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Protocol Buffers - Google's data interchange format
Your Swiss Army Knife for Protocol Buffers
A new way of working with Protocol Buffers.
Documentation generator plugin for Google Protocol Buffers
Google ProtocolBuffers for Apple Swift
Updated
May 30, 2019
Swift
Protocol Buffers Compiler (protoc) plugin for TypeScript and gRPC-Web.
Updated
Sep 11, 2020
TypeScript
A pure Elixir implementation of Google Protobuf
Updated
Aug 6, 2020
Elixir
Protocol Buffer companion tool. Track your .proto files and prevent changes to messages and services which impact API compatibility.
📂 generic protocol generator based on golang's text/template (grpc/protobuf)
Bazel rules for building protocol buffers and gRPC services (java, c++, go, ...)
Updated
Sep 23, 2019
Python
Protocol Buffers Dynamic Schema - create protobuf schemas programmatically
Updated
Apr 26, 2020
Java
Protocol Buffers protobuf maven plugin - based on protoc-jar multi-platform executable protoc JAR
Useful extensions for the grpc-java library
A package-at-a-time wrapper for protoc, for generating Go protobuf code.
Maven Plugin that executes the Protocol Buffers (protoc) compiler
Updated
Aug 16, 2020
Java
Kotlin Code Generator and Runtime for Protocol Buffers
Updated
Jan 3, 2020
Kotlin
Protocol Buffers protobuf compiler - multi-platform executable protoc JAR and API
Updated
Jun 12, 2020
Java
Protoc plugins for generating graphql schema and quickly create servers
transforming your .proto files into .dot files (and .svg, .png if you happen to have graphviz installed)
Some useful Go's protoc plugins.
基于云风的sproto二进制标准上的描述文件及代码生成工具
An all-inclusive protoc Docker image
Updated
Aug 7, 2020
Dockerfile
Generate Kotlin gRPC client libraries from Protocol Buffer definitions.
Updated
Mar 10, 2020
Kotlin
A starter kit for building protoc plugins. Rather than write your own, you can just use an existing one.
protoc plugin to generate to Go's net/http converter
graphql-go schema generator by proto files
Protocol Buffers Compiler Plugin and Support Library for D
protoc-gen-go patch utility
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As discussed in #217, the implementation of UUID matching is sub-optimal because it uses a hard coded constant regex string passed to a regex library. Significant performance gains can be achieved by replacing constant regex expressions with bespoke state machines.
This work is worth doing because UUIDs are so common in distributed systems and PGV sits on the hot path of every service request.