# Relative Imports in Pipeline Wrappers
This example demonstrates how to use **relative imports** to organize your pipeline wrapper code into multiple files.
## Structure
```text
relative_imports/
├── pipeline_wrapper.py # Main wrapper with PipelineWrapper class
├── utils.py # Helper functions
└── README.md # This file
```
## Key Features
- **No configuration needed** - Relative imports work out of the box
- **Clean organization** - Split complex logic into separate modules
- **IDE support** - Full autocomplete and type checking
- **Tracing compatible** - Works with Phoenix/OpenInference and other tracing libraries
## How It Works
Pipeline wrappers are loaded as Python packages, which enables relative imports:
```python
# In pipeline_wrapper.py
from .utils import greet, calculate_sum # ← Relative import
```
## Ruff Linting Note
If your project uses [ruff](https://docs.astral.sh/ruff/) with the `flake8-tidy-imports` plugin, you may need to disable the [`TID252`](https://docs.astral.sh/ruff/rules/relative-imports/) rule which flags relative imports.
Add this comment at the top of your `pipeline_wrapper.py`:
```python
# ruff: noqa: TID252
```
Or configure it in your `pyproject.toml`:
```toml
[tool.ruff.lint.flake8-tidy-imports]
ban-relative-imports = "parents" # Allow sibling relative imports
```
## Running the Example
### 1. Start Hayhooks
```bash
hayhooks run
```
### 2. Deploy the Pipeline
```bash
hayhooks pipeline deploy-files -n calculator examples/pipeline_wrappers/relative_imports
```
### 3. Test the Pipeline
```bash
curl -X 'POST' \
'http://localhost:1416/calculator/run' \
-H 'Content-Type: application/json' \
-d '{
"name": "Alice",
"numbers": [1, 2, 3, 4, 5]
}'
```
**Expected output:**
```json
{
"result": {
"greeting": "Hello, Alice!",
"sum": 15,
"average": 3.0
}
}
```
## When to Use Relative Imports
- Splitting a large wrapper into logical modules
- Keeping helper functions close to where they're used
- Organizing prompts, configs, or utilities separately
- Any code that's specific to a single pipeline
For sharing code across **multiple pipelines**, see the [shared_code_between_wrappers](../../../shared_code_between_wrappers/) example.
