Add cursor rules

.cursor/logging.mdc

@@ -0,0 +1,23 @@
+---
+description: Logging should be actionable, structured, and follow professional practices
+alwaysApply: true
+---
+
+- Never log and raise at the same time. Let logs occur where the exception is handled.
+- Use `.bind()` to attach contextual fields like `job_id`, `trainer`, `dataset`, etc.
+- Propagate the bound logger across modules instead of re-creating it.
+- Use semantic log levels:
+  - `debug`: Diagnostic/internal details, not printed in prod
+  - `info`: Expected events (training started, dataset loaded, etc.)
+  - `warning`: Unexpected but handled (e.g. missing columns)
+  - `error`: Real failures that may abort a process
+- Avoid logs like `"Starting function"` — instead log **what happened**, with context.
+- Avoid excessive logging in loops. Log summary or batch progress only.
+- Enable JSON structured logs only in production environments.
+- Keep logs relevant to external observability, not internal dev experimentation.
+
+**Checklist for evaluating a log:**
+- Does it convey a real event, not just function entry?
+- Is it at the correct level (not everything is warning)?
+- Is the logger properly bound with job/task context?
+- Can this log help diagnose or monitor the system?

.cursor/modular-design-principles.mdc

@@ -0,0 +1,19 @@
+---
+description: Enforce modular design with clear responsibility boundaries
+alwaysApply: true
+---
+
+- Follow **Single Responsibility Principle (SRP)**: one reason to change per module/class/function.
+- Avoid **over-engineering**: modularize only when it improves clarity, reuse or testability.
+- Group related logic in packages: `data/`, `services/`, `utils/`, `models/`, etc.
+- Keep modules cohesive but not overly fragmented.
+- Don't split code into separate files unless they evolve independently or have distinct lifecycles.
+
+**Checklist for evaluating modularity:**
+- Can the module be reused independently?
+- Does it hide internal details behind a clean interface?
+- Would adding more features bloat its logic?
+
+Example:
+✅ `email_service.py` sends emails  
+🚫 `email_sender.py`, `email_templates.py`, `email_config.py` if too small and tightly coupled

.cursor/structured-import-order.mdc

@@ -0,0 +1,56 @@
+---
+description: Enforce structured and absolute import order for Python files
+globs:
+  - "**/*.py"
+alwaysApply: true
+---
+
+Group, order, and format Python imports following these conventions:
+
+### ✅ Use **absolute imports only**:
+Always write imports using the full path from the project root.
+**Avoid** relative imports like `from .module import foo` or `from ..utils import bar`.
+
+- ✅ `from my_project.utils import foo`  
+- ❌ `from .utils import foo`  
+- ❌ `from ..submodule import bar`
+
+This ensures clarity, consistency across refactors, and better compatibility with tools like linters, IDEs, and packaging systems.
+
+---
+
+### 📚 Import grouping and ordering:
+
+Organize imports into **three groups**, separated by a blank line:
+
+1. **Standard Library Imports**  
+   e.g., `import os`, `from datetime import datetime`
+
+2. **Third-Party Library Imports**  
+   e.g., `import numpy as np`, `from sqlalchemy import Column`
+
+3. **Local Application/Library Imports**  
+   e.g., `from my_project.utils import helper_function`
+
+---
+
+### 🔤 Within each group:
+
+- First: `import module` (in alphabetical order)
+- Then: `from module import name` (in alphabetical order)
+
+---
+
+### ✅ Example:
+
+```python
+import os
+import sys
+from datetime import datetime
+
+import numpy as np
+import pandas as pd
+from sqlalchemy import Column, Integer
+
+import my_project
+from my_project.utils import helper_function

.cursor/type-hinting.mdc

@@ -0,0 +1,28 @@
+---
+description: Enforce strict type annotations using Python 3.12+ standards
+globs:
+  - "**/*.py"
+alwaysApply: true
+---
+
+- Always annotate:
+  - Function parameters and return types, even for `None`, `bool`, `str`, etc.
+  - Variable declarations (including attributes and loop vars) when static typing helps comprehension.
+  - Lambda expressions when assigned or passed as arguments.
+- **Avoid** `Any`, `Optional`, `Union`, `List`, `Dict`, etc. unless justified.
+- **Prefer** Python 3.12+ standard generics:
+  - Use `list[str]`, `dict[str, int]`, `tuple[str, int]`
+  - Avoid `List`, `Dict`, `Tuple` from `typing`
+- Use `|` (pipe) syntax for unions:
+  - Use `str | None`
+  - Avoid `Optional[str]`
+- Use `Self` and `classmethod`/`staticmethod` hints as per [PEP 673](https://peps.python.org/pep-0673/)
+
+**Examples:**
+
+```python
+def greet(name: str | None = None) -> str:
+    return f"Hello, {name or 'World'}"
+
+def parse(data: str) -> dict[str, int]:
+    ...

README.md

@@ -116,6 +116,11 @@ This project uses [structlog](https://www.structlog.org/en/stable/) for structur
 
 Structured logs make it easier to parse, search, and analyze logs in production systems, especially when using centralized logging tools like Loki, ELK, or Datadog.
 
+## IDE
+
+This project has some [cursor|https://cursor.com/] rules under `.cursor` that help us write some code, but you are not forced to use it as this is optional.
+
+
 ### Examples
 
 1. Pass context information as key word arguments