wdm0006

designing-python-apis

Designs intuitive Python library APIs following principles of simplicity, consistency, and discoverability. Handles API evolution, deprecation, breaking changes, and error handling. Use when designing new library APIs, reviewing existing APIs for improvements, or managing API versioning and deprecations.

wdm0006 42 8 Updated 3mo ago
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npx skillscat add wdm0006/python-skills/designing-python-apis

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SKILL.md

Python API Design

Core Principles

  1. Simplicity: Simple things simple, complex things possible
  2. Consistency: Similar operations work similarly
  3. Least Surprise: Behave as users expect
  4. Discoverability: Find via autocomplete and help

Progressive Disclosure Pattern

# Level 1: Simple functions
from mylib import encode, decode
result = encode(37.7749, -122.4194)

# Level 2: Configurable classes
from mylib import Encoder
encoder = Encoder(precision=15)

# Level 3: Low-level access
from mylib.internals import BitEncoder

Naming Conventions

# Actions: verbs
encode(), decode(), validate()

# Retrieval: get_*
get_user(), get_config()

# Boolean: is_*, has_*, can_*
is_valid(), has_permission()

# Conversion: to_*, from_*
to_dict(), from_json()

Error Handling

class MyLibError(Exception):
    """Base exception with helpful messages."""
    def __init__(self, message: str, *, hint: str = None):
        super().__init__(message)
        self.hint = hint

# Usage
raise ValidationError(
    f"Latitude must be -90 to 90, got {lat}",
    hint="Did you swap latitude and longitude?"
)

Deprecation

import warnings

def old_function():
    warnings.warn(
        "old_function() deprecated, use new_function()",
        DeprecationWarning,
        stacklevel=2,
    )
    return new_function()

Anti-Patterns

# Bad: Boolean trap
process(data, True, False, True)

# Good: Keyword arguments
process(data, validate=True, cache=False)

# Bad: Mutable default
def process(items: list = []):

# Good: None default
def process(items: list | None = None):

For detailed patterns, see:

Review Checklist

Naming:
- [ ] Clear, self-documenting names
- [ ] Consistent patterns throughout
- [ ] Boolean params read naturally

Parameters:
- [ ] Minimal required parameters
- [ ] Sensible defaults
- [ ] Keyword-only after positional clarity

Errors:
- [ ] Custom exceptions with context
- [ ] Helpful error messages
- [ ] Documented in docstrings

Learn More

This skill is based on the Ergonomics section of the Guide to Developing High-Quality Python Libraries by Will McGinnis.