If your `pyproject.toml` file is not being picked up by Ruff in your Databricks notebooks, there are a few potential reasons and solutions to address the issue:

Common Causes and Solutions

1. Ruff Version Compatibility:
- Ensure you are using a recent version of Ruff (preferably 0.5.1 or later). Earlier versions had issues with reliably detecting `pyproject.toml` configurations automatically.

2. Explicitly Specify the Configuration File:
- If Ruff is not automatically detecting your `pyproject.toml`, you can explicitly pass the configuration file path using the `--config` flag when running Ruff. For example:
```bash ruff check . --config=path/to/pyproject.toml
```
- This ensures that Ruff uses the specified configuration file regardless of its automatic detection logic.

3. Correct Placement of `pyproject.toml`:
- Verify that the `pyproject.toml` file is located in the root directory of your project. Ruff treats the directory containing the configuration file as the "project root" and applies rules accordingly.

4. Databricks-Specific Considerations:
- Databricks environments may not automatically apply Ruff configurations to notebooks. If you are running Ruff as part of a CI/CD pipeline or through a script, ensure that the command explicitly references the configuration file.
- For interactive notebook usage, consider running Ruff commands manually or integrating them into your workflow with explicit configuration paths.

5. Alternative Configuration Files:
- If `pyproject.toml` is not working as expected, try using a `ruff.toml` or `.ruff.toml` file instead. These files do not require the `[tool.ruff]` prefix and may simplify configuration.

6. Restarting Services:
- If you are using a language server (e.g., Ruff's LSP or an IDE integration), restart the server after adding or modifying your `pyproject.toml`. Some services cache settings and need to be refreshed to pick up changes[4][9].

7. Debugging Configuration Issues:
- Use the following command to verify which configuration file Ruff is using:
```bash ruff config path/to/file
```
- This command lists all active settings and can help identify whether your custom rules are being applied.

Example Configuration in `pyproject.toml`
Ensure your `pyproject.toml` includes a valid `[tool.ruff]` section, like this:
```toml
[tool.ruff]
select = ["E", "F", "W"]
ignore = ["E501"]
per-file-ignores = {
"__init__.py" = ["F401"],
"tests/*.py" = ["D"]
}
```

Additional Notes for Databricks
- If you are working with Jupyter Notebooks in Databricks, ensure that you have enabled Ruff's notebook linting support (available in version 0.6.0 and higher). You can configure this via the `exclude` or `per-file-ignores` options for `.ipynb` files.