fix: Update example spaceship-titanic

examples/spaceship-titanic/README.md

@@ -5,29 +5,10 @@ This example demonstrates using Weco to optimize a Python script designed for th
 ## Setup
 
 1.  Ensure you are in the `examples/spaceship-titanic` directory.
-2.  **Kaggle Credentials:** You need your Kaggle API credentials (`kaggle.json`) configured to download the competition dataset. Place the `kaggle.json` file in `~/.kaggle/` or set the `KAGGLE_USERNAME` and `KAGGLE_KEY` environment variables. See [Kaggle API documentation](https://github.com/Kaggle/kaggle-api#api-credentials) for details.
-3.  **Install Dependencies:** Install the required Python packages:
+2.  **Install Dependencies:** Install the required Python packages:
     ```bash
     pip install -r requirements-test.txt
     ```
-4.  **Prepare Data:** Run the utility script once to download the dataset from Kaggle and place it in the expected `./data/` subdirectories:
-    ```bash
-    python get_data.py
-    ```
-    After running `get_data.py`, your directory structure should look like this:
-    ```
-    .
-    ├── competition_description.md
-    ├── data
-    │   ├── sample_submission.csv
-    │   ├── test.csv
-    │   └── train.csv
-    ├── evaluate.py
-    ├── get_data.py
-    ├── README.md # This file
-    ├── requirements-test.txt
-    └── submit.py
-    ```
 
 ## Optimization Command
 
@@ -44,14 +25,6 @@ weco run --source evaluate.py \
          --log-dir .runs/spaceship-titanic
 ```
 
-## Submit the solution
-
-Once the optimization finished, you can submit your predictions to kaggle to see the results. Make sure `submission.csv` is present and then simply run the following command.
-
-```bash
-python submit.py
-```
-
 ### Explanation
 
 *   `--source evaluate.py`: The script provides a baseline as root node and directly optimize the evaluate.py