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<div class="title">Use in C++ </div>  </div>
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<div class="textblock"><p>Assuming you have written a schema using the above language in say <code>mygame.fbs</code> (FlatBuffer Schema, though the extension doesn't matter), you've generated a C++ header called <code>mygame_generated.h</code> using the compiler (e.g. <code>flatc -c mygame.fbs</code>), you can now start using this in your program by including the header. As noted, this header relies on <code>flatbuffers/flatbuffers.h</code>, which should be in your include path.</p>
<h3>Writing in C++</h3>
<p>To start creating a buffer, create an instance of <code>FlatBufferBuilder</code> which will contain the buffer as it grows:</p>
<div class="fragment"><div class="line">FlatBufferBuilder fbb;</div>
</div><!-- fragment --><p>Before we serialize a Monster, we need to first serialize any objects that are contained there-in, i.e. we serialize the data tree using depth first, pre-order traversal. This is generally easy to do on any tree structures. For example:</p>
<div class="fragment"><div class="line"><span class="keyword">auto</span> name = fbb.CreateString(<span class="stringliteral">&quot;MyMonster&quot;</span>);</div>
<div class="line"></div>
<div class="line"><span class="keywordtype">unsigned</span> <span class="keywordtype">char</span> inv[] = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };</div>
<div class="line"><span class="keyword">auto</span> inventory = fbb.CreateVector(inv, 10);</div>
</div><!-- fragment --><p><code>CreateString</code> and <code>CreateVector</code> serialize these two built-in datatypes, and return offsets into the serialized data indicating where they are stored, such that <code>Monster</code> below can refer to them.</p>
<p><code>CreateString</code> can also take an <code>std::string</code>, or a <code>const char *</code> with an explicit length, and is suitable for holding UTF-8 and binary data if needed.</p>
<p><code>CreateVector</code> can also take an <code>std::vector</code>. The offset it returns is typed, i.e. can only be used to set fields of the correct type below. To create a vector of struct objects (which will be stored as contiguous memory in the buffer, use <code>CreateVectorOfStructs</code> instead.</p>
<p>To create a vector of nested objects (e.g. tables, strings or other vectors) collect their offsets in a temporary array/vector, then call <code>CreateVector</code> on that (see e.g. the array of strings example in <code>test.cpp</code> <code>CreateFlatBufferTest</code>).</p>
<div class="fragment"><div class="line">Vec3 vec(1, 2, 3);</div>
</div><!-- fragment --><p><code>Vec3</code> is the first example of code from our generated header. Structs (unlike tables) translate to simple structs in C++, so we can construct them in a familiar way.</p>
<p>We have now serialized the non-scalar components of of the monster example, so we could create the monster something like this:</p>
<div class="fragment"><div class="line"><span class="keyword">auto</span> mloc = CreateMonster(fbb, &amp;vec, 150, 80, name, inventory, Color_Red, 0, Any_NONE);</div>
</div><!-- fragment --><p>Note that we're passing <code>150</code> for the <code>mana</code> field, which happens to be the default value: this means the field will not actually be written to the buffer, since we'll get that value anyway when we query it. This is a nice space savings, since it is very common for fields to be at their default. It means we also don't need to be scared to add fields only used in a minority of cases, since they won't bloat up the buffer sizes if they're not actually used.</p>
<p>We do something similarly for the union field <code>test</code> by specifying a <code>0</code> offset and the <code>NONE</code> enum value (part of every union) to indicate we don't actually want to write this field. You can use <code>0</code> also as a default for other non-scalar types, such as strings, vectors and tables.</p>
<p>Tables (like <code>Monster</code>) give you full flexibility on what fields you write (unlike <code>Vec3</code>, which always has all fields set because it is a <code>struct</code>). If you want even more control over this (i.e. skip fields even when they are not default), instead of the convenient <code>CreateMonster</code> call we can also build the object field-by-field manually:</p>
<div class="fragment"><div class="line">MonsterBuilder mb(fbb);</div>
<div class="line">mb.add_pos(&amp;vec);</div>
<div class="line">mb.add_hp(80);</div>
<div class="line">mb.add_name(name);</div>
<div class="line">mb.add_inventory(inventory);</div>
<div class="line"><span class="keyword">auto</span> mloc = mb.Finish();</div>
</div><!-- fragment --><p>We start with a temporary helper class <code>MonsterBuilder</code> (which is defined in our generated code also), then call the various <code>add_</code> methods to set fields, and <code>Finish</code> to complete the object. This is pretty much the same code as you find inside <code>CreateMonster</code>, except we're leaving out a few fields. Fields may also be added in any order, though orderings with fields of the same size adjacent to each other most efficient in size, due to alignment. You should not nest these Builder classes (serialize your data in pre-order).</p>
<p>Regardless of whether you used <code>CreateMonster</code> or <code>MonsterBuilder</code>, you now have an offset to the root of your data, and you can finish the buffer using:</p>
<div class="fragment"><div class="line">FinishMonsterBuffer(fbb, mloc);</div>
</div><!-- fragment --><p>The buffer is now ready to be stored somewhere, sent over the network, be compressed, or whatever you'd like to do with it. You can access the start of the buffer with <code>fbb.GetBufferPointer()</code>, and it's size from <code>fbb.GetSize()</code>.</p>
<p><code>samples/sample_binary.cpp</code> is a complete code sample similar to the code above, that also includes the reading code below.</p>
<h3>Reading in C++</h3>
<p>If you've received a buffer from somewhere (disk, network, etc.) you can directly start traversing it using:</p>
<div class="fragment"><div class="line"><span class="keyword">auto</span> monster = GetMonster(buffer_pointer);</div>
</div><!-- fragment --><p><code>monster</code> is of type <code>Monster *</code>, and points to somewhere <em>inside</em> your buffer (root object pointers are not the same as <code>buffer_pointer</code> !). If you look in your generated header, you'll see it has convenient accessors for all fields, e.g.</p>
<div class="fragment"><div class="line">assert(monster-&gt;hp() == 80);</div>
<div class="line">assert(monster-&gt;mana() == 150);  <span class="comment">// default</span></div>
<div class="line">assert(strcmp(monster-&gt;name()-&gt;c_str(), <span class="stringliteral">&quot;MyMonster&quot;</span>) == 0);</div>
</div><!-- fragment --><p>These should all be true. Note that we never stored a <code>mana</code> value, so it will return the default.</p>
<p>To access sub-objects, in this case the <code>Vec3</code>:</p>
<div class="fragment"><div class="line"><span class="keyword">auto</span> pos = monster-&gt;pos();</div>
<div class="line">assert(pos);</div>
<div class="line">assert(pos-&gt;z() == 3);</div>
</div><!-- fragment --><p>If we had not set the <code>pos</code> field during serialization, it would be <code>NULL</code>.</p>
<p>Similarly, we can access elements of the inventory array:</p>
<div class="fragment"><div class="line"><span class="keyword">auto</span> inv = monster-&gt;inventory();</div>
<div class="line">assert(inv);</div>
<div class="line">assert(inv-&gt;Get(9) == 9);</div>
</div><!-- fragment --><h3>Storing maps / dictionaries in a FlatBuffer</h3>
<p>FlatBuffers doesn't support maps natively, but there is support to emulate their behavior with vectors and binary search, which means you can have fast lookups directly from a FlatBuffer without having to unpack your data into a <code>std::map</code> or similar.</p>
<p>To use it:</p><ul>
<li>Designate one of the fields in a table as they "key" field. You do this by setting the <code>key</code> attribute on this field, e.g. <code>name:string (key)</code>. You may only have one key field, and it must be of string or scalar type.</li>
<li>Write out tables of this type as usual, collect their offsets in an array or vector.</li>
<li>Instead of <code>CreateVector</code>, call <code>CreateVectorOfSortedTables</code>, which will first sort all offsets such that the tables they refer to are sorted by the key field, then serialize it.</li>
<li>Now when you're accessing the FlatBuffer, you can use <code>Vector::LookupByKey</code> instead of just <code>Vector::Get</code> to access elements of the vector, e.g.: <code>myvector-&gt;LookupByKey("Fred")</code>, which returns a pointer to the corresponding table type, or <code>nullptr</code> if not found. <code>LookupByKey</code> performs a binary search, so should have a similar speed to <code>std::map</code>, though may be faster because of better caching. <code>LookupByKey</code> only works if the vector has been sorted, it will likely not find elements if it hasn't been sorted.</li>
</ul>
<h3>Direct memory access</h3>
<p>As you can see from the above examples, all elements in a buffer are accessed through generated accessors. This is because everything is stored in little endian format on all platforms (the accessor performs a swap operation on big endian machines), and also because the layout of things is generally not known to the user.</p>
<p>For structs, layout is deterministic and guaranteed to be the same accross platforms (scalars are aligned to their own size, and structs themselves to their largest member), and you are allowed to access this memory directly by using <code>sizeof()</code> and <code>memcpy</code> on the pointer to a struct, or even an array of structs.</p>
<p>To compute offsets to sub-elements of a struct, make sure they are a structs themselves, as then you can use the pointers to figure out the offset without having to hardcode it. This is handy for use of arrays of structs with calls like <code>glVertexAttribPointer</code> in OpenGL or similar APIs.</p>
<p>It is important to note is that structs are still little endian on all machines, so only use tricks like this if you can guarantee you're not shipping on a big endian machine (an <code>assert(FLATBUFFERS_LITTLEENDIAN)</code> would be wise).</p>
<h3>Access of untrusted buffers</h3>
<p>The generated accessor functions access fields over offsets, which is very quick. These offsets are not verified at run-time, so a malformed buffer could cause a program to crash by accessing random memory.</p>
<p>When you're processing large amounts of data from a source you know (e.g. your own generated data on disk), this is acceptable, but when reading data from the network that can potentially have been modified by an attacker, this is undesirable.</p>
<p>For this reason, you can optionally use a buffer verifier before you access the data. This verifier will check all offsets, all sizes of fields, and null termination of strings to ensure that when a buffer is accessed, all reads will end up inside the buffer.</p>
<p>Each root type will have a verification function generated for it, e.g. for <code>Monster</code>, you can call:</p>
<div class="fragment"><div class="line"><span class="keywordtype">bool</span> ok = VerifyMonsterBuffer(Verifier(buf, len));</div>
</div><!-- fragment --><p>if <code>ok</code> is true, the buffer is safe to read.</p>
<p>Besides untrusted data, this function may be useful to call in debug mode, as extra insurance against data being corrupted somewhere along the way.</p>
<p>While verifying a buffer isn't "free", it is typically faster than a full traversal (since any scalar data is not actually touched), and since it may cause the buffer to be brought into cache before reading, the actual overhead may be even lower than expected.</p>
<p>In specialized cases where a denial of service attack is possible, the verifier has two additional constructor arguments that allow you to limit the nesting depth and total amount of tables the verifier may encounter before declaring the buffer malformed.</p>
<h2>Text &amp; schema parsing</h2>
<p>Using binary buffers with the generated header provides a super low overhead use of FlatBuffer data. There are, however, times when you want to use text formats, for example because it interacts better with source control, or you want to give your users easy access to data.</p>
<p>Another reason might be that you already have a lot of data in JSON format, or a tool that generates JSON, and if you can write a schema for it, this will provide you an easy way to use that data directly.</p>
<p>(see the schema documentation for some specifics on the JSON format accepted).</p>
<p>There are two ways to use text formats:</p>
<h3>Using the compiler as a conversion tool</h3>
<p>This is the preferred path, as it doesn't require you to add any new code to your program, and is maximally efficient since you can ship with binary data. The disadvantage is that it is an extra step for your users/developers to perform, though you might be able to automate it. </p><pre class="fragment">flatc -b myschema.fbs mydata.json
</pre><p>This will generate the binary file <code>mydata_wire.bin</code> which can be loaded as before.</p>
<h3>Making your program capable of loading text directly</h3>
<p>This gives you maximum flexibility. You could even opt to support both, i.e. check for both files, and regenerate the binary from text when required, otherwise just load the binary.</p>
<p>This option is currently only available for C++, or Java through JNI.</p>
<p>As mentioned in the section "Building" above, this technique requires you to link a few more files into your program, and you'll want to include <code>flatbuffers/idl.h</code>.</p>
<p>Load text (either a schema or json) into an in-memory buffer (there is a convenient <code>LoadFile()</code> utility function in <code>flatbuffers/util.h</code> if you wish). Construct a parser:</p>
<div class="fragment"><div class="line">flatbuffers::Parser parser;</div>
</div><!-- fragment --><p>Now you can parse any number of text files in sequence:</p>
<div class="fragment"><div class="line">parser.Parse(text_file.c_str());</div>
</div><!-- fragment --><p>This works similarly to how the command-line compiler works: a sequence of files parsed by the same <code>Parser</code> object allow later files to reference definitions in earlier files. Typically this means you first load a schema file (which populates <code>Parser</code> with definitions), followed by one or more JSON files.</p>
<p>As optional argument to <code>Parse</code>, you may specify a null-terminated list of include paths. If not specified, any include statements try to resolve from the current directory.</p>
<p>If there were any parsing errors, <code>Parse</code> will return <code>false</code>, and <code>Parser::err</code> contains a human readable error string with a line number etc, which you should present to the creator of that file.</p>
<p>After each JSON file, the <code>Parser::fbb</code> member variable is the <code>FlatBufferBuilder</code> that contains the binary buffer version of that file, that you can access as described above.</p>
<p><code>samples/sample_text.cpp</code> is a code sample showing the above operations.</p>
<h3>Threading</h3>
<p>Reading a FlatBuffer does not touch any memory outside the original buffer, and is entirely read-only (all const), so is safe to access from multiple threads even without synchronisation primitives.</p>
<p>Creating a FlatBuffer is not thread safe. All state related to building a FlatBuffer is contained in a FlatBufferBuilder instance, and no memory outside of it is touched. To make this thread safe, either do not share instances of FlatBufferBuilder between threads (recommended), or manually wrap it in synchronisation primites. There's no automatic way to accomplish this, by design, as we feel multithreaded construction of a single buffer will be rare, and synchronisation overhead would be costly. </p>
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