* added support for parsing hash on vector elements
reversed check for scalar to check for vector
added C++ generation of cpp_type vectors
removed ctor call for vector fields
added condition !vector for cpp_type check
added Pack() and UnPack() code generation for vector of hashes
* schema change:
added table Referrable and weak references towards it from Monster
added single_weak_reference to Monster table
changed order with vector_of_weak_references
* re-generated monster schema dependent code
added Referrable.cs to FlatBuffers.Test.csproj
* Fix issue #4389, if field is ommitted the return type is the same for python generator
* Fix issue #4389, bytes is returned when field is omitted
* Fix issue #4389, added generated python code after generator modification
A Namespace object is now guaranteed unique.
This cleaned up some old workarounds and latent bugs.
Change-Id: Ic3f12d89947871b03b2c449ba51b3186f953adde
Tested: on Linux.
Bug: 21336857
* Add numpy accessor to python flatbuffers scalar vectors
* Update python tests to test numpy vector accessor
* Update appveyor CI to run Python tests, save generated code as artifact
* Update example generated python code
* Add numpy info to python usage docs
* Update test schema and python tests w/ multi-byte vector
* did not mean to push profiling code
* adding float64 numpy tests
* Support binary search for struct in cpp
CreateVectorOfSortedStruct is provided for convenience.
* fix continuous-integration error
* add generated files
* compile Ability.cs in csharp test
* compile Ability.cs in csharp
* modify according to code review
A previous commit that added "f" for C++/Java/C# would break
on gcc of constants like 3f, which are now output as 3.0f
Tested: on Linux
Change-Id: If9cabbe3c6d6948a5050b8b123bda9c06e181f52
Implement code generation and self-contained runtime library for Python.
The test suite verifies:
- Correctness of generated Python code by comparing output to that of
the other language ports.
- The exact bytes in the Builder buffer during many scenarios.
- Vtable deduplication correctness.
- Edge cases for table construction, via a fuzzer derived from the Go
implementation.
- All code is simultaneously valid in Python 2.6, 2.7, and 3.4.
The test suite includes benchmarks for:
- Building 'gold' data.
- Parsing 'gold' data.
- Deduplicating vtables.
All tests pass on this author's system for the following Python
implementations:
- CPython 2.6.7
- CPython 2.7.8
- CPython 3.4.2
- PyPy 2.5.0 (CPython 2.7.8 compatible)
