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📋 Detecting available tools...
   ✅ Found 6 tools:
      • Depyler (Python → Rust)
      • Bashrs (Shell → Rust)
      • Ruchy (Rust scripting)
      • PMAT (Quality analysis)
      • Realizar (Inference runtime)
      • Renacer (Syscall tracing)

📊 Tool Versions:
─────────────────
  Depyler: 3.21.0 (/home/noah/.cargo/bin/depyler)
  Bashrs:  6.39.0 (/home/noah/.cargo/bin/bashrs)
  PMAT:    2.205.0 (/home/noah/.cargo/bin/pmat)
  Ruchy:   3.213.0 (/home/noah/.cargo/bin/ruchy)

🎯 Transpilation Capabilities:
───────────────────────────────
  ✅ Python → Rust (Depyler)
     • NumPy → Trueno tensor operations
     • sklearn → Aprender ML algorithms
     • PyTorch → Realizar inference
     • Full project structure generation
     • Type inference and safety guarantees

  ✅ Shell → Rust (Bashrs)
     • POSIX shell script transpilation
     • Formal verification support
     • Deterministic execution guarantees
     • Standalone binary compilation
     • ShellCheck integration

  ❌ C/C++ → Rust (install decy)

  ✅ Quality Analysis (PMAT)
     • TDG scoring (Technical Debt Grade)
     • Complexity analysis
     • Code quality metrics
     • Adaptive analysis (Muda elimination)

  ✅ Ruchy Scripting
     • Ruby-like syntax with Rust performance
     • Gradual typing (permissive/strict modes)
     • Interactive REPL
     • Formal verification (provability)

📝 Example Workflow:
────────────────────

1. Analyze Python project:
   batuta analyze --languages --tdg /path/to/python_project

2. Transpile to Rust:
   batuta transpile --input /path/to/python_project \
                     --output /path/to/rust_project

3. Optimize with MoE backend selection:
   batuta optimize --enable-gpu --enable-simd \
                   /path/to/rust_project

4. Validate with syscall tracing:
   batuta validate --trace-syscalls \
                   /path/to/rust_project

5. Build production binary:
   batuta build --release /path/to/rust_project

6. Generate migration report:
   batuta report --format html --output report.html

🤖 ML Library Conversion:
──────────────────────────

For Python projects using ML libraries:
  • NumPy operations → Trueno (SIMD/GPU)
  • sklearn algorithms → Aprender
  • PyTorch inference → Realizar

Batuta automatically detects and converts:
  ✓ np.add(a, b) → trueno::add(&a, &b)
  ✓ sklearn.LinearRegression() → aprender::LinearRegression::new()
  ✓ model.generate() → realizar::generate_text()

🏭 Toyota Way Integration:
───────────────────────────

Batuta implements Toyota Production System principles:
  • Jidoka: Stop-the-line quality (error on warnings)
  • Muda: Waste elimination (adaptive analysis)
  • Kaizen: Continuous improvement (MoE optimization)
  • Andon: Problem visualization (PARF analysis)
  • Heijunka: Level scheduling (pipeline orchestration)

⚡ EXTREME TDD Quality Gates:
──────────────────────────────

All transpilations pass through:
  1. Pre-commit checks (< 30s)
  2. Fast test suite (< 5min)
  3. Coverage analysis (< 10min)
  4. Mutation testing (optional)

Run quality checks:
  make pre-commit  # Fast checks before commit
  make test-fast   # Full test suite
  make coverage    # Coverage report
  make tdg         # TDG score with PMAT

📦 Install Missing Tools:
─────────────────────────
  Install Decy: cargo install decy

✅ Batuta Orchestration Framework Ready!

   Convert ANY project (Python/C/C++/Shell) to Rust with:
   • Automatic transpilation
   • ML library conversion (NumPy/sklearn/PyTorch)
   • MoE backend optimization (SIMD/GPU)
   • Quality analysis and reporting
   • Formal verification support

   Start with: batuta analyze <project_path>
% time     seconds  usecs/call     calls    errors syscall
------ ----------- ----------- --------- --------- ----------------
  4.67    0.001060           7       145       139 statx
  3.87    0.000877           7       124           write
  1.81    0.000411           7        52           unknown
  1.27    0.000289           8        34           close
  2.33    0.000529          18        29         6 read
  0.91    0.000207          10        19           mmap
  0.52    0.000117           6        18           ioctl
 77.22    0.017509        1346        13           poll
  0.37    0.000085           7        12           rt_sigprocmask
  0.54    0.000122          12        10           openat
  0.31    0.000070           7         9           getcwd
  0.46    0.000105          13         8           munmap
  0.26    0.000060           8         7         1 access
  0.40    0.000091          15         6           wait4
  0.26    0.000059           9         6           mprotect
  4.00    0.000906         151         6           clone3
  0.13    0.000030           6         5           rt_sigaction
  0.17    0.000038           9         4           newfstatat
  0.11    0.000025           6         4           pread64
  0.08    0.000019           6         3           sigaltstack
  0.12    0.000028           9         3           brk
  0.08    0.000018           9         2         1 arch_prctl
  0.03    0.000007           7         1           getrandom
  0.03    0.000006           6         1           set_robust_list
  0.03    0.000006           6         1           set_tid_address
------ ----------- ----------- --------- --------- ----------------
100.00    0.022674          43       522       147 total
