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# FlatBuffers
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FlatBuffers is an efficient cross platform serialization library in for C++ and
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Java. It was created at Google specifically for game development and other
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performance-critical applications.
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It is available as open source under the Apache license, v2 (see LICENSE.txt).
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## Why use FlatBuffers?
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- **Access to serialized data without parsing/unpacking** - What sets
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FlatBuffers apart is that it represents hierarchical data in a flat
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binary buffer in such a way that it can still be accessed directly
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without parsing/unpacking, while also still supporting data
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structure evolution (forwards/backwards compatibility).
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- **Memory efficiency and speed** - The only memory needed to access
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your data is that of the buffer. It requires 0 additional allocations.
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FlatBuffers is also very
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suitable for use with mmap (or streaming), requiring only part of the
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buffer to be in memory. Access is close to the speed of raw
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struct access with only one extra indirection (a kind of vtable) to
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allow for format evolution and optional fields. It is aimed at
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projects where spending time and space (many memory allocations) to
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be able to access or construct serialized data is undesirable, such
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as in games or any other performance sensitive applications. See the
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[benchmarks](md__benchmarks.html) for details.
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- **Flexible** - Optional fields means not only do you get great
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forwards and backwards compatibility (increasingly important for
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long-lived games: don't have to update all data with each new
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version!). It also means you have a lot of choice in what data you
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write and what data you don't, and how you design data structures.
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- **Tiny code footprint** - Small amounts of generated code, and just
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a single small header as the minimum dependency, which is very easy
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to integrate. Again, see the benchmark section for details.
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- **Strongly typed** - Errors happen at compile time rather than
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manually having to write repetitive and error prone run-time checks.
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Useful code can be generated for you.
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- **Convenient to use** - Generated C++ code allows for terse access
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& construction code. Then there's optional functionality for parsing
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schemas and JSON-like text representations at runtime efficiently if
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needed (faster and more memory efficient than other JSON
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parsers).
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Java code supports object-reuse.
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- **Cross platform C++11/Java code with no dependencies** - will work with
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any recent gcc/clang and VS2010. Comes with build files for the tests &
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samples (Android .mk files, and cmake for all other platforms).
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### Why not use Protocol Buffers, or .. ?
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Protocol Buffers is indeed relatively similar to FlatBuffers,
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with the primary difference being that FlatBuffers does not need a parsing/
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unpacking step to a secondary representation before you can
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access data, often coupled with per-object memory allocation. The code
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is an order of magnitude bigger, too. Protocol Buffers has neither optional
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text import/export nor schema language features like unions.
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### But all the cool kids use JSON!
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JSON is very readable (which is why we use it as our optional text
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format) and very convenient when used together with dynamically typed
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languages (such as JavaScript). When serializing data from statically
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typed languages, however, JSON not only has the obvious drawback of runtime
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inefficiency, but also forces you to write *more* code to access data
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(counterintuitively) due to its dynamic-typing serialization system.
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In this context, it is only a better choice for systems that have very
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little to no information ahead of time about what data needs to be stored.
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Read more about the "why" of FlatBuffers in the
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[white paper](md__white_paper.html).
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## Usage in brief
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This section is a quick rundown of how to use this system. Subsequent
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sections provide a more in-depth usage guide.
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- Write a schema file that allows you to define the data structures
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you may want to serialize. Fields can have a scalar type
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(ints/floats of all sizes), or they can be a: string; array of any type;
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reference to yet another object; or, a set of possible objects (unions).
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Fields are optional and have defaults, so they don't need to be
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present for every object instance.
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- Use `flatc` (the FlatBuffer compiler) to generate a C++ header (or Java
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classes) with helper classes to access and construct serialized data. This
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header (say `mydata_generated.h`) only depends on `flatbuffers.h`, which
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defines the core functionality.
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- Use the `FlatBufferBuilder` class to construct a flat binary buffer.
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The generated functions allow you to add objects to this
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buffer recursively, often as simply as making a single function call.
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- Store or send your buffer somewhere!
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- When reading it back, you can obtain the pointer to the root object
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from the binary buffer, and from there traverse it conveniently
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in-place with `object->field()`.
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## In-depth documentation
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- How to [build the compiler](md__building.html) and samples on various
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platforms.
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- How to [use the compiler](md__compiler.html).
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- How to [write a schema](md__schemas.html).
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- How to [use the generated C++ code](md__cpp_usage.html) in your own
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programs.
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- How to [use the generated Java code](md__java_usage.html) in your own
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programs.
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- Some [benchmarks](md__benchmarks.html) showing the advantage of using
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FlatBuffers.
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- A [white paper](md__white_paper.html) explaining the "why" of FlatBuffers.
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- A description of the [internals](md__internals.html) of FlatBuffers.
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- A formal [grammar](md__grammar.html) of the schema language.
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## Online resources
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- [github repository](http://github.com/google/flatbuffers)
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- [landing page](http://google.github.io/flatbuffers)
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- [FlatBuffers Google Group](http://group.google.com/group/flatbuffers)
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- [FlatBuffers Issues Tracker](http://github.com/google/flatbuffers/issues)
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