# Fixed JobQueue Implementation

The race condition occurs because multiple threads can simultaneously access and modify the shared `jobs` and `results` dictionaries without synchronization. Here's the corrected implementation using proper locking:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        with self.lock:
            self.jobs[job_id] = data
        return job_id

    def process_job(self, job_id, processor):
        with self.lock:
            if job_id not in self.jobs:
                return False

            data = self.jobs[job_id]
            result = processor(data)

            # Critical section - protected by lock
            self.results[job_id] = result
            del self.jobs[job_id]
        
        return True

    def get_result(self, job_id):
        with self.lock:
            return self.results.get(job_id)
```

## Key Fixes

1. **Added `threading.Lock()`**: Created a lock in `__init__` to synchronize access to shared state.

2. **Protected all shared state access**: All reads and writes to `jobs` and `results` dictionaries are now wrapped in `with self.lock:` blocks.

3. **Made `process_job` atomic**: The entire job processing operation (read, process, store result, delete job) is now atomic, preventing race conditions.

4. **Protected `get_result`**: Ensures safe reading of results without data corruption.

## Why This Works

- **Mutual Exclusion**: Only one thread can access the critical sections at a time
- **Atomic Operations**: The entire job processing workflow is now atomic
- **No Lost Updates**: Results won't be overwritten or lost due to concurrent writes
- **No Torn Reads**: Jobs won't be deleted before results are stored

## Performance Note

The current implementation holds the lock during job processing (`processor(data)`). For long-running processors, consider using a more sophisticated approach with separate locks for job retrieval and result storage, or using `threading.RLock` if reentrancy is needed.