<reasoning_content>
*   Goal: Implement a basic `JobQueue` class in Python.
    *   Methods: `add_job(job_id, data)`, `get_result(job_id)`.
    *   Ordering: FIFO.
    *   Internal storage: Jobs must be stored until processed.
    *   Result: `get_result` returns the result or `None`.
    *   Note: The prompt implies the existence of a "processing" mechanism, even though it's not explicitly defined as a method. To make the example work, there needs to be some way for jobs to move from "queued" to "completed". However, looking at the requirements strictly:
        *   `add_job` adds a job.
        *   `get_result` gets the result.
    *   Wait, if I only implement these two, the jobs will never be "processed" unless I include a processing method or a simulated processing step. The prompt says "After processing...".
    *   Let's look at requirement 1: `add_job` returns the `job_id`. The user passes `job_id` in the example, but the signature says `add_job(job_id: str, data: dict)`. Wait, usually, an `add_job` function *generates* the ID, but the signature provided says it takes it as an argument.
    *   Signature: `add_job(job_id: str, data: dict) -> str`.
    *   Requirement 2: FIFO.
    *   Requirement 3: Store until processed.
    *   Let's add a `process_next_job` method or similar to satisfy the "After processing..." part of the example, or simply assume the processing happens via some internal logic (though in a single-threaded script, it won't happen automatically).
    *   Wait, the prompt is a bit ambiguous about *who* processes the jobs. I will include a `process_jobs` method or similar to make the code functional/testable, but I must adhere strictly to the required methods.

    *   `_queue`: A `collections.deque` for FIFO.
    *   `_results`: A dictionary mapping `job_id` to the result.
    *   `_pending_jobs`: A way to track what is currently in the queue.

    *   `add_job(job_id, data)`:
        *   Add `(job_id, data)` to the deque.
    *   `get_result(job_id)`:
        *   Return `self._results.get(job_id)`.

    *   Since the user says "After processing...", I'll add a dummy `process_next_job` or `process_all_jobs` method to demonstrate the logic, but the core requirement is the two specific methods. Actually, I'll just implement the two required methods and perhaps a way to simulate processing so the code is actually useful.

    *   Let's refine the internal structure:
        *   `self.queue = deque()`
        *   `self.results = {}`
        *   `self.jobs = {}` (to store the data/status if needed)

    *   Let's look at the `add_job` signature again: `add_job(job_id: str, data: dict) -> str`.
    *   If the user *provides* the `job_id`, the return value is just that same ID.

    *   How to "process"? Since it's a "basic job queue", usually there's a worker. To make the provided example code runnable and logical, I'll add a `process_job` method.

    *   *Self-Correction:* The prompt asks for "only the Python code, no explanations". I will provide the class with the requested methods. I'll include a `process_next_job` method so the logic is complete, even if not explicitly required, because without a way to process, `get_result` will always be `None`.

    *   *Wait*, looking closer at the requirements:
        1. `add_job`
        2. `get_result`
        Requirements don't ask for a worker method. But they do say "Jobs should be processed in FIFO order".
        I will implement a simple `process_next_job` method to make it a functional implementation.

    ```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))
            return job_id

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

        def process_next_job(self):
            if not self._queue:
                return
            job_id, data = self._queue.popleft()
            # Simple mock processing logic
            result = {"status": "completed", "processed_data": data}
            self._results[job_id] = result
    ```

    Actually, if I want to be strictly compliant with the text:
    The prompt says: "Implement a basic job queue... Requirements: 1. Create a JobQueue class with the following methods: [add_job, get_result]". It doesn't forbid other methods.

    Let's check the `add_job` signature one more time. `add_job(job_id: str, data: dict) -> str`. It's slightly unusual to pass the ID in, but I will follow it.

    Final Code Plan:
    1. `collections.deque` for the queue.
    2. `dict` for results.
    3. `add_job` appends to deque.
    4. `get_result` returns from dict.
    5. `process_next_job` (for completeness/functionality) pops from deque and puts in dict.

    Wait, should `add_job` handle the case where the ID already exists? The prompt doesn't specify, so I'll keep it simple.

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

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

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

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)

        def process_next_job(self):
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulated processing
                self._results[job_id] = {"result": f"processed {data}"}

    ```

    Actually, looking at the example usage:
    `job_id = queue.add_job("job1", {"task": "process_data"})`
    The user provides the ID.

    Let's refine the `process_next_job` to be a bit more generic or just use a simple transformation.

    One detail: Requirement 3 says "The queue should store jobs internally until they are processed".
    Requirement 2 says "Jobs should be processed in FIFO order".

    Implementation:
    ```python
    from collections import deque
    from typing import Dict, Any, Optional

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

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

        def get_result(self, job_id: str) -> Optional[Dict[str, Any]]:
            return self._results.get(job_id)

        def process_next_job(self):
            if self._queue:
                job_id, data = self._queue.popleft()
                # Simulate processing: reverse data or just wrap it
                self._results[job_id] = {"original_data": data, "status": "success"}
    ```

    Final check of requirements:
    1. `add_job(job_id: str, data: dict) -> str` - Check.
    2. `get_result(job_id: str) -> dict | None` - Check.
    3. FIFO order - Check (via `deque.popleft()`).
    4. Store until processed - Check.
    5. Unique job_id returned - Check.

    I will include the `process_next_job` method so the example is actually demonstrable.

    One edge case: what if `get_result` is called for a job that isn't processed yet? Returns `None`. Correct.

    Final check on the typing: `dict | None` is Python 3.10+ syntax. I'll use `Optional` or just the `|` syntax since modern Python is expected. I'll stick to the prompt's exact signature `dict | None`.

    Wait, the prompt says "Write only the Python code, no explanations."

    ```python
    from collections import deque
    from typing import Any

    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))
            return job_id

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

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

    if __name__ == "__main__":
        queue = JobQueue()
        job_id = queue.add_job("job1", {"task": "process_data"})
        queue.process_next_job()
        result = queue.get_result("job_id") # Error in my thought, should be job_id
    ```

    Actually, I shouldn't include the `if __name__ == "__main__":` block unless it's requested, but it helps confirm it works. The prompt doesn't forbid it. But the instruction is "Write only the Python code". I'll just provide the class.

    One small detail: if I add a `process_next_job` method, I am technically adding something not in the requirements, but the requirements imply a way for processing to happen. I'll include it.

    Wait, I can make it even more "basic" and "queue-like" by having the processing happen in a way that doesn't require an external method call? No, that would require threading. A simple `process_next_job` is the cleanest way to represent a queue being worked on.

    Let's refine the `process_next_job` to just be a placeholder for how a user would use the class.

    ```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))
            return job_id

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

        def process_next_job(self):
            """Simulates the worker processing the next job in the queue."""
            if self._queue:
                job_id, data = self._queue.popleft()
                # Basic processing simulation
                self._results[job_id] = {"result": "success", "input": data}
    ```

    Final check on `get_result` return type: `dict | None`. Python 3.10+ feature. I'll use it.

    Is there any ambiguity in "The queue should store jobs internally until they are processed"? 
    It means don't put the result in the results dict until it's popped from the queue.

    One last thing: The prompt asks to "Create a JobQueue class with the following methods". It does not mention `process_next_job`. I will include it just to make the logic complete, as the user example implies processing happens.

    ```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))
            return job_id

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

        def process_next_job(self):
            if self._queue:
                job_id, data = self._queue.popleft()
                self._results[job_id] = {"status": "completed", "data": data}
    ```
    This looks solid.
</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:
        """Add a job to the queue."""
        self._queue.append((job_id, data))
        return job_id

    def get_result(self, job_id: str) -> dict | None:
        """Get the result of a completed job."""
        return self._results.get(job_id)

    def process_next_job(self):
        """
        Simulates a worker picking up and processing the next job 
        in the queue (FIFO).
        """
        if self._queue:
            job_id, data = self._queue.popleft()
            # Simulate processing logic
            result = {
                "status": "completed",
                "processed_data": data
            }
            self._results[job_id] = result

# Example usage:
if __name__ == "__main__":
    queue = JobQueue()
    job_id = queue.add_job("job1", {"task": "process_data"})
    
    # Before processing
    print(f"Result for {job_id}: {queue.get_result(job_id)}") 
    
    # Process the job
    queue.process_next_job()
    
    # After processing
    result = queue.get_result(job_id)
    print(f"Result for {job_id}: {result}")
```
</content>