Commit Graph

118 Commits

Author SHA1 Message Date
Dean Moldovan
5f07facef5 Fix pointer to reference error in type_caster on MSVC (#583) 2017-01-03 11:52:05 +01:00
Jason Rhinelander
6e036e78a7 Support binding noexcept function/methods in C++17
When compiling in C++17 mode the noexcept specifier is part of the
function type.  This causes a failure in pybind11 because, by omitting
a noexcept specifier when deducing function return and argument types,
we are implicitly making `noexcept(false)` part of the type.

This means that functions with `noexcept` fail to match the function
templates in cpp_function (and other places), and we get compilation
failure (we end up trying to fit it into the lambda function version,
which fails since a function pointer has no `operator()`).

We can, however, deduce the true/false `B` in noexcept(B), so we don't
need to add a whole other set of overloads, but need to deduce the extra
argument when under C++17.  That will *not* work under pre-C++17,
however.

This commit adds two macros to fix the problem: under C++17 (with the
appropriate feature macro set) they provide an extra `bool NoExceptions`
template argument and provide the `noexcept(NoExceptions)` deduced
specifier.  Under pre-C++17 they expand to nothing.

This is needed to compile pybind11 with gcc7 under -std=c++17.
2016-12-14 20:40:49 +01:00
Dean Moldovan
8c85a85747 Use C++14 index_sequence when possible
Newer standard libraries use compiler intrinsics for std::index_sequence
which makes it ‘free’. This prevents hitting instantiation limits for
recursive templates (-ftemplate-depth).
2016-12-03 23:13:53 +01:00
Patrick Stewart
5271576828 Use correct itemsize when constructing a numpy dtype from a buffer_info 2016-11-22 22:01:03 +01:00
patstew
47681c183d Only mark unaligned types in buffers (#505)
Previously all types are marked unaligned in buffer format strings,
now we test for alignment before adding the '=' marker.
2016-11-22 12:17:07 +01:00
Sylvain Corlay
b14f065fa9 numpy.h replace macros with functions (#514) 2016-11-22 11:29:55 +01:00
Dean Moldovan
4de271027d Improve consistency of array and array_t with regard to other pytypes
* `array_t(const object &)` now throws on error
* `array_t::ensure()` is intended for casters —- old constructor is
  deprecated
* `array` and `array_t` get default constructors (empty array)
* `array` gets a converting constructor
* `py::isinstance<array_T<T>>()` checks the type (but not flags)

There is only one special thing which must remain: `array_t` gets
its own `type_caster` specialization which uses `ensure` instead
of a simple check.
2016-11-17 08:55:42 +01:00
Dean Moldovan
c7ac16bb2e Add py::reinterpret_borrow<T>()/steal<T>() for low-level unchecked casts
The pytype converting constructors are convenient and safe for user
code, but for library internals the additional type checks and possible
conversions are sometimes not desired. `reinterpret_borrow<T>()` and
`reinterpret_steal<T>()` serve as the low-level unsafe counterparts
of `cast<T>()`.

This deprecates the `object(handle, bool)` constructor.

Renamed `borrowed` parameter to `is_borrowed` to avoid shadowing
warnings on MSVC.
2016-11-17 08:55:42 +01:00
Dean Moldovan
e18bc02fc9 Add default and converting constructors for all concrete Python types
* Deprecate the `py::object::str()` member function since `py::str(obj)`
  is now equivalent and preferred

* Make `py::repr()` a free function

* Make sure obj.cast<T>() works as expected when T is a Python type

`obj.cast<T>()` should be the same as `T(obj)`, i.e. it should convert
the given object to a different Python type. However, `obj.cast<T>()`
usually calls `type_caster::load()` which only checks the type without
doing any actual conversion. That causes a very unexpected `cast_error`.
This commit makes it so that `obj.cast<T>()` and `T(obj)` are the same
when T is a Python type.

* Simplify pytypes converting constructor implementation

It's not necessary to maintain a full set of converting constructors
and assignment operators + const& and &&. A single converting const&
constructor will work and there is no impact on binary size. On the
other hand, the conversion functions can be significantly simplified.
2016-11-17 08:55:42 +01:00
Dean Moldovan
b4498ef44d Add py::isinstance<T>(obj) for generalized Python type checking
Allows checking the Python types before creating an object instead of
after. For example:
```c++
auto l = list(ptr, true);
if (l.check())
   // ...
```
The above is replaced with:
```c++
if (isinstance<list>(ptr)) {
    auto l = reinterpret_borrow(ptr);
    // ...
}
```

This deprecates `py::object::check()`. `py::isinstance()` covers the
same use case, but it can also check for user-defined types:
```c++
class Pet { ... };
py::class_<Pet>(...);

m.def("is_pet", [](py::object obj) {
    return py::isinstance<Pet>(obj); // works as expected
});
```
2016-11-17 08:55:42 +01:00
Sylvain Corlay
5027c4f95b Switch NumPy variadic indexing to per-value arguments (#500)
* Also added unsafe version without checks
2016-11-16 17:53:37 +01:00
Wenzel Jakob
cc4efe69c2 more code style checks in Travis CI :) 2016-11-08 10:53:30 +01:00
Ivan Smirnov
cc8ff16547 Move register_dtype() outside of the template
(avoid code bloat if possible)
2016-11-03 09:35:05 +00:00
Ivan Smirnov
2dbf029705 Add public shared_data API
NumPy internals are stored under "_numpy_internals" key.
2016-11-03 09:35:05 +00:00
Ivan Smirnov
2184f6d4d6 NumPy dtypes are now shared across extensions 2016-11-03 09:35:05 +00:00
Ivan Smirnov
e8b50360fe Add dtype binding macro that allows setting names
PYBIND11_NUMPY_DTYPE_EX(Type, F1, "N1", F2, "N2", ...)
2016-11-01 13:27:35 +00:00
Wenzel Jakob
dd9bd7778f Merge pull request #453 from aldanor/feature/numpy-scalars
NumPy scalars to ctypes conversion support
2016-10-25 01:15:25 +02:00
Ivan Smirnov
a6e6a8b108 Require existing typeinfo for direct conversions
This avoid a hashmap lookup since the pointer to the list of
direct converters is now cached in the typeinfo.
2016-10-23 15:29:10 +01:00
Ivan Smirnov
43a88f4574 Reraise existing exception if dtype ctor fails 2016-10-22 18:57:07 +02:00
Ivan Smirnov
694269435b Allow implicit casts from literal strings to dtype 2016-10-22 18:57:07 +02:00
Ivan Smirnov
ef5a38044c A few dtype method docstrings 2016-10-22 18:57:07 +02:00
Ivan Smirnov
f70cc112f0 Make dtype from string ctor accept const ref 2016-10-22 18:57:07 +02:00
Ivan Smirnov
7edd72db24 Disallow registering dtypes multiple times 2016-10-20 16:57:12 +01:00
Ivan Smirnov
7bf90e8008 Add a direct converter for numpy scalars 2016-10-20 16:11:08 +01:00
Ivan Smirnov
ba08db4da5 Import a few more numpy extern symbols 2016-10-20 16:09:10 +01:00
Ivan Smirnov
fb74df50c9 Implement format/numpy descriptors for enums 2016-10-20 12:38:43 +01:00
Jason Rhinelander
12d76600f8 Disable most implicit conversion constructors
We have various classes that have non-explicit constructors that accept
a single argument, which is implicitly making them implicitly
convertible from the argument.  In a few cases, this is desirable (e.g.
implicit conversion of std::string to py::str, or conversion of double
to py::float_); in many others, however, it is unintended (e.g. implicit
conversion of size_t to some pre-declared py::array_t<T> type).

This disables most of the unwanted implicit conversions by marking them
`explicit`, and comments the ones that are deliberately left implicit.
2016-10-16 16:27:42 -04:00
Wenzel Jakob
c01a1c1ade added array::ensure() function wrapping PyArray_FromAny
This convenience function ensures that a py::object is either a
py::array, or the implementation will try to convert it into one. Layout
requirements (such as c_style or f_style) can be also be provided.
2016-10-14 01:08:07 +02:00
Wenzel Jakob
fac7c09458 NumPy "base" feature: integrated feedback by @aldanor 2016-10-13 10:49:53 +02:00
Wenzel Jakob
369e9b3937 Permit creation of NumPy arrays with a "base" object that owns the data
This patch adds an extra base handle parameter to most ``py::array`` and
``py::array_t<>`` constructors. If specified along with a pointer to
data, the base object will be registered within NumPy, which increases
the base's reference count. This feature is useful to create shallow
copies of C++ or Python arrays while ensuring that the owners of the
underlying can't be garbage collected while referenced by NumPy.

The commit also adds a simple test function involving a ``wrap()``
function that creates shallow copies of various N-D arrays.
2016-10-13 01:03:40 +02:00
Wenzel Jakob
ba7678016c numpy.h: added array::squeeze() method 2016-10-07 11:19:57 +02:00
Dean Moldovan
242b146a51 Extend attribute and item accessor interface using object_api 2016-09-23 02:00:01 +02:00
Dean Moldovan
865e43034b Make attr and item accessors throw on error instead of returning nullptr
This also adds the `hasattr` and `getattr` functions which are needed
with the new attribute behavior. The new functions behave exactly like
their Python counterparts.

Similarly `object` gets a `contains` method which calls `__contains__`,
i.e. it's the same as the `in` keyword in Python.
2016-09-23 01:40:22 +02:00
Dzhelil Rufat
c250ee5146 Use more consistent indentation and typenames names. 2016-09-22 14:51:41 -07:00
Wenzel Jakob
c1fc27e2b5 use detail::enable_if_t everywhere 2016-09-19 13:45:34 +02:00
Ivan Smirnov
f2a0ad5855 array: add direct data access and indexing methods 2016-09-10 16:24:00 +01:00
Ivan Smirnov
91b3d681ad Expose some dtype/array attributes via NumPy C API 2016-09-10 16:24:00 +01:00
Wenzel Jakob
a3906778eb minor: renamed argument in array constructor 2016-08-28 01:55:07 +02:00
Ivan Smirnov
d8b11b8708 Fix dtype::strip_padding() on Intel compiler 2016-08-25 21:52:52 +01:00
Wenzel Jakob
9a777a263d numpy.h: fix test suite issues on the Intel Compiler 2016-08-25 02:18:00 +02:00
Ivan Smirnov
1c8828fe8f Fix int_ shadowing problem in detail namespace
If operators.h is included, int_ function in the `detail`
namespace will shadow pybind11::int_ type, so the fully qualified
name has to be used.
2016-08-25 00:33:02 +01:00
Ivan Smirnov
67b3daeea4 Always decay type param of npy_format_descriptor 2016-08-15 18:41:54 +01:00
Ivan Smirnov
edbd4cb0a7 Decay const qualifiers in is_pod_struct<> 2016-08-15 18:41:54 +01:00
Ivan Smirnov
03fb488579 format_descriptor::format() now yields std::string
This is required since format descriptors for string types that
were using PYBIND11_DESCR were causing problems on C++14 on Linux.

Although this is technically a breaking change, it shouldn't cause
problems since the only use of format strings is passing them to
buffer_info constructor which expects std::string.

Note: for non-structured types, the const char * value is still
accessible via ::value for compatibility purpose.
2016-08-15 00:40:29 +01:00
Ivan Smirnov
61e3b0bd15 Use builtin str type for recarray field names 2016-08-13 12:51:31 +01:00
Ivan Smirnov
ad5ca6d4e6 Added dtype from const char pointer ctor 2016-08-13 12:43:16 +01:00
Ivan Smirnov
c6257f8641 Allow nullptr in array ctors wherever possible 2016-08-13 12:43:16 +01:00
Ivan Smirnov
6636ae9d4e Also add the new ctors to py::array_t 2016-08-13 12:43:16 +01:00
Ivan Smirnov
6bb0ee1186 Add all possible ctors for py::array 2016-08-13 12:43:16 +01:00
Ivan Smirnov
d77bc8c343 Add dtype(names, offsets, formats, itemsize) ctor 2016-08-13 12:43:16 +01:00