FlatBuffers
An open source project by FPL.
|
FlatBuffers supports reading and writing binary FlatBuffers in Java and C#. Generate code for Java with the -j
option to flatc
, or for C# with -n
(think .Net).
Note that this document is from the perspective of Java. Code for both languages is generated in the same way, with only minor differences. These differences are explained in a section below.
See javaTest.java
for an example. Essentially, you read a FlatBuffer binary file into a byte[]
, which you then turn into a ByteBuffer
, which you pass to the getRootAsMyRootType
function:
Now you can access values much like C++:
Note that whenever you access a new object like in the pos
example above, a new temporary accessor object gets created. If your code is very performance sensitive (you iterate through a lot of objects), there's a second pos()
method to which you can pass a Vec3
object you've already created. This allows you to reuse it across many calls and reduce the amount of object allocation (and thus garbage collection) your program does.
Java does not support unsigned scalars. This means that any unsigned types you use in your schema will actually be represented as a signed value. This means all bits are still present, but may represent a negative value when used. For example, to read a byte b
as an unsigned number, you can do: (short)(b & 0xFF)
The default string accessor (e.g. monster.name()
) currently always create a new Java String
when accessed, since FlatBuffer's UTF-8 strings can't be used in-place by String
. Alternatively, use monster.nameAsByteBuffer()
which returns a ByteBuffer
referring to the UTF-8 data in the original ByteBuffer
, which is much more efficient. The ByteBuffer
's position
points to the first character, and its limit
to just after the last.
Vector access is also a bit different from C++: you pass an extra index to the vector field accessor. Then a second method with the same name suffixed by Length
let's you know the number of elements you can access:
Alternatively, much like strings, you can use monster.inventoryAsByteBuffer()
to get a ByteBuffer
referring to the whole vector. Use ByteBuffer
methods like asFloatBuffer
to get specific views if needed.
If you specified a file_indentifier in the schema, you can query if the buffer is of the desired type before accessing it using:
You can also construct these buffers in Java using the static methods found in the generated code, and the FlatBufferBuilder class:
Create strings:
Create a table with a struct contained therein:
For some simpler types, you can use a convenient create
function call that allows you to construct tables in one function call. This example definition however contains an inline struct field, so we have to create the table manually. This is to create the buffer without using temporary object allocation.
It's important to understand that fields that are structs are inline (like Vec3
above), and MUST thus be created between the start and end calls of a table. Everything else (other tables, strings, vectors) MUST be created before the start of the table they are referenced in.
Structs do have convenient methods that even have arguments for nested structs.
As you can see, references to other objects (e.g. the string above) are simple ints, and thus do not have the type-safety of the Offset type in C++. Extra care must thus be taken that you set the right offset on the right field.
Vectors can be created from the corresponding Java array like so:
This works for arrays of scalars and (int) offsets to strings/tables, but not structs. If you want to write structs, or what you want to write does not sit in an array, you can also use the start/end pattern:
You can use the generated method startInventoryVector
to conveniently call startVector
with the right element size. You pass the number of elements you want to write. Note how you write the elements backwards since the buffer is being constructed back to front. You then pass inv
to the corresponding Add
call when you construct the table containing it afterwards.
There are add
functions for all the scalar types. You use addOffset
for any previously constructed objects (such as other tables, strings, vectors). For structs, you use the appropriate create
function in-line, as shown above in the Monster
example.
To finish the buffer, call:
The buffer is now ready to be transmitted. It is contained in the ByteBuffer
which you can obtain from fbb.dataBuffer()
. Importantly, the valid data does not start from offset 0 in this buffer, but from fbb.dataBuffer().position()
(this is because the data was built backwards in memory). It ends at fbb.capacity()
.
C# code works almost identically to Java, with only a few minor differences. You can see an example of C# code in tests/FlatBuffers.Test/FlatBuffersExampleTests.cs
.
First of all, naming follows standard C# style with PascalCasing
identifiers, e.g. GetRootAsMyRootType
. Also, values (except vectors and unions) are available as properties instead of parameterless accessor methods as in Java. The performance-enhancing methods to which you can pass an already created object are prefixed with Get
, e.g.:
There currently is no support for parsing text (Schema's and JSON) directly from Java or C#, though you could use the C++ parser through native call interfaces available to each language. Please see the C++ documentation for more on text parsing.