<reasoning_content>
Thinking Process:

1.  **Analyze the Request:**
    *   Goal: Implement a basic job queue in Python.
    *   Class: `JobQueue`
    *   Methods:
        *   `add_job(job_id: str, data: dict) -> str`: Add job, return `job_id`.
        *   `get_result(job_id: str) -> dict | None`: Get result.
    *   Behavior:
        *   FIFO processing.
        *   Store jobs internally until processed.
        *   Unique `job_id` (though the example shows passing `job_id` in, the requirement says "return job_id", and the signature says `job_id: str`. Usually, job queues generate IDs, but the example explicitly passes `"job1"`. I should follow the signature `add_job(job_id: str, data: dict) -> str`. It takes a job_id, stores it, returns it).
    *   Output: Only Python code, no explanations.

2.  **Determine Internal Structure:**
    *   Need a way to store jobs for processing. A `deque` is good for FIFO.
    *   Need a way to store results for retrieval. A dictionary mapping `job_id` to result is suitable.
    *   Need a mechanism to "process" jobs. Since this is a basic implementation, I need a way to trigger processing or simulate it. The prompt implies the queue *stores* jobs until processed. It doesn't explicitly ask for a worker thread or loop, but usually, a job queue implies some mechanism to move from "pending" to "completed".
    *   However, looking at the requirements strictly:
        1.  `add_job` adds to queue.
        2.  `get_result` gets result.
        3.  Jobs processed in FIFO.
        4.  Store internally until processed.
    *   To make `get_result` work, jobs must be processed somewhere. A simple way to implement this without external workers is to provide a `process()` method or assume the user calls a processing method. But the requirements only list `add_job` and `get_result`.
    *   If I only have `add_job` and `get_result`, how does the job get processed?
        *   Option A: `get_result` triggers processing if not done.
        *   Option B: Add a `process()` method implicitly required to make the system work, even if not explicitly listed as a *method* in the class definition section (though usually "Implement a class with methods..." implies those are the interface).
        *   Option C: The prompt asks for a "basic job queue". In many contexts, this implies a simulation where I manually process it or the queue handles it.
        *   Let's look at the example:
            ```python
            queue = JobQueue()
            job_id = queue.add_job("job1", {"task": "process_data"})
            # After processing...
            result = queue.get_result("job1")
            ```
            The comment "# After processing..." implies processing happens externally or via a method not explicitly named in the summary but necessary for the logic.
        *   To make the code functional based on the provided signature, I should probably add a `process()` or `_process_jobs()` method to actually move items from the queue to the results store, otherwise `get_result` will always return `None` unless I simulate processing inside `get_result` (which might be inefficient or confusing).
        *   However, strict adherence to "Create a `JobQueue` class with the following methods" suggests I should stick to those two methods if possible, or add helper methods.
        *   Let's check the constraint: "Write only the Python code".
        *   If I only implement `add_job` and `get_result`, `get_result` needs to know the result. The result isn't defined in `add_job`. Usually, a job implies a task function. But here `data` is just a dict.
        *   Let's assume a simple simulation: `add_job` stores the job. A `process` method (or similar) moves it to "completed". Since the prompt asks for *specific* methods, I will add a `process` method (or `run`) to make it work, or I can process inside `get_result`.
        *   Actually, usually "Job Queue" implies an asynchronous system. But for a basic implementation without threading, I need a way to execute the logic.
        *   Let's add a `process()` method to clear the queue and generate dummy results, or simply store the data and return it as result.
        *   Wait, the prompt says "Create a `JobQueue` class with the following methods: `add_job`, `get_result`". It doesn't explicitly forbid other methods, but it highlights these.
        *   To ensure `get_result` returns something meaningful, I need to simulate processing.
        *   Let's implement a `process` method to handle the FIFO execution.
        *   Wait, if I strictly follow "with the following methods", I might need to put processing logic inside `get_result` or assume the user calls a `process` method. Given the comment "# After processing...", a `process` method is the most logical addition to make the queue functional. I will include it.
        *   Actually, looking at the example: `job_id = queue.add_job(...)`. `get_result` retrieves.
        *   I will implement a `process` method to simulate the worker consuming the queue, as `get_result` alone cannot generate a result without knowing what the job did.
        *   Wait, maybe I should just store the data and return the data as the result? Or store a dummy result.
        *   Let's create a `JobQueue` class.
        *   Internal storage: `collections.deque` for queue, `dict` for results.
        *   `add_job`: append to deque, store in results dict (pending state).
        *   `process`: iterate through deque, mark as done, store result.
        *   `get_result`: return from results dict.

    *   Refined Plan:
        1.  Import `deque` from `collections`.
        2.  Class `JobQueue`.
        3.  `__init__`: init `deque` and `results` dict.
        4.  `add_job`: validate ID, append to deque, store in results with status 'pending'. Return ID.
        5.  `process`: iterate deque, pop left, compute dummy result (or just store data), mark 'completed'.
        6.  `get_result`: return result if 'completed', else None.
        *   Wait, the requirement says "with the following methods: add_job, get_result". It doesn't list `process`. If I add `process`, is it okay? Yes, usually helper methods are allowed to make the required ones work.
        *   However, to be safest regarding the "with the following methods" constraint, I could make `get_result` trigger a process if I assume single-threaded execution. But that's complex.
        *   Let's look at the example again.
            ```python
            job_id = queue.add_job("job1", {"task": "process_data"})
            # After processing...
            result = queue.get_result("job1")
            ```
            This implies the processing happens *between* add and get. If I don't provide a `process` method, the user has to write the logic.
            I will add a `process` method to the class to make it functional, as a job queue is useless without a mechanism to move items from queue to result.
        *   Actually, to be strictly compliant with "Create a `JobQueue` class with the following methods", I should prioritize those two. I can add `process` as a private or public method. Let's make it public to make the example work.
        *   Wait, looking at the prompt "Implement a basic job queue... Create a JobQueue class with the following methods...". It lists specific methods. I should probably stick to those or ensure the code works.
        *   If I don't add `process`, how does the job get done?
        *   Maybe the "job" is just data storage? No, "processed".
        *   I'll add a `process` method to simulate the worker. It's necessary for the logic to hold.

    *   Wait, I can interpret `get_result` as the trigger.
    *   Or I can just implement a `process` method. Most implementations of this prompt type expect a `process` or `run` method. I will include `process` to ensure the FIFO logic is demonstrated.
    *   Wait, strict reading: "with the following methods: [list]". It might imply *only* these. But a queue needs a way to execute.
    *   Let's check the example usage again. It doesn't show the call to process.
    *   I will add a `process()` method to the class definition to ensure the example logic (implied) works, or I will assume the user calls `process` before `get_result`.
    *   Better yet, I'll implement `process` as a method of the class so the example makes sense.

    *   Wait, looking at the prompt again: "Implement a basic job queue... Create a JobQueue class with the following methods...".
    *   I will provide the class with `add_job`, `get_result`, and `process` (to make it work).
    *   Wait, I should check if I can do it without `process`.
    *   If I put processing logic inside `get_result`, it processes one job per call? Or all?
    *   Let's create `process` method. It clarifies the FIFO aspect.

    *   Wait, I need to make sure I don't add too much extra.
    *   Let's stick to the required methods primarily.
    *   I will add a `process` method because without it, the queue is just a storage.
    *   Actually, I'll implement the logic such that `add_job` returns the ID, and `get_result` retrieves it. I need to store the result somewhere.
    *   Let's define a simple logic:
        1.  Store jobs in a list/deque.
        2.  Store results in a dict.
        3.  When `process` is called (I'll add it), jobs are moved from queue to results.
        4.  Wait, if the prompt says "with the following methods", adding `process` might be seen as violating the list.
        5.  But if I don't add `process`, the example `# After processing...` implies an external process.
        6.  I'll add `process` as a method to the class to make it a complete implementation.

    *   Wait, I'll check the constraint "Write only the Python code".
    *   Okay, Code structure:
        ```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, data))
                self.results[job_id] = None
                return job_id

            def process(self):
                while self.queue:
                    job_id, data = self.queue.popleft()
                    self.results[job_id] = {"status": "completed", "data": data}

            def get_result(self, job_id: str) -> dict | None:
                return self.results.get(job_id)
        ```
    *   Wait, the prompt says "with the following methods: add_job, get_result". It does not explicitly forbid others. However, to be safe and clean, I will include `process` because a queue needs processing.
    *   Actually, I can simulate processing inside `get_result` if I want to strictly adhere to the list, but `process` is more standard.
    *   Let's look at the "Example usage". It has a comment `# After processing...`. This strongly suggests a separate processing step.
    *   I will include the `process` method in the class.

    *   Wait, I should check if I need to handle duplicates. The prompt says "unique job_id".
    *   I'll ensure `add_job` handles the ID.

    *   Wait, I need to be careful about "Write only the Python code". No markdown text outside the code block? Or just no explanation text. Usually, it means output the code block.
    *   I will output the code block.

    *   Refining the `process` logic:
        The prompt asks for `add_job` and `get_result`. It doesn't explicitly ask for `process`.
        If I add `process`, does it violate "with the following methods"? Usually, "with the following methods" defines the interface, but implementation details (like `process`) are allowed.
        However, to be extremely precise, I could implement the processing logic inside `get_result` lazily, or assume the user handles processing.
        But `get_result` returning `None` if not processed is correct.
        Let's assume the user calls a `process` method or I implement a `run` method.
        I will add `process` to make it a valid "queue" that processes jobs.
        Actually, to minimize assumptions, I will add a `process` method.

    *   Wait, I'll check the exact wording: "Create a `JobQueue` class with the following methods: ...".
    *   If I add `process`, is it okay? Yes.
    *   Let's write the code.

    *   Wait, one detail: `get_result` returns `dict | None`.
    *   If I store the `data` as the result, it satisfies the return type.
    *   I will implement a `process` method to move items from queue to results.

    *   Wait, I should check if I need imports. `collections.deque` is standard.

    *   Final check on constraints:
        1. `JobQueue` class.
        2. `add_job(job_id: str, data: dict) -> str`.
        3. `get_result(job_id: str) -> dict | None`.
        4. FIFO.
        5. Internal storage.
        6. Unique ID.
        7. Only Python code.

    *   I will add a `process` method to the class to make the example logic valid (processing happens before result retrieval).
    *   Wait, if I strictly follow "with the following methods", I shouldn't add `process` if I can avoid it.
    *   Can I make `get_result` trigger processing?
        `get_result`:
        If job not in results, process it now.
        This might be confusing.
        Let's just add `process`. It's standard for a Job Queue implementation.

    *   Wait, I'll check the example again.
        ```python
        job_id = queue.add_job("job1", {"task": "process_data"})
        # After processing...
        result = queue.get_result("job1")
        ```
        The comment implies processing is an action that happens. If I don't provide a method for it, the user has to write it. Providing `process` makes the class usable.
        I will add `process`.

    *   Wait, I'll check if the prompt implies I should *only* implement those methods.
        "Create a JobQueue class with the following methods: [list]".
        It doesn't say "only".
        Okay, I will add `process`.

    *   Wait, I'll reconsider. If I add `process`, is it better to name it `process_one` or `process_all`? `process` implies all pending.
    *   I'll implement `process` to clear the queue.
    *   Wait, what if I just store the job in a dict mapping ID to result, and a list for queue order?
    *   `self.queue` (deque for order), `self.results` (dict for storage).
    *   When `process` is called, pop from `queue`, save to `results`.
    *   `get_result` reads from `results`.

    *   Wait, I need to make sure I don't print anything.
    *   I will write the class.

    *   Wait, one more thing: The return type of `add_job` is `str`. It returns `job_id`.
    *   The return type of `get_result` is `dict | None`.
    *   I need to make sure `get_result` returns `None` if the job doesn't exist or isn't processed.

    *   Okay, plan:
        1. Import deque.
        2. Define class.
        3. Init.
        4. Add job.
        5. Process method (to enable the FIFO logic).
        6. Get result.

    *   Wait, I'll try to minimize methods to strictly follow the prompt if possible.
    *   If I don't add `process`, the code is:
        ```python
        class JobQueue:
            def __init__(self):
                self.jobs = []
                self.results = {}

            def add_job(self, job_id: str, data: dict) -> str:
                self.jobs.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)
        ```
    *   This works, but `process` isn't done. The comment says "After processing". If I don't provide `process`, the user must manually mark it processed.
    *   I will add `process` to make it a complete solution.

    *   Wait, I'll check if `process` is required. "Implement a basic job queue". A job queue implies jobs are processed.
    *   I'll add `process`.

    *   Wait, I'll check if I should use `typing`. The prompt uses `dict | None`. This is Python 3.10+ syntax. I will use it.
    *   I need to import `deque`.

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

    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, data))
            self._results[job_id] = None
            return job_id

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

        def get_result(self, job_id: str) -> dict | None:
            return self._results.get(job_id)
    ```
    Wait, `dict | None` is valid in Python 3.10+. I should stick to the prompt's type hint style.
    Also, I should ensure I don't add extra text.

    *   Wait, I need to check if `process` is allowed.
    *   If I look at "with the following methods", it lists `add_job` and `get_result`.
    *   If I add `process`, is it a violation?
    *   Usually, "with the following methods" defines the public API. Adding a helper `process` is acceptable.
    *   However, to be safe, I can put the processing logic inside `get_result` lazily? No, that's messy.
    *   I will add `process` as it's the most logical way to implement "processing".

    *   Wait, I'll check the prompt again. "Create a `JobQueue` class with the following methods: ...".
    *   I will include `process` to ensure the example works (processing step).
    *   Actually, I can make `process` private `_process`.
    *   No, I'll make it public so the user can call it.

    *   Wait, I'll check if I can make `get_result` process the job?
    *   If `get_result` is called and job is pending, process it?
    *   That might be too much logic inside `get_result`.
    *   I'll stick to adding `process`.

    *   Wait, I'll check if I should use `typing` module for `dict | None` or just use the syntax. The prompt uses `dict | None`, so I will use that syntax.

    *   One more check: "Each job has a unique job_id that is returned when added".
    *   My `add_job` takes `job_id` as argument. It returns the same ID. This satisfies "unique job_id that is returned".
    *   Wait, does it mean the class generates the ID?
    *   Signature: `add_job(job_id: str, data: dict) -> str`.
    *   Example: `job_id = queue.add_job("job1", ...)`
    *   So the caller provides the ID. The class returns it (to confirm).
    *   The requirement "Each job has a unique job_id that is returned when added" means the returned ID must be unique across jobs. Since the caller provides it, I should probably validate uniqueness, or just assume the caller provides unique IDs.
    *   Given "Basic", I'll assume caller provides unique IDs or just store them. I won't enforce uniqueness strictly unless necessary, but I'll store it.
    *   Wait, "unique job_id that is returned when added". This phrasing is slightly ambiguous. Does it mean the class generates it? The signature `job_id: str` implies input. The example `add_job("job1", ...)` confirms input.
    *   Okay, I will just store it.

    *   Wait, I'll remove `process` if I want to be strict.
    *   But without `process`, the queue doesn't process.
    *   I will add `process`.

    *   Wait, I'll check if I can simulate processing without `process` method by having `get_result` return the data if I stored it as result immediately?
    *   No, "processed".
    *   Okay, I'll add `process`.

    *   Wait, I'll check the "Write only the Python code" constraint.
    *   I should output the code block.

    *   Final check on imports. `collections.deque` is needed.
    *   Final check on types. `dict | None`.

    *   Wait, one detail: `get_result` returns `dict | None`.
    *   My `process` sets result to `{"status": "completed", "data": data}`. This is a dict.
    *   If not processed, returns `None`.
    *   If job never added, `get` returns `None`.
    *   This matches.

    *   Wait, I'll consider if `process` should be inside the class.
    *   Yes.

    *   Okay, writing the code.

</reasoning_content>

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

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

    def add_job(self, job_id: str, data: dict) -> str:
        if job_id in self._results:
            raise ValueError(f"Job ID {job_id} already exists")
        self._queue.append((job_id, data))
        self._results[job_id] = None
        return job_id

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

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