.  This allows an application to complete a run in the
presence of conditions that would otherwise halt the program.

class <tt class="descclassname">decimal.</tt><tt class="descname">DefaultContext</tt>¶

This context is used by the <tt class="xref py py-class docutils literal">Context</tt> 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 <tt class="xref py py-class docutils literal">Context</tt> 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 <tt class="xref py py-attr docutils literal">prec</tt>=<tt class="xref py py-const docutils literal">28</tt>,
<tt class="xref py py-attr docutils literal">rounding</tt>=<tt class="xref py py-const docutils literal">ROUND_HALF_EVEN</tt>,
and enabled traps for <tt class="xref py py-class docutils literal">Overflow</tt>, <tt class="xref py py-class docutils literal">InvalidOperation</tt>, and
<tt class="xref py py-class docutils literal">DivisionByZero</tt>.

In addition to the three supplied contexts, new contexts can be created with the
<tt class="xref py py-class docutils literal">Context</tt> constructor.

class <tt class="descclassname">decimal.</tt><tt class="descname">Context</tt><big>(</big>prec=None, rounding=None, Emin=None, Emax=None, capitals=None, clamp=None, flags=None, traps=None<big>)</big>¶

Creates a new context.  If a field is not specified or is <tt class="xref py py-const docutils literal">None</tt>, the
default values are copied from the <tt class="xref py py-const docutils literal">DefaultContext</tt>.  If the flags
field is not specified or is <tt class="xref py py-const docutils literal">None</tt>, all flags are cleared.

prec is an integer in the range [<tt class="xref py py-const docutils literal">1</tt>, <tt class="xref py py-const docutils literal">MAX_PREC</tt>] 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 [<tt class="xref py py-const docutils literal">MIN_EMIN</tt>, <tt class="xref py py-const docutils literal">0</tt>],
Emax in the range [<tt class="xref py py-const docutils literal">0</tt>, <tt class="xref py py-const docutils literal">MAX_EMAX</tt>].

The capitals field is either <tt class="xref py py-const docutils literal">0</tt> or <tt class="xref py py-const docutils literal">1</tt> (the default). If set to
<tt class="xref py py-const docutils literal">1</tt>, exponents are printed with a capital <tt class="xref py py-const docutils literal">E</tt>; otherwise, a
lowercase <tt class="xref py py-const docutils literal">e</tt> is used: <tt class="xref py py-const docutils literal">Decimal('6.02e+23')</tt>.

The clamp field is either <tt class="xref py py-const docutils literal">0</tt> (the default) or <tt class="xref py py-const docutils literal">1</tt>.
If set to <tt class="xref py py-const docutils literal">1</tt>, the exponent <tt class="docutils literal">e</tt> of a <tt class="xref py py-class docutils literal">Decimal</tt>
instance representable in this context is strictly limited to the
range <tt class="docutils literal">Emin - prec + 1 <= e <= Emax - prec + 1</tt>.  If clamp is
<tt class="xref py py-const docutils literal">0</tt> then a weaker condition holds: the adjusted exponent of
the <tt class="xref py py-class docutils literal">Decimal</tt> instance is at most <tt class="docutils literal">Emax</tt>.  When clamp is
<tt class="xref py py-const docutils literal">1</tt>, 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 <tt class="xref py py-const docutils literal">1</tt> allows compatibility with the
fixed-width decimal interchange formats specified in IEEE 754.

The <tt class="xref py py-class docutils literal">Context</tt> 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 <tt class="xref py py-class docutils literal">Decimal</tt> methods described above (with
the exception of the <tt class="xref py py-meth docutils literal">adjusted()</tt> and <tt class="xref py py-meth docutils literal">as_tuple()</tt> methods) there is
a corresponding <tt class="xref py py-class docutils literal">Context</tt> method.  For example, for a <tt class="xref py py-class docutils literal">Context</tt>
instance <tt class="docutils literal">C</tt> and <tt class="xref py py-class docutils literal">Decimal</tt> instance <tt class="docutils literal">x</tt>, <tt class="docutils literal">C.exp(x)</tt> is
equivalent to <tt class="docutils literal">x.exp(context=C)</tt>.  Each <tt class="xref py py-class docutils literal">Context</tt> method accepts a
Python integer (an instance of <tt class="xref py py-class docutils literal">int</tt>) anywhere that a
Decimal instance is accepted.

<tt class="descname">clear_flags</tt><big>(</big><big>)</big>¶

Resets all of the flags to <tt class="xref py py-const docutils literal">0</tt>.

<tt class="descname">clear_traps</tt><big>(</big><big>)</big>¶

Resets all of the traps to <tt class="xref py py-const docutils literal">0</tt>.

New in version 3.3.

<tt class="descname">copy</tt><big>(</big><big>)</big>¶

Return a duplicate of the context.

<tt class="descname">copy_decimal</tt><big>(</big>num<big>)</big>¶

Return a copy of the Decimal instance num.

<tt class="descname">create_decimal</tt><big>(</big>num<big>)</big>¶

Creates a new Decimal instance from num but using self as
context. Unlike the <tt class="xref py py-class docutils literal">Decimal</tt> 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 is
permitted.

<tt class="descname">create_decimal_from_float</tt><big>(</big>f<big>)</big>¶

Creates a new Decimal instance from a float f but rounding using self
as the context.  Unlike the <tt class="xref py py-meth docutils literal">Decimal.from_float()</tt> 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.

<tt class="descname">Etiny</tt><big>(</big><big>)</big>¶

Returns a value equal to <tt class="docutils literal">Emin - prec + 1</tt> which is the minimum exponent
value for subnormal results.  When underflow occurs, the exponent is set
to <tt class="xref py py-const docutils literal">Etiny</tt>.

<tt class="descname">Etop</tt><big>(</big><big>)</big>¶

Returns a value equal to <tt class="docutils literal">Emax - prec + 1</tt>.

The usual approach to working with decimals is to create <tt class="xref py py-class docutils literal">Decimal</tt>
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 <tt class="xref py py-class docutils literal">Decimal</tt> class and are only briefly
recounted here.

<tt class="descname">abs</tt><big>(</big>x<big>)</big>¶

Returns the absolute value of x.

<tt class="descname">add</tt><big>(</big>x, y<big>)</big>¶

Return the sum of x and y.

<tt class="descname">canonical</tt><big>(</big>x<big>)</big>¶

Returns the same Decimal object x.

<tt class="descname">compare</tt><big>(</big>x, y<big>)</big>¶

Compares x and y numerically.

<tt class="descname">compare_signal</tt><big>(</big>x, y<big>)</big>¶

Compares the values of the two operands numerically.

<tt class="descname">compare_total</tt><big>(</big>x, y<big>)</big>¶

Compares two operands using their abstract representation.

<tt class="descname">compare_total_mag</tt><big>(</big>x, y<big>)</big>¶

Compares two operands using their abstract representation, ignoring sign.

<tt class="descname">copy_abs</tt><big>(</big>x<big>)</big>¶

Returns a copy of x with the sign set to 0.

<tt class="descname">copy_negate</tt><big>(</big>x<big>)</big>¶

Returns a copy of x with the sign inverted.

<tt class="descname">copy_sign</tt><big>(</big>x, y<big>)</big>¶

Copies the sign from y to x.

<tt class="descname">divide</tt><big>(</big>x, y<big>)</big>¶

Return x divided by y.

<tt class="descname">divide_int</tt><big>(</big>x, y<big>)</big>¶

Return x divided by y, truncated to an integer.

<tt class="descname">divmod</tt><big>(</big>x, y<big>)</big>¶

Divides two numbers and returns the integer part of the result.

<tt class="descname">exp</tt><big>(</big>x<big>)</big>¶

Returns e ** x.

<tt class="descname">fma</tt><big>(</big>x, y, z<big>)</big>¶

Returns x multiplied by y, plus z.

<tt class="descname">is_canonical</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is canonical; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_finite</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is finite; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_infinite</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is infinite; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_nan</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is a qNaN or sNaN; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_normal</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is a normal number; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_qnan</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is a quiet NaN; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_signed</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is negative; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_snan</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is a signaling NaN; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_subnormal</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is subnormal; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">is_zero</tt><big>(</big>x<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if x is a zero; otherwise returns <tt class="docutils literal">False</tt>.

<tt class="descname">ln</tt><big>(</big>x<big>)</big>¶

Returns the natural (base e) logarithm of x.

<tt class="descname">log10</tt><big>(</big>x<big>)</big>¶

Returns the base 10 logarithm of x.

<tt class="descname">logb</tt><big>(</big>x<big>)</big>¶

Returns the exponent of the magnitude of the operand’s MSD.

<tt class="descname">logical_and</tt><big>(</big>x, y<big>)</big>¶

Applies the logical operation and between each operand’s digits.

<tt class="descname">logical_invert</tt><big>(</big>x<big>)</big>¶

Invert all the digits in x.

<tt class="descname">logical_or</tt><big>(</big>x, y<big>)</big>¶

Applies the logical operation or between each operand’s digits.

<tt class="descname">logical_xor</tt><big>(</big>x, y<big>)</big>¶

Applies the logical operation xor between each operand’s digits.

<tt class="descname">max</tt><big>(</big>x, y<big>)</big>¶

Compares two values numerically and returns the maximum.

<tt class="descname">max_mag</tt><big>(</big>x, y<big>)</big>¶

Compares the values numerically with their sign ignored.

<tt class="descname">min</tt><big>(</big>x, y<big>)</big>¶

Compares two values numerically and returns the minimum.

<tt class="descname">min_mag</tt><big>(</big>x, y<big>)</big>¶

Compares the values numerically with their sign ignored.

<tt class="descname">minus</tt><big>(</big>x<big>)</big>¶

Minus corresponds to the unary prefix minus operator in Python.

<tt class="descname">multiply</tt><big>(</big>x, y<big>)</big>¶

Return the product of x and y.

<tt class="descname">next_minus</tt><big>(</big>x<big>)</big>¶

Returns the largest representable number smaller than x.

<tt class="descname">next_plus</tt><big>(</big>x<big>)</big>¶

Returns the smallest representable number larger than x.

<tt class="descname">next_toward</tt><big>(</big>x, y<big>)</big>¶

Returns the number closest to x, in direction towards y.

<tt class="descname">normalize</tt><big>(</big>x<big>)</big>¶

Reduces x to its simplest form.

<tt class="descname">number_class</tt><big>(</big>x<big>)</big>¶

Returns an indication of the class of x.

<tt class="descname">plus</tt><big>(</big>x<big>)</big>¶

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.

<tt class="descname">power</tt><big>(</big>x, y, modulo=None<big>)</big>¶

Return <tt class="docutils literal">x</tt> to the power of <tt class="docutils literal">y</tt>, reduced modulo <tt class="docutils literal">modulo</tt> if given.

With two arguments, compute <tt class="docutils literal">x**y</tt>.  If <tt class="docutils literal">x</tt> is negative then <tt class="docutils literal">y</tt>
must be integral.  The result will be inexact unless <tt class="docutils literal">y</tt> 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.

Changed in version 3.3: The C module computes <tt class="xref py py-meth docutils literal">power()</tt> in terms of the correctly-rounded
<tt class="xref py py-meth docutils literal">exp()</tt> and <tt class="xref py py-meth docutils literal">ln()</tt> functions. The result is well-defined but
only “almost always correctly-rounded”.

With three arguments, compute <tt class="docutils literal">(x**y) % modulo</tt>.  For the three argument
form, the following restrictions on the arguments hold:

all three arguments must be integral

<tt class="docutils literal">y</tt> must be nonnegative

at least one of <tt class="docutils literal">x</tt> or <tt class="docutils literal">y</tt> must be nonzero

<tt class="docutils literal">modulo</tt> must be nonzero and have at most ‘precision’ digits

The value resulting from <tt class="docutils literal">Context.power(x, y, modulo)</tt> is
equal to the value that would be obtained by computing <tt class="docutils literal">(x**y)
% modulo</tt> with unbounded precision, but is computed more
efficiently.  The exponent of the result is zero, regardless of
the exponents of <tt class="docutils literal">x</tt>, <tt class="docutils literal">y</tt> and <tt class="docutils literal">modulo</tt>.  The result is
always exact.

<tt class="descname">quantize</tt><big>(</big>x, y<big>)</big>¶

Returns a value equal to x (rounded), having the exponent of y.

<tt class="descname">radix</tt><big>(</big><big>)</big>¶

Just returns 10, as this is Decimal, :)

<tt class="descname">remainder</tt><big>(</big>x, y<big>)</big>¶

Returns the remainder from integer division.

The sign of the result, if non-zero, is the same as that of the original
dividend.

<tt class="descname">remainder_near</tt><big>(</big>x, y<big>)</big>¶

Returns <tt class="docutils literal">x - y * n</tt>, where n is the integer nearest the exact value
of <tt class="docutils literal">x / y</tt> (if the result is 0 then its sign will be the sign of x).

<tt class="descname">rotate</tt><big>(</big>x, y<big>)</big>¶

Returns a rotated copy of x, y times.

<tt class="descname">same_quantum</tt><big>(</big>x, y<big>)</big>¶

Returns <tt class="docutils literal">True</tt> if the two operands have the same exponent.

<tt class="descname">scaleb</tt><big>(</big>x, y<big>)</big>¶

Returns the first operand after adding the second value its exp.

<tt class="descname">shift</tt><big>(</big>x, y<big>)</big>¶

Returns a shifted copy of x, y times.

<tt class="descname">sqrt</tt><big>(</big>x<big>)</big>¶

Square root of a non-negative number to context precision.

<tt class="descname">subtract</tt><big>(</big>x, y<big>)</big>¶

Return the difference between x and y.

<tt class="descname">to_eng_string</tt><big>(</big>x<big>)</big>¶

Converts a number to a string, using scientific notation.

<tt class="descname">to_integral_exact</tt><big>(</big>x<big>)</big>¶

Rounds to an integer.

<tt class="descname">to_sci_string</tt><big>(</big>x<big>)</big>¶

Converts a number to a string using scientific notation.

9.4.4. Constants¶

The constants in this section are only relevant for the C module. They
are also included in the pure Python version for compatibility.

<colgroup>
<col width="29%" />
<col width="29%" />
<col width="42%" />
</colgroup>

32-bit
64-bit

<tt class="descclassname">decimal.</tt><tt class="descname">MAX_PREC</tt>¶

<tt class="xref py py-const docutils literal">425000000</tt>
<tt class="xref py py-const docutils literal">999999999999999999</tt>

<tt class="descclassname">decimal.</tt><tt class="descname">MAX_EMAX</tt>¶

<tt class="xref py py-const docutils literal">425000000</tt>
<tt class="xref py py-const docutils literal">999999999999999999</tt>

<tt class="descclassname">decimal.</tt><tt class="descname">MIN_EMIN</tt>¶

<tt class="xref py py-const docutils literal">-425000000</tt>
<tt class="xref py py-const docutils literal">-999999999999999999</tt>

<tt class="descclassname">decimal.</tt><tt class="descname">MIN_ETINY</tt>¶

<tt class="xref py py-const docutils literal">-849999999</tt>
<tt class="xref py py-const docutils literal">-1999999999999999997</tt>

<tt class="descclassname">decimal.</tt><tt class="descname">HAVE_THREADS</tt>¶

The default value is <tt class="docutils literal">True</tt>. If Python is compiled without threads, the
C version automatically disables the expensive thread local context
machinery. In this case, the value is <tt class="docutils literal">False</tt>.

9.4.5. Rounding modes¶

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_CEILING</tt>¶

Round towards <tt class="xref py py-const docutils literal">Infinity</tt>.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_DOWN</tt>¶

Round towards zero.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_FLOOR</tt>¶

Round towards <tt class="xref py py-const docutils literal">-Infinity</tt>.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_HALF_DOWN</tt>¶

Round to nearest with ties going towards zero.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_HALF_EVEN</tt>¶

Round to nearest with ties going to nearest even integer.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_HALF_UP</tt>¶

Round to nearest with ties going away from zero.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_UP</tt>¶

Round away from zero.

<tt class="descclassname">decimal.</tt><tt class="descname">ROUND_05UP</tt>¶

Round away from zero if last digit after rounding towards zero would have
been 0 or 5; otherwise round towards zero.

9.4.6. 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 <tt class="xref py py-class docutils literal">DivisionByZero</tt> trap
is set, then a <tt class="xref py py-exc docutils literal">DivisionByZero</tt> exception is raised upon encountering the
condition.

class <tt class="descclassname">decimal.</tt><tt class="descname">Clamped</tt>¶

Altered an exponent to fit representation constraints.

Typically, clamping occurs when an exponent falls outside the context’s
<tt class="xref py py-attr docutils literal">Emin</tt> and <tt class="xref py py-attr docutils literal">Emax</tt> limits.  If possible, the exponent is reduced to
fit by adding zeros to the coefficient.

class <tt class="descclassname">decimal.</tt><tt class="descname">DecimalException</tt>¶

Base class for other signals and a subclass of <tt class="xref py py-exc docutils literal">ArithmeticError</tt>.

class <tt class="descclassname">decimal.</tt><tt class="descname">DivisionByZero</tt>¶

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 <tt class="xref py py-const docutils literal">Infinity</tt> or
<tt class="xref py py-const docutils literal">-Infinity</tt> with the sign determined by the inputs to the calculation.

class <tt class="descclassname">decimal.</tt><tt class="descname">Inexact</tt>¶

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 <tt class="descclassname">decimal.</tt><tt class="descname">InvalidOperation</tt>¶

An invalid operation was performed.

Indicates that an operation was requested that does not make sense. If not
trapped, returns <tt class="xref py py-const docutils literal">NaN</tt>.  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 <tt class="descclassname">decimal.</tt><tt class="descname">Overflow</tt>¶

Numerical overflow.

Indicates the exponent is larger than <tt class="xref py py-attr docutils literal">Emax</tt> 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 <tt class="xref py py-const docutils literal">Infinity</tt>.  In either case, <tt class="xref py py-class docutils literal">Inexact</tt> and <tt class="xref py py-class docutils literal">Rounded</tt>
are also signaled.

class <tt class="descclassname">decimal.</tt><tt class="descname">Rounded</tt>¶

Rounding occurred though possibly no information was lost.

Signaled whenever rounding discards digits; even if those digits are zero
(such as rounding <tt class="xref py py-const docutils literal">5.00</tt> to <tt class="xref py py-const docutils literal">5.0</tt>).  If not trapped, returns
the result unchanged.  This signal is used to detect loss of significant
digits.

class <tt class="descclassname">decimal.</tt><tt class="descname">Subnormal</tt>¶

Exponent was lower than <tt class="xref py py-attr docutils literal">Emin</tt> prior to rounding.

Occurs when an operation result is subnormal (the exponent is too small). If
not trapped, returns the result unchanged.

class <tt class="descclassname">decimal.</tt><tt class="descname">Underflow</tt>¶

Numerical underflow with result rounded to zero.

Occurs when a subnormal result is pushed to zero by rounding. <tt class="xref py py-class docutils literal">Inexact</tt>
and <tt class="xref py py-class docutils literal">Subnormal</tt> are also signaled.

class <tt class="descclassname">decimal.</tt><tt class="descname">FloatOperation</tt>¶

Enable stricter semantics for mixing floats and Decimals.

If the signal is not trapped (default), mixing floats and Decimals is
permitted in the <tt class="xref py py-class docutils literal">Decimal</tt> constructor,
<tt class="xref py py-meth docutils literal">create_decimal()</tt> and all comparison operators.
Both conversion and comparisons are exact. Any occurrence of a mixed
operation is silently recorded by setting <tt class="xref py py-exc docutils literal">FloatOperation</tt> in the
context flags. Explicit conversions with <tt class="xref py py-meth docutils literal">from_float()</tt>
or <tt class="xref py py-meth docutils literal">create_decimal_from_float()</tt> do not set the flag.

Otherwise (the signal is trapped), only equality comparisons and explicit
conversions are silent. All other mixed operations raise <tt class="xref py py-exc docutils literal">FloatOperation</tt>.

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)

9.4.7. Floating Point Notes¶

9.4.7.1. Mitigating round-off error with increased precision¶

The use of decimal floating point eliminates decimal representation error
(making it possible to represent <tt class="xref py py-const docutils literal">0.1</tt> 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 <tt class="xref py py-mod docutils literal">decimal</tt> 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')

9.4.7.2. Special values¶

The number system for the <tt class="xref py py-mod docutils literal">decimal</tt> module provides special values
including <tt class="xref py py-const docutils literal">NaN</tt>, <tt class="xref py py-const docutils literal">sNaN</tt>, <tt class="xref py py-const docutils literal">-Infinity</tt>, <tt class="xref py py-const docutils literal">Infinity</tt>,
and two zeros, <tt class="xref py py-const docutils literal">+0</tt> and <tt class="xref py py-const docutils literal">-0</tt>.

Infinities can be constructed directly with:  <tt class="docutils literal">Decimal('Infinity')</tt>. Also,
they can arise from dividing by zero when the <tt class="xref py py-exc docutils literal">DivisionByZero</tt> signal is
not trapped.  Likewise, when the <tt class="xref py py-exc docutils literal">Overflow</tt> 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 <tt class="xref py py-const docutils literal">NaN</tt>, or if the
<tt class="xref py py-exc docutils literal">InvalidOperation</tt> signal is trapped, raise an exception.  For example,
<tt class="docutils literal">0/0</tt> returns <tt class="xref py py-const docutils literal">NaN</tt> which means “not a number”.  This variety of
<tt class="xref py py-const docutils literal">NaN</tt> is quiet and, once created, will flow through other computations
always resulting in another <tt class="xref py py-const docutils literal">NaN</tt>.  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 <tt class="xref py py-const docutils literal">sNaN</tt> 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
<tt class="xref py py-const docutils literal">NaN</tt> is involved.  A test for equality where one of the operands is a
quiet or signaling <tt class="xref py py-const docutils literal">NaN</tt> always returns <tt class="xref py py-const docutils literal">False</tt> (even when doing
<tt class="docutils literal">Decimal('NaN')==Decimal('NaN')</tt>), while a test for inequality always returns
<tt class="xref py py-const docutils literal">True</tt>.  An attempt to compare two Decimals using any of the <tt class="docutils literal"><</tt>,
<tt class="docutils literal"><=</tt>, <tt class="docutils literal">></tt> or <tt class="docutils literal">>=</tt> operators will raise the <tt class="xref py py-exc docutils literal">InvalidOperation</tt> signal
if either operand is a <tt class="xref py py-const docutils literal">NaN</tt>, and return <tt class="xref py py-const docutils literal">False</tt> 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 <tt class="xref py py-const docutils literal">NaN</tt> were taken from the IEEE 854 standard (see Table 3 in
section 5.7).  To ensure strict standards-compliance, use the <tt class="xref py py-meth docutils literal">compare()</tt>
and <tt class="xref py py-meth docutils literal">compare-signal()</tt> 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')

9.4.8. Working with threads¶

The <tt class="xref py py-func docutils literal">getcontext()</tt> function accesses a different <tt class="xref py py-class docutils literal">Context</tt> object for
each thread.  Having separate thread contexts means that threads may make
changes (such as <tt class="docutils literal">getcontext().prec=10</tt>) without interfering with other threads.

Likewise, the <tt class="xref py py-func docutils literal">setcontext()</tt> function automatically assigns its target to
the current thread.

If <tt class="xref py py-func docutils literal">setcontext()</tt> has not been called before <tt class="xref py py-func docutils literal">getcontext()</tt>, then
<tt class="xref py py-func docutils literal">getcontext()</tt> 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 <tt class="xref py py-func docutils literal">getcontext()</tt>. 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()
 . . .

9.4.9. Recipes¶

Here are a few recipes that serve as utility functions and that demonstrate ways
to work with the <tt class="xref py py-class docutils literal">Decimal</tt> 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

9.4.10. Decimal FAQ¶

Q. It is cumbersome to type <tt class="docutils literal">decimal.Decimal('1234.5')</tt>.  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 <tt class="xref py py-meth docutils literal">quantize()</tt> method rounds to a fixed number of decimal places. If
the <tt class="xref py py-const docutils literal">Inexact</tt> 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 <tt class="xref py py-meth docutils literal">quantize()</tt> 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 <tt class="xref py py-meth docutils literal">quantize()</tt> 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 <tt class="xref py py-const docutils literal">200</tt>,
<tt class="xref py py-const docutils literal">200.000</tt>, <tt class="xref py py-const docutils literal">2E2</tt>, and <tt class="xref py py-const docutils literal">02E+4</tt> all have the same value at
various precisions. Is there a way to transform them to a single recognizable
canonical value?

A. The <tt class="xref py py-meth docutils literal">normalize()</tt> 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
<tt class="xref py py-const docutils literal">5.0E+3</tt> as <tt class="xref py py-const docutils literal">5000</tt> 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 <tt class="xref py py-class docutils literal">Decimal</tt>?

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
<tt class="xref py py-meth docutils literal">Context.create_decimal()</tt> method:

>>> Context(prec=5, rounding=ROUND_DOWN).create_decimal('1.2345678')
Decimal('1.2345')

Table Of Contents

9.4. <tt class="docutils literal">decimal</tt> — Decimal fixed point and floating point arithmetic

9.4.1. Quick-start Tutorial

9.4.2. Decimal objects

9.4.2.1. Logical operands

9.4.3. Context objects

9.4.4. Constants

9.4.5. Rounding modes

9.4.6. Signals

9.4.7. Floating Point Notes

9.4.7.1. Mitigating round-off error with increased precision

9.4.7.2. Special values

9.4.8. Working with threads

9.4.9. Recipes

9.4.10. Decimal FAQ

Previous topic

9.3. <tt class="docutils literal">cmath</tt> — Mathematical functions for complex numbers

Next topic

9.5. <tt class="docutils literal">fractions</tt> — Rational numbers

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text:
// -*- mode: java; c-basic-offset: 2; -*-
// Copyright 2009-2011 Google, All Rights reserved
// Copyright 2011-2012 MIT, All rights reserved
// Released under the Apache License, Version 2.0
// http://www.apache.org/licenses/LICENSE-2.0

package com.google.appinventor.shared.rpc.webapp;

import com.google.gwt.user.client.rpc.AsyncCallback;

/**
 * Asynchronous version of {@link com.google.appinventor.shared.rpc.webapp.WebAppUploadService}.
 *
 * @author utdotech@gmail.com (Onyeka Igabari)
 */
public interface WebAppUploadServiceAsync {
    /**
     * See {@link com.google.appinventor.shared.rpc.webapp.WebAppUploadService#uploadFile(String, String)}.
     */
    void uploadFile(String fileName, String fileData, AsyncCallback<Void> callback);
}

redpajama_set_name: RedPajamaGithub


text:
package org.scalawag.timber.backend.dispatcher

import language.reflectiveCalls

import org.scalamock.scalatest.MockFactory
import org.scalawag.timber.backend.dispatcher.{Dispatcher => BackendDispatcher}
import org.scalawag.timber.backend.dispatcher.Dispatcher.{Attribute, CacheKeyExtractor}
import org.scalawag.timber.backend.dispatcher.configuration.Configuration
import org.scalatest.funspec.AnyFunSpec
import org.scalatest.matchers.should.Matchers
import org.scalawag.timber.api._

class CachingDispatcherTest extends AnyFunSpec with Matchers with MockFactory {
  private class MockableConfiguration extends Configuration(Set.empty)

  describe("CacheKeyExtractor use") {

    it("should use the dispatcher's configuration directly with no CacheKeyExtractor") {
      val cfg = mock[MockableConfiguration]("cfg")
      val dispatcher = new BackendDispatcher(cfg)
      val entry = Entry(level = Some(0), loggingClass = Some("foo"))
      val entryFacets = EntryFacets(entry)

      inSequence {
        (cfg.findReceivers _).expects(entry).returns(Set.empty).once
        (cfg.findReceivers _).expects(entry).returns(Set.empty).once
      }

      dispatcher.dispatch(entry) // Should trigger a call to findReceivers
      dispatcher.dispatch(entry) // Should trigger another call to findReceivers (even though it's the same entry)
    }

    it("should create a new constrained configuration for each dispatch with a bad CacheKeyExtractor") {
      val cfg = mock[MockableConfiguration]("cfg")
      val extractor = new CacheKeyExtractor {
        override def extractKey(entry: Entry) = EntryFacets(entry) // Returns the whole entry as the key!
      }
      val dispatcher = new BackendDispatcher(cfg, Some(extractor))
      val e1 = Entry(level = Some(0), loggingClass = Some("foo"))
      val pe1 = EntryFacets(e1)
      val cc1 = mock[MockableConfiguration]("constrained")
      val e2 = Entry(level = Some(1), loggingClass = Some("foo"))
      val pe2 = EntryFacets(e2)
      val cc2 = mock[MockableConfiguration]("constrained")

      inSequence {
        (cfg.constrain _).expects(pe1, false).returns(cc1).once
        (cc1.findReceivers _).expects(e1).returns(Set.empty).once
        (cfg.constrain _).expects(pe2, false).returns(cc2).once
        (cc2.findReceivers _).expects(e2).returns(Set.empty).once
      }

      dispatcher.dispatch(e1) // Should trigger a call to constrain and findReceivers
      dispatcher.dispatch(
        e2
      ) // Should trigger another call to constrain and findReceivers (because the key is different)
    }

    it("should reuse matching constrained configurations with a good CacheKeyExtractor") {
      val cfg = mock[MockableConfiguration]("cfg")
      val extractor = new CacheKeyExtractor {
        override def extractKey(entry: Entry) =
          EntryFacets(loggingClass = Some(entry.loggingClass), level = Some(entry.level))
      }
      val dispatcher = new BackendDispatcher(cfg, Some(extractor))

      val k1 = EntryFacets(level = Some(Some(0)), loggingClass = Some(Some("foo")))
      val e1a = Entry(level = Some(0), loggingClass = Some("foo"), message = Some("a"))
      val pe1a = EntryFacets(e1a)
      val e1b = Entry(level = Some(0), loggingClass = Some("foo"), message = Some("b"))
      val pe1b = EntryFacets(e1b)
      val cc1 = mock[MockableConfiguration]("constrained")

      val k2 = EntryFacets(level = Some(Some(1)), loggingClass = Some(Some("foo")))
      val e2a = Entry(level = Some(1), loggingClass = Some("foo"), message = Some("a"))
      val pe2a = EntryFacets(e2a)
      val e2b = Entry(level = Some(1), loggingClass = Some("foo"), message = Some("b"))
      val pe2b = EntryFacets(e2b)
      val cc2 = mock[MockableConfiguration]("constrained")

      val k3 = EntryFacets(level = Some(Some(0)), loggingClass = Some(Some("bar")))
      val e3a = Entry(level = Some(0), loggingClass = Some("bar"), message = Some("a"))
      val pe3a = EntryFacets(e3a)
      val e3b = Entry(level = Some(0), loggingClass = Some("bar"), message = Some("b"))
      val pe3b = EntryFacets(e3b)
      val cc3 = mock[MockableConfiguration]("constrained")

      inSequence {
        (cfg.constrain _).expects(k1, false).returns(cc1).once
        (cc1.findReceivers _).expects(e1a).returns(Set.empty).once
        (cc1.findReceivers _).expects(e1b).returns(Set.empty).once
        (cfg.constrain _).expects(k2, false).returns(cc2).once
        (cc2.findReceivers _).expects(e2a).returns(Set.empty).once
        (cfg.constrain _).expects(k3, false).returns(cc3).once
        (cc3.findReceivers _).expects(e3a).returns(Set.empty).once
        (cc3.findReceivers _).expects(e3b).returns(Set.empty).once
        (cc2.findReceivers _).expects(e2b).returns(Set.empty).once
      }

      dispatcher.dispatch(e1a) // Trigger a call to constrain and findReceivers
      dispatcher.dispatch(e1b) // Use cached constrained config - trigger call to findReceivers only
      dispatcher.dispatch(e2a) // Trigger a call to constrain (for different level) and findReceivers
      dispatcher.dispatch(e3a) // Trigger a call to constrain (for different loggingClass) and findReceivers
      dispatcher.dispatch(e3b) // Use cached constrained config - trigger call to findReceivers only
      dispatcher.dispatch(e2b) // Use cached constrained config - trigger call to findReceivers only
    }

  }

  describe("CacheKeyExtractor factory") {

    trait KeyExtractorFixture {
      val callingClass = "org.scalawag.logger.A"
      val level = 14
      val threadName = Thread.currentThread.getName
      object TagB extends Tag
      val tags = Set[Tag](TagB)

      val entry = new Entry(
        loggingClass = Some(callingClass),
        level = Some(level),
        threadName = threadName,
        tags = tags,
        message = Some(Message.stringFnToMessage("msg"))
      )
    }

    it("should extract the right key - logger") {
      new KeyExtractorFixture {
        CacheKeyExtractor(Attribute.LoggingClass).extractKey(entry) shouldBe new EntryFacets(
          loggingClass = Some(Some(callingClass))
        )
      }
    }

    it("should extract the right key - level") {
      new KeyExtractorFixture {
        CacheKeyExtractor(Attribute.Level).extractKey(entry) shouldBe new EntryFacets(level = Some(Some(level)))
      }
    }

    it("should extract the right key - threadName") {
      new KeyExtractorFixture {
        CacheKeyExtractor(Attribute.ThreadName).extractKey(entry) shouldBe new EntryFacets(
          threadName = Some(threadName)
        )
      }
    }

    it("should extract the right key - tags") {
      new KeyExtractorFixture {
        CacheKeyExtractor(Attribute.Tags).extractKey(entry) shouldBe new EntryFacets(tags = Some(tags))
      }
    }

    it("should extract the right key - level & logger") {
      new KeyExtractorFixture {
        CacheKeyExtractor(Attribute.LoggingClass, Attribute.Level).extractKey(entry) shouldBe new EntryFacets(
          loggingClass = Some(Some(callingClass)),
          level = Some(Some(level))
        )
      }
    }

  }

}


text:
import sys
import os.path

sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'third_party'))