Log message:

	wip:
	added dependency: sympy, numpy
	CHANGES:
	
0.3.1 (2014-10-24)

    Better support for Python 3.3 and 3.4
    Proper integration in Travis CI
    Improved support for Linux systems (accepting x86_64-linux-gnu-gcc)
    Avoiding warning on Linux by removing Wstrict-prototypes arg
    Supporting gcc proxied clang (OS X)
    Added set of examples

0.3.0 (2014-10-16)

    Language: scalar return values
    Shared libraries are written to hope.config.prefix
    Function call can have return values
    Fixed function calls to function with no arguments
    Make sure code is recompiled if the python code has changed
    Added config.optimize to simplify expression using sympy and replace pow
    Speed improvements for hope
    Added support for object properties
    Added support for object methods
    Addes support for True and False
    Addes support for While
    Addes support for numpy.sum
    Addes support for numpy.pi
    Added support for numpy.floor, numpy.ceil, numpy.trunc, numpy.fabs, numpy.log
    improved error messages
    Added config.rangecheck flag
    Support xrange in for loop
    Added cast operators for np.bool_, np.int_, np.intc, np.int8, np.int16, \ 
np.int32, np.int64, np.uint8, np.uint16, np.uint32, np.uint64, np.float_, \ 
np.float32, np.float64,
    Added bool operators
    Added the following operators:

FloorDiv 	a // b
Mod 	a % b
LShift 	a << b
RShift 	a >> b
BitOr 	a | b
BitXor 	a ^ b
BitAnd 	a & b
AugFloorDiv 	a //= b
AugPow 	a **= b
AugMod 	a %= b
AugLShift 	a <<= b
AugRShift 	a <<= b
AugBitOr 	a | b
AugBitXor 	a ^ b
AugBitAnd 	a & b
0.2.0 (2014-03-05)

    First release on private PyPI.

0.1.0 (2014-02-27)

    Initial creation.

Log message:
Import py27-hope-0.3.0 as wip/py-hope.

HOPE is a specialized method-at-a-time JIT compiler written in Python for
translating Python source code into C++ and compiles this at runtime
In contrast to other existing JIT compliers, which are designed for general
purpose, we have focused our development of the subset of the Python language
that is most relevant for astrophysical calculations.
By concentrating on this subset, HOPE is able to achieve the highest possible
performance