# floating point behavior in python 2.6 vs 2.7

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• Techknowledgy :

To get the same result in Python 2.6, you'll have to format the string yourself:

`'%.12g' % fp_value`

or use the `format()` function:

`format(fp_value, '.12g')`

Suggestion : 2

Numeric handling has been improved in many ways, for both floating-point numbers and for the Decimal class. There are some useful additions to the standard library, such as a greatly enhanced unittest module, the argparse module for parsing command-line options, convenient OrderedDict and Counter classes in the collections module, and many other improvements.,This article explains the new features in Python 2.7. Python 2.7 was released on July 3, 2010.,Therefore, a simple comma-grouping mechanism has been added to the mini-language used by the str.format() method. When formatting a floating-point number, simply include a comma between the width and the precision:,The string format() method changed the default precision used for floating-point and complex numbers from 6 decimal places to 12, which matches the precision used by str(). (Changed by Eric Smith; bpo-5920.)

```>>> from collections
import OrderedDict
>>>
d = OrderedDict([('first', 1),
...('second', 2),
...('third', 3)
]) >>>
d.items()[('first', 1), ('second', 2), ('third', 3)]```
```>>> d['second'] = 4 >>>
d.items()[('first', 1), ('second', 4), ('third', 3)]```
```>>> del d['second'] >>>
d['second'] = 5 >>>
d.items()[('first', 1), ('third', 3), ('second', 5)]```
```>>> od = OrderedDict([(x, 0) for x in range(20)]) >>>
od.popitem()
(19, 0) >>>
od.popitem()
(18, 0) >>>
od.popitem(last = False)
(0, 0) >>>
od.popitem(last = False)
(1, 0)```
```>>> od1 = OrderedDict([('first', 1),
...('second', 2),
...('third', 3)
]) >>>
od2 = OrderedDict([('third', 3),
...('first', 1),
...('second', 2)
]) >>>
od1 == od2
False
>>>
# Move 'third'
key to the end
>>>
del od2['third'];
od2['third'] = 3 >>>
od1 == od2
True```
```>>> '{:20,.2f}'.format(18446744073709551616.0)
'18,446,744,073,709,551,616.00'```

Suggestion : 3

I have to convert string to tuple of float. In Python 2.7, it gives correct conversion, but in Python it is not same case., 1 week ago I have to convert string to tuple of float. In Python 2.7, it gives correct conversion, but in Python it is not same case. I want same behaviour in Python 2.6 . Can anyone help me why this is not same in Python 2.6 and how to do in Python 2.6. Python 2.6 >>> a '60.000,494.100,361.600,553.494' >>> eval(a) , One among them is the float () function. With the help of the float () function, we can convert an input string or an integer value to a floating point value. We already knew that it is not mandatory to send a parameter to the float (), in such a case the function returns 0.0 as output. , 1 week ago Oct 06, 2016  · 1 Answer. In order to get the same result in Python 2.6, you have to explicitly do: Changed in version 2.6: leading and trailing whitespace characters are permitted when creating a Decimal instance from a string. Changed in version 2.7: The argument to the constructor is now permitted to be a float instance.

```>>> a '60.000,494.100,361.600,553.494' >>> eval(a)(60.0, 494.10000000000002, 361.60000000000002, 553.49400000000003) >>>
import ast >>> ast.literal_eval(a)(60.0, 494.10000000000002, 361.60000000000002, 553.49400000000003) >>> >>>
for i in a.split(","): ...float(i)...60.0 494.10000000000002 361.60000000000002 553.49400000000003 >>>```
```>>> a '60.000,494.100,361.600,553.494' >>> eval(a)(60.0, 494.10000000000002, 361.60000000000002, 553.49400000000003) >>>
import ast >>> ast.literal_eval(a)(60.0, 494.10000000000002, 361.60000000000002, 553.49400000000003) >>> >>>
for i in a.split(","): ...float(i)...60.0 494.10000000000002 361.60000000000002 553.49400000000003 >>>```
```>>> a '60.000,494.100,361.600,553.494' >>> eval(a)(60.0, 494.1, 361.6, 553.494) >>>
import ast >>> ast.literal_eval(a)(60.0, 494.1, 361.6, 553.494) >>> >>>
for i in a.split(","): ...float(i)...60.0 494.1 361.6 553.494```
`print fGalleyTopRightOddX, ">=", tLinetextBbox[2], fGalleyTopRightOddX >= tLinetextBbox[2] 361.6 >= 361.6 False`
`'%.12g' % float_variable`
`def convert_to_my_float(float_value): return float('%.12g' % float_value)`

Suggestion : 4

The decimal module provides support for decimal floating point arithmetic. It offers several advantages over the float datatype:,In addition to the standard numeric properties, decimal floating point objects also have a number of specialized methods:,The decimal module makes it possible to restore the identities by expanding the precision sufficiently to avoid loss of significance:,The use of decimal floating point eliminates decimal representation error (making it possible to represent 0.1 exactly); however, some operations can still incur round-off error when non-zero digits exceed the fixed precision.

```>>> from decimal
import *
>>>
getcontext().prec = 6 >>>
Decimal(1) / Decimal(7)
Decimal('0.142857') >>>
getcontext().prec = 28 >>>
Decimal(1) / Decimal(7)
Decimal('0.1428571428571428571428571429')```
```>>> from decimal
import *
>>>
getcontext()
Context(prec = 28, rounding = ROUND_HALF_EVEN, Emin = -999999999, Emax = 999999999,
capitals = 1, flags = [], traps = [Overflow, DivisionByZero,
InvalidOperation
])

>>>
getcontext().prec = 7 # Set a new precision```
```>>> getcontext().prec = 28 >>>
Decimal(10)
Decimal('10') >>>
Decimal('3.14')
Decimal('3.14') >>>
Decimal(3.14)
Decimal('3.140000000000000124344978758017532527446746826171875') >>>
Decimal((0, (3, 1, 4), -2))
Decimal('3.14') >>>
Decimal(str(2.0 ** 0.5))
Decimal('1.41421356237') >>>
Decimal(2) ** Decimal('0.5')
Decimal('1.414213562373095048801688724') >>>
Decimal('NaN')
Decimal('NaN') >>>
Decimal('-Infinity')
Decimal('-Infinity')```
```>>> 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')```
```>>> data = map(Decimal, '1.34 1.87 3.45 2.35 1.00 0.03 9.25'.split()) >>>
max(data)
Decimal('9.25') >>>
min(data)
Decimal('0.03') >>>
sorted(data)[Decimal('0.03'), Decimal('1.00'), Decimal('1.34'), Decimal('1.87'),
Decimal('2.35'), Decimal('3.45'), Decimal('9.25')] >>>
sum(data)
Decimal('19.29') >>>
a, b, c = data[: 3] >>>
str(a)
'1.34' >>>
float(a)
1.34
>>>
round(a, 1) # round() first converts to binary floating point
1.3
>>>
int(a)
1
>>>
a * 5
Decimal('6.70') >>>
a * b
Decimal('2.5058') >>>
c % a
Decimal('0.77')```
```>>> 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')```

Suggestion : 5

Jun 1, 2014 by Sebastian Raschka

```from __future__
import division```
```from platform
import python_version```
```print 'Python', python_version()
print 'Hello, World!'
print('Hello, World!')
print "text", ;
print 'print more text on the same line'```
```Python 2.7 .6
Hello, World!
Hello, World!
text print more text on the same line```
```print('Python', python_version())
print('Hello, World!')

print("some text,", end = "")
print(' print more text on the same line')```
```Python 3.4 .1
Hello, World!
some text, print more text on the same line```

Suggestion : 6

Last Updated : 01 Mar, 2021,GATE CS 2021 Syllabus

Output :

```1.4

-
1.4```

Output:

`GeeksforGeeks`

Suggestion : 7

Much as Python 2.6 incorporated features from Python 3.0, version 2.7 incorporates some of the new features in Python 3.1. The 2.x series continues to provide tools for migrating to the 3.x series.,Numeric handling has been improved in many ways, for both floating-point numbers and for the Decimal class. There are some useful additions to the standard library, such as a greatly enhanced unittest module, the argparse module for parsing command-line options, convenient OrderedDict and Counter classes in the collections module, and many other improvements.,PEP 466 describes a number of network security enhancement proposals that have been approved for inclusion in Python 2.7 maintenance releases, with the first of those changes appearing in the Python 2.7.7 release.,This means that Python 2.7 will remain in place for a long time, providing a stable and supported base platform for production systems that have not yet been ported to Python 3. The full expected lifecycle of the Python 2.7 series is detailed in PEP 373.

```>>> from collections
import OrderedDict
>>>
d = OrderedDict([('first', 1),
...('second', 2),
...('third', 3)
]) >>>
d.items()[('first', 1), ('second', 2), ('third', 3)]```
```>>> d['second'] = 4 >>>
d.items()[('first', 1), ('second', 4), ('third', 3)]```
```>>> del d['second'] >>>
d['second'] = 5 >>>
d.items()[('first', 1), ('third', 3), ('second', 5)]```
```>>> od = OrderedDict([(x, 0) for x in range(20)]) >>>
od.popitem()
(19, 0) >>>
od.popitem()
(18, 0) >>>
od.popitem(last = False)
(0, 0) >>>
od.popitem(last = False)
(1, 0)```
```>>> od1 = OrderedDict([('first', 1),
...('second', 2),
...('third', 3)
]) >>>
od2 = OrderedDict([('third', 3),
...('first', 1),
...('second', 2)
]) >>>
od1 == od2
False
>>>
# Move 'third'
key to the end
>>>
del od2['third'];
od2['third'] = 3 >>>
od1 == od2
True```
```>>> '{:20,.2f}'.format(18446744073709551616.0)
'18,446,744,073,709,551,616.00'```

Suggestion : 8

Python 2.6 also sees a number of improvements and bugfixes throughout the source. A search through the change logs finds there were 259 patches applied and 612 bugs fixed between Python 2.5 and 2.6. Both figures are likely to be underestimates.,A new function, catch_warnings(), is a context manager intended for testing purposes that lets you temporarily modify the warning filters and then restore their original values (issue 3781).,As in every release, Python’s standard library received a number of enhancements and bug fixes. Here’s a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the Subversion logs for all the details.,The localcontext() function in the decimal module makes it easy to save and restore the current decimal context, which encapsulates the desired precision and rounding characteristics for computations:

```with expression[as variable]:
with - block```
```with open('/etc/passwd', 'r') as f:
for line in f:
print line
...more processing code...```
```lock = threading.Lock()
with lock:
# Critical section of code
...```
```from decimal
import Decimal, Context, localcontext

# Displays with
default precision of 28 digits
v = Decimal('578')
print v.sqrt()

with localcontext(Context(prec = 16)):
# All code in this block uses a precision of 16 digits.
# The original context is restored on exiting the block.
print v.sqrt()```
```db_connection = DatabaseConnection()
with db_connection as cursor:
cursor.execute('insert into ...')
cursor.execute('delete from ...')
#...more operations...```
```class DatabaseConnection:
# Database interface
def cursor(self):
"Returns a cursor object and starts a new transaction"
def commit(self):
"Commits current transaction"
def rollback(self):
"Rolls back current transaction"```