GitHub Java Daily Trending

spring-projects/spring-boot

Spring Boot helps you to create Spring-powered, production-grade applications and services with absolute minimum fuss.

Spring Boot

Spring Boot helps you to create Spring-powered, production-grade applications and services with absolute minimum fuss. It takes an opinionated view of the Spring platform so that new and existing users can quickly get to the bits they need.

You can use Spring Boot to create stand-alone Java applications that can be started using java -jar or more traditional WAR deployments. We also provide a command-line tool that runs Spring scripts.

Our primary goals are:

Provide a radically faster and widely accessible getting started experience for all Spring development.
Be opinionated, but get out of the way quickly as requirements start to diverge from the defaults.
Provide a range of non-functional features common to large classes of projects (for example, embedded servers, security, metrics, health checks, externalized configuration).
Absolutely no code generation and no requirement for XML configuration.

Installation and Getting Started

The reference documentation includes detailed installation instructions as well as a comprehensive getting started guide.

Here is a quick teaser of a complete Spring Boot application in Java:

import org.springframework.boot.*;
import org.springframework.boot.autoconfigure.*;
import org.springframework.web.bind.annotation.*;

@RestController
@SpringBootApplication
public class Example {

	@RequestMapping("/")
	String home() {
		return "Hello World!";
	}

	public static void main(String[] args) {
		SpringApplication.run(Example.class, args);
	}

}

Getting Help

Are you having trouble with Spring Boot? We want to help!

Check the reference documentation, especially the How-to’s — they provide solutions to the most common questions.
Learn the Spring basics — Spring Boot builds on many other Spring projects; check the spring.io website for a wealth of reference documentation. If you are new to Spring, try one of the guides.
If you are upgrading, read the release notes for upgrade instructions and "new and noteworthy" features.
Ask a question — we monitor stackoverflow.com for questions tagged with spring-boot.
Report bugs with Spring Boot at github.com/spring-projects/spring-boot/issues.

Contributing

We welcome contributions of all kinds! Please read our contribution guidelines before submitting a pull request.

Reporting Issues

Spring Boot uses GitHub’s integrated issue tracking system to record bugs and feature requests. If you want to raise an issue, please follow the recommendations below:

Before you log a bug, please search the issue tracker to see if someone has already reported the problem.
If the issue doesn’t already exist, create a new issue.
Please provide as much information as possible with the issue report. We like to know the Spring Boot version, operating system, and JVM version you’re using.
If you need to paste code or include a stack trace, use Markdown. ``` escapes before and after your text.
If possible, try to create a test case or project that replicates the problem and attach it to the issue.

Building from Source

You don’t need to build from source to use Spring Boot. If you want to try out the latest and greatest, Spring Boot can be built and published to your local Maven cache using the Gradle wrapper. You also need JDK 25.

$ ./gradlew publishToMavenLocal

This command builds all modules and publishes them to your local Maven cache. It won’t run any of the tests. If you want to build everything, use the build task:

$ ./gradlew build

Guides

The spring.io site contains several guides that show how to use Spring Boot step-by-step:

Building an Application with Spring Boot is an introductory guide that shows you how to create an application, run it, and add some management services.
Building a RESTful Web Service with Spring Boot Actuator is a guide to creating a REST web service and also shows how the server can be configured.

License

Spring Boot is Open Source software released under the Apache 2.0 license.

github/copilot-sdk

Multi-platform SDK for integrating GitHub Copilot Agent into apps and services

GitHub Copilot CLI SDKs

Agents for every app.

Embed Copilot's agentic workflows in your application with the GitHub Copilot SDK for Python, TypeScript, Go, .NET, Java, and Rust.

The GitHub Copilot SDK exposes the same engine behind Copilot CLI: a production-tested agent runtime you can invoke programmatically. No need to build your own orchestration—you define agent behavior, Copilot handles planning, tool invocation, file edits, and more.

Available SDKs

SDK	Location	Cookbook	Installation
Node.js / TypeScript	`nodejs/`	Cookbook	`npm install @github/copilot-sdk`
Python	`python/`	Cookbook	`pip install github-copilot-sdk`
Go	`go/`	Cookbook	`go get github.com/github/copilot-sdk/go`
.NET	`dotnet/`	Cookbook	`dotnet add package GitHub.Copilot.SDK`
Rust	`rust/`	—	`cargo add github-copilot-sdk`
Java	`java/`	Cookbook	Maven coordinates `com.github:copilot-sdk-java` See instructions for Maven and Gradle

See the individual SDK READMEs for installation, usage examples, and API reference.

Getting Started

For a complete walkthrough, see the Getting Started Guide.

Quick steps:

(Optional) Install the Copilot CLI

For Node.js, Python, and .NET SDKs, the Copilot CLI is bundled automatically and no separate installation is required. For Go, Java, and Rust, install the CLI manually or ensure copilot is available in your PATH. Go and Rust also expose application-level CLI bundling features.

Install your preferred SDK using the commands above.
See the SDK README for usage examples and API documentation.

Architecture

All SDKs communicate with the Copilot CLI server via JSON-RPC:

Your Application
       ↓
  SDK Client
       ↓ JSON-RPC
  Copilot CLI (server mode)

The SDK manages the CLI process lifecycle automatically. You can also connect to an external CLI server—see the Getting Started Guide for details on running the CLI in server mode.

FAQ

Do I need a GitHub Copilot subscription to use the SDK?

Yes, a GitHub Copilot subscription is required to use the GitHub Copilot SDK, unless you are using BYOK (Bring Your Own Key). With BYOK, you can use the SDK without GitHub authentication by configuring your own API keys from supported LLM providers. For standard usage (non-BYOK), refer to the GitHub Copilot pricing page, which includes a free tier with limited usage.

How does billing work for SDK usage?

Billing for the GitHub Copilot SDK is based on the same model as the Copilot CLI, with each prompt being counted towards your premium request quota. For more information on premium requests, see Requests in GitHub Copilot.

Does it support BYOK (Bring Your Own Key)?

Yes, the GitHub Copilot SDK supports BYOK (Bring Your Own Key). You can configure the SDK to use your own API keys from supported LLM providers (e.g. OpenAI, Azure AI Foundry, Anthropic) to access models through those providers. See the BYOK documentation for setup instructions and examples.

Note: BYOK uses key-based authentication only. Microsoft Entra ID (Azure AD), managed identities, and third-party identity providers are not supported.

What authentication methods are supported?

The SDK supports multiple authentication methods:

GitHub signed-in user - Uses stored OAuth credentials from copilot CLI login
OAuth GitHub App - Pass user tokens from your GitHub OAuth app
Environment variables - COPILOT_GITHUB_TOKEN, GH_TOKEN, GITHUB_TOKEN
BYOK - Use your own API keys (no GitHub auth required)

See the Authentication documentation for details on each method.

Do I need to install the Copilot CLI separately?

No — for Node.js, Python, and .NET SDKs, the Copilot CLI is bundled automatically as a dependency. You do not need to install it separately.

For Go, Java, and Rust SDKs, the CLI is not bundled by default. Install the CLI manually or ensure copilot is available in your PATH. Go and Rust also expose application-level CLI bundling features.

Advanced: You can override the CLI binary or connect to an external server. See the individual SDK README for language-specific options.

What tools are enabled by default?

By default, the SDK exposes the Copilot CLI's first-party tools, similar to running the CLI with --allow-all. Tool execution is still governed by each SDK's permission handler, so applications can approve, deny, or customize tool calls. You can customize tool availability by configuring the SDK client options to enable and disable specific tools. Refer to the individual SDK documentation for details on tool configuration and to the Copilot CLI documentation for the list of available tools.

Can I use custom agents, skills or tools?

Yes, the GitHub Copilot SDK allows you to define custom agents, skills, and tools. You can extend the functionality of the agents by implementing your own logic and integrating additional tools as needed. Refer to the SDK documentation of your preferred language for more details.

Are there instructions or SDK guidance for Copilot to speed up development?

Yes, check out the custom instructions and SDK-specific guidance:

Node.js / TypeScript
Python
.NET
Go
Rust (SDK guidance; custom instructions not yet published)
Java

What models are supported?

All models available via Copilot CLI are supported in the SDK. The SDK also exposes a method which will return the models available so they can be accessed at runtime.

Is the SDK production-ready?

The GitHub Copilot SDK is generally available and follows semantic versioning. See CHANGELOG.md for release notes.

How do I report issues or request features?

Please use the GitHub Issues page to report bugs or request new features. We welcome your feedback to help improve the SDK.

Quick Links

Documentation – Full documentation index
Getting Started – Tutorial to get up and running
Setup Guides – Architecture, deployment, and scaling
Authentication – GitHub OAuth, BYOK, and more
Features – Hooks, custom agents, MCP, skills, and more
Troubleshooting – Common issues and solutions
Cookbook – Practical recipes for common tasks across all languages
More Resources – Additional examples, tutorials, and community resources

Unofficial, Community-maintained SDKs

⚠️ Disclaimer: These are unofficial, community-driven SDKs and they are not supported by GitHub. Use at your own risk.

SDK	Location
Clojure	copilot-community-sdk/copilot-sdk-clojure
C++	0xeb/copilot-sdk-cpp

Contributing

See CONTRIBUTING.md for contribution guidelines.

License

MIT

agentscope-ai/agentscope-java

AgentScope Java: Agent-Oriented Programming for Building LLM Applications

Build Production-Ready AI Agents in Java

📖 Documentation | 中文 | Discord

AgentScope Java is an agent-oriented programming framework for building LLM-powered applications. It provides everything you need to create intelligent agents: ReAct reasoning, tool calling, memory management, multi-agent collaboration, and more.

Highlights

🎯 Smart Agents, Full Control

AgentScope adopts the ReAct (Reasoning-Acting) paradigm, enabling agents to autonomously plan and execute complex tasks. Unlike rigid workflow-based approaches, ReAct agents dynamically decide which tools to use and when, adapting to changing requirements in real-time.

However, autonomy without control is a liability in production. AgentScope provides comprehensive runtime intervention mechanisms:

Safe Interruption - Pause agent execution at any point while preserving full context and tool state, enabling seamless resumption without data loss
Graceful Cancellation - Terminate long-running or unresponsive tool calls without corrupting agent state, allowing immediate recovery and redirection
Human-in-the-Loop - Inject corrections, additional context, or guidance at any reasoning step through the Hook system, maintaining human oversight over critical decisions

🛠️ Built-in Tools

AgentScope includes production-ready tools that address common challenges in agent development:

PlanNotebook - A structured task management system that decomposes complex objectives into ordered, trackable steps. Agents can create, modify, pause, and resume multiple concurrent plans, ensuring systematic execution of multi-step workflows.
Structured Output - A self-correcting output parser that guarantees type-safe responses. When LLM output deviates from the expected format, the system automatically detects errors and guides the model to produce valid output, mapping results directly to Java POJOs without manual parsing.
Long-term Memory - Persistent memory storage with semantic search capabilities across sessions. Supports automatic management, agent-controlled recording, or hybrid modes. Enables multi-tenant isolation for enterprise deployments where agents serve multiple users independently.
RAG (Retrieval-Augmented Generation) - Seamless integration with enterprise knowledge bases. Supports both self-hosted embedding-based retrieval and managed services like Alibaba Cloud Bailian, grounding agent responses in authoritative data sources.

🔌 Seamless Integration

AgentScope is designed to integrate with existing enterprise infrastructure without requiring extensive modifications:

MCP Protocol - Integrate with any MCP-compatible server to instantly extend agent capabilities. Connect to the growing ecosystem of MCP tools and services—from file systems and databases to web browsers and code interpreters—without writing custom integration code.
A2A Protocol - Enable distributed multi-agent collaboration through standard service discovery. Register agent capabilities to Nacos or similar registries, allowing agents to discover and invoke each other as naturally as calling microservices.

🚀 Production Grade

Built for enterprise deployment requirements:

High Performance - Reactive architecture based on Project Reactor ensures non-blocking execution. GraalVM native image compilation achieves 200ms cold start times, making AgentScope suitable for serverless and auto-scaling environments.
Security Sandbox - AgentScope Runtime provides isolated execution environments for untrusted tool code. Includes pre-built sandboxes for GUI automation, file system operations, and mobile device interaction, preventing unauthorized access to system resources.
Observability - Native integration with OpenTelemetry for distributed tracing across the entire agent execution pipeline. AgentScope Studio provides visual debugging, real-time monitoring, and comprehensive logging for development and production environments.

Quick Start

Requirements: JDK 17+

<dependency>
    <groupId>io.agentscope</groupId>
    <artifactId>agentscope</artifactId>
    <version>1.0.12</version>
</dependency>

ReActAgent agent = ReActAgent.builder()
    .name("Assistant")
    .sysPrompt("You are a helpful AI assistant.")
    .model(DashScopeChatModel.builder()
        .apiKey(System.getenv("DASHSCOPE_API_KEY"))
        .modelName("qwen-max")
        .build())
    .build();

Msg response = agent.call(Msg.builder()
        .textContent("Hello!")
        .build()).block();
System.out.println(response.getTextContent());

For more examples, see the documentation.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Community

Discord	DingTalk	WeChat

License

Apache License 2.0 - see LICENSE for details.

Publications

If you find AgentScope helpful, please cite our papers:

Contributors

OpenAPITools/openapi-generator

OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (v2, v3)

OpenAPI Generator

Master (7.23.0):

⭐⭐⭐ If you would like to contribute, please refer to guidelines and a list of open tasks. ⭐⭐⭐

‼️ To migrate from Swagger Codegen to OpenAPI Generator, please refer to the migration guide ‼️

📔 For more information, please refer to the Wiki page and FAQ 📔

📔 The eBook A Beginner's Guide to Code Generation for REST APIs is a good starting point for beginners 📔

⚠️ If the OpenAPI spec, templates or any input (e.g. options, environment variables) is obtained from an untrusted source or environment, please make sure you've reviewed these inputs before using OpenAPI Generator to generate the API client, server stub or documentation to avoid potential security issues (e.g. code injection). For security vulnerabilities, please contact team@openapitools.org. ⚠️

‼️ Both "OpenAPI Tools" (https://OpenAPITools.org - the parent organization of OpenAPI Generator) and "OpenAPI Generator" are not affiliated with OpenAPI Initiative (OAI) ‼️

Overview

OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (both 2.0 and 3.0 are supported). Currently, the following languages/frameworks are supported:

	Languages/Frameworks
API clients	ActionScript, Ada, Apex, Bash, C, C# (.net 2.0, 3.5 or later, .NET Standard 1.3 - 2.1, .NET Core 3.1, .NET 5.0. Libraries: RestSharp, GenericHost, HttpClient), C++ (Arduino, cpp-restsdk, Qt5, Tizen, Unreal Engine 4), Clojure, Crystal, Dart, Elixir, Elm, Eiffel, Erlang, Go, Groovy, Haskell (http-client, Servant), Java (Apache HttpClient 4.x, Apache HttpClient 5.x, Jersey2.x, OkHttp, Retrofit1.x, Retrofit2.x, Feign, RestTemplate, RESTEasy, Vertx, Google API Client Library for Java, Rest-assured, Spring 5 Web Client, Spring 6 RestClient, MicroProfile Rest Client, Helidon), Jetbrains HTTP Client, Julia, k6, Kotlin, Lua, N4JS, Nim, Node.js/JavaScript (ES5, ES6, AngularJS with Google Closure Compiler annotations, Flow types, Apollo GraphQL DataStore), Objective-C, OCaml, Perl, PHP, PowerShell, Python, R, Ruby, Rust (hyper, reqwest, rust-server), Scala (akka, http4s, scalaz, sttp, swagger-async-httpclient, pekko), Swift (2.x, 3.x, 4.x, 5.x, 6.x), Typescript (AngularJS, Angular (9.x - 19.x), Aurelia, Axios, Fetch, Inversify, jQuery, Nestjs, Node, redux-query, Rxjs), XoJo, Zapier
Server stubs	Ada, C# (ASP.NET Core, Azure Functions), C++ (Httplib, Oat++, Pistache, Restbed, Qt5 QHTTPEngine), Erlang, F# (Giraffe), Go (net/http, Gin, Echo), Haskell (Servant, Yesod), Java (MSF4J, Spring, Undertow, JAX-RS: CDI, CXF, Inflector, Jersey, RestEasy, Play Framework, PKMST, Vert.x, Apache Camel, Helidon), Julia, Kotlin (Spring Boot, Ktor, Vert.x), PHP (Flight, Laravel, Lumen, Mezzio (fka Zend Expressive), Slim, Silex, Symfony), Python (FastAPI, Flask), NodeJS, Ruby (Sinatra, Rails5), Rust (rust-server), Scala (Akka, Finch, Lagom, Play, Cask, Scalatra)
API documentation generators	HTML, Confluence Wiki, Asciidoc, Markdown, PlantUML
Configuration files	Apache2
Others	GraphQL, JMeter, Ktorm, MySQL Schema, Postman Collection, Protocol Buffer, WSDL

1 - Installation

1.1 - Compatibility

The OpenAPI Specification has undergone 3 revisions since initial creation in 2010. The openapi-generator project has the following compatibilities with the OpenAPI Specification:

OpenAPI Generator Version	Release Date	Notes
7.23.0 (upcoming minor release) SNAPSHOT	08.06.2026	Minor release with breaking changes (with fallback)
7.22.0 (latest stable release)	28.04.2026	Minor release with breaking changes (with fallback)
6.6.0	11.05.2023	Minor release with breaking changes (with fallback)
5.4.0	31.01.2022	Minor release with breaking changes (with fallback)
4.3.1	06.05.2020	Patch release (enhancements, bug fixes, etc)

OpenAPI Spec compatibility: 1.0, 1.1, 1.2, 2.0, 3.0, 3.1 (beta support)

(We do not publish daily/nightly build. Please use SNAPSHOT instead)

For old releases, please refer to the Release page.

For decommissioned generators/libraries/frameworks, please refer to the "Decommission" label in the pull request page.

1.2 - Artifacts on Maven Central

You can find our released artifacts on maven central:

Core:

<dependency>
    <groupId>org.openapitools</groupId>
    <artifactId>openapi-generator</artifactId>
    <version>${openapi-generator-version}</version>
</dependency>

See the different versions of the openapi-generator artifact available on maven central.

Cli:

<dependency>
    <groupId>org.openapitools</groupId>
    <artifactId>openapi-generator-cli</artifactId>
    <version>${openapi-generator-version}</version>
</dependency>

See the different versions of the openapi-generator-cli artifact available on maven central.

Maven plugin:

<dependency>
    <groupId>org.openapitools</groupId>
    <artifactId>openapi-generator-maven-plugin</artifactId>
    <version>${openapi-generator-version}</version>
</dependency>

See the different versions of the openapi-generator-maven-plugin artifact available on maven central.
Readme

Gradle plugin:

<dependency>
    <groupId>org.openapitools</groupId>
    <artifactId>openapi-generator-gradle-plugin</artifactId>
    <version>${openapi-generator-version}</version>
</dependency>

See the different versions of the openapi-generator-gradle-plugin artifact available on maven central.
Readme

1.3 - Download JAR

If you're looking for the latest stable version, you can grab it directly from Maven.org (Java 11 runtime at a minimum):

JAR location: https://repo1.maven.org/maven2/org/openapitools/openapi-generator-cli/7.22.0/openapi-generator-cli-7.22.0.jar

For Mac/Linux users:

wget https://repo1.maven.org/maven2/org/openapitools/openapi-generator-cli/7.22.0/openapi-generator-cli-7.22.0.jar -O openapi-generator-cli.jar

For Windows users, you will need to install wget or you can use Invoke-WebRequest in PowerShell (3.0+), e.g.

Invoke-WebRequest -OutFile openapi-generator-cli.jar https://repo1.maven.org/maven2/org/openapitools/openapi-generator-cli/7.22.0/openapi-generator-cli-7.22.0.jar

After downloading the JAR, run java -jar openapi-generator-cli.jar help to show the usage.

For Mac users, please make sure Java 11 is installed (Tips: run java -version to check the version), and export JAVA_HOME in order to use the supported Java version:

export JAVA_HOME=`/usr/libexec/java_home -v 1.11`
export PATH=${JAVA_HOME}/bin:$PATH

Launcher Script

One downside to manual jar downloads is that you don't keep up-to-date with the latest released version. We have a Bash launcher script at bin/utils/openapi-generator.cli.sh which resolves this issue.

To install the launcher script, copy the contents of the script to a location on your path and make the script executable.

An example of setting this up (NOTE: Always evaluate scripts curled from external systems before executing them).

mkdir -p ~/bin/openapitools
curl https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/bin/utils/openapi-generator-cli.sh > ~/bin/openapitools/openapi-generator-cli
chmod u+x ~/bin/openapitools/openapi-generator-cli
export PATH=$PATH:~/bin/openapitools/

Now, openapi-generator-cli is "installed". On invocation, it will query the GitHub repository for the most recently released version. If this matches the last downloaded jar, it will execute as normal. If a newer version is found, the script will download the latest release and execute it.

If you need to invoke an older version of the generator, you can define the variable OPENAPI_GENERATOR_VERSION either ad hoc or globally. You can export this variable if you'd like to persist a specific release version.

Examples:

# Execute latest released openapi-generator-cli
openapi-generator-cli version

# Execute version 4.1.0 for the current invocation, regardless of the latest released version
OPENAPI_GENERATOR_VERSION=4.1.0 openapi-generator-cli version

# Execute version 4.1.0-SNAPSHOT for the current invocation
OPENAPI_GENERATOR_VERSION=4.1.0-SNAPSHOT openapi-generator-cli version

# Execute version 4.0.2 for every invocation in the current shell session
export OPENAPI_GENERATOR_VERSION=4.0.2
openapi-generator-cli version # is 4.0.2
openapi-generator-cli version # is also 4.0.2

# To "install" a specific version, set the variable in .bashrc/.bash_profile
echo "export OPENAPI_GENERATOR_VERSION=4.0.2" >> ~/.bashrc
source ~/.bashrc
openapi-generator-cli version # is always 4.0.2, unless any of the above overrides are done ad hoc

1.4 - Build Projects

To build from source, you need the following installed and available in your $PATH:

Java 11
Apache Maven 3.8.8 or greater (optional)

After cloning the project, you can build it from source using maven wrapper:

Linux: ./mvnw clean install
Windows: mvnw.cmd clean install

Nix users

If you're a nix user, you can enter OpenAPI Generator shell, by typing:

nix develop

It will enter a shell with Java 11 installed.

Direnv supports automatically loading of the nix developer shell, so if you're using direnv too, type:

direnv allow

and have java and mvn set up with correct versions each time you enter project directory.

The default build contains minimal static analysis (via CheckStyle). To run your build with PMD and Spotbugs, use the static-analysis profile:

Linux: ./mvnw -Pstatic-analysis clean install
Windows: mvnw.cmd -Pstatic-analysis clean install

1.5 - Homebrew

To install, run brew install openapi-generator

Here is an example usage to generate a Ruby client:

openapi-generator generate -i https://raw.githubusercontent.com/openapitools/openapi-generator/master/modules/openapi-generator/src/test/resources/3_0/petstore.yaml -g ruby -o /tmp/test/

To reinstall with the latest master, run brew uninstall openapi-generator && brew install --HEAD openapi-generator

To install OpenJDK (pre-requisites), please run

brew tap AdoptOpenJDK/openjdk
brew install --cask adoptopenjdk11
export JAVA_HOME=`/usr/libexec/java_home -v 1.11`

or download installer via https://adoptium.net/

To install Maven (optional), please run

brew install maven

1.6 - Docker

Public Pre-built Docker images

https://hub.docker.com/r/openapitools/openapi-generator-cli/ (official CLI)
https://hub.docker.com/r/openapitools/openapi-generator-online/ (official web service)

OpenAPI Generator CLI Docker Image

The OpenAPI Generator image acts as a standalone executable. It can be used as an alternative to installing via homebrew, or for developers who are unable to install Java or upgrade the installed version.

To generate code with this image, you'll need to mount a local location as a volume.

Example:

docker run --rm -v "${PWD}:/local" openapitools/openapi-generator-cli generate \
    -i https://raw.githubusercontent.com/openapitools/openapi-generator/master/modules/openapi-generator/src/test/resources/3_0/petstore.yaml \
    -g go \
    -o /local/out/go

The generated code will be located under ./out/go in the current directory.

OpenAPI Generator Online Docker Image

The openapi-generator-online image can act as a self-hosted web application and API for generating code. This container can be incorporated into a CI pipeline, and requires at least two HTTP requests and some docker orchestration to access generated code.

Example usage:

# Start container at port 8888 and save the container id
> CID=$(docker run -d -p 8888:8080 openapitools/openapi-generator-online)

# allow for startup
> sleep 10

# Get the IP of the running container (optional)
GEN_IP=$(docker inspect --format '{{.NetworkSettings.IPAddress}}'  $CID)

# Execute an HTTP request to generate a Ruby client
> curl -X POST --header 'Content-Type: application/json' --header 'Accept: application/json' \
-d '{"openAPIUrl": "https://raw.githubusercontent.com/openapitools/openapi-generator/master/modules/openapi-generator/src/test/resources/3_0/petstore.yaml"}' \
'http://localhost:8888/api/gen/clients/ruby'

{"code":"c2d483.3.4672-40e9-91df-b9ffd18d22b8","link":"http://localhost:8888/api/gen/download/c2d483.3.4672-40e9-91df-b9ffd18d22b8"}

# Download the generated zip file
> wget http://localhost:8888/api/gen/download/c2d483.3.4672-40e9-91df-b9ffd18d22b8

# Unzip the file
> unzip c2d483.3.4672-40e9-91df-b9ffd18d22b8

# Shutdown the openapi generator image
> docker stop $CID && docker rm $CID

Development in docker

You can use run-in-docker.sh to do all development. This script maps your local repository to /gen in the docker container. It also maps ~/.m2/repository to the appropriate container location.

To execute mvn package:

git clone https://github.com/openapitools/openapi-generator
cd openapi-generator
./run-in-docker.sh mvn package

Build artifacts are now accessible in your working directory.

Once built, run-in-docker.sh will act as an executable for openapi-generator-cli. To generate code, you'll need to output to a directory under /gen (e.g. /gen/out). For example:

./run-in-docker.sh help # Executes 'help' command for openapi-generator-cli
./run-in-docker.sh list # Executes 'list' command for openapi-generator-cli
./run-in-docker.sh generate -i modules/openapi-generator/src/test/resources/3_0/petstore.yaml \
    -g go -o /gen/out/go-petstore -p packageName=petstore # generates go client, outputs locally to ./out/go-petstore

Troubleshooting

If an error like this occurs, just execute the mvn clean install -U command:

org.apache.maven.lifecycle.LifecycleExecutionException: Failed to execute goal org.apache.maven.plugins:maven-surefire-plugin:2.19.1:test (default-test) on project openapi-generator: A type incompatibility occurred while executing org.apache.maven.plugins:maven-surefire-plugin:2.19.1:test: java.lang.ExceptionInInitializerError cannot be cast to java.io.IOException

./run-in-docker.sh mvn clean install -U

Failed to execute goal org.fortasoft:gradle-maven-plugin:1.0.8:invoke (default) on project openapi-generator-gradle-plugin-mvn-wrapper: org.gradle.tooling.BuildException: Could not execute build using Gradle distribution 'https://services.gradle.org/distributions/gradle-4.7-bin.zip'

Right now: no solution for this one 😐

Run Docker in Vagrant

Prerequisite: install Vagrant and VirtualBox.

git clone https://github.com/openapitools/openapi-generator.git
cd openapi-generator
vagrant up
vagrant ssh
cd /vagrant
./run-in-docker.sh mvn package

1.7 - NPM

There is also an NPM package wrapper available for different platforms (e.g. Linux, Mac, Windows). (JVM is still required) Please see the project's README there for more information.

Install it globally to get the CLI available on the command line:

npm install @openapitools/openapi-generator-cli -g
openapi-generator-cli version

To use a specific version of "openapi-generator-cli"

openapi-generator-cli version-manager set 7.22.0

Or install it as dev-dependency:

npm install @openapitools/openapi-generator-cli -D

You can use locally built JARs or SNAPSHOT versions as well.

1.8 - pip

Platform(s): Linux, macOS, Windows Install via PyPI (java executable is needed to run):

pip install openapi-generator-cli

To install a specific version

pip install openapi-generator-cli==7.22.0

You can also install with jdk4py instead of java binary. (python>=3.10 is required)

pip install openapi-generator-cli[jdk4py]

Ref: https://github.com/openAPITools/openapi-generator-pip

2 - Getting Started

To generate a PHP client for petstore.yaml, please run the following

git clone https://github.com/openapitools/openapi-generator
cd openapi-generator
./mvnw clean package
java -jar modules/openapi-generator-cli/target/openapi-generator-cli.jar generate \
   -i https://raw.githubusercontent.com/openapitools/openapi-generator/master/modules/openapi-generator/src/test/resources/3_0/petstore.yaml \
   -g php \
   -o /var/tmp/php_api_client

(if you're on Windows, replace the last command with java -jar modules\openapi-generator-cli\target\openapi-generator-cli.jar generate -i https://raw.githubusercontent.com/openapitools/openapi-generator/master/modules/openapi-generator/src/test/resources/3_0/petstore.yaml -g php -o c:\temp\php_api_client)

You can also download the JAR (latest release) directly from maven.org

To get a list of general options available, please run java -jar modules/openapi-generator-cli/target/openapi-generator-cli.jar help generate

To get a list of PHP specified options (which can be passed to the generator with a config file via the -c option), please run java -jar modules/openapi-generator-cli/target/openapi-generator-cli.jar config-help -g php

3 - Usage

To generate a sample client library

You can build a client against the Petstore API as follows:

./bin/generate-samples.sh ./bin/configs/java-okhttp-gson.yaml

(On Windows, please install GIT Bash for Windows to run the command above)

This script uses the default library, which is okhttp-gson. It will run the generator with this command:

java -jar modules/openapi-generator-cli/target/openapi-generator-cli.jar generate \
  -i https://raw.githubusercontent.com/openapitools/openapi-generator/master/modules/openapi-generator/src/test/resources/3_0/petstore.yaml \
  -g java \
  -t modules/openapi-generator/src/main/resources/Java \
  --additional-properties artifactId=petstore-okhttp-gson,hideGenerationTimestamp=true \
  -o samples/client/petstore/java/okhttp-gson

with a number of options. The java options are documented here.

You can also get the options with the help generate command (below only shows partial results):

NAME
        openapi-generator-cli generate - Generate code with the specified
        generator.

SYNOPSIS
        openapi-generator-cli generate
                [(-a <authorization> | --auth <authorization>)]
                [--api-name-suffix <api name suffix>] [--api-package <api package>]
                [--artifact-id <artifact id>] [--artifact-version <artifact version>]
                [(-c <configuration file> | --config <configuration file>)] [--dry-run]
                [(-e <templating engine> | --engine <templating engine>)]
                [--enable-post-process-file]
                [(-g <generator name> | --generator-name <generator name>)]
                [--generate-alias-as-model] [--git-host <git host>]
                [--git-repo-id <git repo id>] [--git-user-id <git user id>]
                [--global-property <global properties>...] [--group-id <group id>]
                [--http-user-agent <http user agent>]
                [(-i <spec file> | --input-spec <spec file>)]
                [--ignore-file-override <ignore file override location>]
                [--import-mappings <import mappings>...]
                [--instantiation-types <instantiation types>...]
                [--invoker-package <invoker package>]
                [--language-specific-primitives <language specific primitives>...]
                [--legacy-discriminator-behavior] [--library <library>]
                [--log-to-stderr] [--minimal-update]
                [--model-name-prefix <model name prefix>]
                [--model-name-suffix <model name suffix>]
                [--model-package <model package>]
                [(-o <output directory> | --output <output directory>)] [(-p <additional properties> | --additional-properties <additional properties>)...]
                [--package-name <package name>] [--release-note <release note>]
                [--remove-operation-id-prefix]
                [--reserved-words-mappings <reserved word mappings>...]
                [(-s | --skip-overwrite)] [--server-variables <server variables>...]
                [--skip-validate-spec] [--strict-spec <true/false strict behavior>]
                [(-t <template directory> | --template-dir <template directory>)]
                [--type-mappings <type mappings>...] [(-v | --verbose)]

OPTIONS
        -a <authorization>, --auth <authorization>
            adds authorization headers when fetching the OpenAPI definitions
            remotely. Pass in a URL-encoded string of name:header with a comma
            separating multiple values

...... (results omitted)

        -v, --verbose
            verbose mode

You can then compile and run the client, as well as unit tests against it:

cd samples/client/petstore/java/okhttp-gson
mvn package

Other generators have samples too.

3.1 - Customization

Please refer to customization.md on how to customize the output (e.g. package name, version)

3.2 - Workflow Integration (Maven, Gradle, Github, CI/CD)

Please refer to integration.md on how to integrate OpenAPI generator with Maven, Gradle, sbt, Bazel, Github and CI/CD.

3.3 - Online OpenAPI generator

Here are the public online services:

latest stable version: https://api.openapi-generator.tech
latest master: https://api-latest-master.openapi-generator.tech (updated with latest master every hour)

The server is sponsored by Linode

(These services are beta and do not have any guarantee on service level)

Please refer to online.md on how to run and use the openapi-generator-online - a web service for openapi-generator.

3.4 - License information on Generated Code

The OpenAPI Generator project is intended as a benefit for users of the Open API Specification. The project itself has the License as specified. In addition, please understand the following points:

The templates included with this project are subject to the License.
Generated code is intentionally not subject to the parent project license

When code is generated from this project, it shall be considered AS IS and owned by the user of the software. There are no warranties--expressed or implied--for generated code. You can do what you wish with it, and once generated, the code is your responsibility and subject to the licensing terms that you deem appropriate.

3.5 - IDE Integration

Here is a list of community-contributed IDE plug-ins that integrate with OpenAPI Generator:

Eclipse: Codewind OpenAPI Tools for Eclipse by IBM
IntelliJ IDEA: OpenAPI Generator by Jim Schubert
IntelliJ IDEA: Senya Editor by senya.io
RepreZen API Studio
Visual Studio: REST API Client Code Generator by Christian Resma Helle
Visual Studio Code: Codewind OpenAPI Tools by IBM

4 - Companies/Projects using OpenAPI Generator

Here are some companies/projects (alphabetical order) using OpenAPI Generator in production. To add your company/project to the list, please visit README.md and click on the icon to edit the page.

Aalborg University
act coding
Adaptant Solutions AG
adesso SE
adorsys GmbH & Co.KG
Adyen
Agoda
Airthings
Aleri Solutions Gmbh
Allianz
Angular.Schule
Aqovia
Australia and New Zealand Banking Group (ANZ)
Arduino
ASKUL
Amazon Web Services (AWS)
b<>com
百度营销
Bandwidth
Banzai Cloud
BIMData.io
Bithost GmbH
Bosch Connected Industry
Boxever
Brevy
Bunker Holding Group
California State University, Northridge
CAM
Camptocamp
Carlsberg Group
CERN
Christopher Queen Consulting
Cisco
codecentric AG
CoinAPI
Commencis
ConfigCat
cronn GmbH
Crossover Health
Cupix
Datadog
DB Systel
Deeporute.ai
Devsupply
dmTECH GmbH
DocSpring
dwango
Edge Impulse
Element AI
Embotics
emineo
fastly
Fenergo
freee
FreshCells
Fuse
Gantner
GenFlow
GetYourGuide
Glovo
GMO Pepabo
GoDaddy
Gumtree
Here
IBM
Instana
Interxion
Inquisico
JustStar
k6.io
Klarna
Kronsoft Development
Kubernetes
Landeshauptstadt München - it@M
Linode
Logicdrop
Lumeris
LVM Versicherungen
MailSlurp
Manticore Search
Mastercard
Médiavision
Metaswitch
MoonVision
Myworkout
NamSor
Neverfail
NeuerEnergy
Nokia
OneSignal
Options Clearing Corporation (OCC)
Openet
openVALIDATION
Oracle
Paxos
Plaid
PLAID, Inc.
Pinterest
Ponicode
Pricefx
PrintNanny
Prometheus/Alertmanager
Qavar
QEDIT
Qovery
Qulix Systems
Raksul
Raiffeisen Schweiz Genossenschaft
RedHat
RepreZen API Studio
REST United
Robocorp
Robotinfra
Sarvika Technologies Pvt. Ltd.
SearchApi
SmartHR
Sony Interactive Entertainment
Splitit
Stingray
Suva
Svix
Telstra
Tencent
The University of Aizu
TINQIN
Translucent ApS
TravelTime platform
TribalScale
Trifork
TUI InfoTec GmbH
Twilio
Twitter
unblu inc.
Veamly
VMWare
wbt-solutions
Woleet
WSO2
Vouchery.io
Xero
Yahoo Japan
viadee
Vonage
YITU Technology
Yelp
Zalando
3DS Outscale

5 - Presentations/Videos/Tutorials/Books

2018/05/12 - OpenAPI Generator - community drivenで成長するコードジェネレータ by 中野暁人
2018/05/15 - Starting a new open-source project by Jeremie Bresson
2018/05/15 - REST API仕様からAPIクライアントやスタブサーバを自動生成する「OpenAPI Generator」オープンソースで公開。Swagger Codegenからのフォーク by Publickey
2018/06/08 - Swagger Codegen is now OpenAPI Generator by JohannesHoppe
2018/06/21 - Connect your JHipster apps to the world of APIs with OpenAPI and gRPC by Christophe Bornet at JHipster Conf 2018
2018/06/22 - OpenAPI Generator で Gatling Client を生成してみた at ソモサン
2018/06/27 - Lessons Learned from Leading an Open-Source Project Supporting 30+ Programming Languages - William Cheng at LinuxCon + ContainerCon + CloudOpen China 2018
2018/07/19 - OpenAPI Generator Contribution Quickstart - RingCentral Go SDK by John Wang
2018/08/22 - OpenAPI Generatorのプロジェクト構成などのメモ by Yusuke Iinuma
2018/09/12 - RepreZen and OpenAPI 3.0: Now is the Time by Miles Daffin
2018/10/31 - A node package wrapper for openapi-generator
2018/11/03 - OpenAPI Generator + golang + Flutter でアプリ開発 by Ryuichi Daigo
2018/11/15 - 基于openapi3.0的yaml文件生成java代码的一次实践 by 焱魔王
2018/11/18 - Generating PHP library code from OpenAPI by Lorna Jane at LORNAJANE Blog
2018/11/19 - OpenAPIs are everywhere by Jeremie Bresson (Unblu) at EclipseCon Europe 2018
2018/12/09 - openapi-generator をカスタマイズする方法 by @watiko
2019/01/03 - Calling a Swagger service from Apex using openapi-generator by Mikkel Flindt Heisterberg
2019/01/13 - OpenAPI GeneratorでRESTful APIの定義書から色々自動生成する by @ky_yk_d
2019/01/20 - Contract-First API Development with OpenAPI Generator and Connexion by Anil Can Aydin
2019/01/30 - Rapid Application Development With API First Approach Using Open-API Generator by Milan Sonkar
2019/02/02 - 平静を保ち、コードを生成せよ〜 OpenAPI Generator誕生の背景と軌跡〜 by 中野暁人 at Gunma.web #34 スキーマ駆動開発
2019/02/20 - An adventure in OpenAPI V3 code generation by Phil Cluff
2019/02/26 - Building API Services: A Beginner’s Guide by Ratros Y. in Google Cloud Platform Blog
2019/02/26 - Building APIs with OpenAPI: Continued by Ratros Y. in Google Cloud Platform Blog
2019-03-07 - OpenAPI Generator で Spring Boot と Angular をタイプセーフに繋ぐ by Tomofumi Chiba
2019-03-16 - A Quick introduction to manual OpenAPI V3 by vados at VADOSWARE
2019-03-25 - Access any REST service with the SAP S/4HANA Cloud SDK by Alexander Duemont
2019-03-25 - OpenAPI generatorを試してみる by @amuyikam
2019-03-27 - OpenAPI3を使ってみよう！Go言語でクライアントとスタブの自動生成まで！ by @gold_kou
2019-04-17 - OpenAPIによるスキーマファースト開発の実施サンプルとCloud Runについて by @yukey1031
2019-04-18 - How to use OpenAPI3 for API developer (RubyKaigi 2019) by @ota42y at RubyKaigi 2019
2019-04-29 - A Beginner's Guide to Code Generation for REST APIs (OpenAPI Generator) by William Cheng
2019-05-01 - Design and generate a REST API from Swagger / OpenAPI in Java, Python, C# and more by Simply How
2019-05-17 - Generate Spring Boot REST API using Swagger/OpenAPI by Antonie Zafirov
2019-05-22 - REST APIs代码生成指南(OpenAPI Generator) by William Cheng, Xin Meng
2019-05-24 - REST API 代碼生成指南 (OpenAPI Generator) by William Cheng
2019-06-24 - Kubernetes Clients and OpenAPI Generator by William Cheng at Kubernetes Contributor Summits Shanghai 2019
2019-06-28 Codewind OpenAPI Tools in Eclipse Marketplace by IBM
2019-06-29 Codewind OpenAPI Tools in Visual Studio Marketplace by IBM
2019-07-04 - REST API のためのコード生成入門 (OpenAPI Generator) by William Cheng, 中野暁人, 和田拓朗
2019-07-08 - OpenAPI Generator にコントリビュートしたら社名が載った話。(CAM) - CAM TECH BLOG by CAM, Inc.
2019-07-14 - OpenAPI GeneratorでPythonのクライアントライブラリを作成した by yuji38kwmt
2019-07-19 - Developer Experience (DX) for Open-Source Projects: How to Engage Developers and Build a Growing Developer Community by William Cheng, 中野暁人 at Open Source Summit Japan 2019
2019-08-14 - Our OpenAPI journey with Standardizing SDKs by Sebastian Burgstaller at Bitmovin
2019-08-15 - APIのコードを自動生成させたいだけならgRPCでなくてもよくない? by M3, Inc.
2019-08-22 - マイクロサービスにおけるWeb APIスキーマの管理─ GraphQL、gRPC、OpenAPIの特徴と使いどころ by @ota42y
2019-08-24 - SwaggerドキュメントからOpenAPI Generatorを使ってモックサーバー作成 by 坂本正義
2019-08-29 - OpenAPI初探 by peakxie at 腾讯云社区
2019-08-29 - 全面进化：Kubernetes CRD 1.16 GA前瞻 by Min Kim at ServiceMesher Blog
2019-09-01 - Creating a PHP-Slim server using OpenAPI (Youtube video) by Daniel Persson
2019-09-06 - Vert.x and OpenAPI by Stephan H Wissel at wissel.net blog
2019-09-09 - Cloud-native development - Creating RESTful microservices in IBM Cloud Docs
2019-09-14 - Generating and Configuring a Mastercard API Client at Mastercard Developers Platform
2019-09-15 - OpenAPI(Swagger)導入下調べ by Shoichi Kuraoka
2019-09-17 - Tutorial: Documenting http4k APIs with OpenApi3 by http4k
2019-09-22 - OpenAPI 3を完全に理解できる本 by @ota42y
2019-09-22 - RESTful APIs: Tutorial of OpenAPI Specification by Amir Lavasani
2019-09-22 - Redefining SDKs as software diversity kits by Sid Maestre (Xero) at DevRelCon San Francisco 2019
2019-09-23 - swaggerからOpenApi GeneratorでSpringのコードを自動生成 by @littleFeet at Qiita
2019-09-24 - Eine Stunde was mit Api First! by @janweinschenker at Java Forum Nord
2019-10-09 - openapi-generator で生成した Go クライアントで Bearer 認証をする by Akira Tanimura
2019-10-10 - Automatic Generation of REST Clients by Thomas Peyrard, Senior Software Engineer at Criteo in Full-Stack Tech Talks (Meetup)
2019-10-12 - OpenApi自动生成client by 郑泽洲
2019-10-16 - How to ship APIs faster? by Simon Guilliams @ PoniCode
2019-10-22 - OpenAPI + Spring Boot(Kotlin)でファイルダウンロードAPIを作成する by Yuki Furukawa
2019-10-24 - Microprofile OpenAPI - Code First or Design First? by Peter [pɛʃə] Steiner at eclipsecon Europe 2019
2019-11-06 - Generating API clients based on OpenAPI v3 specifications by Dominik Jastrzębski @ 98elements
2019-11-06 - OpenAPIを利用して自前のAPIサーバー(Sinatra)を移植した時のメモ by Yasuhiro ABE
2019-11-07 - API First development with OpenAPI - You should you practise it !? by Nick Van Hoof at Devoxx Belgium 2019
2019-11-08 - JHipster beyond CRUD - API-First for Enterprises by Enrico Costanzi by Enrico Costanzi at JHipster Conf 2019 in Paris
2019-11-11 - TypeScript REST APIクライアント by @unhurried
2019-11-11 - One Spec to Rule them all - OpenAPI in Action by Andreas Litt at code.talks 2019
2019-11-13 - OpenAPI 3.0 Editor And Generator With A Spring Boot Example at Simply How
2019-11-17 - OpenAPI Generator YouTube playlist at YouTube
2019-11-20 - Introduction to OpenAPI by Lorna Mitchell at GOTO Copenhagen 2019
2019-11-20 - How to Generate Angular code from OpenAPI specifications by Anuraj
2019-11-23 - Swagger ではない OpenAPI Specification 3.0 による API サーバー開発 by Tetsuya Morimoto at JJUG CCC 2019 Fall
2019-11-24 - Accelerate Flutter development with OpenAPI and Dart code generation by Irina Southwell
2019-11-25 - openapi-generatorで手軽にスタブサーバとクライアントの生成 by @pochopocho13
2019-11-26 - CordaCon 2019 Highlights: Braid Server and OpenAPI Generator for Corda Client API’s by Adel Rustum at B9lab
2019-12-03 - A Road to Less Coding: Auto-Generate APILibrary at Corda Blog
2019-12-04 - Angular＋NestJS＋OpenAPI（Swagger）でマイクロサービスを視野に入れた環境を考える by てらしー
2019-12-05 - Code generation on the Java VM by Sean Sullivan
2019-12-17 - OpenAPI Generator で OAuth2 アクセストークン発行のコードまで生成してみる by TECHSCORE
2019-12-23 - Use Ada for Your Web Development by Stephane Carrez
2019-12-23 - OpenAPIのスキーマを分割・構造化していく方法 by 小飯塚達也 at GiFT, Inc
2020-01-17 - OpenAPI demo for Pulp 3.0 GA by Pulp at Youtube
2020-01-19 - Why document a REST API as code? by Rolf Streefkerk at DEV Community
2020-01-28 - Get Your Serverless Swagger Back with OpenAPI by Matt Tyler
2020-01-30 - OpenAPI Generatorへのコントリビュート by yutaka0m
2020-02-01 - Using OpenAPI to Maximise Your Pulp 3 Experience by Dennis Kliban at FOSDEM
2020-02-07 - Why you should use OpenAPI for your API design by Nick Van Hoof at API Conference
2020-02-17 - Rubynetes: using OpenAPI to validate Kubernetes configs by Neil Wilson at Brightbox
2020-02-20 - Building SDKs for the future by Sid Maestre (Xero)
2020-02-27 - Nuxt利用プロダクトでIE11と仲良くするためのE2E at Medpeer.co.jp Tech Blog
2020-02-29 - Providing Support to IoT Devices Deployed in Disconnected Rural Environment (Conference paper) by Sergio Laso, Daniel Flores-Martín, Juan Luis HerreraCarlos, CanalJuan Manuel, MurilloJavier Berrocal
2020-03-02 - How To Generate Angular & Spring Code From OpenAPI Specification by Michael Hoffmann
2020-03-02 - OpenAPI Generator + TypeScript で始める自動生成の型に守られた豊かなクライアント生活 by 五百蔵直樹 at GiFT株式会社
2020-03-10 - OpenAPI Generator Meetup #1 by 中野暁人 at OpenAPI Generator Meetup #1
2020-03-15 - Load Testing Your API with Swagger/OpenAPI and k6
2020-04-13 - 俺的【OAS】との向き合い方 (爆速でOpenAPIと友達になろう) in OPTim Blog
2020-04-22 - Introduction to OpenAPI Generator by Kristopher Sandoval in Nordic APIs
2020-04-27 - How we use Open API v3 specification to auto-generate API documentation, code-snippets and clients by Tanel Tähepõld
2020-05-09 - OpenAPIでお手軽にモックAPIサーバーを動かす by Sachie Kamba
2020-05-18 - Spring Boot REST with OpenAPI 3 by Alfonz Jan Frithz
2020-05-19 - Dead Simple APIs with Open API by Chris Tankersley at Nexmo
2020-05-22 - TypeScript REST API Client by "unhurried"
2020-05-28 - 【使用 lotify + Swagger 建置可共用的 LINE Notify bot】 - #NiJia @ Chatbot Developer Taiwan 第 #19 小聚 by Chatbot Developer Taiwan
2020-05-28 - Building APIs with Laravel using OpenAPI by Chris Tankersley at Laracon EU
2020-06-12 - Interoperability by construction: code generation for Arrowhead Clients by Michele Albano, Brian Nielsen at 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS)
2020-06-23 - 新規サーバーアプリケーションにTypeScriptを採用してみた at CAM Tech Blog
2020-06-29 - Artifact Abstract: Deployment of APIs on Android Mobile Devices and Microcontrollers by Sergio Laso ; Marino Linaje ; Jose Garcia-Alonso ; Juan M. Murillo ; Javier Berrocal at 2020 IEEE International Conference on Pervasive Computing and Communications (PerCom)
2020-07-07 - 5 Best API Documentation Tools by Susanna Bouse at DreamFactory Blog
2020-07-12 - Open API 3.0の定義からgolangのサーバコードのスケルトンを作成する by @professor (Qiita Blog)
2020-07-20 - Datadog API client libraries now available for Java and Go by Jordan Obey at Datadog Blog
2020-07-23 - Generate Client SDK for .NET Core using Open Api by Nuno Reis
2020-07-26 - Dartのhttp_interceptorライブラリを使うと配列のクエリパラメータが消えてしまう件の応急処置 by @gyamoto
2020-08-01 - Generate Angular ReactiveForms from Swagger/OpenAPI by Martin McWhorter
2020-08-03 - Criando Bibliotecas para APIs RESTful com OpenAPI, Swagger Editor e OpenAPI Generator by everis Brasil (an NTT DATA Company)
2020-08-19 - マイクロサービスを連携してみよう by 岡井裕矢(おかいゆうや), 泉勝(いずみまさる) at Think IT（シンクイット）
2020-08-25 - OpenAPI Generator と TypeScript で型安全にフロントエンド開発をしている話 at SmartHR Tech Blog
2020-09-10 - Introduction to OpenAPI with Instana by Cedric Ziel at Instana Blog
2020-09-17 - Generate PowerShellSDK using openapi-generator by Ghufran Zahidi
2020-09-24 - How to automate API code generation (OpenAPI/Swagger) and boost productivity - Tutorial with React Native featuring TypeScript by Sanjin Celeski
2020-09-25 - Generate OpenAPI Angular Client by Patric
2020-10-24 - Working with Microsoft Identity - React Native Client by Joseph Guadagno
2020-10-31 - [B2] OpenAPI Specification으로 타입-세이프하게 API 개발하기: 희망편 VS 절망편 by 최태건 at FEConf 2020
2020-11-05 - Automated REST-Api Code Generation: Wie IT-Systeme miteinander sprechen by Stefan Rottensteiner at MASSIVE ART Blog
2020-12-01 - OpenAPI GeneratorでGoのAPIサーバー/クライアントコードを自動生成する by @saki-engineering
2020-12-04 - Scaling the Test Coverage of OpenAPI Generator for 30+ Programming Languages by William Cheng at Open Source Summit Japan + Automotive Linux Summit 2020 (Slides)
2020-12-09 - プロジェクトにOpenAPI Generatorで自動生成された型付きAPI Clientを導入した話 by @yoshifujiT
2020-12-15 - Next.js + NestJS + GraphQLで変化に追従するフロントエンドへ〜ショッピングクーポンの事例紹介 by 小倉陸 at Yahoo! JAPAN Tech Blog
2021-01-08 - Hello, New API – Part 1 by Jeremy Schulman at Major League Baseball
2021-01-18 - 「アプリ開発あるある」を疑うことから始まった、API Clientコードの自動生成【デブスト2020】 by CodeZine編集部
2021-02-05 - REST-API-Roundtrip with SpringDoc and OpenAPI Generator by Benjamin Klatt at viadee
2021-02-17 - REST-API-Roundtrip with SpringDoc and OpenAPI Generator by cloud @viadee
2021-03-08 - OpenAPI Generator 工具的躺坑尝试 by 独家雨天 at CSDN官方博客
2021-03-16 - 如何基于 Swagger 使用 OpenAPI Generator 生成 JMeter 脚本？ by 高楼Zee at 腾讯云专栏
2021-03-24 - openapi-generator-cli による TypeScript 型定義 by Takefumi Yoshii
2021-03-28 - Trying out NestJS part 4: Generate Typescript clients from OpenAPI documents by Arnaud Cortisse
2021-03-31 - Open API Server Implementation Using OpenAPI Generator at Baeldung
2021-03-31 - 使用OpenAPI Generator實現Open API Server at 億聚網
2021-04-19 - Introducing Twilio’s OpenAPI Specification Beta by GARETH PAUL JONES at Twilio Blog
2021-04-22 - Leveraging OpenApi strengths in a Micro-Service environment by Nicolas Jellab at Unibuddy Technology Blog
2021-04-27 - From zero to publishing PowerShell API clients in PowerShell Gallery within minutes by William Cheng at PowerShell + DevOps Global Summit 2021
2021-05-31 - FlutterでOpen Api Generator(Swagger)を使う by AAkira
2021-06-22 - Rest API Documentation and Client Generation With OpenAPI by Prasanth Gullapalli
2021-07-16 - 銀行事業のサーバーサイド開発について / LINE 京都開発室エンジニア採用説明会 by 野田誠人, Robert Mitchell
2021-07-19 - OpenAPI code generation with kotlin by sylhare
2021-07-29 - How To Rewrite a Huge Codebase by Curtis Poe
2021-08-21 - Generating Client APIs using Swagger Part 1 by FlowSquad.io
2021-09-11 - Invoking AWS ParallelCluster API at AWS ParallelCluster API official documentation
2021-09-20 - OpenAPI Generator - The Babel Fish of the API World by Cliffano Subagio (Principal Engineer at Shine Solutions) at Apidays LIVE Australia 2021
2021-10-02 - How to Write Fewer Lines of Code with the OpenAPI Generator by Mikhail Alfa
2021-10-12 - OpenAPI Generator : 4000 étoiles sur GitHub et des spaghettis by Jérémie Bresson at Devoxx FR 2021
2021-10-17 - Generate a TypeScript HTTP Client From An OpenAPI Spec In DotNET 5 by Richard Willis
2021-11-06 - スタートアップの開発で意識したこと by woo-noo
2021-11-09 - Effective Software Development using OpenAPI Generator by Ajil Oomme
2021-12-07 - An Introduction to OpenAPI by Na'aman Hirschfeld
2022-01-02 - Towards a secure API client generator for IoT devices by Anders Aaen Springborg, Martin Kaldahl Andersen, Kaare Holland Hattel, Michele Albano
2022-02-02 - Use OpenApi generator to share your models between Flutter and your backend by Guillaume Bernos at Flutter Vikings Conference 2022 (Hybrid)
2022-03-15 - OpenAPI Specでハイフン区切りのEnum値をOpenAPI Generatorで出力すると、ハイフン区切りのまま出力される by yuji38kwmt
2022-04-01 - OpenAPI Generatorのコード生成とSpring Frameworkのカスタムデータバインディングを共存させる in ZOZO Tech Blog
2022-04-06 - Effective Software Development using OpenAPI Generator by Ajil Oommen (Senior Flutter Developer)
2022-05-13 - A Path From an API To Client Libraries by Filip Srnec at Infobip
2022-06-01 - API First, using OpenAPI and Spring Boot by Micael Estrázulas Vianna
2022-06-10 - Autogenerating Clients with FastAPI and Github Actions by Andrew Israel
2022-06-12 - Mustache templates with OpenAPI specs by Beppe Catanese
2022-07-01 - Generate API contract using OpenAPI Generator Maven plugin by Khanh Nguyen
2022-07-22 - 使用OpenAPI Generator Maven plugin开发api优先的java客户端和服务端代码 by Lincest
2022-08-01 - Tutorial: Etsy Open API v3 (ruby) by Thierry Joyal
2022-09-03 - OpenAPI Generator For Go Web Development by Kevin Hu
2022-10-01 - OpenAPI Generatorをカスタマイズしたコードを生成する（Swagger Codegenとほぼ同じ） by きり丸
2022-10-21 - Kotlin（Spring Boot）の API を OpenAPI Generator で自動生成 by msksgm
2022-10-26 - Quarkus Insights #106: Quarkiverse Extension Spotlight: OpenApi Generator by Quarkusio
2022-11-28 - The REST API implementation flow by Imre Tömösvári
2022-12-13 - API-First with Spring WebFlux and OpenAPI Generator by Eric Anicet
2023-01-06 - Major Improvements with Helidon and OpenAPI by Tim Quinn
2023-02-02 - Replacing Postman with the Jetbrains HTTP Client by julien Lengrand-Lambert
2023-03-15 - OpenAPI Generatorに適したOpenAPIの書き方 by ZOZO Tech Blog
2023-03-19 - EXOGEM: Extending OpenAPI Generator for Monitoring of RESTful APIs by Daniel Friis Holtebo, Jannik Lucas Sommer, Magnus Mølgaard Lund, Alessandro Tibo, Junior Dongo & Michele Albano at "ICSOC 2022: Service-Oriented Computing – ICSOC 2022 Workshops"
2023-03-28 - API-First Design with OpenAPI Generator by Jonathan Manera
2023-03-28 - ハンズオンで学ぶサーバーサイド Kotlin（Spring Boot&Arrow&OpenAPI Generator）v1.0.1 by msk
2023-04-01 - OpenAPI Client Code Generation by Kwo Ding
2023-04-27 - [Create an Angular Client using OpenAPI Specifications](Create an Angular Client using OpenAPI Specifications) by Patric
2023-05-16 - Adyen for Java developers by Beppe Catanese, Developer Advocate, Adyen
2023-05-18 - 如何基于 Swagger 使用 OpenAPI Generator 生成 JMeter 脚本？ by 高楼（Zee)
2023-06-28 - Generate API contract using OpenAPI Generator Maven plugin by Khanh Nguyen
2023-06-30 - Generate Client SDKs with OpenApi Generator in Springboot by Vinayak Ramavath
2023-12-10 - UnityでOpenAPI Generatorを使う by Soup Tori
2024-01-24 - Comment générer des stubs wiremock avec openapi generator by Alexis Couvreur
2024-03-04 - Generating TypeScript Types with OpenAPI for REST API Consumption by PullRequest
2024-03-07 - Fully typed Web Apps with OpenAPI (Part 1) by Guillaume Renard
2024-03-08 - Laravel OpenAPIによる "辛くない" スキーマ駆動開発 by KentarouTakeda
2024-04-04 - Working with OpenAPI using Rust by Joshua Mo
2024-04-08 - Implement API first strategy with OpenAPI generator plugin by Rui Zhou
2024-05-06 - OpenAPI Generator Custom Templates by Mary Zheng
2025-02-09 - Custom validation with OpenApiGenerator and Spring Boot 3 by Jugurtha Aitoufella
2025-02-20 - Optimizing API Integration in a Large React Application Using OpenAPI Generator by Stefano Marzo

6 - About Us

What's the design philosophy or principle behind OpenAPI Generator?

We focus on developer experience. The generators should produce code, config, documentation, and more that are easily understandable and consumable by users. We focused on simple use cases to start with (bottom-up approach). Since then the project and the community have grown a lot: 600k weekly downloads via NPM CLI wrapper, 30M downloads via openapi-generator-cli docker image just to highlight a few. We've gradually supported more features (e.g. oneOf, anyOf introduced in OpenAPI 3.0) in various generators and we will continue this approach to deliver something based on our understanding of user demand and what they want, and continue to add support of new features introduced in OpenAPI specification (such as v3.1 and future versions of the OpenAPI specification).

6.1 - OpenAPI Generator Core Team

OpenAPI Generator core team members are contributors who have been making significant contributions (review issues, fix bugs, make enhancements, etc) to the project on a regular basis.

Core Team Members

@wing328 (2015/07) ❤️
@jimschubert (2016/05) ❤️
@cbornet (2016/05)
@jmini (2018/04) ❤️
@etherealjoy (2019/06)

❤️ = Link to support the contributor directly

Template Creator

NOTE: Embedded templates are only supported in Mustache format. Support for all other formats is experimental and subject to change at any time.

Here is a list of template creators:

API Clients:
- Ada: @stcarrez
- Apex: @asnelling
- Bash: @bkryza
- C: @PowerOfCreation @zhemant ❤️
- C++ Httplib: @rajvesh
- C++ Oat++: @Kraust
- C++ REST: @Danielku15
- C++ Tiny: @AndersSpringborg @kaareHH @michelealbano @mkakbas
- C++ UE4: @Kahncode
- C# (.NET 2.0): @who
- C# (.NET Standard 1.3 ): @Gronsak
- C# (.NET 4.5 refactored): @jimschubert ❤️
- C# (GenericHost): @devhl-labs
- C# (HttpClient): @Blackclaws
- Clojure: @xhh
- Crystal: @wing328
- Dart: @yissachar
- Dart (refactor): @joernahrens
- Dart 2: @swipesight
- Dart (Jaguar): @jaumard
- Dart (Dio): @josh-burton
- Elixir: @niku
- Elm: @eriktim
- Eiffel: @jvelilla
- Erlang: @tsloughter
- Erlang (PropEr): @jfacorro @robertoaloi
- Groovy: @victorgit
- Go: @wing328 ❤️
- Go (rewritten in 2.3.0): @antihax
- Godot (GDScript): @Goutte ❤️
- Haskell (http-client): @jonschoning
- Java (Feign): @davidkiss
- Java (Retrofit): @0legg
- Java (Retrofit2): @emilianobonassi
- Java (Jersey2): @xhh
- Java (okhttp-gson): @xhh
- Java (RestTemplate): @nbruno
- Java (Spring 5 WebClient): @daonomic
- Java (Spring 6 RestClient): @nicklas2751
- Java (RESTEasy): @gayathrigs
- Java (Vertx): @lopesmcc
- Java (Google APIs Client Library): @charlescapps
- Java (Rest-assured): @viclovsky
- Java (Java 11 Native HTTP client): @bbdouglas
- Java (Apache HttpClient 5.x): @harrywhite4 @andrevegas
- Java (Helidon): @spericas @tjquinno @tvallin
- Javascript/NodeJS: @jfiala
- JavaScript (Apollo DataSource): @erithmetic
- JavaScript (Closure-annotated Angular) @achew22
- JavaScript (Flow types) @jaypea
- Jetbrains HTTP Client : @jlengrand
- JMeter: @davidkiss
- Julia: @tanmaykm
- Kotlin: @jimschubert ❤️
- Kotlin (MultiPlatform): @andrewemery
- Kotlin (Volley): @alisters
- Kotlin (jvm-spring-webclient): @stefankoppier
- Kotlin (jvm-spring-restclient): @stefankoppier
- Lua: @daurnimator
- N4JS: @mmews-n4
- Nim: @hokamoto
- OCaml: @cgensoul
- Perl: @wing328 ❤️
- PHP (Guzzle): @baartosz
- PHP (with Data Transfer): @Articus
- PowerShell: @beatcracker
- PowerShell (refactored in 5.0.0): @wing328
- Python: @spacether [❤️][spacether sponsorship]
- Python-Experimental: @spacether [❤️][spacether sponsorship]
- Python (refactored in 7.0.0): @wing328
- R: @ramnov
- Ruby (Faraday): @meganemura @dkliban
- Ruby (HTTPX): @honeyryderchuck
- Rust: @farcaller
- Rust (rust-server): @metaswitch
- Scala (scalaz & http4s): @tbrown1979
- Scala (Akka): @cchafer
- Scala (sttp): @chameleon82
- Scala (sttp4): @flsh86
- Scala (scala-sttp4-jsoniter): @lbialy
- Scala (Pekko): @mickaelmagniez
- Scala (http4s): @JennyLeahy
- Swift: @tkqubo
- Swift 3: @hexelon
- Swift 4: @ehyche
- Swift 5: @4brunu
- Swift 6: @4brunu
- Swift Combine: @dydus0x14
- Terraform: @jasondamour
- TypeScript (Angular1): @mhardorf
- TypeScript (Angular2): @roni-frantchi
- TypeScript (Angular6): @akehir
- TypeScript (Angular7): @topce
- TypeScript (Axios): @nicokoenig
- TypeScript (Fetch): @leonyu
- TypeScript (Inversify): @gualtierim
- TypeScript (jQuery): @bherila
- TypeScript (Nestjs): @vfrank66
- TypeScript (Node): @mhardorf
- TypeScript (Rxjs): @denyo
- TypeScript (redux-query): @petejohansonxo
- Xojo: @Topheee
- Zapier: @valmoz, @emajo
Server Stubs
- Ada: @stcarrez
- C# ASP.NET 5: @jimschubert ❤️
- C# ASP.NET Core 3.0: @A-Joshi
- C# APS.NET Core 3.1: @phatcher
- C# Azure functions: @Abrhm7786
- C# NancyFX: @mstefaniuk
- C++ (Qt5 QHttpEngine): @etherealjoy
- C++ Httplib: @rajvesh
- C++ Oat++: @Kraust
- C++ Pistache: @sebymiano
- C++ Restbed: @stkrwork
- Erlang Server: @galaxie @nelsonvides
- F# (Giraffe) Server: @nmfisher
- Go Server: @guohuang
- Go Server (refactored in 7.0.0): @lwj5
- Go (Echo) Server: @ph4r5h4d
- Go (Gin) Server: @kemokemo
- GraphQL Express Server: @renepardon
- Haskell Servant: @algas
- Haskell Yesod: @yotsuya
- Java Camel: @carnevalegiacomo
- Java Dubbo: @redoom
- Java MSF4J: @sanjeewa-malalgoda
- Java Spring Boot: @diyfr
- Java Undertow: @stevehu
- Java Play Framework: @JFCote
- Java PKMST: @anshu2185 @sanshuman @rkumar-pk @ninodpillai
- Java Vert.x: @lwlee2608
- Java Micronaut: @andriy-dmytruk
- Java Helidon: @spericas @tjquinno @tvallin
- Java WireMock: @acouvreur
- JAX-RS RestEasy: @chameleon82
- JAX-RS CXF: @hiveship
- JAX-RS CXF (CDI): @nickcmaynard
- JAX-RS RestEasy (JBoss EAP): @jfiala
- Julia: @tanmaykm
- Kotlin: @jimschubert ❤️
- Kotlin (Spring Boot): @dr4ke616
- Kotlin (Vertx): @Wooyme
- Kotlin (JAX-RS): @anttileppa
- Kotlin Misk: @andrewwilsonnew @guiarn
- Kotlin WireMock: @stefankoppier
- NodeJS Express: @YishTish
- PHP Flight: @daniel-sc
- PHP Laravel: @renepardon
- PHP Laravel (refactor in 7.12.0): @gijs-blanken
- PHP Lumen: @abcsun
- PHP Mezzio (with Path Handler): @Articus
- PHP Slim: @jfastnacht
- PHP Slim4: @ybelenko
- PHP Symfony: @ksm2
- PHP Symfony6: @BenjaminHae
- Python FastAPI: @krjakbrjak
- Python AIOHTTP:
- Ruby on Rails 5: @zlx
- Rust (rust-server): @metaswitch
- Rust (rust-axum): @linxGnu
- Scala Akka: @Bouillie
- Scala Cask: @aaronp
- Scala Finch: @jimschubert ❤️
- Scala Lagom: @gmkumar2005
- Scala Play: @adigerber
- TypeScript NestJS: @aryobenholzner
Documentation
- AsciiDoc: @man-at-home
- HTML Doc 2: @jhitchcock
- Confluence Wiki: @jhitchcock
- PlantUML: @pburls
Configuration
- Apache2: @stkrwork
- k6: @mostafa
Schema
- Avro: @sgadouar
- GraphQL: @wing328 ❤️
- Ktorm: @Luiz-Monad
- MySQL: @ybelenko
- PostgreSQL: @iri
- Postman Collection: @gcatanese
- Protocol Buffer: @wing328
- WSDL: @adessoDpd

❤️ = Link to support the contributor directly

How to join the core team

Here are the requirements to become a core team member:

rank within top 50 in https://github.com/openapitools/openapi-generator/graphs/contributors
- to contribute, here are some good starting points
regular contributions to the project
- about 3 hours per week
- for contribution, it can be addressing issues, reviewing PRs submitted by others, submitting PR to fix bugs or make enhancements, etc
- must be active in the past 3 months at the time of application

To join the core team, please reach out to team@openapitools.org for more information.

To become a Template Creator, simply submit a PR for new API client (e.g. Rust, Elixir) or server stub (e.g. Ruby Grape) generator.

6.2 - OpenAPI Generator Technical Committee

Members of the OpenAPI Generator technical committee shoulder the following responsibilities:

Provides guidance and direction to other users
Reviews pull requests and issues
Improves the generator by making enhancements, fixing bugs or updating documentations
Sets the technical direction of the generator

Who is eligible? Those who want to join must have at least 3 PRs merged into a generator. (Exceptions can be granted to template creators or contributors who have made a lot of code changes with less than 3 merged PRs)

If you want to join the committee, please kindly apply by sending an email to team@openapitools.org with your Github ID.

Members of Technical Committee

Languages/Generators	Member (join date)
ActionScript
Ada	@stcarrez (2018/02) @michelealbano (2018/02)
Android	@jaz-ah (2017/09)
Apex
Bash	@frol (2017/07) @bkryza (2017/08) @kenjones-cisco (2017/09)
C	@zhemant (2018/11) @ityuhui (2019/12) @michelealbano (2020/03) @eafer (2024/12)
C++	@ravinikam (2017/07) @stkrwork (2017/07) @etherealjoy (2018/02) @martindelille (2018/03) @muttleyxd (2019/08) @aminya (2025/05)
C#	@mandrean (2017/08) @shibayan (2020/02) @Blackclaws (2021/03) @lucamazzanti (2021/05) @iBicha (2023/07)
Clojure
Crystal	@cyangle (2021/01)
Dart	@jaumard (2018/09) @josh-burton (2019/12) @amondnet (2019/12) @sbu-WBT (2020/12) @kuhnroyal (2020/12) @agilob (2020/12) @ahmednfwela (2021/08)
Eiffel	@jvelilla (2017/09)
Elixir	@mrmstn (2018/12)
Elm	@eriktim (2018/09)
Erlang	@tsloughter (2017/11) @jfacorro (2018/10) @robertoaloi (2018/10) @nelsonvides (2024/09)
F#	@nmfisher (2019/05)
Go	@antihax (2017/11) @grokify (2018/07) @kemokemo (2018/09) @jirikuncar (2021/01) @ph4r5h4d (2021/04) @lwj5 (2023/04)
GraphQL	@renepardon (2018/12)
Groovy
Haskell
Java	@bbdouglas (2017/07) @sreeshas (2017/08) @jfiala (2017/08) @lukoyanov (2017/09) @cbornet (2017/09) @jeff9finger (2018/01) @karismann (2019/03) @Zomzog (2019/04) @lwlee2608 (2019/10) @martin-mfg (2023/08)
Java Spring	@cachescrubber (2022/02) @welshm (2022/02) @MelleD (2022/02) @atextor (2022/02) @manedev79 (2022/02) @javisst (2022/02) @borsch (2022/02) @banlevente (2022/02) @Zomzog (2022/09) @martin-mfg (2023/08)
JMeter	@kannkyo (2021/01)
Jetbrains HTTP Client	@jlengrand (2023/01)
Julia	@tanmaykm (2023/01)
Kotlin	@karismann (2019/03) @Zomzog (2019/04) @andrewemery (2019/10) @4brunu (2019/11) @yutaka0m (2020/03) @stefankoppier (2022/06) @e5l (2024/10) @dennisameling (2026/02)
Lua	@daurnimator (2017/08)
N4JS	@mmews-n4 (2023/03)
Nim
NodeJS/Javascript	@CodeNinjai (2017/07) @frol (2017/07) @cliffano (2017/07)
ObjC
OCaml	@cgensoul (2019/08), @sir4ur0n (2025/08)
Perl	@wing328 (2017/07) ❤️ @yue9944882 (2019/06)
PHP	@jebentier (2017/07), @dkarlovi (2017/07), @mandrean (2017/08), @jfastnacht (2017/09), @ybelenko (2018/07), @renepardon (2018/12)
PowerShell	@wing328 (2020/05)
Python	@cbornet (2017/09) @tomplus (2018/10) @krjakbrjak (2023/02) @fa0311 (2023/10) @multani (2023/10)
R	@Ramanth (2019/07) @saigiridhar21 (2019/07)
Ruby	@cliffano (2017/07) @zlx (2017/09) @autopp (2019/02)
Rust	@frol (2017/07) @farcaller (2017/08) @richardwhiuk (2019/07) @paladinzh (2020/05) @jacob-pro (2022/10) @dsteeley (2025/07)
Scala	@clasnake (2017/07), @shijinkui (2018/01), @ramzimaalej (2018/03), @chameleon82 (2020/03), @Bouillie (2020/04) @fish86 (2023/06)
Swift	@jgavris (2017/07) @ehyche (2017/08) @Edubits (2017/09) @jaz-ah (2017/09) @4brunu (2019/11) @dydus0x14 (2023/06)
TypeScript	@TiFu (2017/07) @taxpon (2017/07) @sebastianhaas (2017/07) @kenisteward (2017/07) @Vrolijkx (2017/09) @macjohnny (2018/01) @topce (2018/10) @akehir (2019/07) @petejohansonxo (2019/11) @amakhrov (2020/02) @davidgamero (2022/03) @mkusaka (2022/04) @joscha (2024/10) @dennisameling (2026/02)
Xojo	@Topheee (2023/04)

Past Members of Technical Committee:

Languages/Generators	Member (join date)
Python	@taxpon (2017/07) @frol (2017/07) @mbohlool (2017/07) @cbornet (2017/09) @kenjones-cisco (2017/11) @tomplus (2018/10) @arun-nalla (2019/11)

❤️ = Link to support the contributor directly

6.3 - History of OpenAPI Generator

OpenAPI Generator is a fork of Swagger Codegen. In view of the issues with the Swagger Codegen 3.0.0 (beta) release and the disagreement on the project's direction, more than 40 top contributors and template creators of Swagger Codegen decided to fork Swagger Codegen and maintain a community-driven version called "OpenAPI Generator". Please refer to the Q&A for more information.

Founding Members (alphabetical order):

❤️ = Link to support the contributor directly

7 - License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

StarRocks/starrocks

The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project.

Download | Docs | Benchmarks | Demo

StarRocks is the world's fastest open query engine for sub-second, ad-hoc analytics both on and off the data lakehouse. With average query performance 3x faster than other popular alternatives, StarRocks is a query engine that eliminates the need for denormalization and adapts to your use cases, without having to move your data or rewrite SQL. A Linux Foundation project.

Learn more 👉🏻 What Is StarRocks: Features and Use Cases, Join StarRocks Summit 2025!

Features

🚀 Native vectorized SQL engine: StarRocks adopts vectorization technology to make full use of the parallel computing power of CPU, achieving sub-second query returns in multi-dimensional analyses, which is 5 to 10 times faster than previous systems.
📊 Standard SQL: StarRocks supports ANSI SQL syntax (fully supported TPC-H and TPC-DS). It is also compatible with the MySQL protocol. Various clients and BI software can be used to access StarRocks.
💡 Smart query optimization: StarRocks can optimize complex queries through CBO (Cost Based Optimizer). With a better execution plan, the data analysis efficiency will be greatly improved.
⚡ Real-time update: The updated model of StarRocks can perform upsert/delete operations according to the primary key, and achieve efficient query while concurrent updates.
🪟 Intelligent materialized view: The materialized view of StarRocks can be automatically updated during the data import and automatically selected when the query is executed.
✨ Querying data in data lakes directly: StarRocks allows direct access to data from Apache Hive™, Apache Iceberg™, Delta Lake™ and Apache Hudi™ without importing.
🎛️ Resource management: This feature allows StarRocks to limit resource consumption for queries and implement isolation and efficient use of resources among tenants in the same cluster.
💠 Easy to maintain: Simple architecture makes StarRocks easy to deploy, maintain and scale out. StarRocks tunes its query plan agilely, balances the resources when the cluster is scaled in or out, and recovers the data replica under node failure automatically.

Architecture Overview

StarRocks’s streamlined architecture is mainly composed of two modules: Frontend (FE) and Backend (BE). The entire system eliminates single points of failure through seamless and horizontal scaling of FE and BE, as well as replication of metadata and data.

Starting from version 3.0, StarRocks supports a new shared-data architecture, which can provide better scalability and lower costs.

Resources

📚 Read the docs

Section	Description
Quick Starts	How-tos and Tutorials.
Deploy	Learn how to run and configure StarRocks.
Docs	Full documentation.
Blogs	StarRocks deep dive and user stories.

❓ Get support

Slack community: join technical discussions, ask questions, and meet other users!
YouTube channel: subscribe to the latest video tutorials and webcasts.
GitHub issues: report an issue with StarRocks.

Contributing to StarRocks

We welcome all kinds of contributions from the community, individuals and partners. We owe our success to your active involvement.

See Contributing.md to get started.
Set up StarRocks development environment:

Understand our GitHub workflow for opening a pull request; use this PR Template when submitting a pull request.
Pick a good first issue and start contributing.

📝 License: StarRocks is licensed under Apache License 2.0.

👥 Community Membership: Learn more about different contributor roles in StarRocks community.

💬 Developer Group： Please join our Google Groups to discuss StarRocks features, project directions, issues, pull requests, or share suggestions.

Used By

This project is used by the following companies. Learn more about their use cases:

elastic/elasticsearch

Free and Open Source, Distributed, RESTful Search Engine

Elasticsearch

Elasticsearch is a distributed search and analytics engine, scalable data store and vector database optimized for speed and relevance on production-scale workloads. Elasticsearch is the foundation of Elastic’s open Stack platform. Search in near real-time over massive datasets, perform vector searches, integrate with generative AI applications, and much more.

Use cases enabled by Elasticsearch include:

Retrieval Augmented Generation (RAG)
Vector search
Full-text search
Logs
Metrics
Application performance monitoring (APM)
Security logs

... and more!

To learn more about Elasticsearch’s features and capabilities, see our product page.

To access information on machine learning innovations and the latest Lucene contributions from Elastic, more information can be found in Search Labs.

Get started

The simplest way to set up Elasticsearch is to create a managed deployment with Elasticsearch Service on Elastic Cloud.

If you prefer to install and manage Elasticsearch yourself, you can download the latest version from elastic.co/downloads/elasticsearch.

Run Elasticsearch locally

Warning

DO NOT USE THESE INSTRUCTIONS FOR PRODUCTION DEPLOYMENTS.

This setup is intended for local development and testing only.

Quickly set up Elasticsearch and Kibana in Docker for local development or testing, using the start-local script.

ℹ️ For more detailed information about the start-local setup, refer to the README on GitHub.

Prerequisites

If you don’t have Docker installed, download and install Docker Desktop for your operating system.
If you’re using Microsoft Windows, then install Windows Subsystem for Linux (WSL).

Trial license

This setup comes with a one-month trial license that includes all Elastic features.

After the trial period, the license reverts to Free and open - Basic. Refer to Elastic subscriptions for more information.

Run `start-local`

To set up Elasticsearch and Kibana locally, run the start-local script:

curl -fsSL https://elastic.co/start-local | sh

This script creates an elastic-start-local folder containing configuration files and starts both Elasticsearch and Kibana using Docker.

After running the script, you can access Elastic services at the following endpoints:

Elasticsearch: http://localhost:9200
Kibana: http://localhost:5601

The script generates a random password for the elastic user, which is displayed at the end of the installation and stored in the .env file.

Caution

This setup is for local testing only. HTTPS is disabled, and Basic authentication is used for Elasticsearch. For security, Elasticsearch and Kibana are accessible only through localhost.

API access

An API key for Elasticsearch is generated and stored in the .env file as ES_LOCAL_API_KEY. Use this key to connect to Elasticsearch with a programming language client or the REST API.

From the elastic-start-local folder, check the connection to Elasticsearch using curl:

source .env
curl $ES_LOCAL_URL -H "Authorization: ApiKey ${ES_LOCAL_API_KEY}"

To use the password for the elastic user, set and export the ES_LOCAL_PASSWORD environment variable. For example:

source .env
export ES_LOCAL_PASSWORD

Send requests to Elasticsearch

You send data and other requests to Elasticsearch through REST APIs. You can interact with Elasticsearch using any client that sends HTTP requests, such as the Elasticsearch language clients and curl.

Using curl

Here’s an example curl command to create a new Elasticsearch index, using basic auth:

curl -u elastic:$ES_LOCAL_PASSWORD \
  -X PUT \
  http://localhost:9200/my-new-index \
  -H 'Content-Type: application/json'

Using a language client

To connect to your local dev Elasticsearch cluster with a language client, you can use basic authentication with the elastic username and the password stored in the ES_LOCAL_PASSWORD environment variable.

You’ll use the following connection details:

Elasticsearch endpoint: http://localhost:9200
Username: elastic
Password: $ES_LOCAL_PASSWORD (Value you set in the environment variable)

For example, to connect with the Python elasticsearch client:

import os
from elasticsearch import Elasticsearch

username = 'elastic'
password = os.getenv('ES_LOCAL_PASSWORD') # Value you set in the environment variable

client = Elasticsearch(
    "http://localhost:9200",
    basic_auth=(username, password)
)

print(client.info())

Using the Dev Tools Console

Kibana’s developer console provides an easy way to experiment and test requests. To access the console, open Kibana, then go to Management > Dev Tools.

Add data

You index data into Elasticsearch by sending JSON objects (documents) through the REST APIs. Whether you have structured or unstructured text, numerical data, or geospatial data, Elasticsearch efficiently stores and indexes it in a way that supports fast searches.

For timestamped data such as logs and metrics, you typically add documents to a data stream made up of multiple auto-generated backing indices.

To add a single document to an index, submit an HTTP post request that targets the index.

POST /customer/_doc/1
{
  "firstname": "Jennifer",
  "lastname": "Walters"
}

This request automatically creates the customer index if it doesn’t exist, adds a new document that has an ID of 1, and stores and indexes the firstname and lastname fields.

The new document is available immediately from any node in the cluster. You can retrieve it with a GET request that specifies its document ID:

GET /customer/_doc/1

To add multiple documents in one request, use the _bulk API. Bulk data must be newline-delimited JSON (NDJSON). Each line must end in a newline character (\n), including the last line.

PUT customer/_bulk
{ "create": { } }
{ "firstname": "Monica","lastname":"Rambeau"}
{ "create": { } }
{ "firstname": "Carol","lastname":"Danvers"}
{ "create": { } }
{ "firstname": "Wanda","lastname":"Maximoff"}
{ "create": { } }
{ "firstname": "Jennifer","lastname":"Takeda"}

Search

Indexed documents are available for search in near real-time. The following search matches all customers with a first name of Jennifer in the customer index.

GET customer/_search
{
  "query" : {
    "match" : { "firstname": "Jennifer" }
  }
}

Explore

You can use Discover in Kibana to interactively search and filter your data. From there, you can start creating visualizations and building and sharing dashboards.

To get started, create a data view that connects to one or more Elasticsearch indices, data streams, or index aliases.

Go to Management > Stack Management > Kibana > Data Views.
Select Create data view.
Enter a name for the data view and a pattern that matches one or more indices, such as customer.
Select Save data view to Kibana.

To start exploring, go to Analytics > Discover.

Upgrade

To upgrade from an earlier version of Elasticsearch, see the Elasticsearch upgrade documentation.

Build from source

Elasticsearch uses Gradle for its build system.

To build a distribution for your local OS and print its output location upon completion, run:

./gradlew localDistro

To build a distribution for another platform, run the related command:

./gradlew :distribution:archives:linux-tar:assemble
./gradlew :distribution:archives:darwin-tar:assemble
./gradlew :distribution:archives:windows-zip:assemble

Distributions are output to distribution/archives.

To run the test suite, see TESTING.

Documentation

For the complete Elasticsearch documentation visit elastic.co.

For information about our documentation processes, see the docs README.

Examples and guides

The elasticsearch-labs repo contains executable Python notebooks, sample apps, and resources to test out Elasticsearch for vector search, hybrid search and generative AI use cases.

Contribute

For contribution guidelines, see CONTRIBUTING.

Questions? Problems? Suggestions?

To report a bug or request a feature, create a GitHub Issue. Please ensure someone else hasn’t created an issue for the same topic.
Need help using Elasticsearch? Reach out on the Elastic Forum or Slack. A fellow community member or Elastic engineer will be happy to help you out.

adityatandon15/Low-Level-Design-Course

All Code of LLD Playlist

LLD

All Codes and Notes for System Design (LLD) Playlist of Coder Army. Absolutely Free on Coder Army Youtube Channel.

Playlist Link : https://youtube.com/playlist?list=PLQEaRBV9gAFvzp6XhcNFpk1WdOcyVo9qT&si=Ihevlxfa3nczoXp0

quarkusio/quarkus

Quarkus: Supersonic Subatomic Java.

Quarkus - Supersonic Subatomic Java

Quarkus is a Cloud Native, (Linux) Container First framework for writing Java applications.

Container First: Minimal footprint Java applications optimal for running in containers.
Cloud Native: Embraces 12 factor architecture in environments like Kubernetes.
Versatile: From the smallest microservice to the largest monolith.
Fast startup: We do more at build time, we start fast.
JVM and native JVM for high throughput, native for constrained environments.
Unify imperative and reactive: Brings under one programming model non-blocking and imperative styles of development.
Standards-based: Based on the standards and frameworks you love and use (RESTEasy and JAX-RS, Hibernate ORM and JPA, Netty, Eclipse Vert.x, Eclipse MicroProfile, Apache Camel...).
Developer Joy: Development centric experience without compromise to bring your amazing apps to life in no time.

All under ONE framework.

Getting Started

Migration Guides

We collect all the migration notes in our migration guides.

Release Planning

Interested in when the next release is coming? Check our release planning document for details.

How to build Quarkus

The build instructions are available in the contribution guide.

apache/flink

Apache Flink

Apache Flink is an open source stream processing framework with powerful stream- and batch-processing capabilities.

Learn more about Flink at https://flink.apache.org/

Features

A streaming-first runtime that supports both batch processing and data streaming programs
Elegant and fluent APIs in Java
A runtime that supports very high throughput and low event latency at the same time
Support for event time and out-of-order processing in the DataStream API, based on the Dataflow Model
Flexible windowing (time, count, sessions, custom triggers) across different time semantics (event time, processing time)
Fault-tolerance with exactly-once processing guarantees
Natural back-pressure in streaming programs
Libraries for Graph processing (batch), Machine Learning (batch), and Complex Event Processing (streaming)
Custom memory management for efficient and robust switching between in-memory and out-of-core data processing algorithms
Compatibility layers for Apache Hadoop MapReduce
Integration with YARN, HDFS, HBase, and other components of the Apache Hadoop ecosystem

Streaming Example

// pojo class WordWithCount
public class WordWithCount {
    public String word;
    public int count;

    public WordWithCount() {}
    
    public WordWithCount(String word, int count) {
        this.word = word;
        this.count = count;
    }
}

// main method
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> text = env.socketTextStream(host, port);
DataStream<WordWithCount> windowCounts = text
    .flatMap(
        (FlatMapFunction<String, String>) (line, collector) 
            -> Arrays.stream(line.split("\\s")).forEach(collector::collect)
    ).returns(String.class)
    .map(word -> new WordWithCount(word, 1)).returns(TypeInformation.of(WordWithCount.class))
    .keyBy(wordWithCnt -> wordWithCnt.word)
    .window(TumblingProcessingTimeWindows.of(Duration.ofSeconds(5)))
    .sum("count").returns(TypeInformation.of(WordWithCount.class));

windowCounts.print();
env.execute();
}

Batch Example

// pojo class WordWithCount
public class WordWithCount {
    public String word;
    public int count;

    public WordWithCount() {}

    public WordWithCount(String word, int count) {
        this.word = word;
        this.count = count;
    }
}

// main method
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setRuntimeMode(RuntimeExecutionMode.BATCH);
FileSource<String> source = FileSource.forRecordStreamFormat(new TextLineInputFormat(), new Path("MyInput.txt")).build();
DataStreamSource<String> text = env.fromSource(source, WatermarkStrategy.noWatermarks(), "MySource");
DataStream<WordWithCount> windowCounts = text
        .flatMap((FlatMapFunction<String, String>) (line, collector) -> Arrays
                .stream(line.split("\\s"))
                .forEach(collector::collect)).returns(String.class)
        .map(word -> new WordWithCount(word, 1)).returns(TypeInformation.of(WordWithCount.class))
        .keyBy(wordWithCount -> wordWithCount.word)
        .sum("count").returns(TypeInformation.of(WordWithCount.class));

windowCounts.print();
env.execute();

Building Apache Flink from Source

Prerequisites for building Flink:

Unix-like environment (we use Linux, Mac OS X, Cygwin, WSL)
Git
Maven (we require version 3.8.6)
Java (version 11, 17, or 21)

Basic Build Instructions

First, clone the repository:

git clone https://github.com/apache/flink.git
cd flink

Then, choose one of the following commands based on your preferred Java version:

For Java 11

./mvnw clean package -DskipTests -Djdk11 -Pjava11-target

For Java 17 (Default)

./mvnw clean package -DskipTests -Djdk17 -Pjava17-target

For Java 21

./mvnw clean package -DskipTests -Djdk21 -Pjava21-target

The build process will take approximately 10 minutes to complete. Flink will be installed in build-target.

Notes

Make sure your JAVA_HOME environment variable points to the correct JDK version
The build command uses Maven wrapper (mvnw) which ensures the correct Maven version is used
The -DskipTests flag skips running tests to speed up the build process
Each Java version requires its corresponding profile (-Pjava -target) and JDK flag (-Djdk )

Developing Flink

The Flink committers use IntelliJ IDEA to develop the Flink codebase. We recommend IntelliJ IDEA for developing projects that involve Scala code.

Minimal requirements for an IDE are:

Support for Java and Scala (also mixed projects)
Support for Maven with Java and Scala

IntelliJ IDEA

The IntelliJ IDE supports Maven out of the box and offers a plugin for Scala development.

IntelliJ download: https://www.jetbrains.com/idea/
IntelliJ Scala Plugin: https://plugins.jetbrains.com/plugin/?id=1347

Check out our DEVELOPMENT.md guide for detailed IDE setup instructions.

Eclipse Scala IDE

NOTE: From our experience, this setup does not work with Flink due to deficiencies of the old Eclipse version bundled with Scala IDE 3.0.3 or due to version incompatibilities with the bundled Scala version in Scala IDE 4.4.1.

We recommend to use IntelliJ instead (see above)

Support

Don’t hesitate to ask!

Contact the developers and community on the mailing lists if you need any help.

Open an issue if you find a bug in Flink.

Documentation

The documentation of Apache Flink is located on the website: https://flink.apache.org or in the docs/ directory of the source code.

Fork and Contribute

This is an active open-source project. We are always open to people who want to use the system or contribute to it. Contact us if you are looking for implementation tasks that fit your skills. This article describes how to contribute to Apache Flink.

Externalized Connectors

Most Flink connectors have been externalized to individual repos under the Apache Software Foundation:

About

Apache Flink is an open source project of The Apache Software Foundation (ASF). The Apache Flink project originated from the Stratosphere research project.

conductor-oss/conductor

Conductor is an event driven agentic workflow engine providing durable and highly resilient execution engine for applications and AI Agents

Conductor - Internet scale Agentic Workflow Engine

Orchestrating distributed systems means wrestling with failures, retries, and state recovery. Conductor handles all of that so you don't have to.

Conductor is an open-source, durable workflow engine built at Netflix for orchestrating microservices, AI agents, and durable workflows at internet scale. Trusted in production at Netflix, Tesla, LinkedIn, and J.P. Morgan. Actively maintained by Orkes and a growing community.

Get Running in 60 Seconds

Prerequisites: Node.js v16+ and Java 21+ must be installed.

npm install -g @conductor-oss/conductor-cli
conductor server start

Open http://localhost:8080 — your server is running with the built-in UI.

Run your first workflow:

# Create a workflow that calls an API and parses the response — no workers needed
curl -s https://raw.githubusercontent.com/conductor-oss/conductor/main/docs/quickstart/workflow.json -o workflow.json
conductor workflow create workflow.json

Note: Running this command twice will return an error on the second call — the workflow already exists. This is expected behavior. Use conductor workflow update to modify an existing workflow.

conductor workflow start -w hello_workflow --sync

See the Quickstart guide for the full walkthrough, including writing workers and replaying workflows.

Docker Image for Conductor:

docker run -p 8080:8080 conductoross/conductor:latest # replace latest with the published version to pin to a specific version

All CLI commands have equivalent cURL/API calls. See the Quickstart for details.

Why Conductor is the workflow engine of choice for developers


Durable execution	Every step is persisted. Survives crashes, restarts, and network failures with configurable retries and timeouts.
Deterministic by design	Orchestration is separated from business logic — determinism is architectural, not developer discipline. Workers run any code; the workflow graph stays deterministic by construction.
AI agent orchestration	14+ native LLM providers, MCP tool calling, function calling, human-in-the-loop approval, and vector databases for RAG.
Dynamic at runtime	Dynamic forks, tasks, and sub-workflows resolved at runtime. LLMs generate JSON workflow definitions and Conductor executes them immediately.
Full replayability	Restart from the beginning, rerun from any task, or retry just the failed step — on any workflow, at any time.
Internet scale	Battle-tested at Netflix, Tesla, LinkedIn, and J.P. Morgan. Scales horizontally to billions of workflow executions.
Polyglot workers	Workers in Java, Python, Go, JavaScript, C#, Ruby, or Rust. Workers poll, execute, and report — run them anywhere.
Self-hosted, no lock-in	Apache 2.0. 5 persistence backends, 6 message brokers. Runs anywhere Docker or a JVM runs.

Ship Agents, Not Framework Code

Conductor workers are plain code — any language, any library, any I/O. No determinism constraints, no SDK ritual. The orchestration layer is declarative and machine-readable, so LLMs generate and compose workflows natively. If an agent crashes at iteration 12, it resumes from iteration 12.

An autonomous think-act agent in Conductor: discover tools via MCP, reason with an LLM, call the chosen tool, repeat until done.

{
  "name": "autonomous_agent",
  "description": "Agent that loops until the task is complete",
  "version": 1,
  "tasks": [
    {
      "name": "discover_tools",
      "taskReferenceName": "discover",
      "type": "LIST_MCP_TOOLS",
      "inputParameters": {
        "mcpServer": "${workflow.input.mcpServerUrl}"
      }
    },
    {
      "name": "agent_loop",
      "taskReferenceName": "loop",
      "type": "DO_WHILE",
      "loopCondition": "if ($.loop['think'].output.result.done == true) { false; } else { true; }",
      "loopOver": [
        {
          "name": "think",
          "taskReferenceName": "think",
          "type": "LLM_CHAT_COMPLETE",
          "inputParameters": {
            "llmProvider": "openai",
            "model": "gpt-4o-mini",
            "messages": [
              {
                "role": "system",
                "message": "You are an autonomous agent. Available tools: ${discover.output.tools}. Previous results: ${loop.output.results}. Respond with JSON: {\"action\": \"tool_name\", \"arguments\": {}, \"done\": false} or {\"answer\": \"final answer\", \"done\": true}."
              },
              { "role": "user", "message": "${workflow.input.task}" }
            ]
          }
        },
        {
          "name": "act",
          "taskReferenceName": "act",
          "type": "SWITCH",
          "expression": "$.think.output.result.done ? 'done' : 'call_tool'",
          "decisionCases": {
            "call_tool": [
              {
                "name": "execute_tool",
                "taskReferenceName": "tool_call",
                "type": "CALL_MCP_TOOL",
                "inputParameters": {
                  "mcpServer": "${workflow.input.mcpServerUrl}",
                  "method": "${think.output.result.action}",
                  "arguments": "${think.output.result.arguments}"
                }
              }
            ]
          }
        }
      ]
    }
  ]
}

Every step is durably persisted — no framework, no SDK lock-in. Code-first engines force your code to be deterministic so the framework can replay it. Conductor makes the engine deterministic — so your code doesn't have to be.

See the Build Your First AI Agent guide for the full walkthrough.

Conductor Skills for AI Coding Assistants

Conductor Skills let AI coding assistants (Claude Code, Gemini CLI, and others) create, manage, and deploy Conductor workflows directly from your terminal.

Claude

# Install Skills for Claude Code
/plugin marketplace add conductor-oss/conductor-skills
/plugin install conductor@conductor-skills

Install for all detected agents

One command to auto-detect every supported agent on your system and install globally where possible. Re-run anytime — it only installs for newly detected agents.

macOS / Linux

curl -sSL https://conductor-oss.github.io/conductor-skills/install.sh | bash -s -- --all

Windows (PowerShell) / (cmd)

# powershell
irm https://conductor-oss.github.io/conductor-skills/install.ps1 -OutFile install.ps1; .\install.ps1 -All

# cmd
powershell -c "irm https://conductor-oss.github.io/conductor-skills/install.ps1 -OutFile install.ps1; .\install.ps1 -All"

SDKs

Language	Repository	Install
☕ Java	conductor-oss/java-sdk	Maven Central
🐍 Python	conductor-oss/python-sdk	`pip install conductor-python`
🟨 JavaScript	conductor-oss/javascript-sdk	`npm install @io-orkes/conductor-javascript`
🐹 Go	conductor-oss/go-sdk	`go get github.com/conductor-sdk/conductor-go`
🟣 C#	conductor-oss/csharp-sdk	`dotnet add package conductor-csharp`
💎 Ruby	conductor-oss/ruby-sdk	(incubating)
🦀 Rust	conductor-oss/rust-sdk	(incubating)

Documentation & Community

Documentation — Architecture, guides, API reference, and cookbook recipes.
Slack — Community discussions and support.
Community Forum — Ask questions and share patterns.

Backend Configuration

Backend	Configuration
Redis + ES7 (default)	config-redis.properties
Redis + ES8	config-redis-es8.properties
Redis + OpenSearch	config-redis-os.properties
Postgres	config-postgres.properties
Postgres + ES7	config-postgres-es7.properties
MySQL + ES7	config-mysql.properties

Build From Source

Requirements and instructions

Requirements: Docker Desktop, Java (JDK) 21+, Node 18 (for UI)

git clone https://github.com/conductor-oss/conductor
cd conductor
./gradlew build

# (optional) Build UI
# ./build_ui.sh

# Start local server
cd server
../gradlew bootRun

See the full build guide for details.

FAQ

Is this the same as Netflix Conductor?

Yes. Conductor OSS is the continuation of the original Netflix Conductor repository after Netflix contributed the project to the open-source foundation.

Is Conductor open source?

Yes. Conductor is a fully open-source workflow engine licensed under Apache 2.0. You can self-host on your own infrastructure with 5 persistence backends and 6 message brokers.

Is this project actively maintained?

Yes. Orkes is the primary maintainer and offers an enterprise SaaS platform for Conductor across all major cloud providers.

Can Conductor scale to handle my workload?

Yes. Built at Netflix, battle-tested at internet scale. Conductor scales horizontally across multiple server instances to handle billions of workflow executions.

Does Conductor support durable execution?

Yes. Conductor pioneered durable execution patterns, ensuring workflows and durable agents complete reliably despite infrastructure failures or crashes. Every step is persisted and recoverable.

Can I replay a workflow after it completes or fails?

Yes. Conductor preserves full execution history indefinitely. You can restart from the beginning, rerun from a specific task, or retry just the failed step — via API or UI.

Can Conductor orchestrate AI agents and LLMs?

Yes. Conductor provides native integration with 14+ LLM providers (Anthropic, OpenAI, Gemini, Bedrock, and more), MCP tool calling, function calling, human-in-the-loop approval, and vector database integration for RAG.

Why does Conductor separate orchestration from code?

Coupling orchestration logic with business logic forces developers to maintain determinism constraints manually — no direct I/O, no system time, no randomness in workflow definitions. Conductor eliminates this entire class of bugs by making the orchestration layer deterministic by construction. Workers are plain code with zero framework constraints — write them in any language, use any library, call any API.

Isn't writing workflows as code more powerful than JSON?

It depends on what you mean by "powerful." In code-first engines, the workflow definition and your business logic live in the same runtime — which means the engine must replay your code to recover state. That forces determinism constraints on your business logic: no direct I/O, no system time, no threads, no randomness. Conductor separates these concerns. The orchestration graph is declarative (JSON), so it's deterministic by construction. Your workers are plain code with zero constraints — use any language, any library, call any API. You get the full power of code where it matters (business logic) without the framework tax where it doesn't (orchestration).

Can JSON workflows handle complex logic like branching, loops, and error handling?

Yes. Conductor supports SWITCH (conditional branching), DO_WHILE (loops with configurable iteration cleanup), FORK_JOIN (parallel execution with dynamic fanout), SUB_WORKFLOW (composition), and DYNAMIC tasks resolved at runtime. These are composable — you can nest loops inside branches inside forks. For error handling, every task supports configurable retries, timeouts, and optional/compensating tasks. The declarative model doesn't limit complexity — it makes complexity visible and debuggable.

How does Conductor handle workflow versioning?

Workflow definitions are versioned by number. Running executions continue on the version they started with — deploying a new version never breaks in-flight workflows. There's no replay compatibility problem because Conductor doesn't replay your code. The orchestration graph is the source of truth, and each execution is pinned to its definition version. Update orchestration logic without redeploying workers and without worrying about breaking running workflows.

What about developer experience — IDE support, type checking, debugging?

Conductor provides a built-in visual UI for designing, running, and debugging workflows. Every execution is fully observable: you can inspect the input, output, timing, and retry history of every task. For type safety, Conductor validates workflow inputs and task I/O against JSON Schema. Workers are plain code in your language of choice — you get full IDE support, type checking, and debugging for your business logic. The orchestration layer is visible in the UI, not hidden inside a framework.

Can Conductor handle long-running workflows (days, weeks, months)?

Yes. Conductor is designed for long-running workflows. Executions are fully persisted — a workflow can pause for months waiting for a human approval, an external signal, or a scheduled timer, and resume exactly where it left off. There's no in-memory state to lose. This is the same mechanism that makes AI agent loops durable: if iteration 12 waits for a human review for three weeks, iteration 13 picks up right where it left off.

Don't I lose flexibility by not having orchestration in code?

You gain flexibility. Because workflows are JSON, LLMs can generate and modify them at runtime — no compile/deploy cycle. Dynamic forks let you fan out to a variable number of parallel tasks determined at runtime. Dynamic sub-workflows let one workflow compose others by name. And because workers are decoupled from orchestration, you can update the workflow graph or swap worker implementations independently. Code-first engines couple these together, so changing orchestration means redeploying and re-versioning your code.

How does Conductor compare to other workflow engines?

Conductor is an open-source workflow engine with native LLM task types for 14+ providers, built-in MCP integration, durable execution, full replayability, and 7 language SDKs. Unlike code-first engines, Conductor separates orchestration from business logic — determinism is an architectural guarantee, not a developer constraint. Your workers are plain code with zero framework rules. The orchestration layer is declarative, so it's observable, versionable, and composable by LLMs. Battle-tested at Netflix, Tesla, LinkedIn, and J.P. Morgan.

Is Orkes Conductor compatible with Conductor OSS?

100% compatible. Orkes Conductor is built on top of Conductor OSS with full API and workflow compatibility.

Contributing

We welcome contributions from everyone!

Report Issues: Open an issue on GitHub.
Contribute code: Check out our Contribution Guide and good first issues.
Improve docs: Help keep our documentation great.

Contributors

Roadmap

See the Conductor OSS Roadmap. Want to participate? Reach out.

License

Conductor is licensed under the Apache 2.0 License.

bethington/ghidra-mcp

Ghidra MCP Server — 200+ MCP tools for AI-powered reverse engineering. GUI plugin + headless server, lazy tool loading, convention enforcement, batch operations, Ghidra Server integration, and Docker deployment.

Ghidra MCP Server

If you find this useful, please ⭐ star the repo — it helps others discover it!

If Ghidra MCP saves you time, consider sponsoring the project. One-time and recurring support both help fund compatibility updates, production hardening, docs, and new tooling.

A production-ready Model Context Protocol (MCP) server that bridges Ghidra's powerful reverse engineering capabilities with modern AI tools and automation frameworks. 252 MCP tools, battle-tested AI workflows, and the most comprehensive Ghidra-MCP integration available — now including P-code emulation, live debugger integration, and PCode-graph data flow analysis.

Why Ghidra MCP?

Most Ghidra MCP implementations give you a handful of read-only tools and call it a day. This project is different — it was built by a reverse engineer who uses it daily on real binaries, not as a demo.

252 MCP tools — 3x more than any competing implementation. Not just read operations — full write access for renaming, typing, commenting, structure creation, script execution, P-code emulation, and live debugging.
Battle-tested AI workflows — Proven documentation workflows (V5) refined across hundreds of functions. Includes step-by-step prompts, Hungarian notation reference, batch processing guides, and orphaned code discovery.
Production-grade reliability — Atomic transactions, batch operations (93% API call reduction), configurable timeouts, and graceful error handling. No silent failures.
Cross-binary documentation transfer — SHA-256 function hash matching propagates documentation across binary versions automatically. Document once, apply everywhere.
Full Ghidra Server integration — Connect to shared Ghidra servers, manage repositories, version control, checkout/checkin workflows, and multi-user collaboration.
Headless and GUI modes — Run with or without the Ghidra GUI. Docker-ready for CI/CD pipelines and automated analysis at scale.
Opinionated by design — v5.0 moves naming conventions, type safety, and documentation standards into the tool layer. AI agents and human engineers produce consistent output without style guides in every prompt.

Convention Enforcement

You've been there: six months into a project you find ProcessItem, process_items, handleItem, and ItemProc in the same codebase — four functions doing the same thing, named by four different sessions or engineers with no shared contract. Fixing it takes longer than it should, and the problem will happen again.

v5.0 moves conventions from "things to remember" into the tool layer, where they can actually be enforced.

Tier	Behavior	Example
Auto-fix	Applied silently	`count` field on a `uint32` → auto-prefixed `dwCount` on save
Warn	Change goes through, warning returned	`processData` → "name should be PascalCase with a verb: `ProcessData`"
Reject	Change blocked with explanation	`undefined → undefined` type change → "no-op rejected, type unchanged"

For AI agents, this means consistent output across every session, every model, every run — without pasting a style guide into every prompt. The tool knows the rules; the model just needs to make the call.

For teams, it eliminates the entire class of review comment that says "that's not our naming convention." Convention arbitration stays in the tool, not in code review.

For solo work at scale, analyze_function_completeness gives you a 0–100% score that measures honestly: structural deductions (unfixable compiler artifacts) are forgiven in your effective score, log-scaling prevents one bad category from burying everything else, and tiered plate comment quality means you know exactly what's missing and why.

🌟 Features

Core MCP Integration

Full MCP Compatibility — Complete implementation of Model Context Protocol
252 MCP Tools — Comprehensive API surface covering every aspect of binary analysis
Production-Ready Reliability — Atomic transactions, batch operations, configurable timeouts
Real-time Analysis — Live integration with Ghidra's analysis engine

Compatibility note: MCP tool names are normalized for GitHub Copilot CLI and CAPI validation. Exposed tool names use lowercase letters, digits, underscores, and hyphens only; nested HTTP paths such as /debugger/status are advertised as names like debugger_status_2 when needed to avoid collisions with static bridge tools.

Binary Analysis Capabilities

Function Analysis — Decompilation, call graphs, cross-references, completeness scoring
Data Flow Analysis — PCode-graph value propagation (forward / backward) from any variable or register
Data Structure Discovery — Struct/union/enum creation with field analysis and naming suggestions
String Extraction — Regex search, quality filtering, and string-anchored function discovery
Import/Export Analysis — Symbol tables, external locations, ordinal import resolution
Memory & Data Inspection — Raw memory reads, byte pattern search, array boundary detection
Cross-Binary Documentation — Function hash matching and documentation propagation across versions

Dynamic Analysis (v5.4.0)

P-code Emulation — Run any function in isolation via Ghidra's EmulatorHelper; brute-force API hash resolution in milliseconds
Live Debugger Integration — 17 Java endpoints + 22 Python bridge tools over Ghidra's TraceRmi framework (dbgeng on Windows PE, gdb/lldb otherwise): attach, step, breakpoints, registers, memory reads, non-breaking function tracing, ASLR-aware static↔dynamic address translation

AI-Powered Reverse Engineering Workflows

Function Documentation Workflow V5 — 7-step process for complete function documentation with Hungarian notation, type auditing, and automated verification scoring
Batch Documentation — Parallel subagent dispatch for documenting multiple functions simultaneously
Orphaned Code Discovery — Automated scanner finds undiscovered functions in gaps between known code
Data Type Investigation — Systematic workflows for structure discovery and field analysis
Cross-Version Matching — Hash-based function matching across different binary versions

Development & Automation

Ghidra Script Management — Create, run, update, and delete Ghidra scripts entirely via MCP
Multi-Program Support — Switch between and compare multiple open programs
Batch Operations — Bulk renaming, commenting, typing, and label management (93% fewer API calls)
Headless Server — Full analysis without Ghidra GUI — Docker and CI/CD ready
Project & Version Control — Create projects, manage files, Ghidra Server integration
Analysis Control — List, configure, and trigger Ghidra analyzers programmatically

🚀 Quick Start

Prerequisites

Java 21 LTS (OpenJDK recommended)
Apache Maven 3.9+
Ghidra 12.1 (or compatible version)
Python 3.10+ with pip

Shared Ghidra Server users: Ghidra 12.1 clients require a Ghidra Server at 12.1, 12.0.5, or a newer compatible version. Upgrade the server before using this plugin from a 12.1 client.

Ghidra 12.1 ships Jython as an optional extension. Java scripts work by default, but .py scripts in ghidra_scripts/ require installing the Jython extension from File > Install Extensions and restarting Ghidra.

Installation

Recommended for all platforms: use python -m tools.setup directly.

ensure-prereqs installs runtime Python requirements plus the Ghidra JARs needed in the local Maven repository. deploy copies the build output, installs the user-profile extension, and patches Ghidra user config.

Clone the repository:

git clone https://github.com/bethington/ghidra-mcp.git
cd ghidra-mcp

Recommended: run environment preflight first:

python -m tools.setup preflight --ghidra-path "F:\ghidra_12.1_PUBLIC"

Build and deploy to Ghidra:
```
python -m tools.setup ensure-prereqs --ghidra-path "F:\ghidra_12.1_PUBLIC"
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "F:\ghidra_12.1_PUBLIC"
```
deploy saves/closes an already-running matching Ghidra instance when needed, installs the extension, starts Ghidra, waits for MCP health, and runs schema smoke checks.

Optional strict/manual mode (advanced):

# Skip automatic prerequisite setup
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "F:\ghidra_12.1_PUBLIC"

Show command help:
```
python -m tools.setup --help
```

Optional build-only mode (advanced/troubleshooting):

python -m tools.setup build

Supported build path: python -m tools.setup build uses Maven under the hood and is the canonical workflow used by the repo tasks and docs.

# Manual Maven build (requires Ghidra deps already installed in local .m2)
mvn clean package assembly:single -DskipTests

# Secondary/manual Gradle build path only (not used by tools.setup or VS Code tasks)
GHIDRA_INSTALL_DIR=/path/to/ghidra gradle buildExtension

Installation (Linux — Ubuntu/Debian)

Clone the repository:

git clone https://github.com/bethington/ghidra-mcp.git
cd ghidra-mcp

Install system prerequisites (if not already installed):

sudo apt update && sudo apt install -y openjdk-21-jdk maven python3 python3-pip curl jq unzip

Run environment preflight:

python -m tools.setup preflight --ghidra-path ~/ghidra_12.1_PUBLIC

Build and deploy to Ghidra (single command):
```
python -m tools.setup ensure-prereqs --ghidra-path ~/ghidra_12.1_PUBLIC
python -m tools.setup build
python -m tools.setup deploy --ghidra-path ~/ghidra_12.1_PUBLIC
```
This will:
- Install Ghidra JAR dependencies into your local ~/.m2/repository
- Build GhidraMCP-<version>.zip with Maven
- Extract the extension to ~/.config/ghidra/ghidra_<version>_PUBLIC/Extensions/
- Update preferences with LastExtensionImportDirectory
- Install Python requirements

Optional: setup only Maven dependencies:

python -m tools.setup install-ghidra-deps --ghidra-path ~/ghidra_12.1_PUBLIC

Show command help:
```
python -m tools.setup --help
```

Linux paths: The extension is installed to $HOME/.config/ghidra/ghidra_<version>_PUBLIC/Extensions/GhidraMCP/. Ghidra config files are in $HOME/.config/ghidra/ghidra_<version>_PUBLIC/.

Installation (macOS — Homebrew)

Install prerequisites:

brew install openjdk@21 maven python ghidra

Clone the repository:

git clone https://github.com/bethington/ghidra-mcp.git
cd ghidra-mcp

Install Ghidra JARs into local Maven:

 python -m tools.setup install-ghidra-deps \
    --ghidra-path /opt/homebrew/opt/ghidra/libexec

Build and deploy:
```
 python -m tools.setup ensure-prereqs \
    --ghidra-path /opt/homebrew/opt/ghidra/libexec
 python -m tools.setup build
 python -m tools.setup deploy \
    --ghidra-path /opt/homebrew/opt/ghidra/libexec
```
The extension is installed to ~/Library/ghidra/ghidra_12.1_PUBLIC/Extensions/GhidraMCP/.

Note: --ghidra-version is required when using the Homebrew path because the path contains no version string.
Start Ghidra and enable the plugin:
```
/opt/homebrew/opt/ghidra/libexec/ghidraRun
```
In the main project window: Tools > GhidraMCP > Start MCP Server

Configure Cursor/Claude MCP (~/.cursor/mcp.json):

{
  "mcpServers": {
    "ghidra": {
      "command": "uv",
      "args": ["run", "--script", "/path/to/ghidra-mcp/bridge_mcp_ghidra.py"]
    }
  }
}

Installation (Arch Linux — AUR)

@Pandoriaantje maintains community AUR packages:

ghidra-mcp-git — tracks main
ghidra-mcp — tracks tagged releases

Install with your AUR helper of choice, e.g.:

yay -S ghidra-mcp        # or ghidra-mcp-git

Basic Usage

Option 1: Stdio Transport (Recommended for AI tools)

python bridge_mcp_ghidra.py

Option 2: Streamable HTTP Transport (Recommended for web/HTTP clients)

python bridge_mcp_ghidra.py --transport streamable-http --mcp-host 127.0.0.1 --mcp-port 8081

MCP client config for the HTTP transport (add to your client's MCP config file):

{
  "mcpServers": {
    "ghidra-mcp-http": {
      "url": "http://127.0.0.1:8081/mcp"
    }
  }
}

Option 3: SSE Transport (Deprecated — use streamable-http instead)

python bridge_mcp_ghidra.py --transport sse --mcp-host 127.0.0.1 --mcp-port 8081

Bridge advanced flags

Flag	Default	Description
`--transport`	`stdio`	`stdio` (AI tools), `streamable-http` (web clients), `sse` (deprecated)
`--mcp-host`	`127.0.0.1`	Bind host for HTTP transports
`--mcp-port`	—	Port for HTTP transports
`--lazy`	off	Load only the default tool groups on connect. Faster startup, but MCP clients that don't support `tools/list_changed` will see an incomplete tool list. Not recommended for Claude Code.
`--no-lazy`	(default)	Load all tool groups immediately on connect. Required for most AI clients.
`--default-groups`	`listing,function,program`	Comma-separated groups loaded on connect when `--lazy` is set.

Optional: Start the standalone debugger server

python -m pip install -r requirements-debugger.txt
python -m debugger

The debugger server listens on http://127.0.0.1:8099/ by default and is required for the debugger_* proxy tools exposed by the MCP bridge.

Debugger server flags:

Flag	Default	Description
`--port`	`8099`	HTTP server port
`--host`	`127.0.0.1`	Bind address (`0.0.0.0` to expose on LAN)
`--exports-dir`	—	Path to a `dll_exports/` directory for ordinal-to-name resolution
`--log-level`	`INFO`	`DEBUG`, `INFO`, `WARNING`, or `ERROR`

Set GHIDRA_DEBUGGER_URL in .env if you change the default port or host so the bridge can find it.

In Ghidra

Start Ghidra and open a CodeBrowser window
In CodeBrowser, enable the plugin via File > Configure > Configure All Plugins > GhidraMCP
Optional: configure custom port via CodeBrowser > Edit > Tool Options > GhidraMCP HTTP Server
Start the server via Tools > GhidraMCP > Start MCP Server
The server runs on http://127.0.0.1:8089/ by default

Verify It's Working

# Quick health check
curl http://127.0.0.1:8089/check_connection
# Expected: "Connected: GhidraMCP plugin running with program '<name>'"

# Get version info
curl http://127.0.0.1:8089/get_version

Support This Project

If Ghidra MCP saves you engineering or reverse-engineering time, consider sponsoring the project.

One-time sponsorship helps fund fixes, compatibility updates, and release work.
Recurring sponsorship helps keep maintenance, docs, and production hardening moving.
Company support helps prioritize long-term reliability for the bridge, headless server, debugger integration, and workflow tooling.

🔒 Security

GhidraMCP is designed for localhost-only development. The default configuration — HTTP server bound to 127.0.0.1, no authentication — is safe on a trusted single-user workstation and matches pre-v5.4.1 behavior.

If you expose the server beyond loopback, configure these three environment variables first. The server refuses to start on a non-loopback bind without a token.

Env var	Effect
`GHIDRA_MCP_AUTH_TOKEN`	When set, every HTTP request must carry `Authorization: Bearer <token>`. Timing-safe comparison. `/mcp/health`, `/health`, `/check_connection` are exempt.
`GHIDRA_MCP_ALLOW_SCRIPTS`	Set to `1`, `true`, or `yes` to enable `/run_script_inline` and `/run_ghidra_script`. Off by default as of v5.4.1 — these endpoints execute arbitrary Java against the Ghidra process. In headless mode this also triggers OSGi `BundleHost` initialization at server startup (Felix framework, ~hundreds of ms); leave it off if you don't need script execution.
`GHIDRA_MCP_FILE_ROOT`	When set to a directory path, filesystem-path endpoints (`/load_program`, `/import_file`, `/open_project`, `/delete_file`, etc.) canonicalize the input and require it to fall under this root. Prevents path-traversal.

Name-quality enforcement is separate from security. By default, rename_function_by_address and global write endpoints reject names that fail the built-in quality gates, and struct field writes apply the built-in field prefix convention. Disable the built-in convention layer with Edit > Tool Options > GhidraMCP HTTP Server > Strict Naming Enforcement. The same Tool Options checkbox covers rename_data, rename_global_variable, set_global, the apply_data_type prefix/type guard, and struct-field Hungarian prefix auto-fixes in create_struct, add_struct_field, and modify_struct_field. The setting is read when the MCP server starts or restarts. Function/global convention warnings are still returned when enforcement is disabled.

Example: exposing to a private LAN with auth

export GHIDRA_MCP_AUTH_TOKEN=$(openssl rand -hex 32)
export GHIDRA_MCP_ALLOW_SCRIPTS=1     # only if your workflow needs it
export GHIDRA_MCP_FILE_ROOT=/srv/ghidra/inputs

java -jar GhidraMCPHeadless.jar --bind 0.0.0.0 --port 8089

Ghidra Server authentication

When connecting to a shared Ghidra Server, GhidraMCP can suppress the password dialog automatically. It resolves credentials in this order (first non-empty value wins):

Compatibility note: Ghidra 12.1 clients require Ghidra Server 12.1, 12.0.5, or a newer compatible server. Older shared servers are not safe targets for a 12.1 client upgrade.

GHIDRA_SERVER_PASSWORD environment variable (or .env file in the Ghidra install directory or ~)
~/.ghidra-cred — single-line password file in your home directory
<ghidra-install-dir>/.ghidra-cred

Username resolves similarly: GHIDRA_SERVER_USER env var → user.name system property.

If no password is found, Ghidra shows its normal GUI prompt. Set these in .env (see .env.template for the full block) to enable silent auth.

Migration from v5.4.0 → v5.4.1

Script endpoints now default-off. If you relied on /run_script_inline or /run_ghidra_script, export GHIDRA_MCP_ALLOW_SCRIPTS=1. This is a deliberate breaking change; the prior default was unsafe.
Localhost-only deployments need no changes. Auth, bind refusal, and path-root checks are all opt-in.

❓ Troubleshooting

"GhidraMCP" menu not appearing in Tools

Cause: Plugin not enabled or installed incorrectly.

Solution:

Verify extension is installed: File > Install Extensions — GhidraMCP should be listed
Enable the plugin: File > Configure > Configure All Plugins > GhidraMCP (check the box)
Restart Ghidra after installation/enabling

Server not responding / Connection refused

Cause: Server not started or wrong port.

Solution:

Ensure you started the server: Tools > GhidraMCP > Start MCP Server
Check configured port: Edit > Tool Options > GhidraMCP HTTP Server

Check if port is in use:

# Linux/macOS
lsof -i :8089
# Windows
netstat -ano | findstr :8089

Look for errors in Ghidra console: Window > Console

`python -m debugger` fails with `ModuleNotFoundError` for `pybag` or `comtypes`

Cause: The standalone debugger server uses optional Windows-only Python dependencies that are not installed by the base requirements file.

Solution:

python -m pip install -r requirements-debugger.txt
python -m debugger

If you have both a global Python and a project venv, make sure you install into and run from the same interpreter.

500 Internal Server Errors

Cause: Server-side exception, often due to missing program data.

Solution:

Ensure a binary is loaded in CodeBrowser
Run auto-analysis first: Analysis > Auto Analyze
Check Ghidra console (Window > Console) for Java exceptions
Some operations require fully analyzed binaries

404 Not Found Errors

Cause: Endpoint doesn't exist or wrong URL.

Solution:

Verify endpoint exists: curl http://127.0.0.1:8089/get_version
Check for typos in endpoint name
Ensure you're using correct HTTP method (GET vs POST)

Python Ghidra scripts fail with "No script provider found"

Cause: In Ghidra 12.1, Jython support is no longer enabled by default. .py scripts need the bundled Jython extension; Python 3 scripts should use PyGhidra instead of the Ghidra Script Manager.

Solution:

In the Ghidra Front End, open File > Install Extensions.
Check Jython, restart Ghidra, then refresh Script Manager.
For new automation, prefer Java Ghidra scripts or PyGhidra.

Extension not appearing in Install Extensions

Cause: JAR file in wrong location.

Solution:

Manual install location: ~/.ghidra/ghidra_12.1_PUBLIC/Extensions/GhidraMCP/lib/GhidraMCP.jar
Or use: File > Install Extensions > Add and select the ZIP file
Ensure JAR/ZIP was built for your Ghidra version

Build fails with "Ghidra dependencies not found"

Cause: Ghidra JARs not installed in local Maven repository.

Solution:

# Windows (recommended)
python -m tools.setup install-ghidra-deps --ghidra-path "C:\ghidra_12.1_PUBLIC"

📊 Production Performance

MCP Tools: 252 tools fully implemented
Speed: Sub-second response for most operations
Efficiency: 93% reduction in API calls via batch operations
Reliability: Atomic transactions with all-or-nothing semantics
AI Workflows: Proven documentation prompts refined across hundreds of real functions
Deployment: Automated version-aware deployment script

🛠️ API Reference

Core Operations

check_connection - Verify MCP connectivity
get_metadata - Program metadata and info
get_version - Server version information
get_function_count - Return total function count for a program
get_entry_points - Binary entry points discovery
get_current_address - Get cursor address (GUI only)
get_current_function - Get function at cursor (GUI only)
get_current_selection - Get current selection context (address + function)
read_memory - Read raw bytes from memory
save_program - Save the current program
exit_ghidra - Save and exit Ghidra gracefully

Function Analysis

list_functions - List all functions (paginated)
list_functions_enhanced - List with isThunk/isExternal flags
list_classes - List namespace/class names (paginated)
search_functions_enhanced - Advanced function search with filters
decompile_function - Decompile function to C pseudocode
force_decompile - Force fresh decompilation (bypass cache)
batch_decompile - Batch decompile multiple functions
get_function_callers - Get function callers
get_function_callees - Get function callees
get_function_call_graph - Function relationship graph
get_full_call_graph - Complete call graph for program
get_function_signature - Get function prototype string
get_function_hash - SHA-256 hash of normalized function opcodes
get_bulk_function_hashes - Paginated bulk hashing with filter
get_function_jump_targets - Get jump target addresses from disassembly
get_function_metrics - Get complexity metrics for a function
get_function_xrefs - Get function cross-references
analyze_function_full - Comprehensive function analysis
analyze_function_completeness - Documentation completeness score
batch_analyze_completeness - Batch completeness analysis for multiple functions
find_similar_functions_across_programs - Cross-program similarity matching
bulk_fuzzy_match_functions - Bulk fuzzy match across all functions
diff_functions - Diff two functions side by side
validate_function_prototype - Validate a function prototype string
can_rename_at_address - Check if address can be renamed
delete_function - Delete function at address

Memory & Data

list_segments - Memory segments and layout
list_data_items - List defined data labels and values (paginated)
list_data_items_by_xrefs - Data items sorted by xref count
get_function_by_address - Function at address
disassemble_function - Disassembly listing
disassemble_bytes - Raw byte disassembly
get_xrefs_to - Cross-references to address
get_xrefs_from - Cross-references from address
get_bulk_xrefs - Bulk cross-reference lookup
analyze_data_region - Analyze memory region structure
inspect_memory_content - View raw memory content
detect_array_bounds - Detect array boundaries
search_byte_patterns - Search for byte patterns
create_memory_block - Create a new memory block

Cross-Binary Documentation

get_function_documentation - Export complete function documentation
apply_function_documentation - Import documentation to target function
compare_programs_documentation - Compare documentation between programs
build_function_hash_index - Build persistent JSON index
lookup_function_by_hash - Find matching functions in index
propagate_documentation - Apply docs to all matching instances

Data Types & Structures

list_data_types - Available data types
search_data_types - Search for data types
get_data_type_size - Get byte size of a data type
get_valid_data_types - Get list of valid Ghidra builtin types
get_struct_layout - Get detailed field layout of a structure
validate_data_type - Validate data type syntax
validate_data_type_exists - Check if a data type exists
create_struct - Create custom structure
add_struct_field - Add field to structure
modify_struct_field - Modify existing field
remove_struct_field - Remove field from structure
create_enum - Create enumeration
get_enum_values - Get enumeration values
create_array_type - Create array data type
create_typedef - Create typedef alias
create_union - Create union data type
create_pointer_type - Create pointer data type
clone_data_type - Clone a data type with a new name
apply_data_type - Apply type to address
delete_data_type - Delete a data type
consolidate_duplicate_types - Merge duplicate types
suggest_field_names - AI-assisted field name suggestions for a structure
create_data_type_category - Create a category folder in the type manager
move_data_type_to_category - Move a type to a different category
list_data_type_categories - List all data type categories
import_data_types - Import types from a GDT/header file

Symbols & Labels

list_imports - Imported symbols and libraries
list_exports - Exported symbols and functions
list_external_locations - External location references
get_external_location - Specific external location detail
list_strings - Extracted strings with analysis
search_memory_strings - Search strings by regex/substring pattern
list_namespaces - Available namespaces
list_globals - Global variables
create_label - Create label at address
batch_create_labels - Bulk label creation
delete_label - Delete label at address
batch_delete_labels - Bulk label deletion
rename_label - Rename existing label
rename_or_label - Rename or create label

Renaming & Documentation

rename_function - Rename function by name
rename_function_by_address - Rename function by address
rename_data - Rename data item
rename_variables - Rename function variables
rename_global_variable - Rename global variable
rename_external_location - Rename external reference
batch_rename_function_components - Bulk renaming
set_decompiler_comment - Set decompiler comment
set_disassembly_comment - Set disassembly comment
set_plate_comment - Set function plate comment
get_plate_comment - Get function plate comment
batch_set_comments - Bulk comment setting
clear_function_comments - Clear all comments for a function
list_bookmarks - List all bookmarks
set_bookmark - Create or update a bookmark
delete_bookmark - Delete a bookmark

Type System

set_function_prototype - Set function signature
set_local_variable_type - Set variable type
set_parameter_type - Set parameter type
batch_set_variable_types - Bulk type setting
set_variable_storage - Control variable storage location
set_function_no_return - Mark function as non-returning
clear_instruction_flow_override - Clear flow override on instruction
list_calling_conventions - Available calling conventions
get_function_variables - Get all function variables
get_function_labels - Get labels in function

Ghidra Script Management

list_scripts - List available scripts
list_ghidra_scripts - List custom Ghidra scripts
save_ghidra_script - Save new script
get_ghidra_script - Get script contents
run_ghidra_script - Execute Ghidra script by name
run_script_inline - Execute inline script code
update_ghidra_script - Update existing script
delete_ghidra_script - Delete script

Multi-Program Support

list_open_programs - List all open programs
get_current_program_info - Current program details
switch_program - Switch active program
list_project_files - List project files
open_program - Open program from project

Project Lifecycle

create_project - Create a new Ghidra project
open_project - Open an existing project
close_project - Close the current project
delete_project - Delete a project
list_projects - List Ghidra projects in a directory

Project Organization

create_folder - Create a folder in the project tree
move_file - Move a domain file to another folder
move_folder - Move a folder to another location
delete_file - Delete a domain file from the project

Analysis Tools

find_next_undefined_function - Find undefined functions
find_undocumented_by_string - Find functions by string reference
find_undocumented_functions_by_strings - Find undocumented functions by string references
get_assembly_context - Get assembly context
analyze_struct_field_usage - Analyze structure field access
get_field_access_context - Get field access patterns
create_function - Create function at address
analyze_control_flow - Cyclomatic complexity and loop detection
analyze_call_graph - Build function call graph
analyze_api_call_chains - Detect API call threat patterns
detect_malware_behaviors - Detect malware behavior categories
find_anti_analysis_techniques - Find anti-analysis techniques
find_dead_code - Detect unreachable code
extract_iocs_with_context - Extract IOCs from strings
apply_data_classification - Apply data classification to addresses

Analysis Control

list_analyzers - List all available Ghidra analyzers
configure_analyzer - Enable/disable or configure an analyzer
run_analysis - Trigger Ghidra auto-analysis programmatically

Server Connection (Ghidra Server)

connect_server - Connect to a Ghidra Server
disconnect_server - Disconnect from Ghidra Server
server_status - Check server connection status
list_repositories - List repositories on the server
create_repository - Create a new repository
list_repository_files - List files in a server repository folder
get_repository_file - Get metadata for a file in a server repository

Version Control

checkout_file - Check out a file from version control
checkin_file - Check in a file with a comment
undo_checkout - Undo a checkout without committing
add_to_version_control - Add a file to version control

Version History

get_version_history - Get full version history for a file
get_checkouts - Get active checkout status

Admin

terminate_checkout - Forcibly terminate a user's checkout
list_server_users - List all users on the Ghidra Server
set_user_permissions - Set a user's repository access level

See CHANGELOG.md for version history.

🏗️ Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   AI/Automation │◄──►│   MCP Bridge    │◄──►│  Ghidra Plugin  │
│     Tools       │    │ (bridge_mcp_    │    │ (GhidraMCP.jar) │
│  (Claude, etc.) │    │  ghidra.py)     │    │                 │
└─────────────────┘    └─────────────────┘    └─────────────────┘
        │                       │                       │
   MCP Protocol            HTTP REST              Ghidra API
   (stdio/SSE)          (localhost:8089)      (Program, Listing)

Components

bridge_mcp_ghidra.py — Python MCP server that translates MCP protocol to HTTP calls (225 catalog entries)
GhidraMCP.jar — Ghidra plugin that exposes analysis capabilities via HTTP (175 GUI endpoints)
GhidraMCPHeadlessServer — Standalone headless server — 183 endpoints, no GUI required
ghidra_scripts/ — Collection of automation scripts for common tasks

🔧 Development

Building from Source

# Recommended: direct Python-first workflow
python -m tools.setup ensure-prereqs --ghidra-path "C:\ghidra_12.1_PUBLIC"
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "C:\ghidra_12.1_PUBLIC"

# Version bump (updates all maintained version references atomically)
python -m tools.setup bump-version --new X.Y.Z

The authoritative build system today is Maven. tools.setup, the VS Code tasks, and the documented deploy flow all build through pom.xml and write artifacts to target/. build.gradle remains in the repo as a manual fallback for direct Ghidra/Gradle users, but it is not the primary path.

Command Reference

Command	What it does
`ensure-prereqs`	Install Python deps + Ghidra Maven JARs in one shot. Start here on a new machine.
`preflight`	Validate Python, build tool, Ghidra path, and JAR availability without making changes. Add `--strict` to also check network reachability.
`build`	Build the plugin JAR and extension ZIP via Maven (or Gradle when `TOOLS_SETUP_BACKEND=gradle`).
`deploy`	Copy the built extension into the Ghidra profile and patch `FrontEndTool.xml` for auto-activation.
`start-ghidra`	Launch the configured Ghidra installation.
`clean`	Remove Maven/Gradle build outputs (`target/`, `build/`).
`clean-all`	Remove build outputs plus local cache artifacts (`.m2` Ghidra JARs, etc.).
`install-ghidra-deps`	Install only the Ghidra JARs into `~/.m2`. Useful when the build environment changes.
`install-python-deps`	Install only the Python requirements files.
`run-tests`	Run the Java offline test suite (no live Ghidra needed).
`verify-version`	Check that version strings are consistent across `pom.xml`, `CHANGELOG.md`, and `README.md`.
`bump-version --new X.Y.Z`	Atomically update all version references. Pass `--tag` to create a git tag.

Common flags accepted by most commands:

Flag	Description
`--ghidra-path PATH`	Ghidra installation directory. Defaults to `GHIDRA_PATH` from `.env`.
`--dry-run`	Print actions without executing them.
`--force`	Reinstall Ghidra JARs even if already present (`install-ghidra-deps`, `ensure-prereqs`).
`--with-debugger`	Force-install debugger Python requirements (Windows only).
`--use-debugger-toggle`	Read `INSTALL_DEBUGGER_DEPS` from `.env` to decide whether to install debugger deps.
`--test TIER`	(`deploy` only) Opt into live deploy regression tiers such as `release` or `debugger-live`.
`--strict`	(`preflight` only) Also check network reachability for Maven Central and PyPI.

Deploy test tiers are opt-in because benchmark tiers can import/reset Benchmark.dll and BenchmarkDebug.exe in the active Ghidra project. Use --test release before cutting releases, or set GHIDRA_MCP_DEPLOY_TESTS=release in a local .env when you want every deploy on your machine to run the live benchmark regression. See Testing and Release Regression.

# Standard first-time setup and deploy
python -m tools.setup ensure-prereqs --ghidra-path "C:\ghidra_12.1_PUBLIC"
python -m tools.setup build
python -m tools.setup deploy --ghidra-path "C:\ghidra_12.1_PUBLIC"

# Preflight check before deploying
python -m tools.setup preflight --strict --ghidra-path "C:\ghidra_12.1_PUBLIC"

# Version bump and tag
python -m tools.setup bump-version --new X.Y.Z --tag

# Run offline Java tests
python -m tools.setup run-tests

# Show full help
python -m tools.setup --help

Project Structure

ghidra-mcp/
├── bridge_mcp_ghidra.py     # MCP server (Python, 225 catalog entries)
├── src/main/java/           # Ghidra plugin + headless server (Java)
│   └── com/xebyte/
│       ├── GhidraMCPPlugin.java         # GUI plugin (196 endpoints)
│       ├── headless/                    # Headless server (183 endpoints)
│       └── core/                        # Shared service layer (12 services)
├── debugger/                # Optional standalone debugger server (port 8099)
├── ghidra_scripts/          # Automation scripts for batch workflows
├── tests/                   # Python unit tests + endpoint catalog
│   ├── unit/               # Catalog consistency, schema, tool function tests
│   └── endpoints.json      # Endpoint specification (225 entries)
├── docs/                    # Documentation
│   ├── prompts/            # AI workflow prompts (V5 documentation workflows)
│   ├── releases/           # Version release notes
│   └── project-management/ # Contributor planning docs (Gradle migration, etc.)
├── tools/setup/             # Build and deployment CLI (python -m tools.setup)
├── fun-doc/                 # Internal RE curation tool — not part of the MCP plugin
│                            #   Priority-queue worker, LLM scoring, web dashboard.
│                            #   See fun-doc/README.md for details.
└── .github/workflows/      # CI/CD pipelines

Library Dependencies

Ghidra JARs must be installed into your local Maven repository (~/.m2/repository) before compilation. This is a one-time setup per machine, and again when your Ghidra version changes. -Deploy now installs these automatically by default.

The tool enforces version consistency between:

pom.xml (ghidra.version)
--ghidra-path version segment (e.g., ghidra_12.1_PUBLIC)

If these do not match, deployment fails fast with a clear error.

Troubleshooting: Version Mismatch

If you see a version mismatch error, align both values:

pom.xml → ghidra.version
--ghidra-path version segment (ghidra_X.Y.Z_PUBLIC)

Then rerun:

python -m tools.setup preflight --ghidra-path "C:\ghidra_12.1_PUBLIC"

# Windows
python -m tools.setup install-ghidra-deps --ghidra-path "C:\path\to\ghidra_12.1_PUBLIC"

Required Libraries (14 JARs, ~37MB):

Library	Source Path	Purpose
Base.jar	`Features/Base/lib/`	Core Ghidra functionality
Decompiler.jar	`Features/Decompiler/lib/`	Decompilation engine
PDB.jar	`Features/PDB/lib/`	Microsoft PDB symbol support
FunctionID.jar	`Features/FunctionID/lib/`	Function identification
SoftwareModeling.jar	`Framework/SoftwareModeling/lib/`	Program model API
Project.jar	`Framework/Project/lib/`	Project management
Docking.jar	`Framework/Docking/lib/`	UI docking framework
Generic.jar	`Framework/Generic/lib/`	Generic utilities
Utility.jar	`Framework/Utility/lib/`	Core utilities
Gui.jar	`Framework/Gui/lib/`	GUI components
FileSystem.jar	`Framework/FileSystem/lib/`	File system support
Graph.jar	`Framework/Graph/lib/`	Graph/call graph analysis
DB.jar	`Framework/DB/lib/`	Database operations
Emulation.jar	`Framework/Emulation/lib/`	P-code emulation

Note: Libraries are NOT included in the repository (see .gitignore). You must install them from your Ghidra installation before building.

Automation entry point:

python -m tools.setup is the supported setup/build/deploy/versioning interface

use ensure-prereqs, build, deploy, preflight, clean-all, and bump-version directly

these commands currently use Maven as the canonical Java build backend

Development Features

Automated Deployment: Version-aware deployment script
Batch Operations: Reduces API calls by 93%
Atomic Transactions: All-or-nothing semantics
Comprehensive Logging: Debug and trace capabilities

📚 Documentation

Core Documentation

Documentation Index - Complete documentation navigation
Project Structure - Project organization guide
Testing and Release Regression - Local tests, CI, live Ghidra regression, and release gates
Naming Conventions - Code naming standards
Hungarian Notation - Variable naming guide

AI Workflow Prompts

Function Documentation V5 — Primary workflow: 7-step process with Hungarian notation, type auditing, and verification scoring
Batch Documentation V5 — Parallel subagent dispatch for multi-function processing
Orphaned Code Discovery — Automated scanner for undiscovered functions
Data Type Investigation — Systematic structure discovery
Cross-Version Matching — Hash-based function matching
Quick Start Prompt — Simplified beginner workflow
All Prompts — Complete prompt index

Release History

Complete Changelog - All version release notes
Release Notes - Detailed release documentation

🐳 Headless Server (Docker)

GhidraMCP includes a headless server mode for automated analysis without the Ghidra GUI.

Quick Start with Docker

# Build and run
docker-compose up -d ghidra-mcp

# Test connection
curl http://localhost:8089/check_connection
# Connection OK - GhidraMCP Headless Server v5.12.0

Headless API Workflow

# 1. Load a binary
curl -X POST -d "file=/data/program.exe" http://localhost:8089/load_program

# 2. Run auto-analysis (identifies functions, strings, data types)
curl -X POST http://localhost:8089/run_analysis

# 3. List discovered functions
curl "http://localhost:8089/list_functions?limit=20"

# 4. Decompile a function
curl "http://localhost:8089/decompile_function?address=0x401000"

# 5. Get metadata
curl http://localhost:8089/get_metadata

Key Headless Endpoints

Endpoint	Method	Description
`/load_program`	POST	Load binary file for analysis
`/run_analysis`	POST	Run Ghidra auto-analysis
`/list_functions`	GET	List all discovered functions
`/list_exports`	GET	List exported symbols
`/list_imports`	GET	List imported symbols
`/decompile_function`	GET	Decompile function to C code
`/create_function`	POST	Create function at address
`/get_metadata`	GET	Get program metadata
`/create_project`	POST	Create a Ghidra project
`/list_analyzers`	GET	List available analyzers
`/server/status`	GET	Check Ghidra Server connection

Configuration

Environment variables for Docker:

GHIDRA_MCP_PORT - Server port (default: 8089)
GHIDRA_MCP_BIND_ADDRESS - Bind address (default: 0.0.0.0 in Docker)
JAVA_OPTS - JVM options (default: -Xmx4g -XX:+UseG1GC)

🤝 Contributing

See CONTRIBUTING.md for detailed contribution guidelines.

Quick Start

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Build and test your changes (mvn clean package assembly:single -DskipTests or GHIDRA_INSTALL_DIR=/path/to/ghidra gradle buildExtension)
Update documentation as needed
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🏆 Production Status

Metric	Value
Version	5.12.0
MCP Tools	252 fully implemented
GUI Endpoints	196 (GhidraMCPPlugin)
Headless Endpoints	195 (GhidraMCPHeadlessServer)
Compilation	✅ 100% success
Batch Efficiency	93% API call reduction
AI Workflows	7 proven documentation workflows
Ghidra Scripts	Automation scripts included
Documentation	Comprehensive with AI prompts

See CHANGELOG.md for version history and release notes.

🙏 Acknowledgments

This project was originally derived from LaurieWired/GhidraMCP in August 2025 and has since been substantially rewritten and extended. We acknowledge LaurieWired's original work as the starting point. See NOTICE for license attribution.

👥 Contributors

This project has benefited from the work of dedicated contributors:

Core Contributors

@heeen — Significant contributions including:

Fuzzy function matching and structured diff for cross-binary comparison (#13)
Script execution improvements and bug fixes (#12)
New API endpoints: save_program, exit_ghidra, delete_function, create_memory_block, run_script_inline (#11)
Architectural vision: annotation-driven design, UDS transport, Python bridge optimization proposals

@huehuehuehueing — Significant contributions including:

Address-space prefix support — added <space>:<hex> syntax (e.g., mem:1000, code:ff00) to address parsing across the entire endpoint surface, unlocking multi-space targets like embedded firmware (#84, closes #65)
Optional program parameter + required-param schema fixes — made program optional on every endpoint with a sane currentProgram fallback, and fixed several required-vs-optional schema bugs the catalog had inherited (#92)
Seeded #44 (data-type / enum tools) — the issue that motivated the v5.0 enum + struct enforcement layer
Ghidra Team - For the incredible reverse engineering platform
Model Context Protocol - For the standardized AI integration framework
Contributors - For testing, feedback, and improvements

🔗 Related Projects

re-universe — Ghidra BSim PostgreSQL platform for large-scale binary similarity analysis. Pairs perfectly with GhidraMCP for AI-driven reverse engineering workflows.
cheat-engine-server-python — MCP server for dynamic memory analysis and debugging.

Ready for production deployment with enterprise-grade reliability and comprehensive binary analysis capabilities.

openrewrite/rewrite

Automated mass refactoring of source code.

Fast, repeatable refactoring for developers

The OpenRewrite project (managed by Moderne) is an open-source automated refactoring ecosystem for source code, enabling developers to effectively eliminate technical debt within their repositories.

It consists of an auto-refactoring engine that runs prepackaged, open source refactoring recipes for common framework migrations, security fixes, and stylistic consistency tasks—reducing your coding effort from hours or days to minutes.

OpenRewrite provides open-source parsers and base recipes for multiple languages, including Java, Kotlin, Groovy, JavaScript/TypeScript, Python, and C#. For Java, the OpenRewrite Gradle Plugin and OpenRewrite Maven Plugin let you run one recipe at a time against a single repository. Recipes are easy to customize, so you can adapt any of them - or even write your own.

Start with our quickstart guide and let OpenRewrite handle the boring parts of software development for you.

Get and stay informed:

Read the documentation.
Join us on Slack or Discord! We're happy to answer your questions directly.
Check out Code Remix Weekly where we deep dive topics and answer questions.
Subscribe to our YouTube channel for great videos on OpenRewrite recipes.
Follow us on X and LinkedIn.

OpenRewrite is maintained by Moderne. The core framework is Apache2 licensed and will always be open source, as are many recipes in the catalog. See Licensing for how the framework and recipes are licensed.

Building on OpenRewrite with Moderne

OpenRewrite is built to migrate, secure, and refactor code one repository at a time. Moderne is the commercial platform built on that foundation, running the same recipes across hundreds or thousands of repositories at once. Migrations are a common starting point with OpenRewrite, and the platform expands on this to include large-scale impact analysis, security remediation, and the tools coding agents use to understand and change code across a whole organization. Moderne also extends OpenRewrite from Java to additional languages and from individual developers to teams and coding agents. While the parsers and base recipes for those additional languages are open source, running recipes against them requires a Moderne license.

A lot of this comes down to how the Lossless Semantic Tree (LST) is handled. The LST is OpenRewrite's type-aware model of your source code, built in memory each time a recipe runs. Moderne batch-builds LSTs once and serializes them, so they can be reused across repos and across teams without rebuilding. That same LST gives coding agents pre-computed context, type-aware search, and direct access to OpenRewrite recipes as deterministic tool calls through tools like Prethink, Trigrep, and a local MCP server. Agents work with less token overhead and more accuracy than they would reading a codebase file by file.

See how Moderne and OpenRewrite work in different ways to transform your code:

Moderne also includes a multi-repo command line interface (CLI) for building LSTs, running recipes locally, and developing custom recipes across many repositories.

Moderne runs a free public service for the benefit of tens of thousands of open source projects. To learn more about how Moderne can help your team, contact us.

Contributing

We appreciate all types of contributions. See the contributing guide for detailed instructions on how to get started.

alibaba/arthas

Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas

Arthas

Arthas is a Java Diagnostic tool open sourced by Alibaba.

Arthas allows developers to troubleshoot production issues for Java applications without modifying code or restarting servers.

中文说明/Chinese Documentation

Background

Often times, the production system network is inaccessible from the local development environment. If issues are encountered in production systems, it is impossible to use IDEs to debug the application remotely. More importantly, debugging in production environment is unacceptable, as it will suspend all the threads, resulting in the suspension of business services.

Developers could always try to reproduce the same issue on the test/staging environment. However, this is tricky as some issues cannot be reproduced easily on a different environment, or even disappear once restarted.

And if you're thinking of adding some logs to your code to help troubleshoot the issue, you will have to go through the following lifecycle; test, staging, and then to production. Time is money! This approach is inefficient! Besides, the issue may not be reproducible once the JVM is restarted, as described above.

Arthas was built to solve these issues. A developer can troubleshoot your production issues on-the-fly. No JVM restart, no additional code changes. Arthas works as an observer, which will never suspend your existing threads.

Key features

Check whether a class is loaded, or where the class is being loaded. (Useful for troubleshooting jar file conflicts)
Decompile a class to ensure the code is running as expected.
View classloader statistics, e.g. the number of classloaders, the number of classes loaded per classloader, the classloader hierarchy, possible classloader leaks, etc.
View the method invocation details, e.g. method parameter, return object, thrown exception, and etc.
Check the stack trace of specified method invocation. This is useful when a developers wants to know the caller of the said method.
Trace the method invocation to find slow sub-invocations.
Monitor method invocation statistics, e.g. qps, rt, success rate and etc.
Monitor system metrics, thread states and cpu usage, gc statistics, and etc.
Supports command line interactive mode, with auto-complete feature enabled.
Supports telnet and websocket, which enables both local and remote diagnostics with command line and browsers.
Supports profiler/Flame Graph
Support get objects in the heap that are instances of the specified class.
Supports JDK 8+ in version 4.x, including JDK 17, JDK 21, and JDK 25.
Supports Linux/Mac/Windows.

Online Tutorials(Recommended)

View

Quick start

Use `arthas-boot`(Recommended)

Downloadarthas-boot.jar，Start with java command:

curl -O https://arthas.aliyun.com/arthas-boot.jar
java -jar arthas-boot.jar

Print usage:

java -jar arthas-boot.jar -h

Use `as.sh`

You can install Arthas with one single line command on Linux, Unix, and Mac. Copy the following command and paste it into the command line, then press Enter to run:

curl -L https://arthas.aliyun.com/install.sh | sh

The command above will download the bootstrap script as.sh to the current directory. You can move it any other place you want, or put its location in $PATH.

You can enter its interactive interface by executing as.sh, or execute as.sh -h for more help information.

Documentation

Feature Showcase

Dashboard

https://arthas.aliyun.com/doc/en/dashboard

Thread

https://arthas.aliyun.com/doc/en/thread

See what is eating your CPU (ranked by top CPU usage) and what is going on there in one glance:

$ thread -n 3
"as-command-execute-daemon" Id=29 cpuUsage=75% RUNNABLE
    at sun.management.ThreadImpl.dumpThreads0(Native Method)
    at sun.management.ThreadImpl.getThreadInfo(ThreadImpl.java:440)
    at com.taobao.arthas.core.command.monitor200.ThreadCommand$1.action(ThreadCommand.java:58)
    at com.taobao.arthas.core.command.handler.AbstractCommandHandler.execute(AbstractCommandHandler.java:238)
    at com.taobao.arthas.core.command.handler.DefaultCommandHandler.handleCommand(DefaultCommandHandler.java:67)
    at com.taobao.arthas.core.server.ArthasServer$4.run(ArthasServer.java:276)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

    Number of locked synchronizers = 1
    - java.util.concurrent.ThreadPoolExecutor$Worker@6cd0b6f8

"as-session-expire-daemon" Id=25 cpuUsage=24% TIMED_WAITING
    at java.lang.Thread.sleep(Native Method)
    at com.taobao.arthas.core.server.DefaultSessionManager$2.run(DefaultSessionManager.java:85)

"Reference Handler" Id=2 cpuUsage=0% WAITING on java.lang.ref.Reference$Lock@69ba0f27
    at java.lang.Object.wait(Native Method)
    -  waiting on java.lang.ref.Reference$Lock@69ba0f27
    at java.lang.Object.wait(Object.java:503)
    at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:133)

jad

https://arthas.aliyun.com/doc/en/jad

Decompile your class with one shot:

$ jad javax.servlet.Servlet

ClassLoader:
+-java.net.URLClassLoader@6108b2d7
  +-sun.misc.Launcher$AppClassLoader@18b4aac2
    +-sun.misc.Launcher$ExtClassLoader@1ddf84b8

Location:
/Users/xxx/work/test/lib/servlet-api.jar

/*
 * Decompiled with CFR 0_122.
 */
package javax.servlet;

import java.io.IOException;
import javax.servlet.ServletConfig;
import javax.servlet.ServletException;
import javax.servlet.ServletRequest;
import javax.servlet.ServletResponse;

public interface Servlet {
    public void init(ServletConfig var1) throws ServletException;

    public ServletConfig getServletConfig();

    public void service(ServletRequest var1, ServletResponse var2) throws ServletException, IOException;

    public String getServletInfo();

    public void destroy();
}

mc

https://arthas.aliyun.com/doc/en/mc

Memory compiler, compiles .java files into .class files in memory.

$ mc /tmp/Test.java

retransform

https://arthas.aliyun.com/doc/en/retransform

Load the external *.class files to retransform/hotswap the loaded classes in JVM.

retransform /tmp/Test.class
retransform -c 327a647b /tmp/Test.class /tmp/Test\$Inner.class

sc

https://arthas.aliyun.com/doc/en/sc

Search any loaded class with detailed information.

$ sc -d org.springframework.web.context.support.XmlWebApplicationContext
 class-info        org.springframework.web.context.support.XmlWebApplicationContext
 code-source       /Users/xxx/work/test/WEB-INF/lib/spring-web-3.2.11.RELEASE.jar
 name              org.springframework.web.context.support.XmlWebApplicationContext
 isInterface       false
 isAnnotation      false
 isEnum            false
 isAnonymousClass  false
 isArray           false
 isLocalClass      false
 isMemberClass     false
 isPrimitive       false
 isSynthetic       false
 simple-name       XmlWebApplicationContext
 modifier          public
 annotation
 interfaces
 super-class       +-org.springframework.web.context.support.AbstractRefreshableWebApplicationContext
                     +-org.springframework.context.support.AbstractRefreshableConfigApplicationContext
                       +-org.springframework.context.support.AbstractRefreshableApplicationContext
                         +-org.springframework.context.support.AbstractApplicationContext
                           +-org.springframework.core.io.DefaultResourceLoader
                             +-java.lang.Object
 class-loader      +-org.apache.catalina.loader.ParallelWebappClassLoader
                     +-java.net.URLClassLoader@6108b2d7
                       +-sun.misc.Launcher$AppClassLoader@18b4aac2
                         +-sun.misc.Launcher$ExtClassLoader@1ddf84b8
 classLoaderHash   25131501

vmtool

https://arthas.aliyun.com/doc/en/vmtool

Get objects in the heap that are instances of the specified class.

$ vmtool --action getInstances --className java.lang.String --limit 10
@String[][
    @String[com/taobao/arthas/core/shell/session/Session],
    @String[com.taobao.arthas.core.shell.session.Session],
    @String[com/taobao/arthas/core/shell/session/Session],
    @String[com/taobao/arthas/core/shell/session/Session],
    @String[com/taobao/arthas/core/shell/session/Session.class],
    @String[com/taobao/arthas/core/shell/session/Session.class],
    @String[com/taobao/arthas/core/shell/session/Session.class],
    @String[com/],
    @String[java/util/concurrent/ConcurrentHashMap$ValueIterator],
    @String[java/util/concurrent/locks/LockSupport],
]

stack

https://arthas.aliyun.com/doc/en/stack

View the call stack of test.arthas.TestStack#doGet:

$ stack test.arthas.TestStack doGet
Press Ctrl+C to abort.
Affect(class-cnt:1 , method-cnt:1) cost in 286 ms.
ts=2018-09-18 10:11:45;thread_name=http-bio-8080-exec-10;id=d9;is_daemon=true;priority=5;TCCL=org.apache.catalina.loader.ParallelWebappClassLoader@25131501
    @test.arthas.TestStack.doGet()
        at javax.servlet.http.HttpServlet.service(HttpServlet.java:624)
        at javax.servlet.http.HttpServlet.service(HttpServlet.java:731)
        at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:303)
        at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:208)
        at org.apache.tomcat.websocket.server.WsFilter.doFilter(WsFilter.java:52)
        at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:241)
        at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:208)
        at org.apache.catalina.core.ApplicationFilterChain.internalDoFilter(ApplicationFilterChain.java:241)
        at org.apache.catalina.core.ApplicationFilterChain.doFilter(ApplicationFilterChain.java:208)
        at org.apache.catalina.core.StandardWrapperValve.invoke(StandardWrapperValve.java:220)
        at org.apache.catalina.core.StandardContextValve.invoke(StandardContextValve.java:110)
        ...
        at org.apache.catalina.core.StandardHostValve.invoke(StandardHostValve.java:169)
        at org.apache.catalina.valves.ErrorReportValve.invoke(ErrorReportValve.java:103)
        at org.apache.catalina.core.StandardEngineValve.invoke(StandardEngineValve.java:116)
        at org.apache.catalina.connector.CoyoteAdapter.service(CoyoteAdapter.java:451)
        at org.apache.coyote.http11.AbstractHttp11Processor.process(AbstractHttp11Processor.java:1121)
        at org.apache.coyote.AbstractProtocol$AbstractConnectionHandler.process(AbstractProtocol.java:637)
        at org.apache.tomcat.util.net.JIoEndpoint$SocketProcessor.run(JIoEndpoint.java:316)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:745)

Trace

https://arthas.aliyun.com/doc/en/trace

See what is slowing down your method invocation with trace command:

Watch

https://arthas.aliyun.com/doc/en/watch

Watch the first parameter and thrown exception of test.arthas.TestWatch#doGet only if it throws exception.

$ watch test.arthas.TestWatch doGet {params[0], throwExp} -e
Press Ctrl+C to abort.
Affect(class-cnt:1 , method-cnt:1) cost in 65 ms.
ts=2018-09-18 10:26:28;result=@ArrayList[
    @RequestFacade[org.apache.catalina.connector.RequestFacade@79f922b2],
    @NullPointerException[java.lang.NullPointerException],
]

Monitor

https://arthas.aliyun.com/doc/en/monitor

Monitor a specific method invocation statistics, including the total number of invocations, average response time, success rate, and every 5 seconds:

$ monitor -c 5 org.apache.dubbo.demo.provider.DemoServiceImpl sayHello
Press Ctrl+C to abort.
Affect(class-cnt:1 , method-cnt:1) cost in 109 ms.
 timestamp            class                                           method    total  success  fail  avg-rt(ms)  fail-rate
----------------------------------------------------------------------------------------------------------------------------
 2018-09-20 09:45:32  org.apache.dubbo.demo.provider.DemoServiceImpl  sayHello  5      5        0     0.67        0.00%

 timestamp            class                                           method    total  success  fail  avg-rt(ms)  fail-rate
----------------------------------------------------------------------------------------------------------------------------
 2018-09-20 09:45:37  org.apache.dubbo.demo.provider.DemoServiceImpl  sayHello  5      5        0     1.00        0.00%

 timestamp            class                                           method    total  success  fail  avg-rt(ms)  fail-rate
----------------------------------------------------------------------------------------------------------------------------
 2018-09-20 09:45:42  org.apache.dubbo.demo.provider.DemoServiceImpl  sayHello  5      5        0     0.43        0.00%

Time Tunnel(tt)

https://arthas.aliyun.com/doc/en/tt

Record method invocation data, so that you can check the method invocation parameters, returned value, and thrown exceptions later. It works as if you could come back and replay the past method invocation via time tunnel.

$ tt -t org.apache.dubbo.demo.provider.DemoServiceImpl sayHello
Press Ctrl+C to abort.
Affect(class-cnt:1 , method-cnt:1) cost in 75 ms.
 INDEX   TIMESTAMP            COST(ms)  IS-RET  IS-EXP   OBJECT         CLASS                          METHOD
-------------------------------------------------------------------------------------------------------------------------------------
 1000    2018-09-20 09:54:10  1.971195  true    false    0x55965cca     DemoServiceImpl                sayHello
 1001    2018-09-20 09:54:11  0.215685  true    false    0x55965cca     DemoServiceImpl                sayHello
 1002    2018-09-20 09:54:12  0.236303  true    false    0x55965cca     DemoServiceImpl                sayHello
 1003    2018-09-20 09:54:13  0.159598  true    false    0x55965cca     DemoServiceImpl                sayHello
 1004    2018-09-20 09:54:14  0.201982  true    false    0x55965cca     DemoServiceImpl                sayHello
 1005    2018-09-20 09:54:15  0.214205  true    false    0x55965cca     DemoServiceImpl                sayHello
 1006    2018-09-20 09:54:16  0.241863  true    false    0x55965cca     DemoServiceImpl                sayHello
 1007    2018-09-20 09:54:17  0.305747  true    false    0x55965cca     DemoServiceImpl                sayHello
 1008    2018-09-20 09:54:18  0.18468   true    false    0x55965cca     DemoServiceImpl                sayHello

Classloader

https://arthas.aliyun.com/doc/en/classloader

$ classloader
 name                                                  numberOfInstances  loadedCountTotal
 BootstrapClassLoader                                  1                  3346
 com.taobao.arthas.agent.ArthasClassloader             1                  1262
 java.net.URLClassLoader                               2                  1033
 org.apache.catalina.loader.ParallelWebappClassLoader  1                  628
 sun.reflect.DelegatingClassLoader                     166                166
 sun.misc.Launcher$AppClassLoader                      1                  31
 com.alibaba.fastjson.util.ASMClassLoader              6                  15
 sun.misc.Launcher$ExtClassLoader                      1                  7
 org.jvnet.hk2.internal.DelegatingClassLoader          2                  2
 sun.reflect.misc.MethodUtil                           1                  1

Web Console

https://arthas.aliyun.com/doc/en/web-console

Profiler/FlameGraph

https://arthas.aliyun.com/doc/en/profiler

$ profiler start
Started [cpu] profiling

$ profiler stop
profiler output file: /tmp/demo/arthas-output/20211207-111550.html
OK

View profiler results under arthas-output via browser:

Arthas Spring Boot Starter

Arthas Spring Boot Starter

Known Users

Arthas has more than 120 registered users, View All.

Welcome to register the company name in this issue: https://github.com/alibaba/arthas/issues/111 (in order of registration)

Derivative Projects

Credits

Contributors

This project exists, thanks to all the people who contributed.

Projects

bytekit Java Bytecode Kit.
greys-anatomy: The Arthas code base has derived from Greys, we thank for the excellent work done by Greys.
termd: Arthas's terminal implementation is based on termd, an open source library for writing terminal applications in Java.
crash: Arthas's text based user interface rendering is based on codes extracted from here
cli: Arthas's command line interface implementation is based on cli, open sourced by vert.x
compiler Arthas's memory compiler.
Apache Commons Net Arthas's telnet client.
async-profiler Arthas's profiler command.

emanuele-f/PCAPdroid

No-root network monitor, firewall and PCAP dumper for Android

PCAPdroid

PCAPdroid is a privacy-friendly open source app which lets you track, analyze and block the connections made by the other apps in your device. It also allows you to export a PCAP dump of the traffic, inspect HTTP, decrypt TLS traffic and much more!

PCAPdroid simulates a VPN in order to capture the network traffic without root. It does not use a remote VPN server, instead data is processed locally on the device.

Features:

Log and examine the connections made by user and system apps
Extract the SNI, DNS query, HTTP URL and the remote IP address
Inspect HTTP requests and replies thanks to the built-in decoders
Inspect the full connections payload as hexdump/text
Decrypt the HTTPS/TLS traffic and export the SSLKEYLOGFILE
Dump the traffic to a PCAP file, download it from a browser, or stream it to a remote receiver for real-time analysis (e.g. Wireshark)
Create rules to filter out the good traffic and easily spot anomalies
Identify the country and ASN of remote server via offline DB lookups
On rooted devices, capture the traffic while other VPN apps are running

Paid features:

Firewall: create rules to block individual apps, domains and IP addresses
Malware detection: detect malicious connections by using third-party blacklists
PCAPng format: makes it easier to export and analyze decrypted traffic

If you plan to use PCAPdroid to perform packet analysis, please check out the specific section of the manual.

You can test the latest features before the official release by adding the Beta repository to the F-Droid app.

User Guide

Check out the quick start instructions or the full User Guide.

Community

You can help the PCAPdroid project in many ways:

Make a donation
Translate the app on Weblate
Discuss new features
Improve the app theme and layout
Star the project on Github and on Google Play
Of course provide code pull requests!

Join the international PCAPdroid community on Telegram or on Matrix.

Integrating into your APP

Some features of PCAPdroid can be integrated into a third-party app to provide packet capture capabilities.

For rooted devices, the pcapd daemon can be directly integrated into your APK to capture network packets.
For all the devices, PCAPdroid exposes an API to control the packet capture and send the captured packets via UDP to your app. This requires to install PCAPdroid along with your app.

Open Source

PCAPdroid is powered by open source technologies.

nDPI: deep packet inspection library, provides the connections metadata
mitmproxy: a local proxy for the TLS decryption
zdtun: minimal TCP/IP stack for the non-root capture

For the complete list of third party libraries check out the "About" page in the app.

Building

On Windows, install gitforwindows
Clone this repo
Inside the repo dir, run git submodule update --init. The submodules directory should get populated.
Open the project in Android Studio, install the appropriate SDK and the NDK
Build the app

Note: If you get "No valid CMake executable was found", be sure to install the CMake version used by PCAPdroid (currently 3.22.1) from the SDK manager

apache/iceberg

Apache Iceberg

Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time.

Background and documentation is available at https://iceberg.apache.org

Status

Iceberg is under active development at the Apache Software Foundation.

The Iceberg format specification is stable and new features are added with each version.

The core Java library is located in this repository and is the reference implementation for other libraries.

Documentation is available for all libraries and integrations.

Collaboration

Iceberg tracks issues in GitHub and prefers to receive contributions as pull requests.

Community discussions happen primarily on the dev mailing list or on specific issues.

Building

Iceberg is built using Gradle with Java 17 or 21.

To invoke a build and run tests: ./gradlew build
To skip tests: ./gradlew build -x test -x integrationTest
To fix code style for default versions: ./gradlew spotlessApply
To fix code style for all versions of Spark/Hive/Flink:./gradlew spotlessApply -DallModules

Iceberg table support is organized in library modules:

iceberg-common contains utility classes used in other modules
iceberg-api contains the public Iceberg API
iceberg-core contains implementations of the Iceberg API and support for Avro data files, this is what processing engines should depend on
iceberg-parquet is an optional module for working with tables backed by Parquet files
iceberg-arrow is an optional module for reading Parquet into Arrow memory
iceberg-orc is an optional module for working with tables backed by ORC files
iceberg-hive-metastore is an implementation of Iceberg tables backed by the Hive metastore Thrift client
iceberg-data is an optional module for working with tables directly from JVM applications

Iceberg also has modules for adding Iceberg support to processing engines:

iceberg-spark is an implementation of Spark's Datasource V2 API for Iceberg with submodules for each spark versions (use runtime jars for a shaded version to avoid dependency conflicts)
iceberg-flink contains classes for integrating with Apache Flink (use iceberg-flink-runtime for a shaded version)
iceberg-mr contains an InputFormat and other classes for integrating with Apache Hive

NOTE

The tests require Docker to execute. On macOS (with Docker Desktop), you might need to create a symbolic name to the docker socket in order to be detected by the tests:

sudo ln -s $HOME/.docker/run/docker.sock /var/run/docker.sock

In some cases the testcontainer may exit with an initialization error because of an illegal state exception in the GenericContainer. One work around for this problem is to set selinux into permissive mode before running the tests.

sudo setenforce Permissive
./gradlew ...
sudo setenforce Enforcing

Documentation

For information about building the documentation, see here.

Engine Compatibility

See the Multi-Engine Support page to know about Iceberg compatibility with different Spark, Flink and Hive versions. For other engines such as Presto or Trino, please visit their websites for Iceberg integration details.

Implementations

This repository contains the Java implementation of Iceberg. Other implementations can be found at:

Go: iceberg-go
PyIceberg (Python): iceberg-python
Rust: iceberg-rust
C++: iceberg-cpp

kestra-io/kestra

Event Driven Orchestration & Scheduling Platform for Mission Critical Applications

Open-source orchestration platform for data, AI, and infrastructure workflows

Click on the image to learn how to get started with Kestra in 3 minutes.

🌟 What is Kestra?

Kestra is an open-source, event-driven orchestration platform for data, AI, and infrastructure workflows. It unifies scheduled and event-driven automation behind a declarative, language-agnostic interface. By bringing Infrastructure as Code best practices to your data, process, and microservice pipelines, you can build reliable workflows directly from the UI in just a few lines of YAML.

📖 Table of Contents

Key Features:

Everything as Code and from the UI: keep workflows as code with a Git Version Control integration, even when building them from the UI.
Event-Driven & Scheduled Workflows: automate both scheduled and real-time event-driven workflows via a simple trigger definition.
Declarative YAML Interface: define workflows using a simple configuration in the built-in code editor.
Rich Plugin Ecosystem: hundreds of plugins built in to extract data from any database, cloud storage, or API, and run scripts in any language.
Intuitive UI & Code Editor: build and visualize workflows directly from the UI with syntax highlighting, auto-completion and real-time syntax validation.
Scalable: designed to handle millions of workflows, with high availability and fault tolerance.
Version Control Friendly: write your workflows from the built-in code Editor and push them to your preferred Git branch directly from Kestra, enabling best practices with CI/CD pipelines and version control systems.
Structure & Resilience: tame chaos and bring resilience to your workflows with namespaces, labels, subflows, retries, timeout, error handling, inputs, outputs that generate artifacts in the UI, variables, conditional branching, advanced scheduling, event triggers, backfills, dynamic tasks, sequential and parallel tasks, and skip tasks or triggers when needed by setting the flag disabled to true.

🧑‍💻 The YAML definition gets automatically adjusted any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is always managed declaratively in code, even if you modify your workflows in other ways (UI, CI/CD, Terraform, API calls).

Your browser does not support the video tag. Watch the demo here.

🚀 Quick Start

Launch on AWS (CloudFormation)

Deploy Kestra on AWS using our CloudFormation template:

Launch on Google Cloud (Terraform deployment)

Deploy Kestra on Google Cloud Infrastructure Manager using our Terraform module.

Get Started Locally in 5 Minutes

Launch Kestra in Docker

Make sure that Docker is running. Then, start Kestra in a single command:

docker run --pull=always -it -p 8080:8080 --user=root \
  --name kestra --restart=always \
  -v kestra_data:/app/storage \
  -v /var/run/docker.sock:/var/run/docker.sock \
  -v /tmp:/tmp \
  kestra/kestra:latest server local

If you're on Windows and use PowerShell:

docker run --pull=always -it -p 8080:8080 --user=root `
  --name kestra --restart=always `
  -v "kestra_data:/app/storage" `
  -v "/var/run/docker.sock:/var/run/docker.sock" `
  -v "C:/Temp:/tmp" `
  kestra/kestra:latest server local

If you're on Windows and use Command Prompt (CMD):

docker run --pull=always -it -p 8080:8080 --user=root ^
  --name kestra --restart=always ^
  -v "kestra_data:/app/storage" ^
  -v "/var/run/docker.sock:/var/run/docker.sock" ^
  -v "C:/Temp:/tmp" ^
  kestra/kestra:latest server local

If you're on Windows and use WSL (Linux-based environment in Windows):

docker run --pull=always -it -p 8080:8080 --user=root \
  --name kestra --restart=always \
  -v kestra_data:/app/storage \
  -v "/var/run/docker.sock:/var/run/docker.sock" \
  -v "/mnt/c/Temp:/tmp" \
  kestra/kestra:latest server local

Check our Installation Guide for other deployment options (Docker Compose, Podman, Kubernetes, AWS, GCP, Azure, and more).

Access the Kestra UI at http://localhost:8080 and start building your first flow!

Your First Hello World Flow

Create a new flow with the following content:

id: hello_world
namespace: dev

tasks:
  - id: say_hello
    type: io.kestra.plugin.core.log.Log
    message: "Hello, World!"

Run the flow and see the output in the UI!

🧩 Plugin Ecosystem

Kestra's functionality is extended through a rich ecosystem of plugins that empower you to run tasks anywhere and code in any language, including Python, Node.js, R, Go, Shell, and more. Here's how Kestra plugins enhance your workflows:

Run Anywhere:
- Local or Remote Execution: Execute tasks on your local machine, remote servers via SSH, or scale out to serverless containers using Task Runners.
- Docker and Kubernetes Support: Seamlessly run Docker containers within your workflows or launch Kubernetes jobs to handle compute-intensive workloads.
Code in Any Language:
- Scripting Support: Write scripts in your preferred programming language. Kestra supports Python, Node.js, R, Go, Shell, and others, allowing you to integrate existing codebases and deployment patterns.
- Flexible Automation: Execute shell commands, run SQL queries against various databases, and make HTTP requests to interact with APIs.
Event-Driven and Real-Time Processing:
- Real-Time Triggers: React to events from external systems in real-time, such as file arrivals, new messages in message buses (Kafka, Redis, Pulsar, AMQP, MQTT, NATS, AWS SQS, Google Pub/Sub, Azure Event Hubs), and more.
- Custom Events: Define custom events to trigger flows based on specific conditions or external signals, enabling highly responsive workflows.
Cloud Integrations:
- AWS, Google Cloud, Azure: Integrate with a variety of cloud services to interact with storage solutions, messaging systems, compute resources, and more.
- Big Data Processing: Run big data processing tasks using tools like Apache Spark or interact with analytics platforms like Google BigQuery.
Monitoring and Notifications:
- Stay Informed: Send messages to Slack channels, email notifications, or trigger alerts in PagerDuty to keep your team updated on workflow statuses.

Kestra's plugin ecosystem is continually expanding, allowing you to tailor the platform to your specific needs. Whether you're orchestrating complex data pipelines, automating scripts across multiple environments, or integrating with cloud services, there's likely a plugin to assist. And if not, you can always build your own plugins to extend Kestra's capabilities.

🧑‍💻 Note: This is just a glimpse of what Kestra plugins can do. Explore the full list on our Plugins Page.

📚 Key Concepts

Flows: the core unit in Kestra, representing a workflow composed of tasks.
Tasks: individual units of work, such as running a script, moving data, or calling an API.
Namespaces: logical grouping of flows for organization and isolation.
Triggers: schedule or events that initiate the execution of flows.
Inputs & Variables: parameters and dynamic data passed into flows and tasks.

🎨 Build Workflows Visually

Kestra provides an intuitive UI that allows you to interactively build and visualize your workflows:

Drag-and-Drop Interface: add and rearrange tasks from the Topology Editor.
Real-Time Validation: instant feedback on your workflow's syntax and structure to catch errors early.
Auto-Completion: smart suggestions as you type to write flow code quickly and without syntax errors.
Live Topology View: see your workflow as a Directed Acyclic Graph (DAG) that updates in real-time.

🔧 Extensible and Developer-Friendly

Plugin Development

Create custom plugins to extend Kestra's capabilities. Check out our Plugin Developer Guide to get started.

Infrastructure as Code

Version Control: store your flows in Git repositories.
CI/CD Integration: automate deployment of flows using CI/CD pipelines.
Terraform Provider: manage Kestra resources with the official Terraform provider.

🌐 Join the Community

Stay connected and get support:

Slack: Join our Slack community to ask questions and share ideas.
LinkedIn: Follow us on LinkedIn — next to Slack and GitHub, this is our main channel to share updates and product announcements.
YouTube: Subscribe to our YouTube channel for educational video content. We publish new videos every week!
X: Follow us on X if you're still active there.

🤝 Contributing

We welcome contributions of all kinds!

Report Issues: Found a bug or have a feature request? Open an issue on GitHub.
Contribute Code: Check out our Contributor Guide for initial guidelines, and explore our good first issues for beginner-friendly tasks to tackle first.
Develop Plugins: Build and share plugins using our Plugin Developer Guide.
Contribute to our Docs: Contribute edits or updates to keep our documentation top-notch.

📄 License

⭐️ Stay Updated

Give our repository a star to stay informed about the latest features and updates!

Thank you for considering Kestra for your workflow orchestration needs. We can't wait to see what you'll build!

dataease/dataease

🔥 人人可用的开源 BI 工具，数据可视化神器。An open-source BI tool alternative to Tableau.

人人可用的开源 BI 工具

什么是 DataEase？

DataEase 是开源的 BI 工具，帮助用户快速分析数据并洞察业务趋势，从而实现业务的改进与优化。DataEase 支持丰富的数据源连接，能够通过拖拉拽方式快速制作图表，并可以方便的与他人分享。

DataEase 的优势：

开源开放：零门槛，线上快速获取和安装，按月迭代；
简单易用：极易上手，通过鼠标点击和拖拽即可完成分析；
全场景支持：多平台安装和多样化嵌入支持；
安全分享：支持多种数据分享方式，确保数据安全；
AI 加持：无缝集成 SQLBot 实现智能问数。

DataEase 支持的数据源：

OLTP 数据库： MySQL、Oracle、SQL Server、PostgreSQL、MariaDB、Db2、TiDB、MongoDB-BI 等；
OLAP 数据库： ClickHouse、Apache Doris、Apache Impala、StarRocks 等；
数据仓库/数据湖： Amazon RedShift 等；
数据文件： Excel、CSV 等；
API 数据源。

快速开始

# 准备一台 2 核 4G 以上的 Linux 服务器，并以 root 用户运行以下一键安装脚本：

curl -sSL https://dataease.oss-cn-hangzhou.aliyuncs.com/quick_start_v2.sh | bash

# 用户名: admin
# 密码: DataEase@123456

如果是用于生产环境，推荐使用离线安装包方式进行安装部署。

如你有更多问题，可以查看在线文档，或者通过论坛和交流群与我们交流。

在线文档
社区论坛
微信交流群

UI 展示

技术栈

前端：Vue.js、Element
图库：AntV
后端：Spring Boot
数据库：MySQL
数据处理：Apache Calcite、Apache SeaTunnel
基础设施：Docker

飞致云的其他明星项目

1Panel - 现代化、开源的 Linux 服务器运维管理面板
MaxKB - 基于 LLM 大语言模型的开源知识库问答系统
JumpServer - 广受欢迎的开源堡垒机
Cordys CRM - 新一代的开源 AI CRM 系统
Halo - 强大易用的开源建站工具
MeterSphere - 新一代的开源持续测试工具

License

Licensed under The GNU General Public License version 3 (GPLv3) (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

https://www.gnu.org/licenses/gpl-3.0.html

kekingcn/kkFileView

Universal File Online Preview Project based on Spring-Boot

kkFileView

Introduction

Document online preview project solution, built using the popular Spring Boot framework for easy setup and deployment. This versatile open source project provides basic support for a wide range of document formats, including:

Supports Office documents such as doc, docx, xls, xlsx, xlsm, ppt, pptx, csv, tsv, , dotm, xlt, xltm, dot, xlam, dotx, xla, ,pages ,pptm etc.
Supports domestic WPS Office documents such as wps, dps, et , ett, wpt.
Supports OpenOffice, LibreOffice office documents such as odt, ods, ots, odp, otp, six, ott, fodt and fods.
Supports Visio flowchart files such as vsd, vsdx.
Supports Windows system image files such as wmf, emf.
Supports Photoshop software model files such as psd ,eps.
Supports document formats like pdf, ofd, and rtf.
Supports software model files like xmind.
Support for bpmn workflow files.
Support for eml , msg mail files
Support for epub book documents
Supports 3D model files like obj, 3ds, stl, ply, gltf, glb, off, 3dm, fbx, dae, wrl, 3mf, ifc, brep, step, iges, fcstd, bim, etc.
Supports CAD model files such as dwg, dxf, dwf iges , igs, dwt , dng , ifc , dwfx , stl , cf2 , plt, etc.
Supports all plain text files such as txt, xml (rendering), md (rendering), java, php, py, js, css, etc.
Supports compressed packages such as zip, rar, jar, tar, gzip, 7z, etc.
Supports image previewing (flip, zoom, mirror) of jpg, jpeg, png, gif, bmp, ico, jfif, webp, heic, ,heif etc.
Supports image information model files such as tif and tiff.
Supports image format files such as tga.
Supports vector image format files such as svg.
Supports mp3,wav,mp4,flv .
Supports many audio and video format files such as avi, mov, wmv, mkv, 3gp, and rm.
Supports for dcm .
Supports for drawio .

Features

Build with the popular frame spring boot
Easy to build and deploy
Basically support online preview of mainstream office documents, such as Doc, docx, Excel, PDF, TXT, zip, rar, pictures, etc
REST API
Abstract file preview interface so that it is easy to extend more file extensions and develop this project on your own

Official website and DOCS

URL：https://kkview.cn

Live demo

Please treat public service kindly, or this would stop at any time.

URL：https://file.kkview.cn

Contact Us

We will answer your questions carefully and solve any problems you encounter while using the project. We also kindly ask that you at least Google or Baidu before asking questions in order to save time and avoid ineffective communication. Let's cherish our lives and stay away from ineffective communication.

Quick Start

Technology stack

Spring boot： spring boot Development Reference Guide
Freemarker
Redisson
Jodconverter

Dependencies

Redis(Optional, Unnecessary by default)
OpenOffice or LibreOffice(Integrated on Windows, will be installed automatically on Linux, need to be manually installed on Mac OS)

First step：git pull https://github.com/kekingcn/kkFileView.git
second step：Run the main method of /server/src/main/java/cn/keking/ServerMain.java. After starting,visit http://localhost:8012/.

Change History

Version 5.0.0 (April 14, 2026)

Improvements

Enhanced xlsx front-end parsing - Improved Excel file front-end rendering performance
Optimized image parsing - Enhanced image processing mechanism
Improved tif parsing - Enhanced TIF format support
Enhanced svg parsing - Optimized SVG vector image rendering
Improved json parsing - Enhanced JSON file processing
Optimized ftp multi-client access - Improved FTP service compatibility
Enhanced home page directory access - Implemented post server-side pagination mechanism
Improved marked parsing - Enhanced Markdown rendering
Redesigned archive preview into a single workspace with a collapsible tree and inline file preview
Improved archive preview file-type badges and single-image preview styling
Added an agent-focused repository guide for engineering automation and maintenance
Refreshed the demo portal pages, including the index, integration guide, release record, and sponsor pages

New Features

msg email parsing - Added support for msg format email file preview
heic image parsing - Added support for HEIC format image preview
Cross-domain methods - Added cross-domain processing mechanism
Highlighting methods - Added text highlighting functionality
Pagination methods - Added document page control
AES encryption methods - Added AES encryption support
Basic authentication methods - Added Basic authentication mechanism
Key management methods - Added key management functionality
Anti-duplicate conversion - Added duplicate file conversion protection
Async waiting - Added asynchronous processing mechanism
Upload restrictions - Added restrictions for unsupported file uploads
cadviewer conversion methods - Added CAD viewer conversion functionality

Fixed Issues

Compressed file path issues - Fixed internal path handling in compressed files
Security issues - Fixed security vulnerabilities
Incomplete image watermark issues - Fixed incomplete watermark display
SSL self-signed certificate access issues - Fixed compatibility with self-signed certificates
Fixed archive-contained Office files that could stay stuck on loading because repeated extraction appended to existing files
Default Office preview now prefers PDF mode, and PDF preview opens with the thumbnail sidebar visible by default
Updated startup scripts to discover the packaged jar dynamically instead of relying on stale hard-coded jar names
Updated Docker and release helper docs to align with the 5.0.0 release line
Fixed OFD table border overflow rendering issues
Refined the PDF.js compatibility polyfill to avoid preview errors in compatibility environments

Updates

JDK version requirement - Mandatory requirement for JDK 21 or higher
pdf front-end parsing update - Upgraded PDF front-end rendering component
odf front-end parsing update - Upgraded ODF document front-end rendering
3D model front-end parsing update - Upgraded 3D model viewer
pdf backend async conversion optimization - Implemented multi-threaded asynchronous conversion
tif backend async conversion optimization - Implemented multi-threaded asynchronous conversion
Video backend async conversion optimization - Implemented multi-threaded asynchronous conversion
CAD backend async conversion optimization - Implemented multi-threaded asynchronous conversion
Default preview configuration strategy adjusted - Office preview now defaults to PDF mode, the mode switch is hidden by default, and PDF preview opens with the thumbnail sidebar visible. If you need the previous image-first behavior after upgrade, explicitly set office.preview.type=image and office.preview.switch.disabled=false.
Trust host configuration matching expanded - trust.host and related rules now support wildcard and CIDR matching, which may broaden or narrow effective allow/deny behavior after upgrade depending on your patterns

Version 4.4.0 (January 16, 2025)

New Features

xlsx printing support
Added GZIP compression enablement in configuration
CAD format now supports conversion to SVG and TIF formats, added timeout termination and thread management
Added captcha verification for file deletion
Added xbrl format preview support
PDF preview added control over signatures, drawings, illustration control, search positioning pagination, and display content definition
Added CSV format front-end parsing support
Added Docker image support for ARM64
Added Office preview conversion timeout property setting
Added preview file host blacklist mechanism

Optimizations

Optimized OFD mobile preview page adaptability
Updated xlsx front-end parsing component to accelerate parsing speed
Upgraded CAD component
Office function adjustments, supporting comments, conversion page limit, watermark generation, etc.
Upgraded markdown component
Upgraded dcm parsing component
Upgraded PDF.JS parsing component
Changed video player plugin to ckplayer
Smarter tif parsing, supporting modified image formats
Improved character encoding detection accuracy for large and small text files, handling concurrency vulnerabilities
Refactored file download code, added general file server authentication access design
Updated bootstrap component and streamlined unnecessary files
Updated epub version, optimized epub display effect
Fixed issue where scheduled cache cleanup only deleted disk cache files for multimedia file types
Auto-detection of installed Office components, added default paths for LibreOffice 7.5 & 7.6 versions
Changed drawio default to preview mode
Added PDF thread management, timeout management, memory cache management, updated PDF parsing component version
Optimized Dockerfile for true cross-platform image building

Fixes

Fixed forceUpdatedCache property setting issue where local cache files weren't updated
Fixed PDF decryption error after successful encrypted file conversion
Fixed BPMN cross-domain support issue
Fixed special character error in compressed package secondary reverse proxy
Fixed video cross-domain configuration causing video preview failure
Fixed TXT text pagination secondary loading issue
Fixed Drawio missing Base64 component issue
Fixed Markdown escaping issue
Fixed EPUB cross-domain error
Fixed URL special character issues
Fixed compressed package traversal vulnerability
Fixed compressed file path errors, image collection path errors, watermark issues, etc.
Fixed front-end parsing XLSX containing EMF format file errors

Version 4.3.0 (July 5, 2023)

New Features

Added DCM medical digital imaging preview
Added drawio drawing preview
Added command to regenerate with cache enabled: &forceUpdatedCache=true
Added dwg CAD file preview
Added PDF file password support
Added DPI customization for PDF file image generation
Added configuration to delete converted OFFICE, CAD, TIFF, compressed package source files (enabled by default to save disk space)
Added front-end xlsx parsing method
Added support for pages, eps, iges, igs, dwt, dng, ifc, dwfx, stl, cf2, plt and other formats

Optimizations

Modified generated PDF file names to include file extensions to prevent duplicate names
Adjusted SQL file preview method
Optimized OFD preview compatibility
Beautified TXT text pagination box display
Upgraded Linux/Docker built-in office to LibreOffice-7.5.3
Upgraded Windows built-in office to LibreOffice-7.5.3 Portable
Other functional optimizations

Fixes

Fixed compressed package path errors in reverse proxy scenarios
Fixed .click error when image preview URLs contain &
Fixed known OFD preview issues
Fixed page error when clicking on file directories (tree nodes) in compressed package preview
Other known issue fixes

Version 4.2.1 (April 18, 2023)

Change Log

Fixed null pointer bug in dwg file preview

Version 4.2.0 (April 13, 2023)

New Features

Added SVG format file preview support
Added encrypted Office file preview support
Added encrypted zip, rar, and other compressed package file preview support
Added xmind software model file preview support
Added BPMN workflow model file preview support
Added eml email file preview support
Added EPUB e-book file preview support
Added office document format support: dotm, ett, xlt, xltm, wpt, dot, xlam, xla, dotx, etc.
Added 3D model file support: obj, 3ds, stl, ply, gltf, glb, off, 3dm, fbx, dae, wrl, 3mf, ifc, brep, step, iges, fcstd, bim, etc.
Added configurable high-risk file upload restrictions (e.g., exe files)
Added configurable site filing information
Added password requirement for demo site file deletion

Optimizations

Added caching for text document preview
Beautified 404, 500 error pages
Optimized invoice and other OFD file preview seal rendering compatibility
Removed office-plugin module, using new jodconverter component
Optimized Excel file preview effect
Optimized CAD file preview effect
Updated xstream, junrar, pdfbox, and other dependency versions
Updated TIF to PDF conversion plugin, added conversion cache
Optimized demo page UI deployment
Compressed package file preview supports directories

Fixes

Fixed XSS issues in some interfaces
Fixed console printed demo address not following content-path configuration
Fixed OFD file preview cross-domain issues
Fixed internal self-signed certificate HTTPS URL file download issues
Fixed special character file deletion issues
Fixed OOM caused by unreclaimed memory in PDF to image conversion
Fixed garbled preview for xlsx 7.4+ version files
Fixed TrustHostFilter not intercepting cross-domain interfaces (security issue - upgrade required if using TrustHost)
Fixed compressed package file preview filename garbled issue on Linux systems
Fixed OFD file preview only displaying 10 pages

Changelog

December 14, 2022, version 4.1.0 released:

Updated homepage design by @wsd7747.
Compatible with multipage tif for pdf and jpg conversion and multiple page online preview for tif image preview by @zhangzhen1979.
Optimized docker build, using layered build method by @yl-yue.
Implemented file encryption based on userToken cache by @yl-yue.
Implemented preview for encrypted Word, PPT, and Excel files by @yl-yue.
Upgraded Linux & Docker images to LibreOffice 7.3.
Updated OFD preview component, tif preview component, and added support for PPT watermarking.
Numerous other upgrades, optimizations, and bug fixes. We thank @yl-yue, @wsd7747, @zhangzhen1979, @tomhusky, @shenghuadun, and @kischn.sun for their code contributions.

July 6, 2021, version 4.0.0 released:

The integration of OpenOffice in the underlying system has been replaced with LibreOffice, resulting in enhanced compatibility and improved preview effects for Office files.
Fixed the directory traversal vulnerability in compressed files.
Fixed the issue where previewing PPT files in PDF mode was ineffective.
Fixed the issue where the front-end display of image preview mode for PPT files was abnormal.
Added a new feature: the file upload function on the homepage can be enabled or disabled in real-time through configuration.
Optimized the logging of Office process shutdown.
Optimized the logic for finding Office components in Windows environment, with built-in LibreOffice taking priority.
Optimized the synchronous execution of starting Office processes.

June 17, 2021, version 3.6.0 released:

This version includes support for OFD file type versions, and all the important features in this release were contributed by the community. We thank @gaoxingzaq and @zhangxiaoxiao9527 for their code contributions.

Added support for previewing OFD type files. OFD is a domestically produced file format similar to PDF.
Added support for transcoding and previewing video files through ffmpeg. With transcoding enabled, theoretically, all mainstream video file formats such as RM, RMVB, FLV, etc. are supported for preview.
Beautified the preview effect of PPT and PPTX file types, much better looking than the previous version.
Updated the versions of dependencies such as pdfbox, xstream, common-io.

January 28, 2021:

The final update of the Lunar New Year 2020 has been released, mainly including some UI improvements, bug fixes reported by QQ group users and issues, and most importantly, it is a new version for a good year.

Introduced galimatias to solve the problem of abnormal file download caused by non-standard file names.
Updated UI style of index access demonstration interface.
Updated UI style of markdown file preview.
Updated UI style of XML file preview, adjusted the architecture of text file preview to facilitate expansion.
Updated UI style of simTxT file preview.
Adjusted the UI of continuous preview of multiple images to flip up and down.
Simplified all file download IO operations by adopting the apache-common-io package.
XML file preview supports switching to pure text mode.
Enhanced prompt information when url base64 decoding fails.
Fixed import errors and image preview bug.
Fixed the problem of missing log directory when running the release package.
Fixed the bug of continuous preview of multiple images in the compressed package.
Fixed the problem of no universal matching for file type suffixes in uppercase and lowercase.
Specified the use of the Apache Commons-code implementation for Base64 encoding to fix exceptions occurring in some JDK versions.
Fixed the bug of HTML file preview of text-like files.
Fixed the problem of inability to switch between jpg and pdf when previewing dwg files.
Escaped dangerous characters to prevent reflected xss.
Fixed the problem of duplicate encoding causing the failure of document-to-image preview and standardized the encoding.

December 27, 2020:

The year-end major update of 2020 includes comprehensive architecture design, complete code refactoring, significant improvement in code quality, and more convenient secondary development. We welcome you to review the source code and contribute to building by raising issues and pull requests.

Adjusted architecture modules, extensively refactored code, and improved code quality by several levels. Please feel free to review.
Enhanced XML file preview effect and added preview of XML document structure.
Added support for markdown file preview, including support for md rendering and switching between source text and preview.
Switched the underlying web server to jetty, resolving the issue: https://github.com/kekingcn/kkFileView/issues/168
Introduced cpdetector to solve the problem of file encoding recognition.
Adopted double encoding with base64 and urlencode for URLs to completely solve preview problems with bizarre file names.
Added configuration item office.preview.switch.disabled to control the switch of office file preview.
Optimized text file preview logic, transmitting content through Base64 to avoid requesting file content again during preview.
Disabled the image zoom effect in office preview mode to achieve consistent experience with image and pdf preview.
Directly set pdfbox to be compatible with lower version JDK, and there will be no warning prompts even when run in IDEA.
Removed non-essential toolkits like Guava and Hutool to reduce code volume.
Asynchronous loading of Office components speeds up application launch to within 5 seconds.
Reasonable settings of the number of threads in the preview consumption queue.
Fixed the bug where files in compressed packages failed to preview again.
Fixed the bug in image preview.

May 20th 2020 ：

Support for global watermark and dynamic change of watermark content through parameters
Support for CAD file Preview
Add configuration item base.url, support using nginx reverse proxy and set context-path
All configuration items can be read from environment variables, which is convenient for docker image deployment and large-scale use in cluster
Support the configuration of TrustHost (only the file source from the trust site can be previewed), and protect the preview service from abuse
Support configuration of customize cache cleanup time (cron expression)
All recognizable plain text can be previewed directly without downloading, such as .md .java .py, etc
Support configuration to limit PDF file download after conversion
Optimize Maven packaging configuration to solve the problem of line break in .sh script
Place all CDN dependencies on the front end locally for users without external network connection
Comment Service on home page switched from Sohu ChangYan to gitalk
Fixed preview exceptions that may be caused by special characters in the URL
Fixed the addtask exception of the transformation file queue
Fixed other known issues
Official website build: https://kkview.cn
Official docker image repository build: https://hub.docker.com/r/keking/kkfileview

June 18th 2019 ：

Support automatic cleaning of cache and preview files
Support http/https stream url file preview
Support FTP url file preview
Add Docker build

April 8th 2019

Cache and queue implementations abstract, providing JDK and REDIS implementations (REDIS becomes optional dependencies)
Provides zip and tar.gz packages, and provides a one-click startup script

January 17th 2018

Refined the project directory, abstract file preview interface, Easy to extend more file extensions and depoly this project on your own
Added English documentation (@幻幻Fate，@汝辉) contribution
Support for more image file extensions
Fixed the issue that image carousel in zip file will always start from the first

January 12th 2018

Support for multiple images preview
Support for images rotation preview in rar/zip

January 2nd 2018

Fixed gibberish issue when preview a txt document caused by the file encoding problem
Fixed the issue that some module dependencies can not be found
Add a spring boot profile, and support for Multi-environment configuration
Add pdf.js to preview the documents such as doc,etc.,support for generating doc headlines as pdf menu，support for mobile preview

Sponsor Us

If this project has been helpful to you, we welcome your sponsorship. Your support is our greatest motivation.！

tonikelope/megabasterd

Yet another unofficial (and ugly) cross-platform MEGA downloader/uploader/streaming suite.

MegaBasterd

"If it compiles, it's good; if it boots up, it's perfect." (Linus Torvalds)

Download latest build

Note: MegaBasterd jar version requires Java 8 or later.

Would you like to help by translating MegaBasterd into your favorite language?

MegaBasterd DEMO

BONUS: Why the f*ck has MegaBasterd stopped downloading?

IMPORTANT: You are not authorized to use MegaBasterd in any way that violates MEGA's terms of use.

NationalSecurityAgency/ghidra

Ghidra is a software reverse engineering (SRE) framework

Ghidra Software Reverse Engineering Framework

Ghidra is a software reverse engineering (SRE) framework created and maintained by the National Security Agency Research Directorate. This framework includes a suite of full-featured, high-end software analysis tools that enable users to analyze compiled code on a variety of platforms including Windows, macOS, and Linux. Capabilities include disassembly, assembly, decompilation, graphing, and scripting, along with hundreds of other features. Ghidra supports a wide variety of processor instruction sets and executable formats and can be run in both user-interactive and automated modes. Users may also develop their own Ghidra extension components and/or scripts using Java or Python.

In support of NSA's Cybersecurity mission, Ghidra was built to solve scaling and teaming problems on complex SRE efforts, and to provide a customizable and extensible SRE research platform. NSA has applied Ghidra SRE capabilities to a variety of problems that involve analyzing malicious code and generating deep insights for SRE analysts who seek a better understanding of potential vulnerabilities in networks and systems.

If you are a U.S. citizen interested in projects like this, to develop Ghidra and other cybersecurity tools for NSA to help protect our nation and its allies, consider applying for a career with us.

Security Warning

WARNING: There are known security vulnerabilities within certain versions of Ghidra. Before proceeding, please read through Ghidra's Security Advisories for a better understanding of how you might be impacted.

Install

To install an official pre-built multi-platform Ghidra release:

Install JDK 21 64-bit
Download a Ghidra release file
- NOTE: The official multi-platform release file is named ghidra_<version>_<release>_<date>.zip which can be found under the "Assets" drop-down. Downloading either of the files named "Source Code" is not correct for this step.
Extract the Ghidra release file
- NOTE: Do not extract on top of an existing installation
Launch Ghidra: ./ghidraRun (ghidraRun.bat for Windows)
- or launch PyGhidra: ./support/pyghidraRun (support\pyghidraRun.bat for Windows)

For additional information and troubleshooting tips about installing and running a Ghidra release, please refer to the Getting Started document which can be found at the root of a Ghidra installation directory.

Build

To create the latest development build for your platform from this source repository:

Install build tools:

JDK 21 64-bit
Gradle 8.5+ (or provided Gradle wrapper if Internet connection is available)
Python3 (version 3.9 to 3.14) with bundled pip
GCC or Clang, and make (Linux/macOS-only)
Microsoft Visual Studio 2017+ or Microsoft C++ Build Tools with the following components installed (Windows-only):
- MSVC
- Windows SDK
- C++ ATL

Download and extract the source:

Download from GitHub

unzip ghidra-master
cd ghidra-master

NOTE: Instead of downloading the compressed source, you may instead want to clone the GitHub repository: git clone https://github.com/NationalSecurityAgency/ghidra.git

Download additional build dependencies into source repository:

NOTE: If an Internet connection is available and you did not install Gradle, the ./gradlew (or gradlew.bat) command may be used in place of the gradle command in the following instructions.

gradle -I gradle/support/fetchDependencies.gradle

Create development build:

gradle buildGhidra

The compressed development build will be located at build/dist/.

For more detailed information on building Ghidra, please read the Developer's Guide.

For issues building, please check the Known Issues section for possible solutions.

Develop

User Scripts and Extensions

Ghidra installations support users writing custom scripts and extensions via the GhidraDev plugin for Eclipse. The plugin and its corresponding instructions can be found within a Ghidra release at Extensions/Eclipse/GhidraDev/ or at this link. Alternatively, Visual Studio Code may be used to edit scripts by clicking the Visual Studio Code icon in the Script Manager. Fully-featured Visual Studio Code projects can be created from a Ghidra CodeBrowser window at Tools -> Create VSCode Module project.

NOTE: Both the GhidraDev plugin for Eclipse and Visual Studio Code integrations only support developing against fully built Ghidra installations which can be downloaded from the Releases page.

Advanced Development

To develop the Ghidra tool itself, it is highly recommended to use Eclipse, which the Ghidra development process has been highly customized for.

Install build and development tools:

Follow the above build instructions so the build completes without errors
Install Eclipse IDE for Java Developers

Prepare the development environment:

gradle prepdev eclipse buildNatives

Import Ghidra projects into Eclipse:

File -> Import...
General | Existing Projects into Workspace
Select root directory to be your downloaded or cloned ghidra source repository
Check Search for nested projects
Click Finish

When Eclipse finishes building the projects, Ghidra can be launched and debugged with the provided Ghidra Eclipse run configuration.

For more detailed information on developing Ghidra, please read the Developer's Guide.

Contribute

If you would like to contribute bug fixes, improvements, and new features back to Ghidra, please take a look at our Contributor's Guide to see how you can participate in this open source project.

diffplug/spotless

Keep your code spotless

Spotless: Keep your code spotless

You probably want one of the links below:

❇️ Spotless for Gradle (with integrations for VS Code and IntelliJ)

user@machine repo % ./gradlew build
:spotlessJavaCheck FAILED
  The following files had format violations:
  src\main\java\com\diffplug\gradle\spotless\FormatExtension.java
    -\t\t····if·(targets.length·==·0)·{
    +\t\tif·(targets.length·==·0)·{
  Run './gradlew spotlessApply' to fix these violations.
user@machine repo % ./gradlew spotlessApply
:spotlessApply
BUILD SUCCESSFUL
user@machine repo % ./gradlew build
BUILD SUCCESSFUL

❇️ Spotless for Maven

user@machine repo % mvn spotless:check
[ERROR]  > The following files had format violations:
[ERROR]  src\main\java\com\diffplug\gradle\spotless\FormatExtension.java
[ERROR]    -\t\t····if·(targets.length·==·0)·{
[ERROR]    +\t\tif·(targets.length·==·0)·{
[ERROR]  Run 'mvn spotless:apply' to fix these violations.
user@machine repo % mvn spotless:apply
[INFO] BUILD SUCCESS
user@machine repo % mvn spotless:check
[INFO] BUILD SUCCESS

❇️ Spotless for SBT (external for now)

Other build systems

How it works (for potential contributors)

Ideally, a code formatter can do more than just find formatting errors - it should fix them as well. Such a formatter is just a Function<String, String>, which returns a formatted version of its potentially unformatted input.

It's easy to build such a function, but there are some gotchas and lots of integration work (newlines, character encodings, idempotency, git ratcheting, and build-system integration). Spotless tackles those for you so you can focus on just a simple Function<String, String> which can compose with any of the other formatters and build tools in Spotless' arsenal.

Current feature matrix

Feature / FormatterStep	gradle	maven	sbt	(Your build tool here)
Automatic idempotency safeguard	👍	👍	👍	⬜
Misconfigured encoding safeguard	👍	👍	👍	⬜
Toggle with `spotless:off` and `spotless:on`	👍	👍	⬜	⬜
Ratchet from `origin/main` or other git ref	👍	👍	⬜	⬜
Define line endings using git	👍	👍	👍	⬜
Fast incremental format and up-to-date check	👍	👍	⬜	⬜
Fast format on fresh checkout using buildcache	👍	⬜	⬜	⬜
`generic.EndWithNewlineStep`	👍	👍	⬜	⬜
`generic.IndentStep`	👍	👍	⬜	⬜
`generic.Jsr223Step`	⬜	👍	⬜	⬜
`generic.LicenseHeaderStep`	👍	👍	👍	⬜
`generic.NativeCmdStep`	👍	👍	⬜	⬜
`generic.ReplaceRegexStep`	👍	👍	⬜	⬜
`generic.ReplaceStep`	👍	👍	⬜	⬜
`generic.TrimTrailingWhitespaceStep`	👍	👍	⬜	⬜
`antlr4.Antlr4FormatterStep`	👍	👍	⬜	⬜
`biome.BiomeStep`	👍	👍	⬜	⬜
`cpp.ClangFormatStep`	👍	⬜	⬜	⬜
`cpp.EclipseFormatterStep`	👍	👍	👍	⬜
`go.GofmtFormatStep`	👍	⬜	⬜	⬜
`gherkin.GherkinUtilsStep`	👍	👍	⬜	⬜
`groovy.GrEclipseFormatterStep`	👍	👍	👍	⬜
`java.GoogleJavaFormatStep`	👍	👍	👍	⬜
`java.ImportOrderStep`	👍	👍	👍	⬜
`java.PalantirJavaFormatStep`	👍	👍	⬜	⬜
`java.RemoveUnusedImportsStep`	👍	👍	👍	⬜
`java.ExpandWildcardImportsStep`	👍	⬜	⬜	⬜
`java.ForbidWildcardImportsStep`	👍	👍	👍	⬜
`java.ForbidModuleImportsStep`	👍	👍	⬜	⬜
`java.EclipseJdtFormatterStep`	👍	👍	👍	⬜
`java.FormatAnnotationsStep`	👍	👍	⬜	⬜
`java.CleanthatJavaStep`	👍	👍	⬜	⬜
`java.TableTestFormatterStep`	👍	👍	⬜	⬜
`json.gson.GsonStep`	👍	👍	⬜	⬜
`json.JacksonJsonStep`	👍	👍	⬜	⬜
`json.JsonSimpleStep`	👍	👍	⬜	⬜
`json.JsonPatchStep`	👍	👍	⬜	⬜
`kotlin.KtLintStep`	👍	👍	👍	⬜
`kotlin.KtfmtStep`	👍	👍	⬜	⬜
`kotlin.DiktatStep`	👍	👍	⬜	⬜
`markdown.FreshMarkStep`	👍	⬜	⬜	⬜
`markdown.FlexmarkStep`	👍	👍	⬜	⬜
`npm.EslintFormatterStep`	👍	👍	⬜	⬜
`npm.PrettierFormatterStep`	👍	👍	⬜	⬜
`npm.TsFmtFormatterStep`	👍	👍	⬜	⬜
`pom.SortPomStep`	👍	👍	⬜	⬜
`protobuf.BufStep`	👍	⬜	⬜	⬜
`python.BlackStep`	👍	⬜	⬜	⬜
`rdf.RdfFormatterStep`	⬜	👍	⬜	⬜
`scala.ScalaFmtStep`	👍	👍	👍	⬜
`shell.ShfmtStep`	👍	👍	⬜	⬜
`sql.DBeaverSQLFormatterStep`	👍	👍	👍	⬜
`wtp.EclipseWtpFormatterStep`	👍	👍	⬜	⬜
`yaml.JacksonYamlStep`	👍	👍	⬜	⬜
(Your FormatterStep here)	⬜	⬜	⬜	⬜

Why are there empty squares?

Many projects get harder to work on as they get bigger. Spotless is easier to work on than ever, and one of the reasons why is that we don't require contributors to "fill the matrix". If you want to add Bazel support, we'd happily accept the PR even if it only supports the one formatter you use. And if you want to add FooFormatter support, we'll happily accept the PR even if it only supports the one build system you use.

Once someone has filled in one square of the formatter/build system matrix, it's easy for interested parties to fill in any empty squares, since you'll now have a working example for every piece needed.

Acknowledgements

Thanks to over 200 contributors with merged PRs, and also to everyone who helped with code review, file reproducible bugs, etc. A few contributions stand out as especially significant to the history of the project, though regrettably there are certain to be some important omissions!
Thanks to Zongle Wang for an enormous mound of contributions, but especially for his near-rewrite so that Spotless could support Gradle's configuration cache natively.
Thanks to Simon Gamma for adding support for npm-based formatters, twice including prettier and tsfmt.
Thanks to Konstantin Lutovich for implementing and maintaining the Maven plugin, as well as fixing remote-build cache support for Gradle.
Thanks to Frank Vennemeyer for Groovy support via greclipse, C++ support via CDT, XML support via WTP and a huge body of work with other eclipse-based formatters.
Thanks to Jonathan Bluett-Duncan for
- implementing up-to-date checking #31
- breaking spotless into libraries #56
- lots of other things, but especially the diff support in spotlessCheck
- constant improvements on a variety of topics with high-quality code reviews
Thanks to Daz DeBoer for the reworking the guts of our Gradle plugin to support buildcache, InputChanges, and lazy configuration.
Thanks to Richard Willis for creating the VS Code extension for Spotless Gradle.
Thanks to Ryan Gurney for creating the IntelliJ plugin for Spotless Gradle.
Thanks to Alex Danylenko for creating the git pre-push hook.
Thanks to Markus Heberling for adding generic native formatters, jsr-223 formatters, and maven pom sorting.
Thanks to Matthias Balke for adding support for Antlr.
Thanks to Matthias Andreas Benkard for adding support for google-java-format 1.8+ (#563)
Thanks to Thomas Broyer for adding support for google-java-format's skip-reflowing-long-strings option.
Thanks to Hakanai for adding wildcards last support to the import sorter.
Thanks to Kevin Brooks for updating all eclipse-based formatters to 4.13 and fixing Groovy for multiproject.
Thanks to Dylan Baroody for fixing sql formatting support for JDBI bind list params.
Thanks to figroc for adding custom mavenCoordinate support to google-java-format.
Thanks to Thomas Glaeser for finding and fixing a file-permissions-clobbering bug.
Thanks to Joan Goyeau for fixing scalafmt integration.
Thanks to Nick Sutcliffe for fixing scalafmt post-2.0.
Thanks to Baptiste Mesta for
- porting the DBeaver formatter to Spotless, and thanks to DBeaver and its authors for their excellent SQL formatter.
- making license headers date-aware #179
Thanks to vmdominguez and Luis Fors for adding the ability to limit formatting to specific files in Gradle (#322) and Maven (#392), respectively.
Thanks to bender316 for fixing classloading on Java 9 (#426).
Thanks to Stefan Oehme for tons of help on the internal mechanics of Gradle.
Thanks to eyalkaspi for adding configurable date ranges to the date-aware license headers.
Thanks to Andrew Parmet for adding ktfmt support for kotlin gradle.
Thanks to Oliver Horn for adding AOSP support for Spotless' google-java-format integration.
Formatting by Eclipse
- Special thanks to Mateusz Matela for huge improvements to the eclipse code formatter!
Thanks to Zac Sweers for fixing the highly requested ktlint 0.34+ support (#469), multiple build updates and fixing a Gradle deprecation warning (#434 and others).
Thanks to Stephen Panaro for adding support for ktlint FilenameRule (#974).
Thanks to Nelson Osacky for android doc improvements, versions bump, and a build improvement.
Thanks to Stanley Shyiko for his help integrating ktlint.
Thanks to Jonathan Leitschuh for adding ktlint support for Gradle Kotlin DSL files.
Originally forked from gradle-format-plugin by Youri Bonnaffé.
Thanks to Ismaël Mejía for bumping eclipse-jdt deps to 4.11. PR #60.
Thanks to Gábor Bernát for improvements to logging and multi-project support.
Thanks to Oliver Szymanski for porting tsfmt and prettier to maven.
Thanks to Andrew Oberstar for improvements to formatting java source in non-java source sets. PR #60.
Thanks to Sameer Balasubrahmanyam for adding support for IntelliJ-style year placeholders.
Thanks to Jamie Tanna for adding a simple JSON formatter.
Thanks to Adib Saikali and Paul Merlin for tracking down the tricky cause of #506.
Import ordering from EclipseCodeFormatter.
Built by gradle.
Tested by junit.
Maintained by DiffPlug.

oasisfeng/island

Island for Android

Island

Island for Android

Build Instructions

Island depends on "deagle" library, which must be cloned alongside Island in the same path.

\--
  \- island
  \- deagle

This project is constructed into several modules, with assembly module as the build portal, to support separate "light" build for core modules, in the form of "product flavor" in Gradle build configuration.

The "engine" module shares the same package name with the "complete" build, to inherit the profile/device owner privilege. The "mobile" and other modules can be installed and updated separately alongside "engine" module for development convenience.

Open API

Due to the exclusivity nature, user could only use one Android DPC app at a time, and price of switching DPC is far too heavy. To encourage active exploration and broader development in the capabilities of DPC and therefore better benefit users, Island is devoted to build an open collaboration for community developers, either in development of this project or opening DPC capabilities to 3rd-party apps via open API. Island itself will not focus on the rich set of features, but mainly focuses on building a powerful engine as an open platform for much more apps from the community.

Starting from the first public version of Island, all APIs are open to 3rd-party apps with the standard runtime-permission of Android as user authorization. Developers can start building apps now to take advantage of the Island open APIs.

The protocol of all APIs are well defined and maintained in the class "Api".

Contribution

If you found bugs, made minor improvements or translated the strings, please feel free to send us pull-requests.

If you are interested in improving the functionality of Island, please create an issue first to discuss your thoughts with us, we are open to collaboration in future development.

If you need new APIs for your apps to take advantage of the DPC capabilities, please feel free to create an issue to describe your app and its use case of those APIs. We are still in the early stage of building a rich set of open APIs.

doocs/leetcode

🔥LeetCode solutions in any programming language | 多种编程语言实现 LeetCode、《剑指 Offer（第 2 版）》、《程序员面试金典（第 6 版）》题解

介绍

本项目包含 LeetCode、《剑指 Offer（第 2 版）》、《剑指 Offer（专项突击版）》、《程序员面试金典（第 6 版）》等题目的相关题解。所有题解均由多种编程语言实现，包括但不限于：Java、Python、C++、Go、TypeScript、Rust。我们正在全力更新，欢迎 Star 🌟 关注本项目，获取项目最新动态。

English Version

站点

https://leetcode.doocs.org

算法全解

专项突破

算法提升专题

1. 基础算法

在排序数组中查找元素的第一个和最后一个位置 - 二分查找
准时到达的列车最小时速 - 二分查找
可移除字符的最大数目 - 二分查找
排序数组 - 快速排序、归并排序
字符串相加 - 高精度加法
字符串相乘 - 高精度乘法
区域和检索 - 数组不可变 - 前缀和
二维区域和检索 - 矩阵不可变 - 二维前缀和
区间加法 - 前缀和、差分
用邮票贴满网格图 - 二维前缀和、二维差分
无重复字符的最长子串 - 双指针、哈希表
乘积小于 K 的子数组 - 双指针
位 1 的个数 - 位运算、lowbit
合并区间 - 区间合并

2. 数据结构

设计链表 - 单链表、指针引用、数组实现
下一个更大元素 I - 单调栈
每日温度 - 单调栈
子数组的最小值之和 - 单调栈
最大宽度坡 - 单调栈
最多能完成排序的块 II - 单调栈
子数组范围和 - 单调栈
子数组最小乘积的最大值 - 单调栈
滑动窗口最大值 - 单调队列
满足不等式的最大值 - 单调队列
和至少为 K 的最短子数组 - 单调队列
带限制的子序列和 - 动态规划、单调队列优化
单词规律 II - 哈希表、回溯
最短回文串 - 字符串哈希
回文对 - 字符串哈希
最长重复子串 - 字符串哈希、二分查找
不同的循环子字符串 - 字符串哈希

3. 搜索

图像渲染- BFS、DFS、Flood Fill 算法、连通性模型
岛屿数量 - BFS、Flood Fill 算法
01 矩阵 - 多源 BFS
地图中的最高点 - 多源 BFS
进击的骑士 - BFS、最短路模型
二进制矩阵中的最短路径 - BFS、最短路模型
迷宫中离入口最近的出口 - BFS、最短路模型
网格中的最短路径 - BFS、最短路模型
打开转盘锁 - 最小步数模型、双向 BFS、A* 算法
单词接龙 - 最小步数模型、双向 BFS
转化数字的最小运算数 - 最小步数模型、双向 BFS
滑动谜题 - BFS、最小步数模型、A* 算法
访问所有节点的最短路径 - BFS、最小步数模型、A* 算法
为高尔夫比赛砍树 - BFS、A* 算法
使网格图至少有一条有效路径的最小代价 - 双端队列 BFS
到达角落需要移除障碍物的最小数目 - 双端队列 BFS
迷宫 - DFS、连通性模型、Flood Fill 算法
单词搜索 - DFS、搜索顺序、回溯
黄金矿工 - DFS、搜索顺序、回溯
火柴拼正方形 - DFS、回溯、剪枝
划分为 k 个相等的子集 - DFS、回溯、剪枝
完成所有工作的最短时间 - DFS、回溯、剪枝
公平分发饼干 - DFS、回溯、剪枝
矩阵中的最长递增路径 - DFS、记忆化搜索
网格图中递增路径的数目 - DFS、记忆化搜索
翻转游戏 II - DFS、状态压缩、记忆化搜索
统计所有可行路径 - DFS、记忆化搜索
切披萨的方案数 - DFS、记忆化搜索

4. 动态规划（DP）

杨辉三角 - 线性 DP、数字三角形模型
最小路径和 - 线性 DP、数字三角形模型
摘樱桃 - 线性 DP、数字三角形模型
摘樱桃 II - 线性 DP、数字三角形模型
最长递增子序列 - 线性 DP、最长上升子序列模型
无重叠区间 - 线性 DP、最长上升子序列模型、贪心优化
删列造序 III - 线性 DP、最长上升子序列模型
俄罗斯套娃信封问题 - 线性 DP、最长上升子序列模型、贪心优化
堆叠长方体的最大高度 - 排序、线性 DP、最长上升子序列模型
无矛盾的最佳球队 - 排序、线性 DP、最长上升子序列模型
最长公共子序列 - 线性 DP、最长公共子序列模型
两个字符串的最小 ASCII 删除和 - 线性 DP、最长公共子序列模型
两个字符串的删除操作 - 线性 DP、最长公共子序列模型
目标和 - 0-1 背包问题
分割等和子集 - 0-1 背包问题
最后一块石头的重量 II - 0-1 背包问题
零钱兑换 - 完全背包问题
组合总和 Ⅳ - 完全背包问题
从栈中取出 K 个硬币的最大面值和 - 分组背包问题
数字 1 的个数 - 数位 DP、记忆化搜索
统计各位数字都不同的数字个数 - 数位 DP、记忆化搜索、状态压缩
不含连续 1 的非负整数 - 数位 DP、记忆化搜索
旋转数字 - 数位 DP、记忆化搜索
最大为 N 的数字组合 - 数位 DP、记忆化搜索
统计特殊整数 - 数位 DP、记忆化搜索

5. 高级数据结构

二维网格图中探测环 - 并查集、检测环
除法求值 - 并查集、权值维护
由斜杠划分区域 - 并查集、连通分量个数
水位上升的泳池中游泳 - 并查集
交换字符串中的元素 - 并查集
打砖块 - 并查集、逆向思维
尽量减少恶意软件的传播 II - 并查集、逆向思维
检查边长度限制的路径是否存在 - 并查集、离线思维
保证图可完全遍历 - 双并查集
区域和检索 - 数组可修改 - 树状数组、线段树
通过指令创建有序数组 - 树状数组、线段树
统计数组中好三元组数目 - 树状数组、线段树
最多 K 次交换相邻数位后得到的最小整数 - 树状数组
二维区域和检索 - 可变 - 二维树状数组、线段树
计算右侧小于当前元素的个数 - 离散化树状数组、线段树
区间和的个数 - 离散化树状数组、线段树
翻转对 - 离散化树状数组、分治归并、线段树
最长递增子序列的个数 - 离散化树状数组、区间最值问题
奇妙序列 - 动态开点线段树、懒标记
Range 模块 - 动态开点线段树、懒标记
我的日程安排表 III - 动态开点线段树、懒标记
每天绘制的新区域数量 - 动态开点线段树、懒标记、区间染色模型
由单个字符重复的最长子字符串 - 线段树、动态最大子段和模型
矩形面积 II - 线段树、离散化、扫描线

6. 图论

网络延迟时间 - 最短路、Dijkstra 算法、Bellman Ford 算法、SPFA 算法
得到要求路径的最小带权子图 - 最短路、Dijkstra 算法
连接所有点的最小费用 - 最小生成树、Prim 算法、Kruskal 算法
最低成本联通所有城市 - 最小生成树、Kruskal 算法、并查集
水资源分配优化 - 最小生成树、Kruskal 算法、并查集
找到最小生成树里的关键边和伪关键边 - 最小生成树、Kruskal 算法、并查集
判断二分图 - 染色法判定二分图、并查集

加入我们

刷编程题的最大好处就是可以锻炼解决问题的思维能力。相信我，「如何去思考」本身也是一项需要不断学习和练习的技能。非常感谢前微软工程师、现蚂蚁金服技术专家 @kfstorm 贡献了本项目的所有 C# 题解。

如果你对本项目感兴趣，并且希望加入我们刷题小分队，欢迎随时提交 PR。请参考如下步骤：

将本项目 fork 到你的个人 GitHub 帐户，然后 clone 到你的本地机器；
进入 leetcode 目录，切换到一个新的分支；
对项目做出一些变更，然后使用 git add、commit、push 等命令将你的本地变更提交到你的远程 GitHub 仓库；
将你的变更以 PR 的形式提交过来，项目的维护人员会在第一时间对你的变更进行 review！
你也可以参考帮助文档 https://help.github.com/cn 了解更多细节。

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贡献者

感谢以下所有朋友对本项目的贡献！

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