<reasoning_content>
Here's a thinking process:

1.  **Understand User Requirements:**
   - Create a `JobQueue` class
   - Methods:
     - `add_job(job_id: str, data: dict) -> str`: Add job, return job_id
     - `get_result(job_id: str) -> dict | None`: Get result of 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 data structure for FIFO (collections.deque is ideal)
   - Need a storage for results (dictionary mapping job_id to result)
   - Need a way to "process" jobs. The prompt says "Jobs should be processed in FIFO order" and "The queue should store jobs internally until they are processed". It doesn't specify how processing happens, but typically a job queue has a method to process jobs or processes them in the background. Since it's a "basic job queue", I'll add a `process_jobs()` method or process them synchronously when requested, or maybe just simulate processing. Wait, the prompt says "After processing..." in the example, implying processing might happen externally or via a method. I'll implement a simple `process_next()` or `process_all()` method, or maybe just a background thread? The prompt doesn't strictly require threading, but says "Jobs should be processed in FIFO order". I'll add a `process_jobs()` method that simulates processing and stores results. Alternatively, I can make it process jobs automatically when `add_job` is called? No, that defeats the queue purpose. I'll add a `process_jobs()` method that processes all pending jobs in FIFO order.
   - Actually, the prompt says "The queue should store jobs internally until they are processed". It doesn't specify how processing is triggered. I'll implement a simple synchronous processing method, or maybe just a `process()` method. To keep it simple and aligned with typical basic queue implementations, I'll add a `process_jobs()` method that iterates through the queue, simulates processing (just stores the input data as result for simplicity, or applies a dummy function), and moves them to a results dict.
   - Wait, maybe the user expects a simple queue where jobs are just stored, and processing is simulated or handled by a separate method. I'll implement a `process_jobs()` method that processes all queued jobs in FIFO order. For simulation, I'll just convert the input data to a result (e.g., `{"status": "completed", "input": data}`).
   - Let's re-read carefully: "Jobs should be processed in FIFO (First-In-First-Out) order", "The queue should store jobs internally until they are processed". This implies there's a processing step. I'll add a `process_jobs()` method.
   - Actually, many simple job queue implementations just use a deque for pending jobs and a dict for results. I'll stick to that.
   - I should also handle the case where `get_result` is called before processing (returns None).
   - Type hints: `dict | None` is used, so Python 3.10+ syntax is fine.

3.  **Design the Class:**
   ```python
   from collections import deque
   from typing import Dict, Optional

   class JobQueue:
       def __init__(self):
           self._queue: deque = deque()
           self._results: Dict[str, dict] = {}

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

       def process_jobs(self):
           while self._queue:
               job = self._queue.popleft()
               job_id = job["job_id"]
               # Simulate processing
               self._results[job_id] = {"status": "completed", "input": job["data"]}

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

   Wait, the prompt doesn't explicitly ask for a `process_jobs` method, but says "Jobs should be processed in FIFO order". Maybe it expects processing to happen automatically? Or maybe it's just a conceptual requirement. I'll add a `process_jobs()` method to fulfill the "processed" requirement. Alternatively, I could use a background thread, but that's overcomplicating a "basic" queue. I'll stick with an explicit `process_jobs()` method, or maybe just process them on demand? Actually, many simple implementations just have `add_job` and `get_result`, and the "processing" is abstract. But the prompt says "After processing... result = queue.get_result(...)". This implies processing happens somewhere. I'll add a `process_jobs()` method.

   Let's reconsider: Maybe the queue should process jobs automatically when `add_job` is called? No, that's not a queue. Maybe it should have a `process_next()` or `run()` method. I'll add `process_jobs()` that processes all pending jobs.

   Actually, I can make it simpler: just store jobs in a deque, and when `get_result` is called, if it's not processed, return None. The processing step can be a separate method. I'll name it `process_jobs()`.

   Wait, the prompt says "Implement a basic job queue in Python." and lists requirements. It doesn't strictly require a processing method, but says "Jobs should be processed in FIFO order". I'll implement a `process_jobs()` method that processes all queued jobs. To make it more realistic, I'll just simulate processing by storing the data with a "processed" flag.

   Let's check if there's a standard way. Often, basic job queues in interviews just use `deque` for pending and `dict` for results, with a `process()` method. I'll go with that.

   Actually, I can make it even simpler: just use `collections.deque` for the queue, and a dict for results. I'll add a `process_jobs()` method.

   Code structure:
   ```python
   from collections import deque
   from typing import Dict, Optional

   class JobQueue:
       def __init__(self):
           self._queue: deque = deque()
           self._results: Dict[str, dict] = {}

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

       def process_jobs(self) -> None:
           while self._queue:
               job = self._queue.popleft()
               job_id = job["job_id"]
               # Simulate job processing
               self._results[job_id] = {"status": "completed", "input": job["data"]}

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

   Is there any issue with this? The prompt says "Jobs should be processed in FIFO order". My `process_jobs` does exactly that. The example shows:
   ```python
   queue = JobQueue()
   job_id = queue.add_job("job1", {"task": "process_data"})
   # After processing...
   result = queue.get_result("job1")
   ```
   This implies processing happens between add and get. My method fits.

   Could I make it process automatically in a background thread? The prompt says "basic", so explicit processing is fine. I'll stick with explicit.

   Wait, maybe the user expects the queue to process jobs automatically when `add_job` is called? No, that defeats FIFO queue purpose. Maybe they want a `process_next()` method? I'll just keep `process_jobs()`.

   Actually, I can make it even more aligned with the prompt by not requiring an explicit method, but the prompt says "The queue should store jobs internally until they are processed". This implies processing is a separate step. I'll keep `process_jobs()`.

   Let's refine the code to be clean and match type hints exactly:
   ```python
   from collections import deque

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

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

       def process_jobs(self) -> None:
           while self._queue:
               job = self._queue.popleft()
               job_id = job["job_id"]
               # Simulate processing
               self._results[job_id] = {"status": "completed", "input": job["data"]}

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

   Wait, should I include type hints for `_queue` and `_results`? Not strictly necessary but good practice. I'll keep it simple.

   One thing: The prompt says "Write only the Python code, no explanations." I'll output exactly that.

   Let's double check the requirements:
   1. `add_job(job_id: str, data: dict) -> str`: Add a job to the queue, return job_id -> ✅
   2. `get_result(job_id: str) -> dict | None`: Get the result of a completed job -> ✅
   3. Jobs should be processed in FIFO order -> ✅ (deque popleft)
   4. The queue should store jobs internally until they are processed -> ✅
   5. Each job has a unique job_id that is returned when added -> ✅

   The example doesn't show calling `process_jobs()`, but says "# After processing...". I'll add a `process_jobs()` method. Alternatively, maybe they expect processing to happen automatically? If I want to be safe, I could make it process automatically in a background thread, but that's complex. I'll stick with explicit `process_jobs()`. Actually, many basic queue implementations just have `add` and `get`, and the "processing" is abstract. I'll add `process_jobs()` as it's standard.

   Wait, maybe I should just implement it without `process_jobs()` and assume the user will call it, or maybe the queue processes jobs automatically when `get_result` is called? No.

   I'll keep `process_jobs()` but name it clearly. Actually, I can just make the class have a `process_jobs()` method. It's fine.

   Let's consider if the prompt implies a simpler structure: maybe just a deque and a results dict, and the processing is simulated by a method. I'll stick with that.

   One minor adjustment: I'll make sure the type hints match exactly. `dict | None` is Python 3.10+. I'll use that.

   Final code:
   ```python
   from collections import deque

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

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

       def process_jobs(self) -> None:
           while self._queue:
               job = self._queue.popleft()
               job_id = job["job_id"]
               self._results[job_id] = {"status": "completed", "input": job["data"]}

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

   Wait, should I handle duplicate job_ids? The prompt says "Each job has a unique job_id that is returned when added". It doesn't say to enforce uniqueness, just that it's returned. I'll assume the caller provides unique IDs.

   Is there any chance they want automatic processing via a thread? "basic job queue" usually implies synchronous. I'll stick with synchronous.

   I'll output exactly the code. No extra text.
   One thing: I'll add type hints to `_queue` and `_results` for completeness, but it's fine either way.
   I'll make sure it matches the prompt exactly.

   Let's verify the example usage works with my code:
   ```python
   queue = JobQueue()
   job_id = queue.add_job("job1", {"task": "process_data"})
   queue.process_jobs()  # After processing...
   result = queue.get_result("job1")
   ```
   This matches the comment "# After processing...".

   I think it's good. I'll output the code now.
   One minor thing: I'll use `typing` imports if needed, but `dict | None` is fine in 3.10+. I'll just use standard syntax.

   Final check of the prompt: "Write only the Python code, no explanations."
   I will output exactly the class definition.
   Ready. 
   Output matches the refined code.✅
   Proceeds. 
   [Output Generation] -> *Self-Correction/Refinement during thought*: 
   Actually, maybe I should make `process_jobs` not required, but the prompt says "Jobs should be processed in FIFO order". I'll keep it. It's standard.
   I'll also add a docstring or just keep it minimal as requested.
   The code is solid.
   Output matches. 
   Proceeds. 
   [Output] -> *Code block only*
   ```python
   from collections import deque

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

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

       def process_jobs(self) -> None:
           while self._queue:
               job = self._queue.popleft()
               job_id = job["job_id"]
               self._results[job_id] = {"status": "completed", "input": job["data"]}

       def get_result(self, job_id: str) -> dict | None:
           return self._results.get(job_id)
   ```
   This meets all requirements. I'll output it. 
   One thing: The prompt says "Write only the Python code, no explanations." I will strictly follow that.
   All good. 
   Output matches. 
   [Done] 
   *Self-Correction/Note during generation prep*: 
   I should make sure the method names and signatures exactly match the prompt. 
   `add_job(job_id: str, data: dict) -> str` ✅
   `get_result(job_id: str) -> dict | None` ✅
   FIFO ✅
   Store internally ✅
   Unique job_id returned ✅
   All good. 
   Output matches. 
   Proceeds. 
   [Final Output Generation] -> *Code only*
   (Note: I'll include `from collections import deque` at the top)
   Done. 
   [Output] -> *Proceeds*

</reasoning_content>

<content>
```python
from collections import deque

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

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

    def process_jobs(self) -> None:
        while self._queue:
            job = self._queue.popleft()
            job_id = job["job_id"]
            self._results[job_id] = {"status": "completed", "input": job["data"]}

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