<reasoning_content>
Here's a thinking process:

1.  **Understand the User Requirements:**
   - Create a `JobQueue` class in Python
   - Methods:
     - `add_job(job_id: str, data: dict) -> str`: Adds a job, returns `job_id`
     - `get_result(job_id: str) -> dict | None`: Gets result of a completed job
   - FIFO processing order
   - Store jobs internally until processed
   - Each job has a unique `job_id` returned when added
   - Example usage provided
   - Output only Python code, no explanations

2.  **Identify Key Components:**
   - Need a queue structure for FIFO ordering (collections.deque or list)
   - Need storage for job data and results
   - Need a way to simulate/process jobs (the prompt says "until they are processed", but doesn't specify automatic processing. I'll assume a simple synchronous processing or a method to process them, but the example shows `# After processing...`. I should probably include a `process_next()` or similar method, or just process immediately? Wait, the prompt says "The queue should store jobs internally until they are processed". It doesn't explicitly require a processing method, but to make it functional, I'll add a `process()` method or simulate processing. Actually, I can just store jobs and results, and maybe provide a `process_next()` method that moves a job from queue to results. Or I can just implement the class with internal storage and a method to process jobs. Let's stick to the requirements strictly: they only ask for `add_job` and `get_result`. But how does it get processed? I'll add a `process_next()` method that simulates processing and stores the result, or I'll just assume synchronous processing for simplicity. Actually, the prompt says "The queue should store jobs internally until they are processed". I'll implement a simple synchronous processing or a background thread? No, keep it simple. I'll add a `process_next()` method that takes the next job, "processes" it (maybe just returns the data or a mock result), and stores it. Or I can just process immediately in `add_job`? But it says "store jobs internally until they are processed". I'll implement a queue and a results dict, and a `process_next()` method. Wait, the prompt doesn't ask for `process_next`, but it's implied. I'll just implement it simply.

   Let's re-read carefully: "Implement a basic job queue in Python. Requirements: 1. Create a `JobQueue` class with the following methods: `add_job`, `get_result`. 2. Jobs should be processed in FIFO order. 3. The queue should store jobs internally until they are processed. 4. Each job has a unique job_id that is returned when added."

   I think the simplest interpretation is that the class manages a queue and a results dictionary. I'll add a `process_next()` method to actually move jobs from the queue to results, simulating processing. Or maybe I should just process them in a separate thread? The prompt says "basic job queue", so I'll keep it single-threaded with a `process_next()` method, or maybe just process immediately but store in queue first? Actually, many basic queue implementations just have `add_job` and `get_result`, and maybe a `run()` or `process()` method. I'll add `process_next()` for completeness, but the prompt only explicitly requires `add_job` and `get_result`. I'll stick to just those two, but I need a way to process. I'll add a `process_next()` method that simulates processing and stores the result. Or I can just assume the user will call a process method. Actually, I can just implement it with a background thread using `concurrent.futures` or `threading`, but that might be overcomplicating. Let's keep it simple: a `process_next()` method that takes the next job, processes it (e.g., adds a "status": "completed" to the data), and stores it in results.

   Wait, the prompt says "Write only the Python code, no explanations." I'll just implement the class with `add_job`, `get_result`, and a `process_next` method. Or maybe I should just process jobs immediately but store them in a queue first? That doesn't make sense. I'll implement a simple synchronous queue with a `process_next` method. Actually, I can just make `add_job` return the job_id, store it in a deque, and `get_result` checks a results dict. I'll add a `process_next` method to fulfill "until they are processed".

   Let's think about what a "basic job queue" usually looks like in coding tests:
   ```python
   from collections import deque
   import threading

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

       def add_job(self, job_id: str, data: dict) -> str:
           with self.lock:
               self.queue.append({"job_id": job_id, "data": data})
           return job_id

       def process_next(self):
           with self.lock:
               if not self.queue:
                   return
               job = self.queue.popleft()
               # Simulate processing
               result = {**job["data"], "status": "completed"}
               self.results[job["job_id"]] = result
   ```
   But the prompt doesn't ask for `process_next`. Maybe it expects automatic processing? Or maybe it's just a data structure exercise. I'll stick to the exact requirements. I'll add a `process_next` method for functionality, but I'll make sure `add_job` and `get_result` are exactly as specified.

   Actually, I can just implement it without explicit processing method, but that contradicts "until they are processed". I'll add a simple `process` method. Or maybe the prompt implies that processing happens automatically in a separate thread? "basic job queue" often implies threading. But I'll keep it simple and synchronous with a `process_next` method, or just process immediately but store in queue? No.

   Let's re-read: "The queue should store jobs internally until they are processed". This implies there's a processing step. I'll add a `process_next()` method. It's standard.

   Wait, maybe I should just use `queue.Queue` from Python's standard library? That handles FIFO and threading automatically. But the prompt says "Implement a basic job queue", so probably expects manual implementation with `deque`.

   I'll implement it with `collections.deque` and a results dict. I'll add a `process_next` method. To be safe, I'll also make it thread-safe with a lock, though not strictly required.

   Actually, I can just implement it exactly as requested, and add a `process_next` method for completeness. The prompt says "Write only the Python code, no explanations."

   Let's draft:
   ```python
   from collections import deque
   import threading

   class JobQueue:
       def __init__(self):
           self._queue = deque()
           self._results = {}
           self._lock = threading.Lock()

       def add_job(self, job_id: str, data: dict) -> str:
           with self._lock:
               self._queue.append({"job_id": job_id, "data": data})
           return job_id

       def get_result(self, job_id: str) -> dict | None:
           with self._lock:
               return self._results.get(job_id)

       def process_next(self):
           with self._lock:
               if not self._queue:
                   return
               job = self._queue.popleft()
               # Simulate processing
               result = {**job["data"], "status": "completed"}
               self._results[job["job_id"]] = result
   ```

   But wait, the prompt says "Jobs should be processed in FIFO order". This is naturally handled by deque.
   Maybe I should make it automatically process in a background thread? The prompt doesn't specify. I'll stick to synchronous `process_next` as it's simpler and matches "basic".

   Actually, many simple queue implementations just have `add_job` and `get_result`, and maybe a `run` or `process` method. I'll keep it simple.

   Let's reconsider: maybe the prompt expects automatic processing? "The queue should store jobs internally until they are processed" could just mean the data structure holds them. I'll add a `process_next` method. It's fine.

   Wait, I can also just implement it without `process_next` and assume the user will call it, or I can make `add_job` immediately process but store in queue? That doesn't make sense.

   I'll stick with the deque approach. I'll also add type hints as requested.

   One thing: `dict | None` requires Python 3.10+. I'll use it as requested.

   Let's refine:
   ```python
   from collections import deque
   import threading

   class JobQueue:
       def __init__(self):
           self._queue = deque()
           self._results = {}
           self._lock = threading.Lock()

       def add_job(self, job_id: str, data: dict) -> str:
           with self._lock:
               self._queue.append({"job_id": job_id, "data": data})
           return job_id

       def get_result(self, job_id: str) -> dict | None:
           with self._lock:
               return self._results.get(job_id)

       def process_next(self):
           with self._lock:
               if not self._queue:
                   return
               job = self._queue.popleft()
               # Simulate job processing
               result = {**job["data"], "status": "completed"}
               self._results[job["job_id"]] = result
   ```

   Is there any issue with this? The prompt says "Write only the Python code, no explanations." I'll output exactly that.
   But maybe I should make it automatically process in a background thread to be more "queue-like"? The prompt says "basic job queue", so manual processing is fine. I'll keep it simple.

   Actually, I can make it even simpler without threading locks if not required, but it's good practice. I'll keep the lock.

   Wait, the prompt says "Jobs should be processed in FIFO order". This is naturally satisfied.
   I'll remove the lock to keep it minimal, as it's a basic implementation. Or keep it for correctness. I'll keep it.

   Let's check the exact method signatures:
   `add_job(job_id: str, data: dict) -> str`
   `get_result(job_id: str) -> dict | None`

   I'll match exactly.

   One more thing: maybe the processing should be automatic? I'll add a `process_all()` or just `process_next()`. I'll stick with `process_next()`.

   Actually, I can just implement it without any processing method, and assume the user will handle processing, but the requirement says "until they are processed". I'll add `process_next()`.

   I think it's fine. I'll output the code.

   Wait, maybe I should use `queue.Queue`? The prompt says "Implement a basic job queue", which usually means from scratch. I'll use `deque`.

   Final code:
   ```python
   from collections import deque
   import threading

   class JobQueue:
       def __init__(self):
           self._queue = deque()
           self._results = {}
           self._lock = threading.Lock()

       def add_job(self, job_id: str, data: dict) -> str:
           with self._lock:
               self._queue.append({"job_id": job_id, "data": data})
           return job_id

       def get_result(self, job_id: str) -> dict | None:
           with self._lock:
               return self._results.get(job_id)

       def process_next(self):
           with self._lock:
               if not self._queue:
                   return
               job = self._queue.popleft()
               result = {**job["data"], "status": "completed"}
               self._results[job["job_id"]] = result
   ```

   This looks solid. I'll output it.
   One minor thing: `dict | None` syntax is Python 3.10+. It's fine.
   I'll make sure it matches the prompt exactly.
   The prompt says "Write only the Python code, no explanations."
   I'll output just the code block.
   Done. 
   Self-Correction/Refinement during thought: 
   Should I include automatic processing in a background thread? The prompt doesn't specify, so manual `process_next` is safer and simpler. I'll stick with it.
   Also, I can make `process_next` return the result or just store it. Storing it is fine.
   I'll keep it as is.
   Output matches requirements.✅
   Proceeds. 
   Output generation. 
   [Code matches the refined version]✅
   Note: I'll remove the lock if it's considered overcomplicating, but it's good practice. I'll keep it. Actually, for a "basic" queue, locks might be unnecessary. I'll remove them to keep it minimal and focused on the requirements. The prompt doesn't mention concurrency. I'll simplify.

   Simplified version:
   ```python
   from collections import deque

   class JobQueue:
       def __init__(self):
           self._queue = deque()
           self._results = {}

       def add_job(self, job_id: str, data: dict) -> str:
           self._queue.append({"job_id": job_id, "data": data})
           return job_id

       def get_result(self, job_id: str) -> dict | None:
           return self._results.get(job_id)

       def process_next(self):
           if not self._queue:
               return
           job = self._queue.popleft()
           result = {**job["data"], "status": "completed"}
           self._results[job["job_id"]] = result
   ```
   This is cleaner and meets all requirements. I'll output this.✅
   Final check of the prompt: "Jobs should be processed in FIFO order" - deque ensures this. "The queue should store jobs internally until they are processed" - `_queue` stores them, `process_next` moves to `_results`. "Each job has a unique job_id that is returned when added" - `add_job` returns `job_id`. All good.
   Output matches.✅
   Proceeds. 
   [Output Generation] -> *Code only*
   ```python
   from collections import deque

   class JobQueue:
       def __init__(self):
           self._queue = deque()
           self._results = {}

       def add_job(self, job_id: str, data: dict) -> str:
           self._queue.append({"job_id": job_id, "data": data})
           return job_id

       def get_result(self, job_id: str) -> dict | None:
           return self._results.get(job_id)

       def process_next(self):
           if not self._queue:
               return
           job = self._queue.popleft()
           result = {**job["data"], "status": "completed"}
           self._results[job["job_id"]] = result
   ```
   This is ready.✅
   Note: I'll make sure the formatting is exactly as requested. No extra text.
   Done. 
   Output matches response. 
   [Proceeds]

</reasoning_content>

<content>
```python
from collections import deque

class JobQueue:
    def __init__(self):
        self._queue = deque()
        self._results = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append({"job_id": job_id, "data": data})
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        return self._results.get(job_id)

    def process_next(self):
        if not self._queue:
            return
        job = self._queue.popleft()
        result = {**job["data"], "status": "completed"}
        self._results[job["job_id"]] = result
```
</content>