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<!---
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This document contains embedded graphviz diagrams inside ```dot blocks.
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To convert it to rendered form using render.py:
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$ ./render.py wrapping-upb.in.md
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You can also live-preview this document with all diagrams using Markdown Preview Enhanced
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in Visual Studio Code:
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https://marketplace.visualstudio.com/items?itemName=shd101wyy.markdown-preview-enhanced
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--->
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# Wrapping upb in other languages
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upb is a C kernel that is designed to be wrapped in other languages. This is a
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guide for creating a new protobuf implementation based on upb.
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## What you will need
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There are certain things that the language runtime must provide in order to be
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wrapped by upb.
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1. **Finalizers, Destructors, or Cleaners**: This is one unavoidable
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requirement: the language *must* provide finalizers or destructors of some sort.
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There must be a way of calling a C function when the language GCs or otherwise
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destroys an object. We don't care much whether it is a finalizer, a destructor,
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or a cleaner, as long as it gets called eventually when the object is destroyed.
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Without finalizers, we would have no way of cleaning up upb data and everything
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would leak.
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2. **HashMap with weak values**: This is not an absolute requirement, but in
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languages with automatic memory management, we generally end up wanting a
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hash map with weak values to act as a `upb_msg* -> wrapper` object cache.
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We want the values to be weak (not the keys).
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## Reflection vs. Direct Access
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Each language wrapping upb gets to decide whether it will access messages
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through *reflection* or through *direct access*. This decision has some deep
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implications that will affect the design, features, and performance of your
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library.
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### Reflection
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The simplest option is to load full reflection data into the upb library at
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runtime. You can load reflection data using serialized descriptors, which are a
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stable and widely supported format across all protobuf tooling.
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```c
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// A upb_symtab is a dynamic container that we can load reflection data into.
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upb_symtab* symtab = upb_symtab_new();
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// We load reflection data via a serialized descriptor. The code generator
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// for your language should embed serialized descriptors into your generated
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// files; for each file you load, you can add the descriptor to the symtab as
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// shown.
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upb_arena *tmp = upb_arena_new();
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google_protobuf_FileDescriptorProto* file =
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google_protobuf_FileDescriptorProto_parse(desc_data, desc_size, tmp);
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if (!file || !upb_symtab_addfile(symtab, file, NULL)) {
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// Handle error.
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}
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upb_arena_free(tmp);
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// At application exit, we free the symtab.
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upb_symtab_free(symtab);
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```
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The `upb_symtab` will give you full access to all data from the `.proto` file,
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including convenient APIs like looking up a field by name. It will allow you to
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use JSON and text format. The APIs for accessing a message through reflection
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are simple and well-supported. These APIs cleanly encapsulate upb's internal
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implementation details.
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```c
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upb_symtab* symtab = BuildSymtab();
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// Look up a message type in the symtab.
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const upb_msgdef* m = upb_symtab_lookupmsg(symtab, "FooMessage");
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// Construct a new message of this type, via reflection.
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upb_arena *arena = upb_arena_new();
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upb_msg *msg = upb_msg_new(m, arena);
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// Set a message field using reflection.
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const upb_fielddef* f = upb_msgdef_ntof("bar_field");
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upb_msgval val = {.int32_val = 123};
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upb_msg_set(m, f, val, arena);
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// Free the message and symtab.
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upb_arena_free(arena);
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upb_symtab_free(symtab);
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```
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Using reflection is an natural choice in heavily reflective, dynamic runtimes
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like Python, Ruby, PHP, or Lua. These languages generally perform method
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dispatch through a dictionary/hash table anyway, so we are not adding any extra
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overhead by using upb's hash table to lookup fields by name at field access
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time.
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### Direct Access
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Using reflection has some downsides. Reflection data is relatively large, both
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in your binary (at rest) and in RAM (at runtime). It contains names of
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everything, and these names will be exposed in your binary. Reflection APIs for
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accessing a message will have more overhead than you might want, especially if
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crossing the FFI boundary for your language runtime imposes significant
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overhead.
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We can reduce these overheads by using *direct access*. upb's parser and
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serializer do not actually require full reflection data, they use a more compact
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data structure known as **mini tables**. Mini tables will take up less space
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than reflection, both in the binary and in RAM, and they will not leak field
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names. Mini tables will let us parse and serialize binary wire format data
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without reflection.
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```c
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// TODO: demonstrate upb API for loading mini table data at runtime.
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// This API does not exist yet.
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```
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To access messages themselves without the reflection API, we will be using
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different, lower-level APIs that will require you to supply precise data such as
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the offset of a given field. This is information that will come from the upb
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compiler framework, and the correctness (and even memory safety!) of the program
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will rely on you passing these values through from the upb compiler libraries to
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the upb runtime correctly.
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```c
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// TODO: demonstrate using low-level APIs for direct field access.
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// These APIs do not exist yet.
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```
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It can even be possible in certain circumstances to bypass the upb API completely
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and access raw field data directly at a given offset, using unsafe APIs like
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`sun.misc.unsafe`. This can theoretically allow for field access that is no
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more expensive than referencing a struct/class field.
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```java
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import sun.misc.Unsafe;
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class FooProto {
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private final long addr;
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private final Arena arena;
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// Accessor that a Java library built on upb could conceivably generate.
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long getFoo() {
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// The offset 1234 came from the upb compiler library, and was injected by the
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// Java+upb code generator.
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return Unsafe.getLong(self.addr + 1234);
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}
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}
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```
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It is always possible for a library built on direct access to also load reflection
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data as an add-on, optional package for when users want JSON, text format, or
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reflection-based access to a message. You do not give up any of these possibilities
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by using direct access.
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However, using direct access does have some noticeable downsides. It requires
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tighter coupling with upb's implementation details, as the mini table format is
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upb-specific and requires building your code generator against upb's compiler
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libraries. Any direct access of memory is especially tightly coupled, and would
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need to be changed if upb's in-memory format ever changes. It also is more
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prone to hard-to-debug memory errors if you make any mistakes.
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## Memory Management
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One of the core design challenges when wrapping upb is memory management. Every
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language runtime will have some memory management system, whether it is
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garbage collection, reference counting, manual memory management, or some hybrid
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of these. upb is written in C and uses arenas for memory management, but upb is
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designed to integrate with a wide variety of memory management schemes, and it
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provides a number of tools for making this integration as smooth as possible.
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### Arenas
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upb defines data structures in C to represent messages, arrays (repeated
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fields), and maps. A protobuf message is a hierarchical tree of these objects.
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For example, a relatively simple protobuf tree might look something like this:
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```dot {align="center"}
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digraph G {
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rankdir=LR;
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newrank=true;
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node [style="rounded,filled" shape=box colorscheme=accent8 fillcolor=1, ordering=out]
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upb_msg -> upb_msg2;
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upb_msg -> upb_array;
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upb_msg [label="upb Message" fillcolor=1]
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upb_msg2 [label="upb Message"];
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upb_array [label="upb Array"]
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}
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```
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All upb objects are allocated from an arena. An arena lets you allocate objects
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individually, but you cannot free individual objects; you can only free the arena
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as a whole. When the arena is freed, all of the individual objects allocated
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from that arena are freed together.
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```dot {align="center"}
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digraph G {
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rankdir=LR;
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newrank=true;
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subgraph cluster_0 {
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label = "upb Arena"
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graph[style="rounded,filled" fillcolor=gray]
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node [style="rounded,filled" shape=box colorscheme=accent8 fillcolor=1, ordering=out]
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upb_msg -> upb_array;
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upb_msg -> upb_msg2;
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upb_msg [label="upb Message" fillcolor=1]
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upb_msg2 [label="upb Message"];
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upb_array [label="upb Array"];
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}
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}
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```
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In simple cases, the entire tree of objects will all live in a single arena.
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This has the nice property that there cannot be any dangling pointers between
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objects, since all objects are freed at the same time.
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However upb allows you to create links between any two objects, whether or
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not they are in the same arena. The library does not know or care what arenas
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the objects are in when you create links between them.
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```dot {align="center"}
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digraph G {
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rankdir=LR;
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newrank=true;
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subgraph cluster_0 {
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label = "upb Arena 1"
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graph[style="rounded,filled" fillcolor=gray]
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node [style="rounded,filled" shape=box colorscheme=accent8 fillcolor=1, ordering=out]
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upb_msg -> upb_array;
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upb_msg -> upb_msg2;
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upb_msg [label="upb Message 1" fillcolor=1]
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upb_msg2 [label="upb Message 2"];
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upb_array [label="upb Array"];
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}
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subgraph cluster_1 {
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label = "upb Arena 2"
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graph[style="rounded,filled" fillcolor=gray]
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node [style="rounded,filled" shape=box colorscheme=accent8 fillcolor=1]
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upb_msg3;
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}
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upb_msg2 -> upb_msg3;
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upb_msg3 [label="upb Message 3"];
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}
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```
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When objects are on separate arenas, it is the user's responsibility to ensure
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that there are no dangling pointers. In the example above, this means Arena 2
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must outlive Message 1 and Message 2.
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### Integrating GC with upb
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In languages with automatic memory management, the goal is to handle all of the
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arenas behind the scenes, so that the user does not have to manage them manually
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or even know that they exist.
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We can achieve this goal if we set up the object graph in a particular way. The
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general strategy is to create wrapper objects around all of the C objects,
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including the arena. Our key goal is to make sure the arena wrapper is not
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GC'd until all of the C objects in that arena have become unreachable.
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For this example, we will assume we are wrapping upb in Python:
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```dot {align="center"}
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digraph G {
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rankdir=LR;
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newrank=true;
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compound=true;
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subgraph cluster_1 {
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label = "upb Arena"
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graph[style="rounded,filled" fillcolor=gray]
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node [style="rounded,filled" shape=box colorscheme=accent8 fillcolor=1, ordering=out]
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upb_msg -> upb_array [style=dashed];
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upb_msg -> upb_msg2 [style=dashed];
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upb_msg [label="upb Message" fillcolor=1]
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upb_msg2 [label="upb Message"];
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upb_array [label="upb Array"]
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dummy [style=invis]
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}
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subgraph cluster_python {
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node [style="rounded,filled" shape=box colorscheme=accent8 fillcolor=2]
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peripheries=0
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py_upb_msg [label="Python Message"];
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py_upb_msg2 [label="Python Message"];
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py_upb_arena [label="Python Arena"];
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}
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py_upb_msg -> upb_msg [style=dashed];
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py_upb_msg2->upb_msg2 [style=dashed];
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py_upb_msg2 -> py_upb_arena [color=springgreen4];
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py_upb_msg -> py_upb_arena [color=springgreen4];
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py_upb_arena -> dummy [lhead=cluster_1, color=red];
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{
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rank=same;
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upb_msg;
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py_upb_msg;
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}
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{
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rank=same;
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upb_array;
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upb_msg2;
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py_upb_msg2;
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}
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{ rank=same;
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dummy;
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py_upb_arena;
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}
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dummy->upb_array [style=invis];
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dummy->upb_msg2 [style=invis];
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subgraph cluster_01 {
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|
node [shape=plaintext]
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peripheries=0
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key [label=<<table border="0" cellpadding="2" cellspacing="0" cellborder="0">
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<tr><td align="right" port="i1">raw ptr</td></tr>
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|
<tr><td align="right" port="i2">unique ptr</td></tr>
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<tr><td align="right" port="i3">shared (GC) ptr</td></tr>
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</table>>]
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key2 [label=<<table border="0" cellpadding="2" cellspacing="0" cellborder="0">
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<tr><td port="i1"> </td></tr>
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<tr><td port="i2"> </td></tr>
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<tr><td port="i3"> </td></tr>
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</table>>]
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key:i1:e -> key2:i1:w [style=dashed]
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key:i2:e -> key2:i2:w [color=red]
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key:i3:e -> key2:i3:w [color=springgreen4]
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|
}
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key2:i1:w -> upb_msg [style=invis];
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{
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rank=same;
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key;
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upb_msg;
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}
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}
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```
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In this example we have three different kinds of pointers:
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* **raw ptr**: This is a pointer that carries no ownership.
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* **unique ptr**: This is a pointer has *unique ownership* of the target. The owner
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will free the target in its destructor (or finalizer, or cleaner). There can
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only be a single unique pointer to a given object.
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* **shared (GC) ptr**: This is a pointer that has *shared ownership* of the
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|
target. Many objects can point to the target, and the target will be deleted
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|
only when all such references are gone. In a runtime with automatic memory
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|
|
management (GC), this is a reference that participates in GC. In Python such
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|
|
references use reference counting, but in other VMs they may use mark and
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|
|
sweep or some other form of GC instead.
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The Python Message wrappers have only raw pointers to the underlying message,
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|
but they contain a shared pointer to the arena that will ensure that the raw
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pointer remains valid. Only when all message wrapper objects are destroyed
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will the Python Arena become unreachable, and the upb arena ultimately freed.
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### Links between arenas with "Fuse"
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The design given above works well for objects that live in a single arena. But
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what if a user wants to create a link between two objects in different arenas?
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TODO
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## UTF-8 vs. UTF-16
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TODO
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## Object Cache
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TODO
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