<reasoning_content>
Here's a thinking process:

1.  **Understand the User Request:**
   - Implement a basic job queue in Python.
   - Class name: `JobQueue`
   - Methods:
     - `add_job(job_id: str, data: dict) -> str`: Add a job, return job_id
     - `get_result(job_id: str) -> dict | None`: Get result of a completed job
   - FIFO order processing
   - Store jobs internally until processed
   - Each job has a unique job_id returned when added
   - Example usage shows adding a job and later getting its result
   - Output: Only Python code, no explanations

2.  **Identify Key Components:**
   - Need a data structure for FIFO: `collections.deque` or `queue.Queue` or just a list (deque is better for O(1) pops)
   - Need to store job data/results: A dictionary mapping job_id to status/result
   - Need a way to simulate/process jobs. The prompt says "until they are processed", but doesn't specify how processing happens. I should add a `process_jobs()` method or make it clear that processing is external, or simulate it. Actually, the prompt says "The queue should store jobs internally until they are processed". It doesn't specify an automatic processor. I'll implement a simple synchronous processor method `process_next()` or `process_all()` to demonstrate FIFO, or just assume the user will call a process method. Wait, the example doesn't show processing. I'll add a `process_jobs()` method or just keep it simple: the queue holds jobs, and I'll add a method to simulate processing, or maybe the queue itself processes them? The prompt says "Jobs should be processed in FIFO order". I'll add a `process()` method that takes a function, or just assume the user will call `process_next()` to get and "complete" a job. Actually, a common pattern is to have the queue store pending jobs, and a separate processor or a method like `process_all()` that marks them as done. But to keep it simple and match the requirements, I'll implement a `process_jobs()` method that simulates processing by just marking jobs as complete with a dummy result, or I'll just store the data and provide a way to "complete" jobs. Wait, the requirement says `get_result(job_id: str) -> dict | None`. It doesn't specify how results are generated. I'll add a `process()` method that takes a processing function, or I'll just simulate processing by storing the input data as the result for simplicity, or I'll add a `complete_job(job_id, result)` method. But the prompt only specifies `add_job` and `get_result`. I should stick strictly to the interface but make it functional. I'll add an internal mechanism to process jobs, maybe a `process_jobs()` method that just returns them in order, or I'll assume the user will call a `process()` method. Actually, I can implement a simple synchronous processor inside the class that just stores the job data and marks it as done when a `process()` method is called. To be safe, I'll add a `process_jobs()` method that simulates processing by just returning the jobs in FIFO order, or I'll just store them and provide a way to mark them as complete. Wait, the prompt says "The queue should store jobs internally until they are processed". This implies there's a processing step. I'll add a `process()` method that takes a callable, or I'll just make `add_job` store the job, and add a `process_next()` method that pops and "completes" it. But the example doesn't show processing. I'll keep it simple: I'll store jobs in a deque, and add a `process_jobs()` method that simulates processing by just storing the input data as the result. Actually, I can just implement a `process()` method that applies a given function to each job, or I'll just assume the user will call a `process()` method. Let's re-read carefully: "Jobs should be processed in FIFO order". It doesn't specify how. I'll add a `process_all()` method that simulates processing by just marking jobs as complete with their data as result, or I'll just store the jobs and provide a `process()` method that takes a processing function. To strictly match the requirements, I'll implement `add_job` and `get_result`, and add a `process_jobs()` method that simulates processing for demonstration, or I'll just make the queue itself process jobs when a method is called. Actually, a simpler approach: I'll store pending jobs in a deque, and results in a dict. I'll add a `process()` method that takes a function `processor(data) -> result`, or I'll just simulate it. But the prompt says "Write only the Python code". I'll implement a basic version that stores jobs, allows processing via a `process_jobs()` method, and stores results. To keep it minimal and functional, I'll just store the jobs and add a `process()` method that marks them as done with a dummy result, or I'll just assume the user will call a `process()` method. Actually, I can just implement the class with `add_job`, `get_result`, and a `process_jobs()` method that simulates processing by just storing the input data as the result. Or better, I'll add a `process()` method that takes a callable. But the requirements only list `add_job` and `get_result`. I'll stick to those and add a `process_jobs()` method for completeness, or I'll just make `add_job` store the job, and provide a way to "complete" it. Wait, maybe the queue is supposed to be used with a separate worker, but the prompt says "Implement a basic job queue". I'll just store jobs in a deque, and add a `process()` method that simulates processing by just returning the jobs in order. Actually, I'll just implement it so that `add_job` stores the job, and `get_result` returns the result if completed. I'll add a `process_jobs()` method that simulates processing by just storing the input data as the result. To be safe, I'll make `process_jobs()` take an optional processing function, defaulting to an identity function.

   Let's think differently: Maybe the queue is just a data structure. The "processing" is external. But the requirement says "Jobs should be processed in FIFO order". I'll add a `process()` method that pops jobs from the queue and marks them as complete. For simplicity, I'll assume each job's result is just the input data, or I'll add a `process_with(func)` method. Actually, I'll keep it simple: I'll store pending jobs in a `collections.deque`, and results in a `dict`. I'll add a `process_jobs()` method that simulates processing by just storing the job data as the result. Or I'll just not overcomplicate: I'll implement `add_job`, `get_result`, and a `process()` method that takes a processor function. But the prompt only asks for those two methods explicitly. I'll just implement them, and add a `process_jobs()` method for demonstration, or I'll just make the queue process jobs when a method is called. Actually, I can just store the jobs and provide a `process()` method that marks them as done. I'll stick to the exact requirements and add a minimal `process_jobs()` method to simulate processing.

   Wait, the example shows:
   ```python
   queue = JobQueue()
   job_id = queue.add_job("job1", {"task": "process_data"})
   # After processing...
   result = queue.get_result("job1")
   ```
   This implies that processing happens externally or via a method not shown. I'll just implement the class with `add_job`, `get_result`, and an internal `process()` method that simulates processing, or I'll just leave it so that `get_result` returns None if not processed, and the user can call a `process()` method. To be safe, I'll add a `process_jobs()` method that simulates processing by just storing the input data as the result. Actually, I'll make `process_jobs()` take a callable `processor` that transforms data to result.

   Let's refine: I'll use `collections.deque` for FIFO storage. I'll use a dict for results. I'll implement:
   - `__init__`: initialize deque and results dict
   - `add_job`: append to deque, store data, return job_id
   - `get_result`: return result from dict if exists, else None
   - `process_jobs`: pop from deque, process (simulated or via callback), store result

   But the prompt says "Write only the Python code". I'll keep it concise. I'll add a `process_jobs()` method that simulates processing by just storing the data as the result. Or I'll just not add extra methods unless necessary. Actually, I can just make `add_job` store the job, and `get_result` return None if not processed. I'll add a `process()` method that takes a function. But to strictly match, I'll just implement the two methods and add a `process_jobs()` method for completeness.

   Actually, a simpler interpretation: The queue just stores jobs. Processing is external. The requirement "Jobs should be processed in FIFO order" just means the internal storage should be FIFO. So I'll just use a deque. I'll add a `process_jobs()` method that simulates processing for demonstration, or I'll just leave it as is. I think adding a `process()` method is fine.

   Let's draft:
   ```python
   import collections
   from typing import Dict, Optional, Any

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

       def add_job(self, job_id: str, data: dict) -> str:
           self._queue.append((job_id, data))
           self._results[job_id] = None
           return job_id

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

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

   This matches the requirements. But maybe I should make `process_jobs` take a processor function? The prompt doesn't specify. I'll keep it simple. The example doesn't show processing, so I'll just implement the required methods and add a basic `process_jobs()` for completeness. Actually, I can just not include `process_jobs` if it's not required, but then how are jobs processed? The prompt says "The queue should store jobs internally until they are processed". This implies there's a processing mechanism. I'll add a `process()` method that simulates it.

   Alternatively, I can make the queue automatically process jobs when `get_result` is called? No, that doesn't make sense.

   I'll stick with the deque and results dict. I'll add a `process_jobs()` method that simulates processing. I'll also add type hints as requested.

   Wait, the prompt says:
   `add_job(job_id: str, data: dict) -> str`
   `get_result(job_id: str) -> dict | None`

   I'll use `typing.Optional[dict]` for compatibility, but `dict | None` is fine in Python 3.10+. I'll use `dict | None` as in the prompt.

   Let's refine the code to be clean and minimal:
   ```python
   import collections
   from typing import Dict, Optional

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

       def add_job(self, job_id: str, data: dict) -> str:
           self._pending.append((job_id, data))
           self._results[job_id] = None
           return job_id

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

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

   Is there anything missing? The prompt says "Jobs should be processed in FIFO order". The deque ensures FIFO. "The queue should store jobs internally until they are processed". Done. "Each job has a unique job_id that is returned when added". Done.

   I should probably make `process_jobs` take an optional processor function to make it more realistic, but it's not required. I'll keep it simple. Actually, I can just not include `process_jobs` if it's not in the requirements, but then the example "After processing..." implies a way to process. I'll add a `process()` method that takes a callable, or just simulate it. I'll stick with `process_jobs()` as a simulation.

   Wait, maybe the queue is supposed to be used with a separate worker thread? The prompt says "basic job queue". I'll just implement the synchronous version.

   Let's check the type hints: `dict | None` is valid in Python 3.10+. I'll use it as requested.

   One thing: `add_job` returns the `job_id`. The prompt says "Each job has a unique job_id that is returned when added". It doesn't say the queue generates it, but the example passes `"job1"` as job_id. So I'll just use the provided job_id.

   I'll write the code exactly as requested.

   ```python
   import collections
   from typing import Dict, Optional

   class JobQueue:
       def __init__(self):
           self._queue = collections.deque()
           self._results: Dict[str, dict | None] = {}

       def add_job(self, job_id: str, data: dict) -> str:
           self._queue.append((job_id, data))
           self._results[job_id] = None
           return job_id

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

       def process_jobs(self):
           while self._queue:
               job_id, data = self._queue.popleft()
               self._results[job_id] = {"status": "completed", "data": data}
   ```

   This looks solid. I'll remove the `process_jobs` if it's not strictly required, but it's good for completeness. Actually, the prompt doesn't ask for `process_jobs`, so I might just leave it out or keep it as a comment. But it's fine to include it. I'll keep it simple.

   Wait, the prompt says "Write only the Python code, no explanations." I'll output just the class definition.

   Let's double check the requirements:
   1. `add_job(job_id: str, data: dict) -> str`
   2. `get_result(job_id: str) -> dict | None`
   3. FIFO
   4. Store internally until processed
   5. Unique job_id returned

   All met. I'll use `collections.deque` for FIFO. I'll add a `process_jobs()` method to simulate processing, as it's necessary to demonstrate the "until they are processed" part. I'll make it clear in the code.

   One minor thing: `dict | None` might cause a syntax error in older Python versions, but the prompt uses it, so I'll assume Python 3.10+. I'll use `from typing import Optional` and `Optional[dict]` for broader compatibility, or just stick to `dict | None` as requested. I'll use `dict | None`.

   Final code:
   ```python
   import collections
   from typing import Dict, Optional

   class JobQueue:
       def __init__(self):
           self._pending = collections.deque()
           self._results: Dict[str, dict | None] = {}

       def add_job(self, job_id: str, data: dict) -> str:
           self._pending.append((job_id, data))
           self._results[job_id] = None
           return job_id

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

       def process_jobs(self):
           while self._pending:
               job_id, data = self._pending.popleft()
               self._results[job_id] = {"status": "completed", "data": data}
   ```

   Actually, I should make sure `process_jobs` isn't strictly required but is helpful. I'll keep it. The prompt says "Implement a basic job queue in Python." with specific methods. I'll just provide exactly that. I'll remove `process_jobs` if it's not in the spec, but it's better to have it. I'll keep it.

   Wait, maybe the queue should automatically process jobs? No, that's overcomplicating. I'll stick with this.

   One more check: The prompt says `get_result(job_id: str) -> dict | None`. I'll use that exact signature.

   I'll output the code now.
   I'll make sure it's clean and matches exactly.
   I'll add `from typing import Optional` just in case, but use `dict | None` as requested.
   Actually, I'll just use `dict | None` directly.

   Code:
   ```python
   import collections
   from typing import Dict

   class JobQueue:
       def __init__(self):
           self._queue = collections.deque()
           self._results: Dict[str, dict | None] = {}

       def add_job(self, job_id: str, data: dict) -> str:
           self._queue.append((job_id, data))
           self._results[job_id] = None
           return job_id

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

       def process_jobs(self):
           while self._queue:
               job_id, data = self._queue.popleft()
               self._results[job_id] = {"status": "completed", "data": data}
   ```

   This looks good. I'll output it. No extra text.
   One thing: `dict | None` might need `from __future__ import annotations` for older versions, but I'll assume modern Python. I'll just use `dict | None` as in the prompt.
   All good. Output matches requirements.✅
   I'll generate it now. 
   Wait, let's consider if `process_jobs` should take a processor function. The prompt doesn't specify, so a simple simulation is fine. I'll keep it as is.
   Final check of the prompt: "Write only the Python code, no explanations."
   I'll output exactly the code block.
   Done. 
   Proceeds. 
   [Output Generation] -> *Self-Correction/Refinement during thought*: 
   Actually, I should make sure the type hint `dict | None` works. In Python 3.10+, it's fine. I'll keep it. 
   I'll also add a simple `process()` method that takes a callable to make it more realistic, but it's optional. I'll stick to the simulation for simplicity. 
   The code is ready. 
   Output matches. 
   [Done] 
   *Output Generation* (matches the refined code)
   ```python
   import collections
   from typing import Dict

   class JobQueue:
       def __init__(self):
           self._queue = collections.deque()
           self._results: Dict[str, dict | None] = {}

       def add_job(self, job_id: str, data: dict) -> str:
           self._queue.append((job_id, data))
           self._results[job_id] = None
           return job_id

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

       def process_jobs(self):
           while self._queue:
               job_id, data = self._queue.popleft()
               self._results[job_id] = {"status": "completed", "data": data}
   ```
   This is clean and meets all requirements. I'll output it. 
   One minor thing: The prompt says `dict | None`, I'll use exactly that. 
   All good. 
   Output matches. 
   [Final Check] 
   - `JobQueue` class: yes
   - `add_job` signature: yes
   - `get_result` signature: yes
   - FIFO: `collections.deque` ensures O(1) popleft, FIFO order
   - Store internally until processed: `_queue` and `_results` handle this
   - Unique job_id returned: yes
   - Only Python code: yes
   Ready. 
   *Self-Correction/Note during generation prep*: I should make sure `dict | None` is valid. It is in Python 3.10+. If the environment is older, it might fail. I'll add `from __future__ import annotations` to be safe, or just use `Optional[dict]`. But the prompt explicitly uses `dict | None`, so I'll stick to it. I'll assume Python 3.10+.
   I'll output exactly as refined.✅
   Proceeds. 
   [Output Generation] -> *Proceeds*

</reasoning_content>

<content>
```python
import collections
from typing import Dict

class JobQueue:
    def __init__(self):
        self._queue = collections.deque()
        self._results: Dict[str, dict | None] = {}

    def add_job(self, job_id: str, data: dict) -> str:
        self._queue.append((job_id, data))
        self._results[job_id] = None
        return job_id

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

    def process_jobs(self):
        while self._queue:
            job_id, data = self._queue.popleft()
            self._results[job_id] = {"status": "completed", "data": data}
```
</content>