In relational database theory there is a design step called normalization in
which you reorganize fields and tables. The same considerations need to
go into the design of your YAML encoding. But, you may not want to change
-your exisiting native data structures. Therefore, when writing out YAML
+your existing native data structures. Therefore, when writing out YAML
there may be a normalization step, and when reading YAML there would be a
corresponding denormalization step.
YAML I/O uses a non-invasive, traits based design. YAML I/O defines some
abstract base templates. You specialize those templates on your data types.
-For instance, if you have an eumerated type FooBar you could specialize
+For instance, if you have an enumerated type FooBar you could specialize
ScalarEnumerationTraits on that type and define the enumeration() method:
.. code-block:: c++
As with all YAML I/O template specializations, the ScalarEnumerationTraits is used for
both reading and writing YAML. That is, the mapping between in-memory enum
-values and the YAML string representation is only in place.
+values and the YAML string representation is only in one place.
This assures that the code for writing and parsing of YAML stays in sync.
To specify a YAML mappings, you define a specialization on
-llvm::yaml::MapppingTraits.
+llvm::yaml::MappingTraits.
If your native data structure happens to be a struct that is already normalized,
then the specialization is simple. For example:
.. code-block:: c++
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
template <>
- struct Mapp
pingTraits<Person> {
+ struct MappingTraits<Person> {
static void mapping(IO &io, Person &info) {
io.mapRequired("name", info.name);
io.mapOptional("hat-size", info.hatSize);
};
-A YAML sequence is automatically infered if you data type has begin()/end()
+A YAML sequence is automatically inferred if you data type has begin()/end()
iterators and a push_back() method. Therefore any of the STL containers
(such as std::vector<>) will automatically translate to YAML sequences.
* uint16_t
* uint8_t
-That is, you can use those types in fields of MapppingTraits or as element type
+That is, you can use those types in fields of MappingTraits or as element type
in sequence. When reading, YAML I/O will validate that the string found
is convertible to that type and error out if not.
.. code-block:: c++
using llvm::yaml::ScalarEnumerationTraits;
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
template <>
};
template <>
- struct MapppingTraits<Info> {
+ struct MappingTraits<Info> {
static void mapping(IO &io, Info &info) {
io.mapRequired("cpu", info.cpu);
io.mapOptional("flags", info.flags, 0);
flagsRound = 8
};
- LLVM_YAML_UNIQUE_TYPE(MyFlags, uint32_t)
+ LLVM_YAML_STRONG_TYPEDEF(uint32_t, MyFlags)
To support reading and writing of MyFlags, you specialize ScalarBitSetTraits<>
on MyFlags and provide the bit values and their names.
.. code-block:: c++
using llvm::yaml::ScalarBitSetTraits;
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
template <>
};
template <>
- struct MapppingTraits<Info> {
+ struct MappingTraits<Info> {
static void mapping(IO &io, Info& info) {
io.mapRequired("name", info.name);
io.mapRequired("flags", info.flags);
custom formatting and parsing of scalar types by specializing ScalarTraits<> on
your data type. When writing, YAML I/O will provide the native type and
your specialization must create a temporary llvm::StringRef. When reading,
-YAML I/O will provide a llvm::StringRef of scalar and your specialization
+YAML I/O will provide an llvm::StringRef of scalar and your specialization
must convert that to your native data type. An outline of a custom scalar type
looks like:
========
To be translated to or from a YAML mapping for your type T you must specialize
-llvm::yaml::MapppingTraits on T and implement the "void mapping(IO &io, T&)"
+llvm::yaml::MappingTraits on T and implement the "void mapping(IO &io, T&)"
method. If your native data structures use pointers to a class everywhere,
you can specialize on the class pointer. Examples:
.. code-block:: c++
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
// Example of struct Foo which is used by value
template <>
- struct MapppingTraits<Foo> {
+ struct MappingTraits<Foo> {
static void mapping(IO &io, Foo &foo) {
io.mapOptional("size", foo.size);
...
// Example of struct Bar which is natively always a pointer
template <>
- struct MapppingTraits<Bar*> {
+ struct MappingTraits<Bar*> {
static void mapping(IO &io, Bar *&bar) {
io.mapOptional("size", bar->size);
...
.. code-block:: c++
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
template <>
- struct Mapp
pingTraits<Person> {
+ struct MappingTraits<Person> {
static void mapping(IO &io, Person &info) {
io.mapRequired("name", info.name);
io.mapOptional("hat-size", info.hatSize);
x: 10.3
y: -4.7
-You can support this by defining a MapppingTraits that normalizes the polar
+You can support this by defining a MappingTraits that normalizes the polar
coordinates to x,y coordinates when writing YAML and denormalizes x,y
-coordindates into polar when reading YAML.
+coordinates into polar when reading YAML.
.. code-block:: c++
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
template <>
- struct Mapp
pingTraits<Polar> {
+ struct MappingTraits<Polar> {
class NormalizedPolar {
public:
y(polar.distance * sin(polar.angle)) {
}
Polar denormalize(IO &) {
- return Polar(sqrt(x*x+y*y, arctan(x,y));
+ return Polar(sqrt(x*x+y*y), arctan(x,y));
}
float x;
normalized instance is stack allocated. In these cases, the utility template
MappingNormalizationHeap<> can be used instead. It just like
MappingNormalization<> except that it heap allocates the normalized object
-when reading YAML. It never destroyes the normalized object. The denormalize()
+when reading YAML. It never destroys the normalized object. The denormalize()
method can this return "this".
.. code-block:: c++
- using llvm::yaml::MapppingTraits;
+ using llvm::yaml::MappingTraits;
using llvm::yaml::IO;
struct Info {
};
template <>
- struct MapppingTraits<Info> {
+ struct MappingTraits<Info> {
static void mapping(IO &io, Info &info) {
io.mapRequired("cpu", info.cpu);
// flags must come after cpu for this to work when reading yaml
To be translated to or from a YAML sequence for your type T you must specialize
llvm::yaml::SequenceTraits on T and implement two methods:
-“size_t size(IO &io, T&)” and “T::value_type& element(IO &io, T&, size_t indx)”.
-For example:
+``size_t size(IO &io, T&)`` and
+``T::value_type& element(IO &io, T&, size_t indx)``. For example:
.. code-block:: c++
};
With the above, if you used MyList as the data type in your native data
-strucutures, then then when converted to YAML, a flow sequence of integers
+structures, then then when converted to YAML, a flow sequence of integers
will be used (e.g. [ 10, -3, 4 ]).
Utility Macros
--------------
-Since a common source of sequences is std::vector<>, YAML I/O provids macros:
+Since a common source of sequences is std::vector<>, YAML I/O provides macros:
LLVM_YAML_IS_SEQUENCE_VECTOR() and LLVM_YAML_IS_FLOW_SEQUENCE_VECTOR() which
can be used to easily specify SequenceTraits<> on a std::vector type. YAML
I/O does not partial specialize SequenceTraits on std::vector<> because that
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