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johndoe6345789
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Complete implementation of enterprise-grade authentication middleware for email service: Features: - JWT token creation/validation with configurable expiration - Bearer token extraction and validation - Multi-tenant isolation enforced at middleware level - Role-based access control (RBAC) with user/admin roles - Row-level security (RLS) for resource access - Automatic request logging with user context and audit trail - CORS configuration for email client frontend - Rate limiting (50 req/min per user with Redis backend) - Comprehensive error handling with proper HTTP status codes Implementation: - Enhanced src/middleware/auth.py (415 lines) - JWTConfig class for token management - create_jwt_token() for token generation - decode_jwt_token() for token validation - @verify_tenant_context decorator for auth middleware - @verify_role decorator for RBAC - verify_resource_access() for row-level security - log_request_context() for audit logging Testing: - 52 comprehensive test cases covering all features - 100% pass rate with fast execution (0.15s) - Test categories: JWT, multi-tenant, RBAC, RLS, logging, integration - Full coverage of error scenarios and edge cases Documentation: - AUTH_MIDDLEWARE.md: Complete API reference and configuration guide - AUTH_INTEGRATION_EXAMPLE.py: Real-world usage examples for 5+ scenarios - PHASE_7_SUMMARY.md: Implementation summary with checklist - Inline code documentation with type hints Security: - Multi-tenant data isolation at all levels - Constant-time password comparison - JWT signature validation - CORS protection - Rate limiting against abuse - Comprehensive audit logging Dependencies Added: - PyJWT==2.8.1 Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Mojo Examples
Example projects demonstrating Mojo - a new programming language that combines Python syntax with systems programming performance.
Why Mojo?
- Python-like syntax - Familiar to Python developers
- Strictly typed - Compile-time type checking
- Systems performance - Comparable to C/C++/Rust
- Python interop - Import and use Python libraries
- SIMD & parallelism - First-class support for vectorization
Requirements
- Mojo SDK (free to download)
Project Structure
mojo/
├── src/
│ └── main.mojo # Main entry point
├── examples/
│ ├── hello.mojo # Hello world
│ ├── structs.mojo # Struct definitions
│ ├── simd.mojo # SIMD operations
│ ├── python_interop.mojo # Python integration
│ └── performance.mojo # Performance comparison
└── mojoproject.toml # Project configuration
Quick Start
# Run hello world
mojo examples/hello.mojo
# Build optimized binary
mojo build src/main.mojo -o main
# Run with Python interop
mojo examples/python_interop.mojo
Key Features Demonstrated
Strict Typing
fn add(x: Int, y: Int) -> Int:
return x + y
Structs with Ownership
struct Point:
var x: Float64
var y: Float64
fn __init__(inout self, x: Float64, y: Float64):
self.x = x
self.y = y
SIMD Operations
from math import sqrt
fn vector_magnitude[width: Int](v: SIMD[DType.float64, width]) -> Float64:
return sqrt((v * v).reduce_add())
Python Interop
from python import Python
fn main() raises:
let np = Python.import_module("numpy")
let arr = np.array([1, 2, 3, 4, 5])
print(arr.mean())