Object-oriented • JIT-compiled • AI-ready • Cross-platform
Modern programming language with first-class ML and computer vision support
Built for modern development:
- 🚀 JIT-compiled for performance (ARM64/AMD64)
- 🤖 AI/ML first-class: OpenAI, Gemini, Ollama, OpenCV, ONNX
- 💻 Developer-friendly: REPL shell, LSP plugins for VSCode/Sublime/Kate
- 🌍 Cross-platform: Linux, macOS, Windows (including ARM/RPI)
- 🔧 Full-featured: Threads, generics, closures, reflection, serialization
Perfect for: AI/ML prototyping • Computer vision • Web services • Game development
No installation needed - write, compile, and run Objeck code directly in your browser:
👉🏽 Interactive playground with 33 demo programs across 7 categories with Monaco editor and syntax highlighting.
# Install (example for macOS/Linux)
curl -LO https://github.com/objeck/objeck-lang/releases/download/v2026.4.3/objeck-linux-x64_2026.4.3.tgz
tar xzf objeck-linux-x64_2026.4.3.tgz
export PATH=$PATH:./objeck-lang/bin
export OBJECK_LIB_PATH=./objeck-lang/lib
# Hello World
echo 'class Hello {
function : Main(args : String[]) ~ Nil {
"Hello World"->PrintLine();
}
}' > hello.obs
# Compile and run (modern syntax)
obc hello && obr hello📖 Full docs: objeck.org 💡 Examples: github.com/objeck/objeck-lang/programs
Web Playground — Try Objeck in your browser. Code runs in sandboxed Docker containers on a dedicated server. Includes 33 demos covering the language basics, OOP, algorithms, collections, data processing, and more.
v2026.4.3 ✅
- DAP debugger hover — hovering an object shows
ClassName { field=val, ... }with one-level instance field expansion viaFormatObjectForDap - DAP instance/class variable scopes — Variables pane now shows separate Locals, Instance, and Class scopes with correct memory mapping
- DAP stepping + crash fixes — fixed step-into crash, step-over/step-out scoping, stdout corruption, disconnect access violation, and variable display
- Editor setup refresh — updated VS Code, Sublime Text, and gvim/Vim DAP+LSP setup for Windows, Linux, and macOS
- LSP crash fixes — null guards for
textDocument/codeActionwith inferred locals, hover position fix (1-based to 0-based) - Configurable JIT threshold — auto-JIT invocation count can now be tuned
- Fixed JIT S2F callback param count causing segfault on
String:ToFloat - Hardened HTTPS client against null
ReadLineon connection failures
v2026.4.2
- JIT local variable register cache (AMD64 + ARM64) — keeps values in registers after store, avoids redundant reloads, evicts on demand when register pool is exhausted
- Hardened JSON, JSON stream, and XML parsers against malformed input
- DTLS (Datagram TLS) support — new
DTLSSocketandDTLSSocketServerclasses for secure UDP communication (IoT, VoIP, gaming) - Link-time optimization — added
-flto=autoacross all GCC Makefiles (AMD64 and ARM64) - ARM64 native CPU tuning —
-mcpu=nativeauto-detects RPi5 (Cortex-A76) and Jetson Orin (Cortex-A78AE) - Fixed all MSVC and GCC compiler warnings
- Fixed doc generator error on
@hiddentag
v2026.4.1
- Debug Adapter Protocol (DAP) — VS Code debugging with conditional breakpoints, ANSI color output, and readline support
- 3.3x binarytrees speedup — young-gen bump allocator, direct JIT-to-JIT calling, atomic CAS mark bits, auto-JIT dispatch fix
- MTHD_CALL JIT whitelist (x64 + ARM64) — methods containing method calls can now be JIT-compiled and auto-JIT'd
- GC thread safety — memory barriers in PushFrame/PopFrame paired with acquire fences in GC to fix intermittent threading segfaults
- Code signing — macOS Developer ID Application + Installer certificates and notarization; Windows Sectigo signing; all automated in CI
- macOS .pkg installer — signed and notarized native installer with PATH setup via productbuild
- Networking: SSE streaming, socket receive timeouts, ReadBytes partial read fix, HTTP client/server hardening
- ODBC: BigInt support, connection strings, transactions, error handling, schema discovery
- OpenCV: contours, VideoWriter, transforms, normalization, 15 new image processing functions
- Phi-3 Vision multimodal inference — 3-model pipeline with FP16 and DirectML/CUDA support
- Unified ONNX build system — single source with preprocessor-selected providers (DML, CUDA, QNN, CoreML)
- Hash auto-resize at 75% load, Vector in-place Remove, JSON escape/keyword fixes
- Fixed the constructor early return crash, CSV.Median, CSV.Average, URL encoding, Response.ToString nil check
- Performance details and benchmarks →
📋 Full changelog • 🗺️ Roadmap • 📝 Editor & IDE setup
Latest Release: v2026.4.3
| Platform | Architecture | Download |
|---|---|---|
| Windows | x64 | MSI Installer / ZIP |
| Windows | ARM64 | MSI Installer / ZIP |
| Linux | x64 | TGZ Archive |
| Linux | ARM64 | TGZ Archive |
| macOS | ARM64 (M1/M2/M3) | TGZ Archive |
| LSP | All platforms | ZIP Archive |
📦 Alternative: Sourceforge • 📚 API Docs: objeck.org/api/latest
Note: All Windows installers are digitally signed. Releases are fully automated via CI/CD and built on GitHub Actions runners.
# OpenAI Realtime API - get text AND audio
response := Realtime->Respond("How many James Bond movies?",
"gpt-4o-realtime-preview", token);
text := response->GetFirst();
audio := response->GetSecond();
Mixer->PlayPcm(audio->Get(), 22050, AudioFormat->SDL_AUDIO_S16LSB, 1);# OpenCV face detection
detector := FaceDetector->New("haarcascade_frontalface_default.xml");
faces := detector->Detect(image);
faces->Size()->PrintLine(); # "5 faces detected"# Sentiment analysis and TF-IDF
text := "This product is absolutely wonderful!";
sentiment := SentimentAnalyzer->Classify(text); # "positive"
# Train TF-IDF on documents
docs := ["cats are pets", "dogs are pets", "birds can fly"];
tfidf := TF_IDF->New();
tfidf->Fit(docs);
vector := tfidf->Transform("cats and dogs"); # [0.47, 0.0, 0.47, ...]Object-Oriented
- Inheritance, interfaces, generics
- Type inference and boxing
- Reflection and dependency injection
- See OOP examples →
Functional
- Closures and lambda expressions
- First-class functions
- See functional examples →
Platform Support
- Unicode, file I/O, sockets, named pipes
- Threading with mutexes
- See platform features →
AI & Machine Learning
- OpenAI, Gemini, Ollama
- NLP (tokenization, TF-IDF, text similarity, sentiment analysis)
- OpenCV (computer vision)
- ONNX Runtime (cross-platform ML inference)
- Phi-3 / Phi-3 Vision (local SLM text and vision inference)
Web & Networking
Data
- JSON (hierarchical + streaming), XML, CSV
- SQL/ODBC, In-memory queries
- Collections
Other
Modern tooling and practices:
- 🤖 Claude Code for pair programming, debugging, and refactoring
- 🔄 CI/CD: Fully automated build, test, sign, and release pipeline (GitHub Actions)
- ✅ Every push triggers multi-platform builds (Windows, Linux, macOS)
- ✅ Automated code signing for Windows installers
- ✅ One-tag releases:
git tag v2026.2.1→ automated distribution in 60 minutes - ✅ Parallel builds across 6 platforms (x64/ARM64)
- 📖 Release Process Documentation • CI/CD Architecture
- 🔍 Quality: Coverity static analysis + CodeQL security scanning
- 🧪 Testing: 350+ tests across 3 suites (regression, comprehensive, deploy)
- Regression suite: 10 focused tests for critical functionality
- Comprehensive suite: 323+ tests for full language validation
- Deploy suite: 17 real-world usage examples
- Full cross-platform coverage (Windows/Linux/macOS, x64/ARM64)
Editor Support:
- LSP plugins for VSCode, Sublime, Kate, and more
- REPL for interactive development
- API docs at objeck.org
📚 Testing Documentation • 🧪 Regression Tests • 📊 Performance & Benchmarks
- 🌐 Web Playground — try Objeck in your browser
- 📖 Documentation
- 🎯 Examples
- 💬 Discussions
- 🐛 Issues
