Changelogs » Numba

Numba

3.5.1

Updated to 3.5.1 with the same ELF relocation patched for v0.2.2.

3.5

The binaries from the numba binstar channel use a patched LLVM3.5 for fixing
a LLVM ELF relocation bug that is caused by the use of 32-bit relative offset
in 64-bit binaries.  The problem appears to occur more often on hardened
kernels, like in CentOS.  The patched source code is available at:
https://github.com/numba/llvm-mirror/releases/tag/3.5p1

1.17

* PR 4325: accept scalar/0d-arrays
* PR 4338: Fix 4299. Parfors reduction vars not deleted.
* PR 4350: Use process level locks for fork() only.
* PR 4354: Try to fix 4352.
* PR 4357: Fix np1.17 isnan, isinf, isfinite ufuncs
* PR 4363: Fix np.interp for np1.17 nan handling
* PR 4371: Fix nump1.17 random function non-aliasing

Contributors:

* Siu Kwan Lam (core dev)
* Stuart Archibald (core dev)
* Valentin Haenel (core dev)

0.46.0

--------------

This release significantly reworked one of the main parts of Numba, the compiler
pipeline, to make it more extensible and easier to use. The purpose of this was
to continue enhancing Numba's ability for use as a compiler toolkit. In a
similar vein, Numba now has an extension registration mechanism to allow other
Numba-using projects to automatically have their Numba JIT compilable functions
discovered. There were also a number of other related compiler toolkit
enhancement added along with some more NumPy features and a lot of bug fixes.

This release has updated the CUDA Array Interface specification to version 2,
which clarifies the `strides` attribute for C-contiguous arrays and specifies
the treatment for zero-size arrays. The implementation in Numba has been
changed and may affect downstream packages relying on the old behavior
(see issue 4661).

Enhancements from user contributed PRs (with thanks!):

* Aaron Meurer fixed some Python issues in the code base in 4345 and 4341.
* Ashwin Srinath fixed a CUDA performance bug via 4576.
* Ethan Pronovost added support for triangular indices functions in 4601 (the
NumPy functions ``tril_indices``, ``tril_indices_from``, ``triu_indices``, and
``triu_indices_from``).
* Gerald Dalley fixed a tear down race occurring in Python 2.
* Gregory R. Lee fixed the use of deprecated ``inspect.getargspec``.
* Guilherme Leobas contributed five PRs, adding support for ``np.append`` and
``np.count_nonzero`` in 4518 and 4386. The typed List was fixed to accept
unsigned integers in 4510. 4463 made a fix to NamedTuple internals and 4397
updated the docs for ``np.sum``.
* James Bourbeau added a new feature to permit the automatic application of the
`jit` decorator to a whole module in 4331. Also some small fixes to the docs
and the code base were made in 4447 and 4433, and a fix to inplace array
operation in 4228.
* Jim Crist fixed a bug in the rendering of patched errors in 4464.
* Leo Fang updated the CUDA Array Interface contract in 4609.
* Pearu Peterson added support for Unicode based NumPy arrays in 4425.
* Peter Andreas Entschev fixed a CUDA concurrency bug in 4581.
* Lucio Fernandez-Arjona extended Numba's ``np.sum`` support to now accept the
``dtype`` kwarg in 4472.
* Pedro A. Morales Maries added support for ``np.cross`` in 4128 and also added
the necessary extension ``numba.numpy_extensions.cross2d`` in 4595.
* David Hoese, Eric Firing, Joshua Adelman, and Juan Nunez-Iglesias all made
documentation fixes in 4565, 4482, 4455, 4375 respectively.
* Vyacheslav Smirnov and Rujal Desai enabled support for ``count()`` on unicode
strings in 4606.

General Enhancements:

* PR 4113: Add rewrite for semantic constants.
* PR 4128: Add np.cross support
* PR 4162: Make IR comparable and legalize it.
* PR 4208: R&D inlining, jitted and overloaded.
* PR 4331: Automatic JIT of called functions
* PR 4353: Inspection tool to check what numba supports
* PR 4386: Implement np.count_nonzero
* PR 4425: Unicode array support
* PR 4427: Entrypoints for numba extensions
* PR 4467: Literal dispatch
* PR 4472: Allow dtype input argument in np.sum
* PR 4513: New compiler.
* PR 4518: add support for np.append
* PR 4554: Refactor NRT C-API
* PR 4556: 0.46 scheduled deprecations
* PR 4567: Add env var to disable performance warnings.
* PR 4568: add np.array_equal support
* PR 4595: Implement numba.cross2d
* PR 4601: Add triangular indices functions
* PR 4606: Enable support for count() method for unicode string

Fixes:

* PR 4228: Fix inplace operator error for arrays
* PR 4282: Detect and raise unsupported on generator expressions
* PR 4305: Don't allow the allocation of mutable objects written into a
container to be hoisted.
* PR 4311: Avoid deprecated use of inspect.getargspec
* PR 4328:  Replace GC macro with function call
* PR 4330: Loosen up typed container casting checks
* PR 4341: Fix some coding lines at the top of some files (utf8 -> utf-8)
* PR 4345: Replace "import \*" with explicit imports in numba/types
* PR 4346: Fix incorrect alg in isupper for ascii strings.
* PR 4349: test using jitclass in typed-list
* PR 4361: Add allocation hoisting info to LICM section at diagnostic L4
* PR 4366: Offset search box to avoid wrapping on some pages with Safari.
Fixes 4365.
* PR 4372: Replace all "except BaseException" with "except Exception".
* PR 4407: Restore the "free" conda channel for NumPy 1.10 support.
* PR 4408: Add lowering for constant bytes.
* PR 4409: Add exception chaining for better error context
* PR 4411: Name of type should not contain user facing description for debug.
* PR 4412: Fix 4387. Limit the number of return types for recursive functions
* PR 4426: Fixed two module teardown races in py2.
* PR 4431: Fix and test numpy.random.random_sample(n) for np117
* PR 4463: NamedTuple - Raises an error on non-iterable elements
* PR 4464: Add a newline in patched errors
* PR 4474: Fix liveness for remove dead of parfors (and other IR extensions)
* PR 4510: Make List.__getitem__ accept unsigned parameters
* PR 4512: Raise specific error at typing time for iteration on >1D array.
* PR 4532: Fix static_getitem with Literal type as index
* PR 4547: Update to inliner cost model information.
* PR 4557: Use specific random number seed when generating arbitrary test data
* PR 4559: Adjust test timeouts
* PR 4564: Skip unicode array tests on ppc64le that trigger an LLVM bug
* PR 4621: Fix packaging issue due to missing numba/cext
* PR 4623: Fix issue 4520 due to storage model mismatch
* PR 4644: Updates for llvmlite 0.30.0

CUDA Enhancements/Fixes:

* PR 4410: Fix 4111. cudasim mishandling recarray
* PR 4576: Replace use of `np.prod` with `functools.reduce` for computing size
from shape
* PR 4581: Prevent taking the GIL in ForAll
* PR 4592: Fix 4589.  Just pass NULL for b2d_func for constant dynamic
sharedmem
* PR 4609: Update CUDA Array Interface & Enforce Numba compliance
* PR 4619: Implement math.{degrees, radians} for the CUDA target.
* PR 4675: Bump cuda array interface to version 2

Documentation Updates:

* PR 4317: Add docs for ARMv8/AArch64
* PR 4318: Add supported platforms to the docs.  Closes 4316
* PR 4375: Add docstrings to inspect methods
* PR 4388: Update Python 2.7 EOL statement
* PR 4397: Add note about np.sum
* PR 4447: Minor parallel performance tips edits
* PR 4455: Clarify docs for typed dict with regard to arrays
* PR 4482: Fix example in guvectorize docstring.
* PR 4541: fix two typos in architecture.rst
* PR 4548: Document numba.extending.intrinsic and inlining.
* PR 4565: Fix typo in jit-compilation docs
* PR 4607: add dependency list to docs
* PR 4614: Add documentation for implementing new compiler passes.

CI Updates:

* PR 4415: Make 32bit incremental builds on linux not use free channel
* PR 4433: Removes stale azure comment
* PR 4493: Fix Overload Inliner wrt CUDA Intrinsics
* PR 4593: Enable Azure CI batching

Contributors:

* Aaron Meurer
* Ashwin Srinath
* David Hoese
* Ehsan Totoni (core dev)
* Eric Firing
* Ethan Pronovost
* Gerald Dalley
* Gregory R. Lee
* Guilherme Leobas
* James Bourbeau
* Jim Crist
* Joshua Adelman
* Juan Nunez-Iglesias
* Leo Fang
* Lucio Fernandez-Arjona
* Pearu Peterson
* Pedro A. Morales Marie
* Peter Andreas Entschev
* Rujal Desai
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Todd A. Anderson (core dev)
* Valentin Haenel (core dev)
* Vyacheslav Smirnov

0.45.1

--------------

This patch release addresses some regressions reported in the 0.45.0 release and

0.45.0

--------------

In this release, Numba gained an experimental :ref:`numba.typed.List
<feature-typed-list>` container as a future replacement of the :ref:`reflected
list <feature-reflected-list>`. In addition, functions decorated with
``parallel=True`` can now be cached to reduce compilation overhead associated
with the auto-parallelization.


Enhancements from user contributed PRs (with thanks!):

* James Bourbeau added the Numba version to reportable error messages in 4227,
added the ``signature`` parameter to ``inspect_types`` in 4200, improved the
docstring of ``normalize_signature`` in 4205, and fixed 3658 by adding
reference counting to ``register_dispatcher`` in 4254

* Guilherme Leobas implemented the dominator tree and dominance frontier
algorithms in 4216 and 4149, respectively.

* Nick White fixed the issue with ``round`` in the CUDA target in 4137.

* Joshua Adelman added support for determining if a value is in a `range`
(i.e.  ``x in range(...)``) in 4129, and added windowing functions
(``np.bartlett``, ``np.hamming``, ``np.blackman``, ``np.hanning``,
``np.kaiser``) from NumPy in 4076.

* Lucio Fernandez-Arjona added support for ``np.select`` in 4077

* Rob Ennis added support for ``np.flatnonzero`` in 4157

* Keith Kraus extended the ``__cuda_array_interface__`` with an optional mask
attribute in 4199.

* Gregory R. Lee replaced deprecated use of ``inspect.getargspec`` in 4311.


General Enhancements:

* PR 4328: Replace GC macro with function call
* PR 4311: Avoid deprecated use of inspect.getargspec
* PR 4296: Slacken window function testing tol on ppc64le
* PR 4254: Add reference counting to register_dispatcher
* PR 4239: Support len() of multi-dim arrays in array analysis
* PR 4234: Raise informative error for np.kron array order
* PR 4232: Add unicodetype db, low level str functions and examples.
* PR 4229: Make hashing cacheable
* PR 4227: Include numba version in reportable error message
* PR 4216: Add dominator tree
* PR 4200: Add signature parameter to inspect_types
* PR 4196: Catch missing imports of internal functions.
* PR 4180: Update use of unlowerable global message.
* PR 4166: Add tests for PR 4149
* PR 4157: Support for np.flatnonzero
* PR 4149: Implement dominance frontier for SSA for the Numba IR
* PR 4148: Call branch pruning in inline_closure_call()
* PR 4132: Reduce usage of inttoptr
* PR 4129: Support contains for range
* PR 4112: better error messages for np.transpose and tuples
* PR 4110: Add range attrs, start, stop, step
* PR 4077: Add np select
* PR 4076: Add numpy windowing functions support (np.bartlett, np.hamming,
np.blackman, np.hanning, np.kaiser)
* PR 4095: Support ir.Global/FreeVar in find_const()
* PR 3691: Make TypingError abort compiling earlier
* PR 3646: Log internal errors encountered in typeinfer

Fixes:

* PR 4303: Work around scipy bug 10206
* PR 4302: Fix flake8 issue on master
* PR 4301: Fix integer literal bug in np.select impl
* PR 4291: Fix pickling of jitclass type
* PR 4262: Resolves 4251 - Fix bug in reshape analysis.
* PR 4233: Fixes issue revealed by 4215
* PR 4224: Fix 4223. Looplifting error due to StaticSetItem in objectmode
* PR 4222: Fix bad python path.
* PR 4178: Fix unary operator overload, check with unicode impl
* PR 4173: Fix return type in np.bincount with weights
* PR 4153: Fix slice shape assignment in array analysis
* PR 4152: fix status check in dict lookup
* PR 4145: Use callable instead of checking __module__
* PR 4118: Fix inline assembly support on CPU.
* PR 4088: Resolves 4075 - parfors array_analysis bug.
* PR 4085: Resolves 3314 - parfors array_analysis bug with reshape.

CUDA Enhancements/Fixes:

* PR 4199: Extend `__cuda_array_interface__` with optional mask attribute,
bump version to 1
* PR 4137: CUDA - Fix round Builtin
* PR 4114: Support 3rd party activated CUDA context

Documentation Updates:

* PR 4317: Add docs for ARMv8/AArch64
* PR 4318: Add supported platforms to the docs. Closes 4316
* PR 4295: Alter deprecation schedules
* PR 4253: fix typo in pysupported docs
* PR 4252: fix typo on repomap
* PR 4241: remove unused import
* PR 4240: fix typo in jitclass docs
* PR 4205: Update return value order in normalize_signature docstring
* PR 4237: Update doc links to point to latest not dev docs.
* PR 4197: hyperlink repomap
* PR 4170: Clarify docs on accumulating into arrays in prange
* PR 4147: fix docstring for DictType iterables
* PR 3951: A guide to overloading

CI Updates:

* PR 4300: AArch64 has no faulthandler package
* PR 4273: pin to MKL BLAS for testing to get consistent results
* PR 4209: Revert previous network tol patch and try with conda config
* PR 4138: Remove tbb before Azure test only on Python 3, since it was already
removed for Python 2

Contributors:

* Ehsan Totoni (core dev)
* Gregory R. Lee
* Guilherme Leobas
* James Bourbeau
* Joshua L. Adelman
* Keith Kraus
* Lucio Fernandez-Arjona
* Nick White
* Rob Ennis
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Todd A. Anderson (core dev)
* Valentin Haenel (core dev)

0.44.1

--------------

This patch release addresses some regressions reported in the 0.44.0 release:

- PR 4165: Fix 4164 issue with NUMBAPRO_NVVM.
- PR 4172: Abandon branch pruning if an arg name is redefined. (Fixes 4163)
- PR 4183: Fix 4156. Problem with defining in-loop variables.

0.44.0

--------------

IMPORTANT: In this release a few significant deprecations (and some less
significant ones) are being made, users are encouraged to read the related
documentation.

General enhancements in this release include:

- Numba is backed by LLVM 8 on all platforms apart from ppc64le, which, due to
bugs, remains on the LLVM 7.x series.
- Numba's dictionary support now includes type inference for keys and values.
- The .view() method now works for NumPy scalar types.
- Newly supported NumPy functions added: np.delete, np.nanquantile, np.quantile,
np.repeat, np.shape.

In addition considerable effort has been made to fix some long standing bugs and
a large number of other bugs, the "Fixes" section is very large this time!

Enhancements from user contributed PRs (with thanks!):

- Max Bolingbroke added support for the selective use of ``fastmath`` flags in
3847.
- Rob Ennis made min() and max() work on iterables in 3820 and added
np.quantile and np.nanquantile in 3899.
- Sergey Shalnov added numerous unicode string related features, zfill in 3978,
ljust in 4001, rjust and center in 4044 and strip, lstrip and rstrip in
4048.
- Guilherme Leobas added support for np.delete in 3890
- Christoph Deil exposed the Numba CLI via ``python -m numba`` in 4066 and made
numerous documentation fixes.
- Leo Schwarz wrote the bulk of the code for jitclass default constructor
arguments in 3852.
- Nick White enhanced the CUDA backend to use min/max PTX instructions where
possible in 4054.
- Lucio Fernandez-Arjona implemented the unicode string ``__mul__`` function in
3952.
- Dimitri Vorona wrote the bulk of the code to implement getitem and setitem for
jitclass in 3861.

General Enhancements:

* PR 3820: Min max on iterables
* PR 3842: Unicode type iteration
* PR 3847: Allow fine-grained control of fastmath flags to partially address 2923
* PR 3852: Continuation of PR 2894
* PR 3861: Continuation of PR 3730
* PR 3890: Add support for np.delete
* PR 3899: Support for np.quantile and np.nanquantile
* PR 3900: Fix 3457 :: Implements np.repeat
* PR 3928: Add .view() method for NumPy scalars
* PR 3939: Update icc_rt clone recipe.
* PR 3952: __mul__ for strings, initial implementation and tests
* PR 3956: Type-inferred dictionary
* PR 3959: Create a view for string slicing to avoid extra allocations
* PR 3978: zfill operation implementation
* PR 4001: ljust operation implementation
* PR 4010: Support `dict()` and `{}`
* PR 4022: Support for llvm 8
* PR 4034: Make type.Optional str more representative
* PR 4041: Deprecation warnings
* PR 4044: rjust and center operations implementation
* PR 4048: strip, lstrip and rstrip operations implementation
* PR 4066: Expose numba CLI via python -m numba
* PR 4081: Impl `np.shape` and support function for `asarray`.
* PR 4091: Deprecate the use of iternext_impl without RefType

CUDA Enhancements/Fixes:

* PR 3933: Adds `.nbytes` property to CUDA device array objects.
* PR 4011: Add .inspect_ptx() to cuda device function
* PR 4054: CUDA: Use min/max PTX Instructions
* PR 4096: Update env-vars for CUDA libraries lookup

Documentation Updates:

* PR 3867: Code repository map
* PR 3918: adding Joris' Fosdem 2019 presentation
* PR 3926: order talks on applications of Numba by date
* PR 3943: fix two small typos in vectorize docs
* PR 3944: Fixup jitclass docs
* PR 3990: mention preprint repo in FAQ. Fixes 3981
* PR 4012: Correct runtests command in contributing.rst
* PR 4043: fix typo
* PR 4047: Ambiguous Documentation fix for guvectorize.
* PR 4060: Remove remaining mentions of autojit in docs
* PR 4063: Fix annotate example in docstring
* PR 4065: Add FAQ entry explaining Numba project name
* PR 4079: Add Documentation for atomicity of typed.Dict
* PR 4105: Remove info about CUDA ENVVAR potential replacement

Fixes:

* PR 3719: Resolves issue 3528.  Adds support for slices when not using parallel=True.
* PR 3727: Remove dels for known dead vars.
* PR 3845: Fix mutable flag transmission in .astype
* PR 3853: Fix some minor issues in the C source.
* PR 3862: Correct boolean reinterpretation of data
* PR 3863: Comments out the appveyor badge
* PR 3869: fixes flake8 after merge
* PR 3871: Add assert to ir.py to help enforce correct structuring
* PR 3881: fix preparfor dtype transform for datetime64
* PR 3884: Prevent mutation of objmode fallback IR.
* PR 3885: Updates for llvmlite 0.29
* PR 3886: Use `safe_load` from pyyaml.
* PR 3887: Add tolerance to network errors by permitting conda to retry
* PR 3893: Fix casting in namedtuple ctor.
* PR 3894: Fix array inliner for multiple array definition.
* PR 3905: Cherrypick 3903 to main
* PR 3920: Raise better error if unsupported jump opcode found.
* PR 3927: Apply flake8 to the numpy related files
* PR 3935: Silence DeprecationWarning
* PR 3938: Better error message for unknown opcode
* PR 3941: Fix typing of ufuncs in parfor conversion
* PR 3946: Return variable renaming dict from inline_closurecall
* PR 3962: Fix bug in alignment computation of `Record.make_c_struct`
* PR 3967: Fix error with pickling unicode
* PR 3964: Unicode split algo versioning
* PR 3975: Add handler for unknown locale to numba -s
* PR 3991: Permit Optionals in ufunc machinery
* PR 3995: Remove assert in type inference causing poor error message.
* PR 3996: add is_ascii flag to UnicodeType
* PR 4009: Prevent zero division error in np.linalg.cond
* PR 4014: Resolves 4007.
* PR 4021: Add a more specific error message for invalid write to a global.
* PR 4023: Fix handling of titles in record dtype
* PR 4024: Do a check if a call is const before saying that an object is multiply defined.
* PR 4027: Fix issue 4020.  Turn off no_cpython_wrapper flag when compiling for…
* PR 4033: [WIP] Fixing wrong dtype of array inside reflected list 4028
* PR 4061: Change IPython cache dir name to numba_cache
* PR 4067: Delete examples/notebooks/LinearRegr.py
* PR 4070: Catch writes to global typed.Dict and raise.
* PR 4078: Check tuple length
* PR 4084: Fix missing incref on optional return None
* PR 4089: Make the warnings fixer flush work for warning comparing on type.
* PR 4094: Fix function definition finding logic for commented def
* PR 4100: Fix alignment check on 32-bit.
* PR 4104: Use PEP 508 compliant env markers for install deps

Contributors:

* Benjamin Zaitlen
* Christoph Deil
* David Hirschfeld
* Dimitri Vorona
* Ehsan Totoni (core dev)
* Guilherme Leobas
* Leo Schwarz
* Lucio Fernandez-Arjona
* Max Bolingbroke
* NanduTej
* Nick White
* Ravi Teja Gutta
* Rob Ennis
* Sergey Shalnov
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Todd A. Anderson (core dev)
* Valentin Haenel (core dev)

0.43.1

--------------

This is a bugfix release that provides minor changes to fix: a bug in branch
pruning, bugs in `np.interp` functionality, and also fully accommodate the
NumPy 1.16 release series.

* PR 3826: NumPy 1.16 support
* PR 3850: Refactor np.interp
* PR 3883: Rewrite pruned conditionals as their evaluated constants.

Contributors:

* Rob Ennis
* Siu Kwan Lam (core dev)
* Stuart Archibald (core dev)

0.43.0

--------------

In this release, the major new features are:

- Initial support for statically typed dictionaries
- Improvements to `hash()` to match Python 3 behavior
- Support for the heapq module
- Ability to pass C structs to Numba
- More NumPy functions: asarray, trapz, roll, ptp, extract


NOTE:

The vast majority of NumPy 1.16 behaviour is supported, however
``datetime`` and ``timedelta`` use involving ``NaT`` matches the behaviour
present in earlier release. The ufunc suite has not been extending to
accommodate the two new time computation related additions present in NumPy
1.16. In addition the functions ``ediff1d`` and ``interp`` have known minor
issues in replicating outputs exactly when ``NaN``'s occur in certain input
patterns.

General Enhancements:

* PR 3563: Support for np.roll
* PR 3572: Support for np.ptp
* PR 3592: Add dead branch prune before type inference.
* PR 3598: Implement np.asarray()
* PR 3604: Support for np.interp
* PR 3607: Some simplication to lowering
* PR 3612: Exact match flag in dispatcher
* PR 3627: Support for np.trapz
* PR 3630: np.where with broadcasting
* PR 3633: Support for np.extract
* PR 3657: np.max, np.min, np.nanmax, np.nanmin - support for complex dtypes
* PR 3661: Access C Struct as Numpy Structured Array
* PR 3678: Support for str.split and str.join
* PR 3684: Support C array in C struct
* PR 3696: Add intrinsic to help debug refcount
* PR 3703: Implementations of type hashing.
* PR 3715: Port CPython3.7 dictionary for numba internal use
* PR 3716: Support inplace concat of strings
* PR 3718: Add location to ConstantInferenceError exceptions.
* PR 3720: improve error msg about invalid signature
* PR 3731: Support for heapq
* PR 3754: Updates for llvmlite 0.28
* PR 3760: Overloadable operator.setitem
* PR 3775: Support overloading operator.delitem
* PR 3777: Implement compiler support for dictionary
* PR 3791: Implement interpreter-side interface for numba dict
* PR 3799: Support refcount'ed types in numba dict

CUDA Enhancements/Fixes:

* PR 3713: Fix the NvvmSupportError message when CC too low
* PR 3722: Fix 3705: slicing error with negative strides
* PR 3755: Make cuda.to_device accept readonly host array
* PR 3773: Adapt library search to accommodate multiple locations

Documentation Updates:

* PR 3651: fix link to berryconda in docs
* PR 3668: Add Azure Pipelines build badge
* PR 3749: DOC: Clarify when prange is different from range
* PR 3771: fix a few typos
* PR 3785: Clarify use of range as function only.
* PR 3829: Add docs for typed-dict

Fixes:

* PR 3614: Resolve 3586
* PR 3618: Skip gdb tests on ARM.
* PR 3643: Remove support_literals usage
* PR 3645: Enforce and fix that AbstractTemplate.generic must be returning a Signature
* PR 3648: Fail on overload signature mismatch.
* PR 3660: Added Ignore message to test numba.tests.test_lists.TestLists.test_mul_error
* PR 3662: Replace six with numba.six
* PR 3663: Removes coverage computation from travisci builds
* PR 3672: Avoid leaking memory when iterating over uniform tuple
* PR 3676: Fixes constant string lowering inside tuples
* PR 3677: Ensure all referenced compiled functions are linked properly
* PR 3692: Fix test failure due to overly strict test on floating point values.
* PR 3693: Intercept failed import to help users.
* PR 3694: Fix memory leak in enumerate iterator
* PR 3695: Convert return of None from intrinsic implementation to dummy value
* PR 3697: Fix for issue 3687
* PR 3701: Fix array.T analysis (fixes 3700)
* PR 3704: Fixes for overload_method
* PR 3706: Don't push call vars recursively into nested parfors. Resolves 3686.
* PR 3710: Set as non-hoistable if a mutable variable is passed to a function in a loop. Resolves 3699.
* PR 3712: parallel=True to use better builtin mechanism to resolve call types. Resolves issue 3671
* PR 3725: Fix invalid removal of dead empty list
* PR 3740: add uintp as a valid type to the tuple operator.getitem
* PR 3758: Fix target definition update in inlining
* PR 3782: Raise typing error on yield optional.
* PR 3792: Fix non-module object used as the module of a function.
* PR 3800: Bugfix for np.interp
* PR 3808: Bump macro to include VS2014 to fix py3.5 build
* PR 3809: Add debug guard to debug only C function.
* PR 3816: Fix array.sum(axis) 1d input return type.
* PR 3821: Replace PySys_WriteStdout with PySys_FormatStdout to ensure no truncation.
* PR 3830: Getitem should not return optional type
* PR 3832: Handle single string as path in find_file()

Contributors:

* Ehsan Totoni
* Gryllos Prokopis
* Jonathan J. Helmus
* Kayla Ngan
* lalitparate
* luk-f-a
* Matyt
* Max Bolingbroke
* Michael Seifert
* Rob Ennis
* Siu Kwan Lam
* Stan Seibert
* Stuart Archibald
* Todd A. Anderson
* Tao He
* Valentin Haenel

0.42.1

--------------

Bugfix release to fix the incorrect hash in OSX wheel packages.
No change in source code.

0.42.0

--------------

In this release the major features are:

- The capability to launch and attach the GDB debugger from within a jitted
function.
- The upgrading of LLVM to version 7.0.0.

We added a draft of the project roadmap to the developer manual. The roadmap is
for informational purposes only as priorities and resources may change.

Here are some enhancements from contributed PRs:

- 3532. Daniel Wennberg improved the ``cuda.{pinned, mapped}`` API so that
the associated memory is released immediately at the exit of the context
manager.
- 3531. Dimitri Vorona enabled the inlining of jitclass methods.
- 3516. Simon Perkins added the support for passing numpy dtypes (i.e.
``np.dtype("int32")``) and their type constructor (i.e. ``np.int32``) into
a jitted function.
- 3509. Rob Ennis added support for ``np.corrcoef``.

A regression issue (3554, 3461) relating to making an empty slice in parallel
mode is resolved by 3558.

General Enhancements:

* PR 3392: Launch and attach gdb directly from Numba.
* PR 3437: Changes to accommodate LLVM 7.0.x
* PR 3509: Support for np.corrcoef
* PR 3516: Typeof dtype values
* PR 3520: Fix stencil ignoring cval if out kwarg supplied.
* PR 3531: Fix jitclass method inlining and avoid unnecessary increfs
* PR 3538: Avoid future C-level assertion error due to invalid visibility
* PR 3543: Avoid implementation error being hidden by the try-except
* PR 3544: Add `long_running` test flag and feature to exclude tests.
* PR 3549: ParallelAccelerator caching improvements
* PR 3558: Fixes array analysis for inplace binary operators.
* PR 3566: Skip alignment tests on armv7l.
* PR 3567: Fix unifying literal types in namedtuple
* PR 3576: Add special copy routine for NumPy out arrays
* PR 3577: Fix example and docs typos for `objmode` context manager.
reorder statements.
* PR 3580: Use alias information when determining whether it is safe to
* PR 3583: Use `ir.unknown_loc` for unknown `Loc`, as 3390 with tests
* PR 3587: Fix llvm.memset usage changes in llvm7
* PR 3596: Fix Array Analysis for Global Namedtuples
* PR 3597: Warn users if threading backend init unsafe.
* PR 3605: Add guard for writing to read only arrays from ufunc calls
* PR 3606: Improve the accuracy of error message wording for undefined type.
* PR 3611: gdb test guard needs to ack ptrace permissions
* PR 3616: Skip gdb tests on ARM.

CUDA Enhancements:

* PR 3532: Unregister temporarily pinned host arrays at once
* PR 3552: Handle broadcast arrays correctly in host->device transfer.
* PR 3578: Align cuda and cuda simulator kwarg names.

Documentation Updates:

* PR 3545: Fix njit description in 5 min guide
* PR 3570: Minor documentation fixes for numba.cuda
* PR 3581: Fixing minor typo in `reference/types.rst`
* PR 3594: Changing `stencil` docs to correctly reflect `func_or_mode` param
* PR 3617: Draft roadmap as of Dec 2018

Contributors:

* Aaron Critchley
* Daniel Wennberg
* Dimitri Vorona
* Dominik Stańczak
* Ehsan Totoni (core dev)
* Iskander Sharipov
* Rob Ennis
* Simon Muller
* Simon Perkins
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Todd A. Anderson (core dev)

0.41.0

--------------

This release adds the following major features:

* Diagnostics showing the optimizations done by ParallelAccelerator
* Support for profiling Numba-compiled functions in Intel VTune
* Additional NumPy functions: partition, nancumsum, nancumprod, ediff1d, cov,
conj, conjugate, tri, tril, triu
* Initial support for Python 3 Unicode strings

General Enhancements:

* PR 1968: armv7 support
* PR 2983: invert mapping b/w binop operators and the operator module 2297
* PR 3160: First attempt at parallel diagnostics
* PR 3307: Adding NUMBA_ENABLE_PROFILING envvar, enabling jit event
* PR 3320: Support for np.partition
* PR 3324: Support for np.nancumsum and np.nancumprod
* PR 3325: Add location information to exceptions.
* PR 3337: Support for np.ediff1d
* PR 3345: Support for np.cov
* PR 3348: Support user pipeline class in with lifting
* PR 3363: string support
* PR 3373: Improve error message for empty imprecise lists.
* PR 3375: Enable overload(operator.getitem)
* PR 3402: Support negative indexing in tuple.
* PR 3414: Refactor Const type
* PR 3416: Optimized usage of alloca out of the loop
* PR 3424: Updates for llvmlite 0.26
* PR 3462: Add support for `np.conj/np.conjugate`.
* PR 3480: np.tri, np.tril, np.triu - default optional args
* PR 3481: Permit dtype argument as sole kwarg in np.eye

CUDA Enhancements:

* PR 3399: Add max_registers Option to cuda.jit

Continuous Integration / Testing:

* PR 3303: CI with Azure Pipelines
* PR 3309: Workaround race condition with apt
* PR 3371: Fix issues with Azure Pipelines
* PR 3362: Fix 3360: `RuntimeWarning: 'numba.runtests' found in sys.modules`
* PR 3374: Disable openmp in wheel building
* PR 3404: Azure Pipelines templates
* PR 3419: Fix cuda tests and error reporting in test discovery
* PR 3491: Prevent faulthandler installation on armv7l
* PR 3493: Fix CUDA test that used negative indexing behaviour that's fixed.
* PR 3495: Start Flake8 checking of Numba source

Fixes:

* PR 2950: Fix dispatcher to only consider contiguous-ness.
* PR 3124: Fix 3119, raise for 0d arrays in reductions
* PR 3228: Reduce redundant module linking
* PR 3329: Fix AOT on windows.
* PR 3335: Fix memory management of __cuda_array_interface__ views.
* PR 3340: Fix typo in error name.
* PR 3365: Fix the default unboxing logic
* PR 3367: Allow non-global reference to objmode() context-manager
* PR 3381: Fix global reference in objmode for dynamically created function
* PR 3382: CUDA_ERROR_MISALIGNED_ADDRESS Using Multiple Const Arrays
* PR 3384: Correctly handle very old versions of colorama
* PR 3394: Add 32bit package guard for non-32bit installs
* PR 3397: Fix with-objmode warning
* PR 3403 Fix label offset in call inline after parfor pass
* PR 3429: Fixes raising of user defined exceptions for exec(<string>).
* PR 3432: Fix error due to function naming in CI in py2.7
* PR 3444: Fixed TBB's single thread execution and test added for 3440
* PR 3449: Allow matching non-array objects in find_callname()
* PR 3455: Change getiter and iternext to not be pure. Resolves 3425
* PR 3467: Make ir.UndefinedType singleton class.
* PR 3478: Fix np.random.shuffle sideeffect
* PR 3487: Raise unsupported for kwargs given to `print()`
* PR 3488: Remove dead script.
* PR 3498: Fix stencil support for boolean as return type
* PR 3511: Fix handling make_function literals (regression of 3414)
* PR 3514: Add missing unicode != unicode
* PR 3527: Fix complex math sqrt implementation for large -ve values
* PR 3530: This adds arg an check for the pattern supplied to Parfors.
* PR 3536: Sets list dtor linkage to `linkonce_odr` to fix visibility in AOT

Documentation Updates:

* PR 3316: Update 0.40 changelog with additional PRs
* PR 3318: Tweak spacing to avoid search box wrapping onto second line
* PR 3321: Add note about memory leaks with exceptions to docs. Fixes 3263
* PR 3322: Add FAQ on CUDA + fork issue. Fixes 3315.
* PR 3343: Update docs for argsort, kind kwarg partially supported.
* PR 3357: Added mention of njit in 5minguide.rst
* PR 3434: Fix parallel reduction example in docs.
* PR 3452: Fix broken link and mark up problem.
* PR 3484: Size Numba logo in docs in em units. Fixes 3313
* PR 3502: just two typos
* PR 3506: Document string support
* PR 3513: Documentation for parallel diagnostics.
* PR 3526: Fix 5 min guide with respect to njit decl

Contributors:

* Alex Ford
* Andreas Sodeur
* Anton Malakhov
* Daniel Stender
* Ehsan Totoni (core dev)
* Henry Schreiner
* Marcel Bargull
* Matt Cooper
* Nick White
* Nicolas Hug
* rjenc29
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Todd A. Anderson (core dev)

0.40.1

--------------

This is a PyPI-only patch release to ensure that PyPI wheels can enable the
TBB threading backend, and to disable the OpenMP backend in the wheels.
Limitations of manylinux1 and variation in user environments can cause
segfaults when OpenMP is enabled on wheel builds.  Note that this release has
no functional changes for users who obtained Numba 0.40.0 via conda.

Patches:

* PR 3338: Accidentally left Anton off contributor list for 0.40.0
* PR 3374: Disable OpenMP in wheel building
* PR 3376: Update 0.40.1 changelog and docs on OpenMP backend

0.40.0

--------------

This release adds a number of major features:

* A new GPU backend: kernels for AMD GPUs can now be compiled using the ROCm
driver on Linux.
* The thread pool implementation used by Numba for automatic multithreading
is configurable to use TBB, OpenMP, or the old "workqueue" implementation.
(TBB is likely to become the preferred default in a future release.)
* New documentation on thread and fork-safety with Numba, along with overall
improvements in thread-safety.
* Experimental support for executing a block of code inside a nopython mode
function in object mode.
* Parallel loops now allow arrays as reduction variables
* CUDA improvements: FMA, faster float64 atomics on supporting hardware,
records in const memory, and improved datatime dtype support
* More NumPy functions: vander, tri, triu, tril, fill_diagonal


General Enhancements:

* PR 3017: Add facility to support with-contexts
* PR 3033: Add support for multidimensional CFFI arrays
* PR 3122: Add inliner to object mode pipeline
* PR 3127: Support for reductions on arrays.
* PR 3145: Support for np.fill_diagonal
* PR 3151: Keep a queue of references to last N deserialized functions.  Fixes 3026
* PR 3154: Support use of list() if typeable.
* PR 3166: Objmode with-block
* PR 3179: Updates for llvmlite 0.25
* PR 3181: Support function extension in alias analysis
* PR 3189: Support literal constants in typing of object methods
* PR 3190: Support passing closures as literal values in typing
* PR 3199: Support inferring stencil index as constant in simple unary expressions
* PR 3202: Threading layer backend refactor/rewrite/reinvention!
* PR 3209: Support for np.tri, np.tril and np.triu
* PR 3211: Handle unpacking in building tuple (BUILD_TUPLE_UNPACK opcode)
* PR 3212: Support for np.vander
* PR 3227: Add NumPy 1.15 support
* PR 3272: Add MemInfo_data to runtime._nrt_python.c_helpers
* PR 3273: Refactor. Removing thread-local-storage based context nesting.
* PR 3278: compiler threadsafety lockdown
* PR 3291: Add CPU count and CFS restrictions info to numba -s.

CUDA Enhancements:

* PR 3152: Use cuda driver api to get best blocksize for best occupancy
* PR 3165: Add FMA intrinsic support
* PR 3172: Use float64 add Atomics, Where Available
* PR 3186: Support Records in CUDA Const Memory
* PR 3191: CUDA: fix log size
* PR 3198: Fix GPU datetime timedelta types usage
* PR 3221: Support datetime/timedelta scalar argument to a CUDA kernel.
* PR 3259: Add DeviceNDArray.view method to reinterpret data as a different type.
* PR 3310: Fix IPC handling of sliced cuda array.

ROCm Enhancements:

* PR 3023: Support for AMDGCN/ROCm.
* PR 3108: Add ROC info to `numba -s` output.
* PR 3176: Move ROC vectorize init to npyufunc
* PR 3177: Add auto_synchronize support to ROC stream
* PR 3178: Update ROC target documentation.
* PR 3294: Add compiler lock to ROC compilation path.
* PR 3280: Add wavebits property to the HSA Agent.
* PR 3281: Fix ds_permute types and add tests

Continuous Integration / Testing:

* PR 3091: Remove old recipes, switch to test config based on env var.
* PR 3094: Add higher ULP tolerance for products in complex space.
* PR 3096: Set exit on error in incremental scripts
* PR 3109: Add skip to test needing jinja2 if no jinja2.
* PR 3125: Skip cudasim only tests
* PR 3126: add slack, drop flowdock
* PR 3147: Improve error message for arg type unsupported during typing.
* PR 3128: Fix recipe/build for jetson tx2/ARM
* PR 3167: In build script activate env before installing.
* PR 3180: Add skip to broken test.
* PR 3216: Fix libcuda.so loading in some container setup
* PR 3224: Switch to new Gitter notification webhook URL and encrypt it
* PR 3235: Add 32bit Travis CI jobs
* PR 3257: This adds scipy/ipython back into windows conda test phase.

Fixes:

* PR 3038: Fix random integer generation to match results from NumPy.
* PR 3045: Fix 3027 - Numba reassigns sys.stdout
* PR 3059: Handler for known LoweringErrors.
* PR 3060: Adjust attribute error for NumPy functions.
* PR 3067: Abort simulator threads on exception in thread block.
* PR 3079: Implement +/-(types.boolean) Fix 2624
* PR 3080: Compute np.var and np.std correctly for complex types.
* PR 3088: Fix 3066 (array.dtype.type in prange)
* PR 3089: Fix invalid ParallelAccelerator hoisting issue.
* PR 3136: Fix 3135 (lowering error)
* PR 3137: Fix for issue3103 (race condition detection)
* PR 3142: Fix Issue 3139 (parfors reuse of reduction variable across prange blocks)
* PR 3148: Remove dead array equal infer code
* PR 3153: Fix canonicalize_array_math typing for calls with kw args
* PR 3156: Fixes issue with missing pygments in testing and adds guards.
* PR 3168: Py37 bytes output fix.
* PR 3171: Fix 3146.  Fix CFUNCTYPE void* return-type handling
* PR 3193: Fix setitem/getitem resolvers
* PR 3222: Fix 3214.  Mishandling of POP_BLOCK in while True loop.
* PR 3230: Fixes liveness analysis issue in looplifting
* PR 3233: Fix return type difference for 32bit ctypes.c_void_p
* PR 3234: Fix types and layout for `np.where`.
* PR 3237: Fix DeprecationWarning about imp module
* PR 3241: Fix 3225.  Normalize 0nd array to scalar in typing of indexing code.
* PR 3256: Fix 3251: Move imports of ABCs to collections.abc for Python >= 3.3
* PR 3292: Fix issue3279.
* PR 3302: Fix error due to mismatching dtype

Documentation Updates:

* PR 3104: Workaround for 3098 (test_optional_unpack Heisenbug)
* PR 3132: Adds an ~5 minute guide to Numba.
* PR 3194: Fix docs RE: np.random generator fork/thread safety
* PR 3242: Page with Numba talks and tutorial links
* PR 3258: Allow users to choose the type of issue they are reporting.
* PR 3260: Fixed broken link
* PR 3266: Fix cuda pointer ownership problem with user/externally allocated pointer
* PR 3269: Tweak typography with CSS
* PR 3270: Update FAQ for functions passed as arguments
* PR 3274: Update installation instructions
* PR 3275: Note pyobject and voidptr are types in docs
* PR 3288: Do not need to call parallel optimizations "experimental" anymore
* PR 3318: Tweak spacing to avoid search box wrapping onto second line

Contributors:

* Anton Malakhov
* Alex Ford
* Anthony Bisulco
* Ehsan Totoni (core dev)
* Leonard Lausen
* Matthew Petroff
* Nick White
* Ray Donnelly
* rjenc29
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Stuart Reynolds
* Todd A. Anderson (core dev)

0.39.0

--------------

Here are the highlights for the Numba 0.39.0 release.

* This is the first version that supports Python 3.7.
* With help from Intel, we have fixed the issues with SVML support (related
issues 2938, 2998, 3006).
* List has gained support for containing reference-counted types like NumPy
arrays and `list`.  Note, list still cannot hold heterogeneous types.
* We have made a significant change to the internal calling-convention,
which should be transparent to most users, to allow for a future feature that
will permitting jumping back into python-mode from a nopython-mode function.
This also fixes a limitation to `print` that disabled its use from nopython
functions that were deep in the call-stack.
* For CUDA GPU support, we added a `__cuda_array_interface__` following the
NumPy array interface specification to allow Numba to consume externally
defined device arrays.  We have opened a corresponding pull request to CuPy to
test out the concept and be able to use a CuPy GPU array.
* The Numba dispatcher `inspect_types()` method now supports the kwarg `pretty`
which if set to `True` will produce ANSI/HTML output, showing the annotated
types, when invoked from ipython/jupyter-notebook respectively.
* The NumPy functions `ndarray.dot`, `np.percentile` and `np.nanpercentile`, and
`np.unique` are now supported.
* Numba now supports the use of a per-project configuration file to permanently
set behaviours typically set via `NUMBA_*` family environment variables.
* Support for the `ppc64le` architecture has been added.

Enhancements:

* PR 2793: Simplify and remove javascript from html_annotate templates.
* PR 2840: Support list of refcounted types
* PR 2902: Support for np.unique
* PR 2926: Enable fence for all architecture and add developer notes
* PR 2928: Making error about untyped list more informative.
* PR 2930: Add configuration file and color schemes.
* PR 2932: Fix encoding to 'UTF-8' in `check_output` decode.
* PR 2938: Python 3.7 compat: _Py_Finalizing becomes _Py_IsFinalizing()
* PR 2939: Comprehensive SVML unit test
* PR 2946: Add support for `ndarray.dot` method and tests.
* PR 2953: percentile and nanpercentile
* PR 2957: Add new 3.7 opcode support.
* PR 2963: Improve alias analysis to be more comprehensive
* PR 2984: Support for namedtuples in array analysis
* PR 2986: Fix environment propagation
* PR 2990: Improve function call matching for intrinsics
* PR 3002: Second pass at error rewrites (interpreter errors).
* PR 3004: Add numpy.empty to the list of pure functions.
* PR 3008: Augment SVML detection with llvmlite SVML patch detection.
* PR 3012: Make use of the common spelling of heterogeneous/homogeneous.
* PR 3032: Fix pycc ctypes test due to mismatch in calling-convention
* PR 3039: Add SVML detection to Numba environment diagnostic tool.
* PR 3041: This adds needs_blas to tests that use BLAS
* PR 3056: Require llvmlite>=0.24.0

CUDA Enhancements:

* PR 2860: __cuda_array_interface__
* PR 2910: More CUDA intrinsics
* PR 2929: Add Flag To Prevent Unneccessary D->H Copies
* PR 3037: Add CUDA IPC support on non-peer-accessible devices

CI Enhancements:

* PR 3021: Update appveyor config.
* PR 3040: Add fault handler to all builds
* PR 3042: Add catchsegv
* PR 3077: Adds optional number of processes for `-m` in testing

Fixes:

* PR 2897: Fix line position of delete statement in numba ir
* PR 2905: Fix for 2862
* PR 3009: Fix optional type returning in recursive call
* PR 3019: workaround and unittest for issue 3016
* PR 3035: [TESTING] Attempt delayed removal of Env
* PR 3048: [WIP] Fix cuda tests failure on buildfarm
* PR 3054: Make test work on 32-bit
* PR 3062: Fix cuda.In freeing devary before the kernel launch
* PR 3073: Workaround 3072
* PR 3076: Avoid ignored exception due to missing globals at interpreter teardown

Documentation Updates:

* PR 2966: Fix syntax in env var docs.
* PR 2967: Fix typo in CUDA kernel layout example.
* PR 2970: Fix docstring copy paste error.

Contributors:

The following people contributed to this release.

* Anton Malakhov
* Ehsan Totoni  (core dev)
* Julia Tatz
* Matthias Bussonnier
* Nick White
* Ray Donnelly
* Siu Kwan Lam  (core dev)
* Stan Seibert  (core dev)
* Stuart Archibald  (core dev)
* Todd A. Anderson  (core dev)
* Rik-de-Kort
* rjenc29

0.38.1

--------------

This is a critical bug fix release addressing:
https://github.com/numba/numba/issues/3006

The bug does not impact users using conda packages from Anaconda or Intel Python
Distribution (but it does impact conda-forge). It does not impact users of pip
using wheels from PyPI.

This only impacts a small number of users where:

* The ICC runtime (specifically libsvml) is present in the user's environment.
* The user is using an llvmlite statically linked against a version of LLVM
that has not been patched with SVML support.
* The platform is 64-bit.

The release fixes a code generation path that could lead to the production of
incorrect results under the above situation.

Fixes:

* PR 3007: Augment SVML detection with llvmlite SVML patch detection.

Contributors:

The following people contributed to this release.

* Stuart Archibald (core dev)

0.38.0

--------------

Following on from the bug fix focus of the last release, this release swings
back towards the addition of new features and usability improvements based on
community feedback. This release is comparatively large! Three key features/
changes to note are:

* Numba (via llvmlite) is now backed by LLVM 6.0, general vectorization is
improved as a result. A significant long standing LLVM bug that was causing
corruption was also found and fixed.
* Further considerable improvements in vectorization are made available as
Numba now supports Intel's short vector math library (SVML).
Try it out with `conda install -c numba icc_rt`.
* CUDA 8.0 is now the minimum supported CUDA version.

Other highlights include:

* Bug fixes to `parallel=True` have enabled more vectorization opportunities
when using the ParallelAccelerator technology.
* Much effort has gone into improving error reporting and the general usability
of Numba. This includes highlighted error messages and performance tips
documentation. Try it out with `conda install colorama`.
* A number of new NumPy functions are supported, `np.convolve`, `np.correlate`
`np.reshape`, `np.transpose`, `np.permutation`, `np.real`, `np.imag`, and
`np.searchsorted` now supports the`side` kwarg. Further, `np.argsort` now
supports the `kind` kwarg with `quicksort` and `mergesort` available.
* The Numba extension API has gained the ability operate more easily with
functions from Cython modules through the use of
`numba.extending.get_cython_function_address` to obtain function addresses
for direct use in `ctypes.CFUNCTYPE`.
* Numba now allows the passing of jitted functions (and containers of jitted
functions) as arguments to other jitted functions.
* The CUDA functionality has gained support for a larger selection of bit
manipulation intrinsics, also SELP, and has had a number of bugs fixed.
* Initial work to support the PPC64LE platform has been added, full support is
however waiting on the LLVM 6.0.1 release as it contains critical patches
not present in 6.0.0.
It is hoped that any remaining issues will be fixed in the next release.
* The capacity for advanced users/compiler engineers to define their own
compilation pipelines.

Enhancements:

* PR 2660: Support bools from cffi in nopython.
* PR 2741: Enhance error message for undefined variables.
* PR 2744: Add diagnostic error message to test suite discovery failure.
* PR 2748: Added Intel SVML optimizations as opt-out choice working by default
* PR 2762: Support transpose with axes arguments.
* PR 2777: Add support for np.correlate and np.convolve
* PR 2779: Implement np.random.permutation
* PR 2801: Passing jitted functions as args
* PR 2802: Support np.real() and np.imag()
* PR 2807: Expose `import_cython_function`
* PR 2821: Add kwarg 'side' to np.searchsorted
* PR 2822: Adds stable argsort
* PR 2832: Fixups for llvmlite 0.23/llvm 6
* PR 2836: Support `index` method on tuples
* PR 2839: Support for np.transpose and np.reshape.
* PR 2843: Custom pipeline
* PR 2847: Replace signed array access indices in unsiged prange loop body
* PR 2859: Add support for improved error reporting.
* PR 2880: This adds a github issue template.
* PR 2881: Build recipe to clone Intel ICC runtime.
* PR 2882: Update TravisCI to test SVML
* PR 2893: Add reference to the data buffer in array.ctypes object
* PR 2895: Move to CUDA 8.0

Fixes:

* PR 2737: Fix 2007 (part 1). Empty array handling in np.linalg.
* PR 2738: Fix install_requires to allow pip getting pre-release version
* PR 2740: Fix 2208. Generate better error message.
* PR 2765: Fix Bit-ness
* PR 2780: PowerPC reference counting memory fences
* PR 2805: Fix six imports.
* PR 2813: Fix 2812: gufunc scalar output bug.
* PR 2814: Fix the build post 2727
* PR 2831: Attempt to fix 2473
* PR 2842: Fix issue with test discovery and broken CUDA drivers.
* PR 2850: Add rtsys init guard and test.
* PR 2852: Skip vectorization test with targets that are not x86
* PR 2856: Prevent printing to stdout in `test_extending.py`
* PR 2864: Correct C code to prevent compiler warnings.
* PR 2889: Attempt to fix 2386.
* PR 2891: Removed test skipping for inspect_cfg
* PR 2898: Add guard to parallel test on unsupported platforms
* PR 2907: Update change log for PPC64LE LLVM dependency.
* PR 2911: Move build requirement to llvmlite>=0.23.0dev0
* PR 2912: Fix random permutation test.
* PR 2914: Fix MD list syntax in issue template.

Documentation Updates:

* PR 2739: Explicitly state default value of error_model in docstring
* PR 2803: DOC: parallel vectorize requires signatures
* PR 2829: Add Python 2.7 EOL plan to docs
* PR 2838: Use automatic numbering syntax in list.
* PR 2877: Add performance tips documentation.
* PR 2883: Fix 2872: update rng doc about thread/fork-safety
* PR 2908: Add missing link and ref to docs.
* PR 2909: Tiny typo correction

ParallelAccelerator enhancements/fixes:

* PR 2727: Changes to enable vectorization in ParallelAccelerator.
* PR 2816: Array analysis for transpose with arbitrary arguments
* PR 2874: Fix dead code eliminator not to remove a call with side-effect
* PR 2886: Fix ParallelAccelerator arrayexpr repr

CUDA enhancements:

* PR 2734: More Constants From cuda.h
* PR 2767: Add len(..) Support to DeviceNDArray
* PR 2778: Add More Device Array API Functions to CUDA Simulator
* PR 2824: Add CUDA Primitives for Population Count
* PR 2835: Emit selp Instructions to Avoid Branching
* PR 2867: Full support for CUDA device attributes

CUDA fixes:
* PR 2768: Don't Compile Code on Every Assignment
* PR 2878: Fixes a Win64 issue with the test in Pr/2865

Contributors:

The following people contributed to this release.

* Abutalib Aghayev
* Alex Olivas
* Anton Malakhov
* Dong-hee Na
* Ehsan Totoni (core dev)
* John Zwinck
* Josh Wilson
* Kelsey Jordahl
* Nick White
* Olexa Bilaniuk
* Rik-de-Kort
* Siu Kwan Lam (core dev)
* Stan Seibert (core dev)
* Stuart Archibald (core dev)
* Thomas Arildsen
* Todd A. Anderson (core dev)

0.37.0

--------------

This release focuses on bug fixing and stability but also adds a few new
features including support for Numpy 1.14. The key change for Numba core was the
long awaited addition of the final tranche of thread safety improvements that
allow Numba to be run concurrently on multiple threads without hitting known
thread safety issues inside LLVM itself. Further, a number of fixes and
enhancements went into the CUDA implementation and ParallelAccelerator gained
some new features and underwent some internal refactoring.

Misc enhancements:

* PR 2627: Remove hacks to make llvmlite threadsafe
* PR 2672: Add ascontiguousarray
* PR 2678: Add Gitter badge
* PR 2691: Fix 2690: add intrinsic to convert array to tuple
* PR 2703: Test runner feature: failed-first and last-failed
* PR 2708: Patch for issue 1907
* PR 2732: Add support for array.fill

Misc Fixes:

* PR 2610: Fix 2606 lowering of optional.setattr
* PR 2650: Remove skip for win32 cosine test
* PR 2668: Fix empty_like from readonly arrays.
* PR 2682: Fixes 2210, remove _DisableJitWrapper
* PR 2684: Fix 2340, generator error yielding bool
* PR 2693: Add travis-ci testing of NumPy 1.14, and also check on Python 2.7
* PR 2694: Avoid type inference failure due to a typing template rejection
* PR 2695: Update llvmlite version dependency.
* PR 2696: Fix tuple indexing codegeneration for empty tuple
* PR 2698: Fix 2697 by deferring deletion in the simplify_CFG loop.
* PR 2701: Small fix to avoid tempfiles being created in the current directory
* PR 2725: Fix 2481, LLVM IR parsing error due to mutated IR
* PR 2726: Fix 2673: incorrect fork error msg.
* PR 2728: Alternative to 2620.  Remove dead code ByteCodeInst.get.
* PR 2730: Add guard for test needing SciPy/BLAS

Documentation updates:

* PR 2670: Update communication channels
* PR 2671: Add docs about diagnosing loop vectorizer
* PR 2683: Add docs on const arg requirements and on const mem alloc
* PR 2722: Add docs on numpy support in cuda
* PR 2724: Update doc: warning about unsupported arguments

ParallelAccelerator enhancements/fixes:

Parallel support for `np.arange` and `np.linspace`, also `np.mean`, `np.std`
and `np.var` are added. This was performed as part of a general refactor and
cleanup of the core ParallelAccelerator code.

* PR 2674: Core pa
* PR 2704: Generate Dels after parfor sequential lowering
* PR 2716: Handle matching directly supported functions

CUDA enhancements:

* PR 2665: CUDA DeviceNDArray: Support numpy tranpose API
* PR 2681: Allow Assigning to DeviceNDArrays
* PR 2702: Make DummyArray do High Dimensional Reshapes
* PR 2714: Use CFFI to Reuse Code

CUDA fixes:

* PR 2667: Fix CUDA DeviceNDArray slicing
* PR 2686: Fix 2663: incorrect offset when indexing cuda array.
* PR 2687: Ensure Constructed Stream Bound
* PR 2706: Workaround for unexpected warp divergence due to exception raising
code
* PR 2707: Fix regression: cuda test submodules not loading properly in
runtests
* PR 2731: Use more challenging values in slice tests.
* PR 2720: A quick testsuite fix to not run the new cuda testcase in the
multiprocess pool

Contributors:

The following people contributed to this release.

* Coutinho Menezes Nilo
* Daniel
* Ehsan Totoni
* Nick White
* Paul H. Liu
* Siu Kwan Lam
* Stan Seibert
* Stuart Archibald
* Todd A. Anderson

0.36.2

--------------

This is a bugfix release that provides minor changes to address:

* PR 2645: Avoid CPython bug with ``exec`` in older 2.7.x.
* PR 2652: Add support for CUDA 9.

0.36.1

--------------

This release continues to add new features to the work undertaken in partnership
with Intel on ParallelAccelerator technology. Other changes of note include the
compilation chain being updated to use LLVM 5.0 and the production of conda
packages using conda-build 3 and the new compilers that ship with it.

NOTE: A version 0.36.0 was tagged for internal use but not released.

ParallelAccelerator:

NOTE: The ParallelAccelerator technology is under active development and should
be considered experimental.

New features relating to ParallelAccelerator, from work undertaken with Intel,
include the addition of the `stencil` decorator for ease of implementation of
stencil-like computations, support for general reductions, and slice and
range fusion for parallel slice/bit-array assignments. Documentation on both the
use and implementation of the above has been added. Further, a new debug
environment variable `NUMBA_DEBUG_ARRAY_OPT_STATS` is made available to give
information about which operators/calls are converted to parallel for-loops.

ParallelAccelerator features:

* PR 2457: Stencil Computations in ParallelAccelerator
* PR 2548: Slice and range fusion, parallelizing bitarray and slice assignment
* PR 2516: Support general reductions in ParallelAccelerator

ParallelAccelerator fixes:

* PR 2540: Fix bug 2537
* PR 2566: Fix issue 2564.
* PR 2599: Fix nested multi-dimensional parfor type inference issue
* PR 2604: Fixes for stencil tests and cmath sin().
* PR 2605: Fixes issue 2603.

Additional features of note:

This release of Numba (and llvmlite) is updated to use LLVM version 5.0 as the
compiler back end, the main change to Numba to support this was the addition of
a custom symbol tracker to avoid the calls to LLVM's `ExecutionEngine` that was
crashing when asking for non-existent symbol addresses. Further, the conda
packages for this release of Numba are built using conda build version 3 and the
new compilers/recipe grammar that are present in that release.

* PR 2568: Update for LLVM 5
* PR 2607: Fixes abort when getting address to "nrt_unresolved_abort"
* PR 2615: Working towards conda build 3

Thanks to community feedback and bug reports, the following fixes were also
made.

Misc fixes/enhancements:

* PR 2534: Add tuple support to np.take.
* PR 2551: Rebranding fix
* PR 2552: relative doc links
* PR 2570: Fix issue 2561, handle missing successor on loop exit
* PR 2588: Fix 2555. Disable libpython.so linking on linux
* PR 2601: Update llvmlite version dependency.
* PR 2608: Fix potential cache file collision
* PR 2612: Fix NRT test failure due to increased overhead when running in coverage
* PR 2619: Fix dubious pthread_cond_signal not in lock
* PR 2622: Fix `np.nanmedian` for all NaN case.
* PR 2633: Fix markdown in CONTRIBUTING.md
* PR 2635: Make the dependency on compilers for AOT optional.

CUDA support fixes:

* PR 2523: Fix invalid cuda context in memory transfer calls in another thread
* PR 2575: Use CPU to initialize xoroshiro states for GPU RNG. Fixes 2573
* PR 2581: Fix cuda gufunc mishandling of scalar arg as array and out argument

0.35.0

--------------

This release includes some exciting new features as part of the work
performed in partnership with Intel on ParallelAccelerator technology.
There are also some additions made to Numpy support and small but
significant fixes made as a result of considerable effort spent chasing bugs
and implementing stability improvements.


ParallelAccelerator:

NOTE: The ParallelAccelerator technology is under active development and should
be considered experimental.

New features relating to ParallelAccelerator, from work undertaken with Intel,
include support for a larger range of `np.random` functions in `parallel`
mode, printing Numpy arrays in no Python mode, the capacity to initialize Numpy
arrays directly from list comprehensions, and the axis argument to `.sum()`.
Documentation on the ParallelAccelerator technology implementation has also
been added. Further, a large amount of work on equivalence relations was
undertaken to enable runtime checks of broadcasting behaviours in parallel mode.

ParallelAccelerator features:

* PR 2400: Array comprehension
* PR 2405: Support printing Numpy arrays
* PR 2438: from Support more np.random functions in ParallelAccelerator
* PR 2482: Support for sum with axis in nopython mode.
* PR 2487: Adding developer documentation for ParallelAccelerator technology.
* PR 2492: Core PA refactor adds assertions for broadcast semantics

ParallelAccelerator fixes:

* PR 2478: Rename cfg before parfor translation (2477)
* PR 2479: Fix broken array comprehension tests on unsupported platforms
* PR 2484: Fix array comprehension test on win64
* PR 2506: Fix for 32-bit machines.


Additional features of note:

Support for `np.take`, `np.finfo`, `np.iinfo` and `np.MachAr` in no Python
mode is added. Further, three new environment variables are added, two for
overriding CPU target/features and another to warn if `parallel=True` was set
no such transform was possible.

* PR 2490: Implement np.take and ndarray.take
* PR 2493: Display a warning if parallel=True is set but not possible.
* PR 2513: Add np.MachAr, np.finfo, np.iinfo
* PR 2515: Allow environ overriding of cpu target and cpu features.


Due to expansion of the test farm and a focus on fixing bugs, the following
fixes were also made.

Misc fixes/enhancements:

* PR 2455: add contextual information to runtime errors
* PR 2470: Fixes 2458, poor performance in np.median
* PR 2471: Ensure LLVM threadsafety in {g,}ufunc building.
* PR 2494: Update doc theme
* PR 2503: Remove hacky code added in 2482 and feature enhancement
* PR 2505: Serialise env mutation tests during multithreaded testing.
* PR 2520: Fix failing cpu-target override tests

CUDA support fixes:

* PR 2504: Enable CUDA toolkit version testing
* PR 2509: Disable tests generating code unavailable in lower CC versions.
* PR 2511: Fix Windows 64 bit CUDA tests.

0.34.0

--------------

This release adds a significant set of new features arising from combined work
with Intel on ParallelAccelerator technology. It also adds list comprehension
and closure support, support for Numpy 1.13 and a new, faster, CUDA reduction
algorithm. For Linux users this release is the first to be built on Centos 6,
which will be the new base platform for future releases. Finally a number of
thread-safety, type inference and other smaller enhancements and bugs have been
fixed.


ParallelAccelerator features:

NOTE: The ParallelAccelerator technology is under active development and should
be considered experimental.

The ParallelAccelerator technology is accessed via a new "nopython" mode option
"parallel". The ParallelAccelerator technology attempts to identify operations
which have parallel semantics (for instance adding a scalar to a vector), fuse
together adjacent such operations, and then parallelize their execution across
a number of CPU cores. This is essentially auto-parallelization.

In addition to the auto-parallelization feature, explicit loop based
parallelism is made available through the use of `prange` in place of `range`
as a loop iterator.

More information and examples on both auto-parallelization and `prange` are
available in the documentation and examples directory respectively.

As part of the necessary work for ParallelAccelerator, support for closures
and list comprehensions is added:

* PR 2318: Transfer ParallelAccelerator technology to Numba
* PR 2379: ParallelAccelerator Core Improvements
* PR 2367: Add support for len(range(...))
* PR 2369: List comprehension
* PR 2391: Explicit Parallel Loop Support (prange)

The ParallelAccelerator features are available on all supported platforms and
Python versions with the exceptions of (with view of supporting in a future
release):

* The combination of Windows operating systems with Python 2.7.
* Systems running 32 bit Python.


CUDA support enhancements:

* PR 2377: New GPU reduction algorithm


CUDA support fixes:

* PR 2397: Fix 2393, always set alignment of cuda static memory regions


Misc Fixes:

* PR 2373, Issue 2372: 32-bit compatibility fix for parfor related code
* PR 2376: Fix 2375 missing stdint.h for py2.7 vc9
* PR 2378: Fix deadlock in parallel gufunc when kernel acquires the GIL.
* PR 2382: Forbid unsafe casting in bitwise operation
* PR 2385: docs: fix Sphinx errors
* PR 2396: Use 64-bit RHS operand for shift
* PR 2404: Fix threadsafety logic issue in ufunc compilation cache.
* PR 2424: Ensure consistent iteration order of blocks for type inference.
* PR 2425: Guard code to prevent the use of 'parallel' on win32 + py27
* PR 2426: Basic test for Enum member type recovery.
* PR 2433: Fix up the parfors tests with respect to windows py2.7
* PR 2442: Skip tests that need BLAS/LAPACK if scipy is not available.
* PR 2444: Add test for invalid array setitem
* PR 2449: Make the runtime initialiser threadsafe
* PR 2452: Skip CFG test on 64bit windows


Misc Enhancements:

* PR 2366: Improvements to IR utils
* PR 2388: Update README.rst to indicate the proper version of LLVM
* PR 2394: Upgrade to llvmlite 0.19.*
* PR 2395: Update llvmlite version to 0.19
* PR 2406: Expose environment object to ufuncs
* PR 2407: Expose environment object to target-context inside lowerer
* PR 2413: Add flags to pass through to conda build for buildbot
* PR 2414: Add cross compile flags to local recipe
* PR 2415: A few cleanups for rewrites
* PR 2418: Add getitem support for Enum classes
* PR 2419: Add support for returning enums in vectorize
* PR 2421: Add copyright notice for Intel contributed files.
* PR 2422: Patch code base to work with np 1.13 release
* PR 2448: Adds in warning message when using 'parallel' if cache=True
* PR 2450: Add test for keyword arg on .sum-like and .cumsum-like array
methods

0.33.0

--------------

This release resolved several performance issues caused by atomic
reference counting operations inside loop bodies.  New optimization
passes have been added to reduce the impact of these operations.  We
observe speed improvements between 2x-10x in affected programs due to
the removal of unnecessary reference counting operations.

There are also several enhancements to the CUDA GPU support:

* A GPU random number generator based on `xoroshiro128+ algorithm <http://xoroshiro.di.unimi.it/>`_ is added.
See details and examples in :ref:`documentation <cuda-random>`.
* ``cuda.jit`` CUDA kernels can now call ``jit`` and ``njit``
CPU functions and they will automatically be compiled as CUDA device
functions.
* CUDA IPC memory API is exposed for sharing memory between proceses.
See usage details in :ref:`documentation <cuda-ipc-memory>`.

Reference counting enhancements:

* PR 2346, Issue 2345, 2248: Add extra refcount pruning after inlining
* PR 2349: Fix refct pruning not removing refct op with tail call.
* PR 2352, Issue 2350: Add refcount pruning pass for function that does not need refcount

CUDA support enhancements:

* PR 2023: Supports CUDA IPC for device array
* PR 2343, Issue 2335: Allow CPU jit decorated function to be used as cuda device function
* PR 2347: Add random number generator support for CUDA device code
* PR 2361: Update autotune table for CC: 5.3, 6.0, 6.1, 6.2

Misc fixes:

* PR 2362: Avoid test failure due to typing to int32 on 32-bit platforms
* PR 2359: Fixed nogil example that threw a TypeError when executed.
* PR 2357, Issue 2356: Fix fragile test that depends on how the script is executed.
* PR 2355: Fix cpu dispatcher referenced as attribute of another module
* PR 2354: Fixes an issue with caching when function needs NRT and refcount pruning
* PR 2342, Issue 2339: Add warnings to inspection when it is used on unserialized cached code
* PR 2329, Issue 2250: Better handling of missing op codes

Misc enhancements:

* PR 2360: Adds missing values in error mesasge interp.
* PR 2353: Handle when get_host_cpu_features() raises RuntimeError
* PR 2351: Enable SVML for erf/erfc/gamma/lgamma/log2
* PR 2344: Expose error_model setting in jit decorator
* PR 2337: Align blocking terminate support for fork() with new TBB version
* PR 2336: Bump llvmlite version to 0.18
* PR 2330: Core changes in PR 2318

0.32.0

--------------

In this release, we are upgrading to LLVM 4.0.  A lot of work has been done
to fix many race-condition issues inside LLVM when the compiler is
used concurrently, which is likely when Numba is used with Dask.

Improvements:

* PR 2322: Suppress test error due to unknown but consistent error with tgamma
* PR 2320: Update llvmlite dependency to 0.17
* PR 2308: Add details to error message on why cuda support is disabled.
* PR 2302: Add os x to travis
* PR 2294: Disable remove_module on MCJIT due to memory leak inside LLVM
* PR 2291: Split parallel tests and recycle workers to tame memory usage
* PR 2253: Remove the pointer-stuffing hack for storing meminfos in lists

Fixes:

* PR 2331: Fix a bug in the GPU array indexing
* PR 2326: Fix 2321 docs referring to non-existing function.
* PR 2316: Fixing more race-condition problems
* PR 2315: Fix 2314.  Relax strict type check to allow optional type.
* PR 2310: Fix race condition due to concurrent compilation and cache loading
* PR 2304: Fix intrinsic 1st arg not a typing.Context as stated by the docs.
* PR 2287: Fix int64 atomic min-max
* PR 2286: Fix 2285 `overload_method` not linking dependent libs
* PR 2303: Missing import statements to interval-example.rst

0.31.0

--------------

In this release, we added preliminary support for debugging with GDB
version >= 7.0. The feature is enabled by setting the ``debug=True`` compiler
option, which causes GDB compatible debug info to be generated.
The CUDA backend also gained limited debugging support so that source locations
are showed in memory-checking and profiling tools.
For details, see :ref:`numba-troubleshooting`.

Also, we added the ``fastmath=True`` compiler option to enable unsafe
floating-point transformations, which allows LLVM to auto-vectorize more code.

Other important changes include upgrading to LLVM 3.9.1 and adding support for
Numpy 1.12.

Improvements:

* PR 2281: Update for numpy1.12
* PR 2278: Add CUDA atomic.{max, min, compare_and_swap}
* PR 2277: Add about section to conda recipies to identify license and other
metadata in Anaconda Cloud
* PR 2271: Adopt itanium C++-style mangling for CPU and CUDA targets
* PR 2267: Add fastmath flags
* PR 2261: Support dtype.type
* PR 2249: Changes for llvm3.9
* PR 2234: Bump llvmlite requirement to 0.16 and add install_name_tool_fixer to
mviewbuf for OS X
* PR 2230: Add python3.6 to TravisCi
* PR 2227: Enable caching for gufunc wrapper
* PR 2170: Add debugging support
* PR 2037: inspect_cfg() for easier visualization of the function operation

Fixes:

* PR 2274: Fix nvvm ir patch in mishandling "load"
* PR 2272: Fix breakage to cuda7.5
* PR 2269: Fix caching of copy_strides kernel in cuda.reduce
* PR 2265: Fix 2263: error when linking two modules with dynamic globals
* PR 2252: Fix path separator in test
* PR 2246: Fix overuse of memory in some system with fork
* PR 2241: Fix 2240: __module__ in dynamically created function not a str
* PR 2239: Fix fingerprint computation failure preventing fallback

0.30.1

--------------

This is a bug-fix release to enable Python 3.6 support.  In addition,
there is now early Intel TBB support for parallel ufuncs when building from
source with TBBROOT defined.  The TBB feature is not enabled in our official
builds.

Fixes:

* PR 2232: Fix name clashes with _Py_hashtable_xxx in Python 3.6.

Improvements:

* PR 2217: Add Intel TBB threadpool implementation for parallel ufunc.

0.30.0

----------------------------

This release adds support for half-precision float and schedules the
deprecation of memset/memcpy accepting 5 arguments (cf. LLVM change).

* PR 518: Fix use of -fPIC flag in wheels
* PR 513: Remove restriction on sphinx version from Anaconda distro
* PR 512: fix for block labels which contain "interesting" characters
* PR 511: Deprecate the use of memset/memcpy with alias
* PR 510: Add fp16 Intrinsics
* PR 509: Add Half-Precision Type
* PR 502: Add -fPIC flag for manylinux1 wheel building
* PR 491: Fix incorrect hierarchy in the documentation for ir.Constant.
* PR 474: Update docs
* PR 470: Fix leak on string returning APIs.

0.29.0

----------------------

This release upgrades to LLVM 8.0 for all supported platforms except PPC64LE.
Due to numerous problems with LLVM 8.0 running on PPC64LE,
we have decided to use LLVM 7.1, which is more stable on PPC64LE.
In addition, non-host LLVM targets, AMDGPU, NVPTX, and WebAssembly, are enabled
and they are available in our `llvmlite` builds.

* PR 484: Revert "LLVM 7 changed memset intrinsic signature, adjust it"
* PR 483: Depend on enum34 using PEP 508 environment markers
* PR 478: Upgrade to llvm8
* PR 469: Support loading from current directory and egg files
* PR 467: Add missing fastmath flags from LLVM 7
* PR 460: LLVM 7 changed memset intrinsic signature, adjust it

0.28.1

--------------

This is a bug-fix release to resolve packaging issues with setuptools
dependency.

0.28.0

----------------------

This release adds a number of community contributed features, including
support for vector types, as well as atomic loads and stores.

* PR 322: Adding Vector Type
* PR 389: Add symbols from static object files
* PR 417: Add support for atomic loads/stores
* PR 422: Normalize replace_* behaviour and add docs
* PR 426: Fix pickling of IR functions and add tests
* PR 444: Setup manylinux1 buildscripts and CI
* PR 446: Document need for -p1 argument to patch command
* PR 448: Fix "SyntaxWarning: invalid escape sequence \d"
* PR 449: Consolidate the two vector type PRs
* PR 452: Some adjustments to pr426
* PR 454: Truncate long label names when adding label suffix.
* PR 458: Add changelog info about v0.27.1

0.27.1

---------------------

Bugfix release for invalid wheel hash for OSX packages.
No change to source code.

0.27.0

----------------------

This release updates llvmlite to LLVM 7.  Note that LLVM 7.0.0 contains
a critical bug that is resolved with a patch included in the `llvmdev conda
package recipe`_.  The final release of LLVM 7.0.1 may also resolve the issue.

* PR 434: Add another thread for RPi builds.
* PR 430: llvm lld integration, merge 428
* PR 428: Build LLD as part of the llvmdev package
* PR 413: Set up CI with Azure Pipelines
* PR 412: LLVM 7 support

.. _llvmdev conda package recipe: https://github.com/numba/llvmlite/tree/69aed71a829e6c552cca24a28c42abdf1efd2363/conda-recipes/llvmdev

0.26.0

----------------------

The primary new features in this release is support for generation of Intel
JIT events, which makes profiling of JIT compiled code in Intel VTune
possible.  This release also contains some minor build improvements for ARMv7,
and some small fixes.

LLVM 7 support was originally slated for this release, but had to be delayed
after some issues arose in testing.  LLVM 6 is still required for llvmlite.

* PR 409: Use native cmake on armv7l
* PR 407: Throttle thread count for llvm build on armv7l.
* PR 403: Add shutdown detection to ObjectRef __del__ method.
* PR 400: conda recipe: add make as build dep
* PR 399: Add get_element_offset to TargetData
* PR 398: Fix gep method call on Constant objects
* PR 395: Fix typo in irbuilder documentation
* PR 394: Enable IntelJIT events for LLVM for VTune support

0.25.0

----------------------

This release adds support for the FMA instruction, and has some documentation
and build improvements.  Starting with this release, we are including
ARMv8 (AArch64) testig in our CI process.

* PR 391: Fix broken win32 py2.7 build.
* PR 387: protect against empty features in list
* PR 384: Read CMAKE_GENERATOR which conda-build sets
* PR 382: rewrite of install instructions, calling out LLVM build challenges
* PR 380: Add FMA intrinsic support
* PR 379: ARM aarch64 test on jetson tx2
* PR 378: add slack, drop flowdock

0.24.0

---------------------

This release adds support for Python 3.7 and fixes some build issues. It also
contains an updated SVML patch for the llvmdev package that works around some
vectorization issues. It also adds a selective LLVM 6.0.1 llvmdev build for the
`ppc64le` architecture.

* PR 374: Fix up broken patch selector
* PR 373: Add long description from readme
* PR 371: LLVM 6.0.1 build based on RC and fixes for PPC64LE
* PR 369: Recipe fixes for Conda Build 3
* PR 363: Workaround for incorrect vectorization factor computed for SVML
functions
* PR 356: fix build on OpenBSD.
* PR 351: Python 3.7 compat: Properly escape repl in re.sub

0.23.2

---------------------

This is a bug fix release to assist in addressing a critical Numba issue that
can affect users who download llvmlite packages from sources other than PyPI
(pip), Anaconda, or Intel Python: https://github.com/numba/numba/issues/3006

Support for SVML is now detected at compile time and baked into a function that
is exposed by llvmlite. This function can be queried at runtime to find out if
SVML is supported by the LLVM that llvmlite was compiled against, code
generation paths can then be adjusted accordingly.

The following PRs are closed in this release:

* PR 361: Add SVML detection and a function to declare support.

0.23.1

----------------------

This is a minor patch release that includes no code changes. It is issued to
fix a couple of problems with the build recipes for llvmdev (on which llvmlite
relies).

The following PRs are closed in this release:

* PR 353: PR Fix llvmdev build recipe.
* PR 348: llvmdev: enhancements to conda recipe

0.23.0

----------------------

In this release, we upgrade to LLVM 6. Two LLVM patches are added:

1. A patch to fix LLVM bug (https://bugs.llvm.org/show_bug.cgi?id=37019) that
causes undefined behavior during CFG printing.
2. A patch to enable Intel SVML auto-vectorization of transcendentals.

The following PRs are closed in this release:

* PR 343: Fix undefined behavior bug due to Twine usage in LLVM
* PR 340: This moves llvmlite to use LLVM 6.0.0 as its backend.
* PR 339: Add cttz & ctlz
* PR 338: Add 3 Bit Manipulation Intrinsics
* PR 330: Add support for LLVM fence instruction
* PR 326: Enable Intel SVML-enabled auto-vectorization for all the
transcendentals

0.22.1

--------------

This is a bug-fix release to resolve some packaging issues and other
problems found in the 0.22.0 release.

Fixes:

* PR 1515: Include MANIFEST.in in MANIFEST.in so that sdist still works from
source tar files.
* PR 1518: Fix reference counting bug caused by hidden alias
* PR 1519: Fix erroneous assert when passing nopython=True to guvectorize.
* PR 1521: Fix cuda.test()

0.22.0

----------------------

In this release, we have changed the locking strategy that protects LLVM from
race conditions.  Before, the llvmlite user (like Numba) was responsible for
this locking.  Now, llvmlite imposes a global thread lock on all calls into
the LLVM API.  This should be significantly less error prone.  Future llvmlite
releases may manually exempt some functions from locking once they are
determined to be thread-safe.

The following PRs are closed in this release:

* PR318: Ensuring threadsafety in concurrent usage of LLVM C-API
* PR221: Add all function/return value attributes from LLVM 3.9
* PR304: Expose support for static constructors/destructors

0.21.0

---------------------

In this release, we upgrade to LLVM 5.  Our build scripts now use
conda-build 3.  For our prebuilt binaries, GCC 7 toolchain is used
on unix-like systems and the OSX minimum deployment target is 10.9.

The following PRs are closed in this release:

* PR 315: Updates for conda build 3.
* PR 307: Fixes for LLVM5.
* PR 306: Working towards LLVM 5.0 support.

0.20.0

---------------------

Beginning with this minor release, we support wheels for Linux, OSX and Windows.
Pull requests related to enabling wheels are 294, 295, 296 and 297.
There are also fixes to the documentation (283 and 289).

0.19.2

--------------

This release fixes the source distribution on pypi.  The only change is in the
setup.py file.  We do not plan to provide a conda package as this release is
essentially the same as 0.19.1 for conda users.

0.19.1

--------------

* Issue 1196:

* fix double-free segfault due to redundant variable deletion in the
Numba IR (1195)
* fix use-after-delete in array expression rewrite pass

0.19.0

---------------------

This is a minor release with the following fixes.

* PR 281, Issue 280: Fix GEP addrspace issue
* PR 279: Fix 274 addrspace in gep
* PR 278: add Readthedocs badge
* PR 275: Add variables to pass through when doing conda-build
* PR 273: Fix the behavior of module.get_global
* PR 272: cmpop contains comparison type, not lhs
* PR 268, Fix 267: Support packed struct

The following are CI build related changes:

* PR 277: Add pass through gcc flags for llvmdev
* PR 276: Remove jenkins build scripts

0.18.2

--------------

Bug fixes:

* Issue 1073: Fixes missing template file for HTML annotation
* Issue 1074: Fixes CUDA support on Windows machine due to NVVM API mismatch

0.18.1

--------------

Version 0.18.0 is not officially released.

This version removes the old deprecated and undocumented ``argtypes`` and
``restype`` arguments to the ``jit`` decorator.  Function signatures
should always be passed as the first argument to ``jit``.

Features:

* Issue 960: Add inspect_llvm() and inspect_asm() methods to JIT-compiled
functions: they output the LLVM IR and the native assembler source of the
compiled function, respectively.
* Issue 990: Allow passing tuples as arguments to JIT-compiled functions
in ``nopython`` mode.
* Issue 774: Support two-argument round() in ``nopython`` mode.
* Issue 987: Support missing functions from the math module in nopython
mode: frexp(), ldexp(), gamma(), lgamma(), erf(), erfc().
* Issue 995: Improve code generation for round() on Python 3.
* Issue 981: Support functions from the random and numpy.random modules
in ``nopython`` mode.
* Issue 979: Add cuda.atomic.max().
* Issue 1006: Improve exception raising and reporting.  It is now allowed
to raise an exception with an error message in ``nopython`` mode.
* Issue 821: Allow ctypes- and cffi-defined functions as arguments to
``nopython`` functions.
* Issue 901: Allow multiple explicit signatures with ``jit``.  The
signatures must be passed in a list, as with ``vectorize``.
* Issue 884: Better error message when a JIT-compiled function is called
with the wrong types.
* Issue 1010: Simpler and faster CUDA argument marshalling thanks to a
refactoring of the data model.
* Issue 1018: Support arrays of scalars inside Numpy structured types.
* Issue 808: Reduce Numba import time by half.
* Issue 1021: Support the buffer protocol in ``nopython`` mode.
Buffer-providing objects, such as ``bytearray``, ``array.array`` or
``memoryview`` support array-like operations such as indexing and iterating.
Furthermore, some standard attributes on the ``memoryview`` object are
supported.
* Issue 1030: Support nested arrays in Numpy structured arrays.
* Issue 1033: Implement the inspect_types(), inspect_llvm() and inspect_asm()
methods for CUDA kernels.
* Issue 1029: Support Numpy structured arrays with CUDA as well.
* Issue 1034: Support for generators in nopython and object mode.
* Issue 1044: Support default argument values when calling Numba-compiled
functions.
* Issue 1048: Allow calling Numpy scalar constructors from CUDA functions.
* Issue 1047: Allow indexing a multi-dimensional array with a single integer,
to take a view.
* Issue 1050: Support len() on tuples.
* Issue 1011: Revive HTML annotation.

Fixes:

* Issue 977: Assignment optimization was too aggressive.
* Issue 561: One-argument round() now returns an int on Python 3.
* Issue 1001: Fix an unlikely bug where two closures with the same name
and id() would compile to the same LLVM function name, despite different
closure values.
* Issue 1006: Fix reference leak when a JIT-compiled function is disposed of.
* Issue 1017: Update instructions for CUDA in the README.
* Issue 1008: Generate shorter LLVM type names to avoid segfaults with CUDA.
* Issue 1005: Properly clean up references when raising an exception from
object mode.
* Issue 1041: Fix incompatibility between Numba and the third-party
library "future".
* Issue 1053: Fix the size attribute of CUDA shared arrays.

0.18.0

---------------------

This is a minor release that fixes several issues (263, 262, 258, 237) with
the wheel build.  In addition, we have minor fixes for running on PPC64LE
platforms (261).  And, we added CI testing against PyPy (253).

0.17.1

----------------------

This is a bugfix release that addresses issue 258 that our LLVM
binding shared library is missing from the wheel builds.

0.17.0

---------------------

In this release, we are upgrading to LLVM 4.0.  We are also starting to
provide wheel packages for 64-bit Linux platforms (manylinux).

Fixes:

* Issue 249, PR 250: Disable static linking of libstdc++ by default.

Enhancements:

* PR 246: Add requirements.txt for pip dependency resolving
* PR 238: LLVM 4.0
* PR 222: Enable wheel builds

0.16.0

----------------------

API changes:

* Switched from LLVM 3.8 to 3.9
* ``TargetData.add_pass`` is removed in LLVM 3.9.

Enhancements:

* PR 239: Enable fastmath flags
* PR 233: Updates for llvm3.9.1
* PR 199: Update for changes in LLVM 3.9

Fixes:

* PR 236: Fix metadata with long value
* PR 231: Fix setup.py for Python2.7 so that pip auto installs dependencies
* PR 226: Fix get_host_cpu_features() so that it fails properly

0.15.1

--------------

(This was a bug-fix release that superceded version 0.15 before it was
announced.)

Fixes:

* Workaround for missing __ftol2 on Windows XP.
* Do not lift loops for compilation that contain break statements.
* Fix a bug in loop-lifting when multiple values need to be returned to
the enclosing scope.
* Handle the loop-lifting case where an accumulator needs to be updated when
the loop count is zero.

0.15

------------

Features:

* Support for the Python ``cmath`` module.  (NumPy complex functions were
already supported.)
* Support for ``.real``, ``.imag``, and `.conjugate()`` on non-complex
numbers.
* Add support for ``math.isfinite()`` and ``math.copysign()``.
* Compatibility mode: If enabled (off by default), a failure to compile in
object mode will fall back to using the pure Python implementation of the
function.
* *Experimental* support for serializing JIT functions with cloudpickle.
* Loop-jitting in object mode now works with loops that modify scalars that
are accessed after the loop, such as accumulators.
* ``vectorize`` functions can be compiled in object mode.
* Numba can now be built using the `Visual C++ Compiler for Python 2.7 <http://aka.ms/vcpython27>`_
on Windows platforms.
* CUDA JIT functions can be returned by factory functions with variables in
the closure frozen as constants.
* Support for "optional" types in nopython mode, which allow ``None`` to be a
valid value.

Fixes:

* If nopython mode compilation fails for any reason, automatically fall back
to object mode (unless nopython=True is passed to jit) rather than raise
an exeception.
* Allow function objects to be returned from a function compiled in object
mode.
* Fix a linking problem that caused slower platform math functions (such as
``exp()``) to be used on Windows, leading to performance regressions against
NumPy.
* ``min()`` and ``max()`` no longer accept scalars arguments in nopython mode.
* Fix handling of ambigous type promotion among several compiled versions of a
JIT function.  The dispatcher will now compile a new version to resolve the
problem.  (issue 776)
* Fix float32 to uint64 casting bug on 32-bit Linux.
* Fix type inference to allow forced casting of return types.
* Allow the shape of a 1D ``cuda.shared.array`` and ``cuda.local.array`` to be
a one-element tuple.
* More correct handling of signed zeros.
* Add custom implementation of ``atan2()`` on Windows to handle special cases
properly.
* Eliminated race condition in the handling of the pagelocked staging area
used when transferring CUDA arrays.
* Fix non-deterministic type unification leading to varying performance.
(issue 797)

0.15.0

----------------------

Enhancements:

* PR 213: Add partial LLVM bindings for ObjectFile.
* PR 215: Add inline assembly helpers in the builder.
* PR 216: Allow specifying alignment in alloca instructions.
* PR 219: Remove unnecessary verify in module linkage.

Fixes:

* PR 209, Issue 208: Fix overly restrictive test for library filenames.

0.14

------------

Features:

* Support for nearly all the Numpy math functions (including comparison,
logical, bitwise and some previously missing float functions) in nopython mode.
* The Numpy datetime64 and timedelta64 dtypes are supported in nopython mode
with Numpy 1.7 and later.
* Support for Numpy math functions on complex numbers in nopython mode.
* ndarray.sum() is supported in nopython mode.
* Better error messages when unsupported types are used in Numpy math functions.
* Set NUMBA_WARNINGS=1 in the environment to see which functions are compiled
in object mode vs. nopython mode.
* Add support for the two-argument pow() builtin function in nopython mode.
* New developer documentation describing how Numba works, and how to
add new types.
* Support for Numpy record arrays on the GPU. (Note: Improper alignment of dtype
fields will cause an exception to be raised.)
* Slices on GPU device arrays.
* GPU objects can be used as Python context managers to select the active
device in a block.
* GPU device arrays can be bound to a CUDA stream.  All subsequent operations
(such as memory copies) will be queued on that stream instead of the default.
This can prevent unnecessary synchronization with other streams.

Fixes:

* Generation of AVX instructions has been disabled to avoid performance bugs
when calling external math functions that may use SSE instructions,
especially on OS X.
* JIT functions can be removed by the garbage collector when they are no
longer accessible.
* Various other reference counting fixes to prevent memory leaks.
* Fixed handling of exception when input argument is out of range.
* Prevent autojit functions from making unsafe numeric conversions when
called with different numeric types.
* Fix a compilation error when an unhashable global value is accessed.
* Gracefully handle failure to enable faulthandler in the IPython Notebook.
* Fix a bug that caused loop lifting to fail if the loop was inside an
``else`` block.
* Fixed a problem with selecting CUDA devices in multithreaded programs on
Linux.
* The ``pow()`` function (and ``**`` operation) applied to two integers now
returns an integer rather than a float.
* Numpy arrays using the object dtype no longer cause an exception in the
autojit.
* Attempts to write to a global array will cause compilation to fall back
to object mode, rather than attempt and fail at nopython mode.
* ``range()`` works with all negative arguments (ex: ``range(-10, -12, -1)``)

0.14.0

----------------------

Enhancements:

* PR 104: Add binding to get and view function control-flow graph.
* PR 210: Improve llvmdev recipe.
* PR 212: Add initializer for the native assembly parser.

0.13.4

--------------

Features:

* Setting and deleting attributes in object mode
* Added documentation of supported and currently unsupported numpy ufuncs
* Assignment to 1-D numpy array slices
* Closure variables and functions can be used in object mode
* All numeric global values in modules can be used as constants in JIT
compiled code
* Support for the start argument in enumerate()
* Inplace arithmetic operations (+=, -=, etc.)
* Direct iteration over a 1D numpy array (e.g. "for x in array: ...")
in nopython mode

Fixes:

* Support for NVIDIA compute capability 5.0 devices (such as the GTX 750)
* Vectorize no longer crashes/gives an error when bool\_ is used as return type
* Return the correct dictionary when globals() is used in JIT functions
* Fix crash bug when creating dictionary literals in object
* Report more informative error message on import if llvmpy is too old
* Temporarily disable pycc --header, which generates incorrect function
signatures.

0.13.3

--------------

Features:

* Support for enumerate() and zip() in nopython mode
* Increased LLVM optimization of JIT functions to -O1, enabling automatic
vectorization of compiled code in some cases
* Iteration over tuples and unpacking of tuples in nopython mode
* Support for dict and set (Python >= 2.7) literals in object mode

Fixes:

* JIT functions have the same __name__ and __doc__ as the original function.
* Numerous improvements to better match the data types and behavior of Python
math functions in JIT compiled code on different platforms.
* Importing Numba will no longer throw an exception if the CUDA driver is
present, but cannot be initialized.
* guvectorize now properly supports functions with scalar arguments.
* CUDA driver is lazily initialized

0.13.2

--------------

Features:

* vectorize ufunc now can generate SIMD fast path for unit strided array
* Added cuda.gridsize
* Added preliminary exception handling (raise exception class)

Fixes:

* UNARY_POSITIVE
* Handling of closures and dynamically generated functions
* Global None value

0.13.1

--------------

Features:

* Initial support for CUDA array slicing

Fixes:

* Indirectly fixes numbapro when the system has a incompatible CUDA driver
* Fix numba.cuda.detect
* Export numba.intp and numba.intc

0.13

------------

Features:

* Opensourcing NumbaPro CUDA python support in `numba.cuda`
* Add support for ufunc array broadcasting
* Add support for mixed input types for ufuncs
* Add support for returning tuple from jitted function

Fixes:

* Fix store slice bytecode handling for Python2
* Fix inplace subtract
* Fix pycc so that correct header is emitted
* Allow vectorize to work on functions with jit decorator

0.13.0

----------------------

Enhancements:

* PR 176: Switch from LLVM 3.7 to LLVM 3.8.
* PR 191: Allow setting the alignment of a global variable.
* PR 198: Add missing function attributes.
* PR 160: Escape the contents of metadata strings, to allow embedding
any characters.
* PR 162: Add support for creating debug information nodes.
* PR 200: Improve the usability of metadata emission APIs.
* PR 200: Allow calling functions with metadata arguments
(such as ``llvm.dbg.declare``).

Fixes:

* PR 190: Suppress optimization remarks printed out in some cases by LLVM.
* PR 200: Allow attaching metadata to a ``ret`` instruction.

0.12.2

--------------

Fixes:

* Improved NumPy ufunc support in nopython mode
* Misc bug fixes

0.12.1

----------------------

New release to fix packages on PyPI. Same as v0.12.0.

0.12

this refactor was to simplify the code base to create a better foundation for
further work. A secondary objective was to improve the worst case performance
to ensure that compiled functions in object mode never run slower than pure
Python code (this was a problem in several cases with the old code base). This
refactor is still a work in progress and further testing is needed.

Main improvements:

* Major refactor of compiler for performance and maintenance reasons
* Better fallback to object mode when native mode fails
* Improved worst case performance in object mode

The public interface of numba has been slightly changed. The idea is to
make it cleaner and more rational:

* jit decorator has been modified, so that it can be called without a signature.
When called without a signature, it behaves as the old autojit. Autojit
has been deprecated in favour of this approach.
* Jitted functions can now be overloaded.
* Added a "njit" decorator that behaves like "jit" decorator with nopython=True.
* The numba.vectorize namespace is gone. The vectorize decorator will
be in the main numba namespace.
* Added a guvectorize decorator in the main numba namespace. It is
similiar to numba.vectorize, but takes a dimension signature. It
generates gufuncs. This is a replacement for the GUVectorize gufunc
factory which has been deprecated.

Main regressions (will be fixed in a future release):

* Creating new NumPy arrays is not supported in nopython mode
* Returning NumPy arrays is not supported in nopython mode
* NumPy array slicing is not supported in nopython mode
* lists and tuples are not supported in nopython mode
* string, datetime, cdecimal, and struct types are not implemented yet
* Extension types (classes) are not supported in nopython mode
* Closures are not supported
* Raise keyword is not supported
* Recursion is not support in nopython mode

0.12.0

---------------------

Enhancements:

* PR 179: Let llvmlite build on armv7l Linux.
* PR 161: Allow adding metadata to functions.
* PR 163: Allow emitting fast-math ``fcmp`` instructions.
* PR 159: Allow emitting verbose assembly in TargetMachine.

Fixes:

* Issue 177: Make setup.py compatible with ``pip install``.

0.11

------------
* Experimental support for NumPy datetime type

0.11.0

----------------------

Enhancements:

* PR 175: Check LLVM version at build time
* PR 169: Default initializer for non-external global variable
* PR 168: add ir.Constant.literal_array()

0.10

------------
* Annotation tool (./bin/numba --annotate --fancy) (thanks to Jay Bourque)
* Open sourced prange
* Support for raise statement
* Pluggable array representation
* Support for enumerate and zip (thanks to Eugene Toder)
* Better string formatting support (thanks to Eugene Toder)
* Builtins min(), max() and bool() (thanks to Eugene Toder)
* Fix some code reloading issues (thanks to Björn Linse)
* Recognize NumPy scalar objects (thanks to Björn Linse)

0.10.0

----------------------

Enhancements:

* PR 146: Improve ``setup.py clean`` to wipe more leftovers.
* PR 135: Remove some llvmpy compatibility APIs.
* PR 151: Always copy TargetData when adding to a pass manager.
* PR 148: Make errors more explicit on loading the binding DLL.
* PR 144: Allow overriding ``-flto`` in Linux builds.
* PR 136: Remove Python 2.6 and 3.3 compatibility.
* Issue 131: Allow easier creation of constants by making type instances
callable.
* Issue 130: The test suite now ensures the runtime DLL dependencies
are within a certain expected set.
* Issue 121: Simplify build process on Unix and remove hardcoded linking
with LLVMOProfileJIT.
* Issue 125: Speed up formatting of raw array constants.

Fixes:

* PR 155: Properly emit IR for metadata null.
* PR 153: Remove deprecated uses of ``TargetMachine::getDataLayout()``.
* PR 156: Move personality from LandingPadInstr to FunctionAttributes.
It was moved in LLVM 3.7.
* PR 149: Implement LLVM scoping correctly.
* PR 141: Ensure no CMakeCache.txt file is included in sdist.
* PR 132: Correct constant in ``llvmir.py`` example.

0.9

-----------
* Improved math support
* Open sourced generalized ufuncs
* Improved array expressions

0.9.0

---------------------

Enhancements:

* PR 73: Add get_process_triple() and get_host_cpu_features()
* Switch from LLVM 3.6 to LLVM 3.7.  The generated IR for some memory
operations has changed.
* Improved performance of IR serialization.
* Issue 116: improve error message when the operands of a binop have
differing types.
* PR 113: Let Type.get_abi_{size,alignment} not choke on identified types.
* PR 112: Support non-alphanumeric characters in type names.

Fixes:

* Remove the libcurses dependency on Linux.

0.8

-----------
* Support for autojit classes
* Inheritance not yet supported
* Python 3 support for pycc
* Allow retrieval of ctypes function wrapper
* And hence support retrieval of a pointer to the function
* Fixed a memory leak of array slicing views

0.8.0

---------------------

* Update LLVM to 3.6.2
* Add an *align* parameter to IRBuilder.load() and IRBuilder.store().
* Allow setting visibility, DLL storageclass of ValueRef
* Support profiling with OProfile

0.7.2

-------------
* Official Python 3 support (python 3.2 and 3.3)
* Support for intrinsics and instructions
* Various bug fixes (see https://github.com/numba/numba/issues?milestone=7&state=closed)

0.7.1

-------------
* Various bug fixes

0.7

-----------
* Open sourced single-threaded ufunc vectorizer
* Open sourced NumPy array expression compilation
* Open sourced fast NumPy array slicing
* Experimental Python 3 support
* Support for typed containers
* typed lists and tuples
* Support for iteration over objects
* Support object comparisons
* Preliminary CFFI support
* Jit calls to CFFI functions (passed into autojit functions)
* TODO: Recognize ffi_lib.my_func attributes
* Improved support for ctypes
* Allow declaring extension attribute types as through class attributes
* Support for type casting in Python
* Get the same semantics with or without numba compilation
* Support for recursion
* For jit methods and extension classes
* Allow jit functions as C callbacks
* Friendlier error reporting
* Internal improvements
* A variety of bug fixes

0.7.0

---------------------

* PR 88: Provide hooks into the MCJIT object cache
* PR 87: Add indirect branches and exception handling APIs to ir.Builder.
* PR 86: Add ir.Builder APIs for integer arithmetic with overflow
* Issue 76: Fix non-Windows builds when LLVM was built using CMake
* Deprecate .get_pointer_to_global() and add .get_function_address() and
.get_global_value_address() in ExecutionEngine.

0.6.1

--------------
* Support for bitwise operations

0.6

--------------
* Python 2.6 support
* Programmable typing
* Allow users to add type inference for external code
* Better NumPy type inference
* outer, inner, dot, vdot, tensordot, nonzero, where,
binary ufuncs + methods (reduce, accumulate, reduceat, outer)
* Type based alias analysis
* Support for strict aliasing
* Much faster autojit dispatch when calling from Python
* Faster numerical loops through data and stride pre-loading
* Integral overflow and underflow checking for conversions from objects
* Make Meta dependency optional

0.6.0

---------------------

Enhancements:

* Switch from LLVM 3.5 to LLVM 3.6.  The generated IR for metadata nodes
has slightly changed, and the "old JIT" engine has been remove (only
MCJIT is now available).
* Add an optional flags argument to arithmetic instructions on IRBuilder.
* Support attributes on the return type of a function.

0.5.1

--------------------

Fixes:

* Fix implicit termination of basic block in nested if_then()

0.5

--------------
* SSA-based type inference
* Allows variable reuse
* Allow referring to variables before lexical definition
* Support multiple comparisons
* Support for template types
* List comprehensions
* Support for pointers
* Many bug fixes
* Added user documentation

0.5.0

---------------------

New documentation hosted at http://llvmlite.pydata.org

Enhancements:

* Add code-generation helpers from numba.cgutils
* Support for memset, memcpy, memmove intrinsics

Fixes:

* Fix string encoding problem when round-triping parse_assembly()

0.4

--------------

0.4.0

---------------------

Enhancements:

* Add Module.get_global()
* Renamd Module.global_variables to Module.global_values
* Support loading library parmanently
* Add Type.get_abi_alignment()

Fixes:

* Expose LLVM version as a tuple

0.3.2

--------------

* Add support for object arithmetic (issue 56).
* Bug fixes (issue 55).

0.3

--------------
* Changed default compilation approach to ast
* Added support for cross-module linking
* Added support for closures (can jit inner functions and return them) (see examples/closure.py)
* Added support for dtype structures (can access elements of structure with attribute access) (see examples/structures.py)
* Added support for extension types (numba classes) (see examples/numbaclasses.py)
* Added support for general Python code (use nopython to raise an error if Python C-API is used to avoid unexpected slowness because of lack of implementation defaulting to generic Python)
* Fixed many bugs
* Added support to detect math operations.
* Added with python and with nopython contexts
* Added more examples

Many features need to be documented still.  Look at examples and tests for more information.

0.2.2

---------------------

Enhancements:

* Support for addrspacescast
* Support for tail call, calling convention attribute
* Support for IdentifiedStructType

Fixes:

* GEP addrspace propagation
* Various installation process fixes

0.2

--------------
* Added an ast approach to compilation
* Removed d, f, i, b from numba namespace (use f8, f4, i4, b1)
* Changed function to autojit2
* Added autojit function to decorate calls to the function and use types of the variable to create compiled versions.
* changed keyword arguments to jit and autojit functions to restype and argtypes to be consistent with ctypes module.
* Added pycc -- a python to shared library compiler

0.2.0

---------------------

This is the first official release. It contains a few feature additions
and bug fixes. It meets all requirements to replace llvmpy in numba and
numbapro.

0.1.0

---------------------

This is the first release. This is released for beta testing llvmlite
and numba before the official release.