In some cases the user of pythonbuf needs to allocate the internal
buffer to a specific size e.g. for performance or to enable synchronous
writes to the buffer.
By changing `pythonbuf::d_buffer` to be dynamically allocated we can now
enable these use-cases while still providing the default behavior of
allocating a 1024 byte internal buffer (through a default parameter).
Bazel has a "strict" build model that requires all C++ header files be compilable on their own, and thus must explicitly #include all headers they require (even if de facto header inclusion order means they'd get them "for free"). This adds a couple of headers that are needed (but missing) by this model.
* Fixing order of arguments in call to PyErr_GivenExceptionMatches in pybind11::error_already_set.matches
* Added tests on error_already_set::matches fix for exception base classes
* Fix warning that not including a cmake source or build dir will be a fatal error (it is now on newest CMakes)
* Fixes appveyor
* Travis uses CMake 3.9 for more than a year now
* Travis dropped sudo: false in December
* Dropping Sphinx 2
- clang7: Suppress self-assign warnings; fix missing virtual dtors
- pypy:
- Keep old version (newer stuff breaks)
- Pin packages to extra index for speed
- travis:
- Make docker explicit; remove docker if not needed
- Make commands more verbose (for debugging / repro)
- Make Ubuntu dist explicit per job
- Fix Windows
- Add names to travis
This avoids GIL deadlocking when pybind11 tries to acquire the GIL in a thread that already acquired it using standard Python API (e.g. when running from a Python thread).
* Adds std::deque to the types supported by list_caster in stl.h.
* Adds a new test_deque test in test_stl.{py,cpp}.
* Updates the documentation to include std::deque as a default
supported type.
* Check default holder
-Recognize "std::unique_ptr<T, D>" as a default holder even if "D" doesn't match between base and derived holders
* Add test for unique_ptr<T, D> change
Pybind11 provides a cast operator between opaque void* pointers on the
C++ side and capsules on the Python side. The py::cast<void *>
expression was not aware of this possibility and incorrectly triggered a
compile-time assertion ("Unable to cast type to reference: value is
local to type caster") that is now fixed.
* Support C++17 aligned new statement
This patch makes pybind11 aware of nonstandard alignment requirements in
bound types and passes on this information to C++17 aligned 'new'
operator. Pre-C++17, the behavior is unchanged.
This PR brings the std::array<> caster in sync with the other STL type
casters: to accept an arbitrary sequence as input (rather than a list,
which is too restrictive).
* Fix for Issue #1258
list_caster::load method will now check for a Python string and prevent its automatic conversion to a list.
This should fix the issue "pybind11/stl.h converts string to vector<string> #1258" (https://github.com/pybind/pybind11/issues/1258)
* Added tests for fix of issue #1258
* Changelog: stl string auto-conversion
* Fix potential crash when calling an overloaded function
The crash would occur if:
- dispatcher() uses two-pass logic (because the target is overloaded and some arguments support conversions)
- the first pass (with conversions disabled) doesn't find any matching overload
- the second pass does find a matching overload, but its return value can't be converted to Python
The code for formatting the error message assumed `it` still pointed to the selected overload,
but during the second-pass loop `it` was nullptr. Fix by setting `it` correctly if a second-pass
call returns a nullptr `handle`. Add a new test that segfaults without this fix.
* Make overload iteration const-correct so we don't have to iterate again on second-pass error
* Change test_error_after_conversions dependencies to local classes/variables
This commit addresses an inefficiency in how enums are created in
pybind11. Most of the enum_<> implementation is completely generic --
however, being a template class, it ended up instantiating vast amounts
of essentially identical code in larger projects with many enums.
This commit introduces a generic non-templated helper class that is
compatible with any kind of enumeration. enum_ then becomes a thin
wrapper around this new class.
The new enum_<> API is designed to be 100% compatible with the old one.
object_api::operator[] has a powerful overload for py::handle that can
accept slices, tuples (for NumPy), etc.
Lists, sequences, and tuples provide their own specialized operator[],
which unfortunately disables this functionality. This is accidental, and
the purpose of this commit is to re-enable the more general behavior.
This commit is tangentially related to the previous one in that it makes
py::handle/py::object et al. behave more like their Python counterparts.
This commit revamps the object_api class so that it maps most C++
operators to their Python analogs. This makes it possible to, e.g.
perform arithmetic using a py::int_ or py::array.
* check for already existing enum value added; added test
* added enum value name to exception message
* test for defining enum with multiple identical names moved to test_enum.cpp/py
This PR adds a new py::ellipsis() method which can be used in
conjunction with NumPy's generalized slicing support. For instance,
the following is now valid (where "a" is a NumPy array):
py::array b = a[py::make_tuple(0, py::ellipsis(), 0)];
* stl.h: propagate return value policies to type-specific casters
Return value policies for containers like those handled in in 'stl.h'
are currently broken.
The problem is that detail::return_value_policy_override<C>::policy()
always returns 'move' when given a non-pointer/reference type, e.g.
'std::vector<...>'.
This is sensible behavior for custom types that are exposed via
'py::class_<>', but it does not make sense for types that are handled by
other type casters (STL containers, Eigen matrices, etc.).
This commit changes the behavior so that
detail::return_value_policy_override only becomes active when the type
caster derives from type_caster_generic.
Furthermore, the override logic is called recursively in STL type
casters to enable key/value-specific behavior.
* Switching deprecated Thread Local Storage (TLS) usage in Python 3.7 to Thread Specific Storage (TSS)
* Changing Python version from 3.6 to 3.7 for Travis CI, to match brew's version of Python 3
* Introducing PYBIND11_ macros to switch between TLS and TSS API
The current code requires implicitly that integral types are cast-able to floating point. In case of strongly-typed integrals (e.g. as explained at http://www.ilikebigbits.com/blog/2014/5/6/type-safe-identifiers-in-c) this is not always the case.
This commit uses SFINAE to move the numeric conversions into separate `cast()` implementations to avoid the issue.
If an exception is thrown during module initialization, the
error_already_set destructor will try to call `get_internals()` *after*
setting Python's error indicator, resulting in a `SystemError: ...
returned with an error set`.
Fix that by temporarily stashing away the error indicator in the
destructor.
