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elordenador 34481f15ea workflow: add job outputs mapping for cross-job version access
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elordenador 62c1a41c19 workflow: fix package version extraction using pacman -Qp
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elordenador ca295efb41 workflow: fix sed regex for package version
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elordenador 65f2d47d14 workflow: fix indentation for extract package version step
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elordenador 62e4159695 workflow: fix package version extraction format 2026-05-13 13:38:21 +02:00
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---
name: python-executor
description: "Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib"
allowed-tools: Bash(belt *)
---
# Python Code Executor
Execute Python code in a safe, sandboxed environment with 100+ pre-installed libraries.
![Python Code Executor](https://cloud.inference.sh/u/33sqbmzt3mrg2xxphnhw5g5ear/01k8d8b4mckh6z89dhtxh72dsz.png)
## Quick Start
> Requires inference.sh CLI (`belt`). [Install instructions](https://raw.githubusercontent.com/inference-sh/skills/refs/heads/main/cli-install.md)
```bash
belt login
# Run Python code
belt app run infsh/python-executor --input '{
"code": "import pandas as pd\nprint(pd.__version__)"
}'
```
## App Details
| Property | Value |
|----------|-------|
| App ID | `infsh/python-executor` |
| Environment | Python 3.10, CPU-only |
| RAM | 8GB (default) / 16GB (high_memory) |
| Timeout | 1-300 seconds (default: 30) |
## Input Schema
```json
{
"code": "print('Hello World!')",
"timeout": 30,
"capture_output": true,
"working_dir": null
}
```
## Pre-installed Libraries
### Web Scraping & HTTP
- `requests`, `httpx`, `aiohttp` - HTTP clients
- `beautifulsoup4`, `lxml` - HTML/XML parsing
- `selenium`, `playwright` - Browser automation
- `scrapy` - Web scraping framework
### Data Processing
- `numpy`, `pandas`, `scipy` - Numerical computing
- `matplotlib`, `seaborn`, `plotly` - Visualization
### Image Processing
- `pillow`, `opencv-python-headless` - Image manipulation
- `scikit-image`, `imageio` - Image algorithms
### Video & Audio
- `moviepy` - Video editing
- `av` (PyAV), `ffmpeg-python` - Video processing
- `pydub` - Audio manipulation
### 3D Processing
- `trimesh`, `open3d` - 3D mesh processing
- `numpy-stl`, `meshio`, `pyvista` - 3D file formats
### Documents & Graphics
- `svgwrite`, `cairosvg` - SVG creation
- `reportlab`, `pypdf2` - PDF generation
## Examples
### Web Scraping
```bash
belt app run infsh/python-executor --input '{
"code": "import requests\nfrom bs4 import BeautifulSoup\n\nresponse = requests.get(\"https://example.com\")\nsoup = BeautifulSoup(response.content, \"html.parser\")\nprint(soup.find(\"title\").text)"
}'
```
### Data Analysis with Visualization
```bash
belt app run infsh/python-executor --input '{
"code": "import pandas as pd\nimport matplotlib.pyplot as plt\n\ndata = {\"name\": [\"Alice\", \"Bob\"], \"sales\": [100, 150]}\ndf = pd.DataFrame(data)\n\nplt.bar(df[\"name\"], df[\"sales\"])\nplt.savefig(\"outputs/chart.png\")\nprint(\"Chart saved!\")"
}'
```
### Image Processing
```bash
belt app run infsh/python-executor --input '{
"code": "from PIL import Image\nimport numpy as np\n\n# Create gradient image\narr = np.linspace(0, 255, 256*256, dtype=np.uint8).reshape(256, 256)\nimg = Image.fromarray(arr, mode=\"L\")\nimg.save(\"outputs/gradient.png\")\nprint(\"Image created!\")"
}'
```
### Video Creation
```bash
belt app run infsh/python-executor --input '{
"code": "from moviepy.editor import ColorClip, TextClip, CompositeVideoClip\n\nclip = ColorClip(size=(640, 480), color=(0, 100, 200), duration=3)\ntxt = TextClip(\"Hello!\", fontsize=70, color=\"white\").set_position(\"center\").set_duration(3)\nvideo = CompositeVideoClip([clip, txt])\nvideo.write_videofile(\"outputs/hello.mp4\", fps=24)\nprint(\"Video created!\")",
"timeout": 120
}'
```
### 3D Model Processing
```bash
belt app run infsh/python-executor --input '{
"code": "import trimesh\n\nsphere = trimesh.creation.icosphere(subdivisions=3, radius=1.0)\nsphere.export(\"outputs/sphere.stl\")\nprint(f\"Created sphere with {len(sphere.vertices)} vertices\")"
}'
```
### API Calls
```bash
belt app run infsh/python-executor --input '{
"code": "import requests\nimport json\n\nresponse = requests.get(\"https://api.github.com/users/octocat\")\ndata = response.json()\nprint(json.dumps(data, indent=2))"
}'
```
## File Output
Files saved to `outputs/` are automatically returned:
```python
# These files will be in the response
plt.savefig('outputs/chart.png')
df.to_csv('outputs/data.csv')
video.write_videofile('outputs/video.mp4')
mesh.export('outputs/model.stl')
```
## Variants
```bash
# Default (8GB RAM)
belt app run infsh/python-executor --input input.json
# High memory (16GB RAM) for large datasets
belt app run infsh/python-executor@high_memory --input input.json
```
## Use Cases
- **Web scraping** - Extract data from websites
- **Data analysis** - Process and visualize datasets
- **Image manipulation** - Resize, crop, composite images
- **Video creation** - Generate videos with text overlays
- **3D processing** - Load, transform, export 3D models
- **API integration** - Call external APIs
- **PDF generation** - Create reports and documents
- **Automation** - Run any Python script
## Important Notes
- **CPU-only** - No GPU/ML libraries (use dedicated AI apps for that)
- **Safe execution** - Runs in isolated subprocess
- **Non-interactive** - Use `plt.savefig()` not `plt.show()`
- **File detection** - Output files are auto-detected and returned
## Related Skills
```bash
# AI image generation (for ML-based images)
npx skills add inference-sh/skills@ai-image-generation
# AI video generation (for ML-based videos)
npx skills add inference-sh/skills@ai-video-generation
# LLM models (for text generation)
npx skills add inference-sh/skills@llm-models
```
## Documentation
- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [App Code](https://inference.sh/docs/extend/app-code) - Understanding app execution
- [Sandboxed Code Execution](https://inference.sh/blog/tools/sandboxed-execution) - Safe code execution for agents
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---
name: python-patterns
description: Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
origin: ECC
---
# Python Development Patterns
Idiomatic Python patterns and best practices for building robust, efficient, and maintainable applications.
## When to Activate
- Writing new Python code
- Reviewing Python code
- Refactoring existing Python code
- Designing Python packages/modules
## Core Principles
### 1. Readability Counts
Python prioritizes readability. Code should be obvious and easy to understand.
```python
# Good: Clear and readable
def get_active_users(users: list[User]) -> list[User]:
"""Return only active users from the provided list."""
return [user for user in users if user.is_active]
# Bad: Clever but confusing
def get_active_users(u):
return [x for x in u if x.a]
```
### 2. Explicit is Better Than Implicit
Avoid magic; be clear about what your code does.
```python
# Good: Explicit configuration
import logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
# Bad: Hidden side effects
import some_module
some_module.setup() # What does this do?
```
### 3. EAFP - Easier to Ask Forgiveness Than Permission
Python prefers exception handling over checking conditions.
```python
# Good: EAFP style
def get_value(dictionary: dict, key: str) -> Any:
try:
return dictionary[key]
except KeyError:
return default_value
# Bad: LBYL (Look Before You Leap) style
def get_value(dictionary: dict, key: str) -> Any:
if key in dictionary:
return dictionary[key]
else:
return default_value
```
## Type Hints
### Basic Type Annotations
```python
from typing import Optional, List, Dict, Any
def process_user(
user_id: str,
data: Dict[str, Any],
active: bool = True
) -> Optional[User]:
"""Process a user and return the updated User or None."""
if not active:
return None
return User(user_id, data)
```
### Modern Type Hints (Python 3.9+)
```python
# Python 3.9+ - Use built-in types
def process_items(items: list[str]) -> dict[str, int]:
return {item: len(item) for item in items}
# Python 3.8 and earlier - Use typing module
from typing import List, Dict
def process_items(items: List[str]) -> Dict[str, int]:
return {item: len(item) for item in items}
```
### Type Aliases and TypeVar
```python
from typing import TypeVar, Union
# Type alias for complex types
JSON = Union[dict[str, Any], list[Any], str, int, float, bool, None]
def parse_json(data: str) -> JSON:
return json.loads(data)
# Generic types
T = TypeVar('T')
def first(items: list[T]) -> T | None:
"""Return the first item or None if list is empty."""
return items[0] if items else None
```
### Protocol-Based Duck Typing
```python
from typing import Protocol
class Renderable(Protocol):
def render(self) -> str:
"""Render the object to a string."""
def render_all(items: list[Renderable]) -> str:
"""Render all items that implement the Renderable protocol."""
return "\n".join(item.render() for item in items)
```
## Error Handling Patterns
### Specific Exception Handling
```python
# Good: Catch specific exceptions
def load_config(path: str) -> Config:
try:
with open(path) as f:
return Config.from_json(f.read())
except FileNotFoundError as e:
raise ConfigError(f"Config file not found: {path}") from e
except json.JSONDecodeError as e:
raise ConfigError(f"Invalid JSON in config: {path}") from e
# Bad: Bare except
def load_config(path: str) -> Config:
try:
with open(path) as f:
return Config.from_json(f.read())
except:
return None # Silent failure!
```
### Exception Chaining
```python
def process_data(data: str) -> Result:
try:
parsed = json.loads(data)
except json.JSONDecodeError as e:
# Chain exceptions to preserve the traceback
raise ValueError(f"Failed to parse data: {data}") from e
```
### Custom Exception Hierarchy
```python
class AppError(Exception):
"""Base exception for all application errors."""
pass
class ValidationError(AppError):
"""Raised when input validation fails."""
pass
class NotFoundError(AppError):
"""Raised when a requested resource is not found."""
pass
# Usage
def get_user(user_id: str) -> User:
user = db.find_user(user_id)
if not user:
raise NotFoundError(f"User not found: {user_id}")
return user
```
## Context Managers
### Resource Management
```python
# Good: Using context managers
def process_file(path: str) -> str:
with open(path, 'r') as f:
return f.read()
# Bad: Manual resource management
def process_file(path: str) -> str:
f = open(path, 'r')
try:
return f.read()
finally:
f.close()
```
### Custom Context Managers
```python
from contextlib import contextmanager
@contextmanager
def timer(name: str):
"""Context manager to time a block of code."""
start = time.perf_counter()
yield
elapsed = time.perf_counter() - start
print(f"{name} took {elapsed:.4f} seconds")
# Usage
with timer("data processing"):
process_large_dataset()
```
### Context Manager Classes
```python
class DatabaseTransaction:
def __init__(self, connection):
self.connection = connection
def __enter__(self):
self.connection.begin_transaction()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if exc_type is None:
self.connection.commit()
else:
self.connection.rollback()
return False # Don't suppress exceptions
# Usage
with DatabaseTransaction(conn):
user = conn.create_user(user_data)
conn.create_profile(user.id, profile_data)
```
## Comprehensions and Generators
### List Comprehensions
```python
# Good: List comprehension for simple transformations
names = [user.name for user in users if user.is_active]
# Bad: Manual loop
names = []
for user in users:
if user.is_active:
names.append(user.name)
# Complex comprehensions should be expanded
# Bad: Too complex
result = [x * 2 for x in items if x > 0 if x % 2 == 0]
# Good: Use a generator function
def filter_and_transform(items: Iterable[int]) -> list[int]:
result = []
for x in items:
if x > 0 and x % 2 == 0:
result.append(x * 2)
return result
```
### Generator Expressions
```python
# Good: Generator for lazy evaluation
total = sum(x * x for x in range(1_000_000))
# Bad: Creates large intermediate list
total = sum([x * x for x in range(1_000_000)])
```
### Generator Functions
```python
def read_large_file(path: str) -> Iterator[str]:
"""Read a large file line by line."""
with open(path) as f:
for line in f:
yield line.strip()
# Usage
for line in read_large_file("huge.txt"):
process(line)
```
## Data Classes and Named Tuples
### Data Classes
```python
from dataclasses import dataclass, field
from datetime import datetime
@dataclass
class User:
"""User entity with automatic __init__, __repr__, and __eq__."""
id: str
name: str
email: str
created_at: datetime = field(default_factory=datetime.now)
is_active: bool = True
# Usage
user = User(
id="123",
name="Alice",
email="alice@example.com"
)
```
### Data Classes with Validation
```python
@dataclass
class User:
email: str
age: int
def __post_init__(self):
# Validate email format
if "@" not in self.email:
raise ValueError(f"Invalid email: {self.email}")
# Validate age range
if self.age < 0 or self.age > 150:
raise ValueError(f"Invalid age: {self.age}")
```
### Named Tuples
```python
from typing import NamedTuple
class Point(NamedTuple):
"""Immutable 2D point."""
x: float
y: float
def distance(self, other: 'Point') -> float:
return ((self.x - other.x) ** 2 + (self.y - other.y) ** 2) ** 0.5
# Usage
p1 = Point(0, 0)
p2 = Point(3, 4)
print(p1.distance(p2)) # 5.0
```
## Decorators
### Function Decorators
```python
import functools
import time
def timer(func: Callable) -> Callable:
"""Decorator to time function execution."""
@functools.wraps(func)
def wrapper(*args, **kwargs):
start = time.perf_counter()
result = func(*args, **kwargs)
elapsed = time.perf_counter() - start
print(f"{func.__name__} took {elapsed:.4f}s")
return result
return wrapper
@timer
def slow_function():
time.sleep(1)
# slow_function() prints: slow_function took 1.0012s
```
### Parameterized Decorators
```python
def repeat(times: int):
"""Decorator to repeat a function multiple times."""
def decorator(func: Callable) -> Callable:
@functools.wraps(func)
def wrapper(*args, **kwargs):
results = []
for _ in range(times):
results.append(func(*args, **kwargs))
return results
return wrapper
return decorator
@repeat(times=3)
def greet(name: str) -> str:
return f"Hello, {name}!"
# greet("Alice") returns ["Hello, Alice!", "Hello, Alice!", "Hello, Alice!"]
```
### Class-Based Decorators
```python
class CountCalls:
"""Decorator that counts how many times a function is called."""
def __init__(self, func: Callable):
functools.update_wrapper(self, func)
self.func = func
self.count = 0
def __call__(self, *args, **kwargs):
self.count += 1
print(f"{self.func.__name__} has been called {self.count} times")
return self.func(*args, **kwargs)
@CountCalls
def process():
pass
# Each call to process() prints the call count
```
## Concurrency Patterns
### Threading for I/O-Bound Tasks
```python
import concurrent.futures
import threading
def fetch_url(url: str) -> str:
"""Fetch a URL (I/O-bound operation)."""
import urllib.request
with urllib.request.urlopen(url) as response:
return response.read().decode()
def fetch_all_urls(urls: list[str]) -> dict[str, str]:
"""Fetch multiple URLs concurrently using threads."""
with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
future_to_url = {executor.submit(fetch_url, url): url for url in urls}
results = {}
for future in concurrent.futures.as_completed(future_to_url):
url = future_to_url[future]
try:
results[url] = future.result()
except Exception as e:
results[url] = f"Error: {e}"
return results
```
### Multiprocessing for CPU-Bound Tasks
```python
def process_data(data: list[int]) -> int:
"""CPU-intensive computation."""
return sum(x ** 2 for x in data)
def process_all(datasets: list[list[int]]) -> list[int]:
"""Process multiple datasets using multiple processes."""
with concurrent.futures.ProcessPoolExecutor() as executor:
results = list(executor.map(process_data, datasets))
return results
```
### Async/Await for Concurrent I/O
```python
import asyncio
async def fetch_async(url: str) -> str:
"""Fetch a URL asynchronously."""
import aiohttp
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
return await response.text()
async def fetch_all(urls: list[str]) -> dict[str, str]:
"""Fetch multiple URLs concurrently."""
tasks = [fetch_async(url) for url in urls]
results = await asyncio.gather(*tasks, return_exceptions=True)
return dict(zip(urls, results))
```
## Package Organization
### Standard Project Layout
```
myproject/
├── src/
│ └── mypackage/
│ ├── __init__.py
│ ├── main.py
│ ├── api/
│ │ ├── __init__.py
│ │ └── routes.py
│ ├── models/
│ │ ├── __init__.py
│ │ └── user.py
│ └── utils/
│ ├── __init__.py
│ └── helpers.py
├── tests/
│ ├── __init__.py
│ ├── conftest.py
│ ├── test_api.py
│ └── test_models.py
├── pyproject.toml
├── README.md
└── .gitignore
```
### Import Conventions
```python
# Good: Import order - stdlib, third-party, local
import os
import sys
from pathlib import Path
import requests
from fastapi import FastAPI
from mypackage.models import User
from mypackage.utils import format_name
# Good: Use isort for automatic import sorting
# pip install isort
```
### __init__.py for Package Exports
```python
# mypackage/__init__.py
"""mypackage - A sample Python package."""
__version__ = "1.0.0"
# Export main classes/functions at package level
from mypackage.models import User, Post
from mypackage.utils import format_name
__all__ = ["User", "Post", "format_name"]
```
## Memory and Performance
### Using __slots__ for Memory Efficiency
```python
# Bad: Regular class uses __dict__ (more memory)
class Point:
def __init__(self, x: float, y: float):
self.x = x
self.y = y
# Good: __slots__ reduces memory usage
class Point:
__slots__ = ['x', 'y']
def __init__(self, x: float, y: float):
self.x = x
self.y = y
```
### Generator for Large Data
```python
# Bad: Returns full list in memory
def read_lines(path: str) -> list[str]:
with open(path) as f:
return [line.strip() for line in f]
# Good: Yields lines one at a time
def read_lines(path: str) -> Iterator[str]:
with open(path) as f:
for line in f:
yield line.strip()
```
### Avoid String Concatenation in Loops
```python
# Bad: O(n²) due to string immutability
result = ""
for item in items:
result += str(item)
# Good: O(n) using join
result = "".join(str(item) for item in items)
# Good: Using StringIO for building
from io import StringIO
buffer = StringIO()
for item in items:
buffer.write(str(item))
result = buffer.getvalue()
```
## Python Tooling Integration
### Essential Commands
```bash
# Code formatting
black .
isort .
# Linting
ruff check .
pylint mypackage/
# Type checking
mypy .
# Testing
pytest --cov=mypackage --cov-report=html
# Security scanning
bandit -r .
# Dependency management
pip-audit
safety check
```
### pyproject.toml Configuration
```toml
[project]
name = "mypackage"
version = "1.0.0"
requires-python = ">=3.9"
dependencies = [
"requests>=2.31.0",
"pydantic>=2.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.4.0",
"pytest-cov>=4.1.0",
"black>=23.0.0",
"ruff>=0.1.0",
"mypy>=1.5.0",
]
[tool.black]
line-length = 88
target-version = ['py39']
[tool.ruff]
line-length = 88
select = ["E", "F", "I", "N", "W"]
[tool.mypy]
python_version = "3.9"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "--cov=mypackage --cov-report=term-missing"
```
## Quick Reference: Python Idioms
| Idiom | Description |
|-------|-------------|
| EAFP | Easier to Ask Forgiveness than Permission |
| Context managers | Use `with` for resource management |
| List comprehensions | For simple transformations |
| Generators | For lazy evaluation and large datasets |
| Type hints | Annotate function signatures |
| Dataclasses | For data containers with auto-generated methods |
| `__slots__` | For memory optimization |
| f-strings | For string formatting (Python 3.6+) |
| `pathlib.Path` | For path operations (Python 3.4+) |
| `enumerate` | For index-element pairs in loops |
## Anti-Patterns to Avoid
```python
# Bad: Mutable default arguments
def append_to(item, items=[]):
items.append(item)
return items
# Good: Use None and create new list
def append_to(item, items=None):
if items is None:
items = []
items.append(item)
return items
# Bad: Checking type with type()
if type(obj) == list:
process(obj)
# Good: Use isinstance
if isinstance(obj, list):
process(obj)
# Bad: Comparing to None with ==
if value == None:
process()
# Good: Use is
if value is None:
process()
# Bad: from module import *
from os.path import *
# Good: Explicit imports
from os.path import join, exists
# Bad: Bare except
try:
risky_operation()
except:
pass
# Good: Specific exception
try:
risky_operation()
except SpecificError as e:
logger.error(f"Operation failed: {e}")
```
__Remember__: Python code should be readable, explicit, and follow the principle of least surprise. When in doubt, prioritize clarity over cleverness.
@@ -0,0 +1,622 @@
---
name: python-testing-patterns
description: Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
---
# Python Testing Patterns
Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and test-driven development practices.
## When to Use This Skill
- Writing unit tests for Python code
- Setting up test suites and test infrastructure
- Implementing test-driven development (TDD)
- Creating integration tests for APIs and services
- Mocking external dependencies and services
- Testing async code and concurrent operations
- Setting up continuous testing in CI/CD
- Implementing property-based testing
- Testing database operations
- Debugging failing tests
## Core Concepts
### 1. Test Types
- **Unit Tests**: Test individual functions/classes in isolation
- **Integration Tests**: Test interaction between components
- **Functional Tests**: Test complete features end-to-end
- **Performance Tests**: Measure speed and resource usage
### 2. Test Structure (AAA Pattern)
- **Arrange**: Set up test data and preconditions
- **Act**: Execute the code under test
- **Assert**: Verify the results
### 3. Test Coverage
- Measure what code is exercised by tests
- Identify untested code paths
- Aim for meaningful coverage, not just high percentages
### 4. Test Isolation
- Tests should be independent
- No shared state between tests
- Each test should clean up after itself
## Quick Start
```python
# test_example.py
def add(a, b):
return a + b
def test_add():
"""Basic test example."""
result = add(2, 3)
assert result == 5
def test_add_negative():
"""Test with negative numbers."""
assert add(-1, 1) == 0
# Run with: pytest test_example.py
```
## Fundamental Patterns
### Pattern 1: Basic pytest Tests
```python
# test_calculator.py
import pytest
class Calculator:
"""Simple calculator for testing."""
def add(self, a: float, b: float) -> float:
return a + b
def subtract(self, a: float, b: float) -> float:
return a - b
def multiply(self, a: float, b: float) -> float:
return a * b
def divide(self, a: float, b: float) -> float:
if b == 0:
raise ValueError("Cannot divide by zero")
return a / b
def test_addition():
"""Test addition."""
calc = Calculator()
assert calc.add(2, 3) == 5
assert calc.add(-1, 1) == 0
assert calc.add(0, 0) == 0
def test_subtraction():
"""Test subtraction."""
calc = Calculator()
assert calc.subtract(5, 3) == 2
assert calc.subtract(0, 5) == -5
def test_multiplication():
"""Test multiplication."""
calc = Calculator()
assert calc.multiply(3, 4) == 12
assert calc.multiply(0, 5) == 0
def test_division():
"""Test division."""
calc = Calculator()
assert calc.divide(6, 3) == 2
assert calc.divide(5, 2) == 2.5
def test_division_by_zero():
"""Test division by zero raises error."""
calc = Calculator()
with pytest.raises(ValueError, match="Cannot divide by zero"):
calc.divide(5, 0)
```
### Pattern 2: Fixtures for Setup and Teardown
```python
# test_database.py
import pytest
from typing import Generator
class Database:
"""Simple database class."""
def __init__(self, connection_string: str):
self.connection_string = connection_string
self.connected = False
def connect(self):
"""Connect to database."""
self.connected = True
def disconnect(self):
"""Disconnect from database."""
self.connected = False
def query(self, sql: str) -> list:
"""Execute query."""
if not self.connected:
raise RuntimeError("Not connected")
return [{"id": 1, "name": "Test"}]
@pytest.fixture
def db() -> Generator[Database, None, None]:
"""Fixture that provides connected database."""
# Setup
database = Database("sqlite:///:memory:")
database.connect()
# Provide to test
yield database
# Teardown
database.disconnect()
def test_database_query(db):
"""Test database query with fixture."""
results = db.query("SELECT * FROM users")
assert len(results) == 1
assert results[0]["name"] == "Test"
@pytest.fixture(scope="session")
def app_config():
"""Session-scoped fixture - created once per test session."""
return {
"database_url": "postgresql://localhost/test",
"api_key": "test-key",
"debug": True
}
@pytest.fixture(scope="module")
def api_client(app_config):
"""Module-scoped fixture - created once per test module."""
# Setup expensive resource
client = {"config": app_config, "session": "active"}
yield client
# Cleanup
client["session"] = "closed"
def test_api_client(api_client):
"""Test using api client fixture."""
assert api_client["session"] == "active"
assert api_client["config"]["debug"] is True
```
### Pattern 3: Parameterized Tests
```python
# test_validation.py
import pytest
def is_valid_email(email: str) -> bool:
"""Check if email is valid."""
return "@" in email and "." in email.split("@")[1]
@pytest.mark.parametrize("email,expected", [
("user@example.com", True),
("test.user@domain.co.uk", True),
("invalid.email", False),
("@example.com", False),
("user@domain", False),
("", False),
])
def test_email_validation(email, expected):
"""Test email validation with various inputs."""
assert is_valid_email(email) == expected
@pytest.mark.parametrize("a,b,expected", [
(2, 3, 5),
(0, 0, 0),
(-1, 1, 0),
(100, 200, 300),
(-5, -5, -10),
])
def test_addition_parameterized(a, b, expected):
"""Test addition with multiple parameter sets."""
from test_calculator import Calculator
calc = Calculator()
assert calc.add(a, b) == expected
# Using pytest.param for special cases
@pytest.mark.parametrize("value,expected", [
pytest.param(1, True, id="positive"),
pytest.param(0, False, id="zero"),
pytest.param(-1, False, id="negative"),
])
def test_is_positive(value, expected):
"""Test with custom test IDs."""
assert (value > 0) == expected
```
### Pattern 4: Mocking with unittest.mock
```python
# test_api_client.py
import pytest
from unittest.mock import Mock, patch, MagicMock
import requests
class APIClient:
"""Simple API client."""
def __init__(self, base_url: str):
self.base_url = base_url
def get_user(self, user_id: int) -> dict:
"""Fetch user from API."""
response = requests.get(f"{self.base_url}/users/{user_id}")
response.raise_for_status()
return response.json()
def create_user(self, data: dict) -> dict:
"""Create new user."""
response = requests.post(f"{self.base_url}/users", json=data)
response.raise_for_status()
return response.json()
def test_get_user_success():
"""Test successful API call with mock."""
client = APIClient("https://api.example.com")
mock_response = Mock()
mock_response.json.return_value = {"id": 1, "name": "John Doe"}
mock_response.raise_for_status.return_value = None
with patch("requests.get", return_value=mock_response) as mock_get:
user = client.get_user(1)
assert user["id"] == 1
assert user["name"] == "John Doe"
mock_get.assert_called_once_with("https://api.example.com/users/1")
def test_get_user_not_found():
"""Test API call with 404 error."""
client = APIClient("https://api.example.com")
mock_response = Mock()
mock_response.raise_for_status.side_effect = requests.HTTPError("404 Not Found")
with patch("requests.get", return_value=mock_response):
with pytest.raises(requests.HTTPError):
client.get_user(999)
@patch("requests.post")
def test_create_user(mock_post):
"""Test user creation with decorator syntax."""
client = APIClient("https://api.example.com")
mock_post.return_value.json.return_value = {"id": 2, "name": "Jane Doe"}
mock_post.return_value.raise_for_status.return_value = None
user_data = {"name": "Jane Doe", "email": "jane@example.com"}
result = client.create_user(user_data)
assert result["id"] == 2
mock_post.assert_called_once()
call_args = mock_post.call_args
assert call_args.kwargs["json"] == user_data
```
### Pattern 5: Testing Exceptions
```python
# test_exceptions.py
import pytest
def divide(a: float, b: float) -> float:
"""Divide a by b."""
if b == 0:
raise ZeroDivisionError("Division by zero")
if not isinstance(a, (int, float)) or not isinstance(b, (int, float)):
raise TypeError("Arguments must be numbers")
return a / b
def test_zero_division():
"""Test exception is raised for division by zero."""
with pytest.raises(ZeroDivisionError):
divide(10, 0)
def test_zero_division_with_message():
"""Test exception message."""
with pytest.raises(ZeroDivisionError, match="Division by zero"):
divide(5, 0)
def test_type_error():
"""Test type error exception."""
with pytest.raises(TypeError, match="must be numbers"):
divide("10", 5)
def test_exception_info():
"""Test accessing exception info."""
with pytest.raises(ValueError) as exc_info:
int("not a number")
assert "invalid literal" in str(exc_info.value)
```
For advanced patterns including async testing, monkeypatching, temporary files, conftest setup, property-based testing, database testing, CI/CD integration, and configuration files, see [references/advanced-patterns.md](references/advanced-patterns.md)
## Test Design Principles
### One Behavior Per Test
Each test should verify exactly one behavior. This makes failures easy to diagnose and tests easy to maintain.
```python
# BAD - testing multiple behaviors
def test_user_service():
user = service.create_user(data)
assert user.id is not None
assert user.email == data["email"]
updated = service.update_user(user.id, {"name": "New"})
assert updated.name == "New"
# GOOD - focused tests
def test_create_user_assigns_id():
user = service.create_user(data)
assert user.id is not None
def test_create_user_stores_email():
user = service.create_user(data)
assert user.email == data["email"]
def test_update_user_changes_name():
user = service.create_user(data)
updated = service.update_user(user.id, {"name": "New"})
assert updated.name == "New"
```
### Test Error Paths
Always test failure cases, not just happy paths.
```python
def test_get_user_raises_not_found():
with pytest.raises(UserNotFoundError) as exc_info:
service.get_user("nonexistent-id")
assert "nonexistent-id" in str(exc_info.value)
def test_create_user_rejects_invalid_email():
with pytest.raises(ValueError, match="Invalid email format"):
service.create_user({"email": "not-an-email"})
```
## Testing Best Practices
### Test Organization
```python
# tests/
# __init__.py
# conftest.py # Shared fixtures
# test_unit/ # Unit tests
# test_models.py
# test_utils.py
# test_integration/ # Integration tests
# test_api.py
# test_database.py
# test_e2e/ # End-to-end tests
# test_workflows.py
```
### Test Naming Convention
A common pattern: `test_<unit>_<scenario>_<expected_outcome>`. Adapt to your team's preferences.
```python
# Pattern: test_<unit>_<scenario>_<expected>
def test_create_user_with_valid_data_returns_user():
...
def test_create_user_with_duplicate_email_raises_conflict():
...
def test_get_user_with_unknown_id_returns_none():
...
# Good test names - clear and descriptive
def test_user_creation_with_valid_data():
"""Clear name describes what is being tested."""
pass
def test_login_fails_with_invalid_password():
"""Name describes expected behavior."""
pass
def test_api_returns_404_for_missing_resource():
"""Specific about inputs and expected outcomes."""
pass
# Bad test names - avoid these
def test_1(): # Not descriptive
pass
def test_user(): # Too vague
pass
def test_function(): # Doesn't explain what's tested
pass
```
### Testing Retry Behavior
Verify that retry logic works correctly using mock side effects.
```python
from unittest.mock import Mock
def test_retries_on_transient_error():
"""Test that service retries on transient failures."""
client = Mock()
# Fail twice, then succeed
client.request.side_effect = [
ConnectionError("Failed"),
ConnectionError("Failed"),
{"status": "ok"},
]
service = ServiceWithRetry(client, max_retries=3)
result = service.fetch()
assert result == {"status": "ok"}
assert client.request.call_count == 3
def test_gives_up_after_max_retries():
"""Test that service stops retrying after max attempts."""
client = Mock()
client.request.side_effect = ConnectionError("Failed")
service = ServiceWithRetry(client, max_retries=3)
with pytest.raises(ConnectionError):
service.fetch()
assert client.request.call_count == 3
def test_does_not_retry_on_permanent_error():
"""Test that permanent errors are not retried."""
client = Mock()
client.request.side_effect = ValueError("Invalid input")
service = ServiceWithRetry(client, max_retries=3)
with pytest.raises(ValueError):
service.fetch()
# Only called once - no retry for ValueError
assert client.request.call_count == 1
```
### Mocking Time with Freezegun
Use freezegun to control time in tests for predictable time-dependent behavior.
```python
from freezegun import freeze_time
from datetime import datetime, timedelta
@freeze_time("2026-01-15 10:00:00")
def test_token_expiry():
"""Test token expires at correct time."""
token = create_token(expires_in_seconds=3600)
assert token.expires_at == datetime(2026, 1, 15, 11, 0, 0)
@freeze_time("2026-01-15 10:00:00")
def test_is_expired_returns_false_before_expiry():
"""Test token is not expired when within validity period."""
token = create_token(expires_in_seconds=3600)
assert not token.is_expired()
@freeze_time("2026-01-15 12:00:00")
def test_is_expired_returns_true_after_expiry():
"""Test token is expired after validity period."""
token = Token(expires_at=datetime(2026, 1, 15, 11, 30, 0))
assert token.is_expired()
def test_with_time_travel():
"""Test behavior across time using freeze_time context."""
with freeze_time("2026-01-01") as frozen_time:
item = create_item()
assert item.created_at == datetime(2026, 1, 1)
# Move forward in time
frozen_time.move_to("2026-01-15")
assert item.age_days == 14
```
### Test Markers
```python
# test_markers.py
import pytest
@pytest.mark.slow
def test_slow_operation():
"""Mark slow tests."""
import time
time.sleep(2)
@pytest.mark.integration
def test_database_integration():
"""Mark integration tests."""
pass
@pytest.mark.skip(reason="Feature not implemented yet")
def test_future_feature():
"""Skip tests temporarily."""
pass
@pytest.mark.skipif(os.name == "nt", reason="Unix only test")
def test_unix_specific():
"""Conditional skip."""
pass
@pytest.mark.xfail(reason="Known bug #123")
def test_known_bug():
"""Mark expected failures."""
assert False
# Run with:
# pytest -m slow # Run only slow tests
# pytest -m "not slow" # Skip slow tests
# pytest -m integration # Run integration tests
```
### Coverage Reporting
```bash
# Install coverage
pip install pytest-cov
# Run tests with coverage
pytest --cov=myapp tests/
# Generate HTML report
pytest --cov=myapp --cov-report=html tests/
# Fail if coverage below threshold
pytest --cov=myapp --cov-fail-under=80 tests/
# Show missing lines
pytest --cov=myapp --cov-report=term-missing tests/
```
For advanced patterns (async testing, monkeypatching, property-based testing, database testing, CI/CD integration, and configuration), see [references/advanced-patterns.md](references/advanced-patterns.md)
@@ -0,0 +1,411 @@
# Python Testing Patterns — Advanced Reference
Advanced testing patterns including async code, monkeypatching, temporary files, conftest setup, property-based testing, database testing, CI/CD integration, and configuration.
## Pattern 6: Testing Async Code
```python
# test_async.py
import pytest
import asyncio
async def fetch_data(url: str) -> dict:
"""Fetch data asynchronously."""
await asyncio.sleep(0.1)
return {"url": url, "data": "result"}
@pytest.mark.asyncio
async def test_fetch_data():
"""Test async function."""
result = await fetch_data("https://api.example.com")
assert result["url"] == "https://api.example.com"
assert "data" in result
@pytest.mark.asyncio
async def test_concurrent_fetches():
"""Test concurrent async operations."""
urls = ["url1", "url2", "url3"]
tasks = [fetch_data(url) for url in urls]
results = await asyncio.gather(*tasks)
assert len(results) == 3
assert all("data" in r for r in results)
@pytest.fixture
async def async_client():
"""Async fixture."""
client = {"connected": True}
yield client
client["connected"] = False
@pytest.mark.asyncio
async def test_with_async_fixture(async_client):
"""Test using async fixture."""
assert async_client["connected"] is True
```
## Pattern 7: Monkeypatch for Testing
```python
# test_environment.py
import os
import pytest
def get_database_url() -> str:
"""Get database URL from environment."""
return os.environ.get("DATABASE_URL", "sqlite:///:memory:")
def test_database_url_default():
"""Test default database URL."""
# Will use actual environment variable if set
url = get_database_url()
assert url
def test_database_url_custom(monkeypatch):
"""Test custom database URL with monkeypatch."""
monkeypatch.setenv("DATABASE_URL", "postgresql://localhost/test")
assert get_database_url() == "postgresql://localhost/test"
def test_database_url_not_set(monkeypatch):
"""Test when env var is not set."""
monkeypatch.delenv("DATABASE_URL", raising=False)
assert get_database_url() == "sqlite:///:memory:"
class Config:
"""Configuration class."""
def __init__(self):
self.api_key = "production-key"
def get_api_key(self):
return self.api_key
def test_monkeypatch_attribute(monkeypatch):
"""Test monkeypatching object attributes."""
config = Config()
monkeypatch.setattr(config, "api_key", "test-key")
assert config.get_api_key() == "test-key"
```
## Pattern 8: Temporary Files and Directories
```python
# test_file_operations.py
import pytest
from pathlib import Path
def save_data(filepath: Path, data: str):
"""Save data to file."""
filepath.write_text(data)
def load_data(filepath: Path) -> str:
"""Load data from file."""
return filepath.read_text()
def test_file_operations(tmp_path):
"""Test file operations with temporary directory."""
# tmp_path is a pathlib.Path object
test_file = tmp_path / "test_data.txt"
# Save data
save_data(test_file, "Hello, World!")
# Verify file exists
assert test_file.exists()
# Load and verify data
data = load_data(test_file)
assert data == "Hello, World!"
def test_multiple_files(tmp_path):
"""Test with multiple temporary files."""
files = {
"file1.txt": "Content 1",
"file2.txt": "Content 2",
"file3.txt": "Content 3"
}
for filename, content in files.items():
filepath = tmp_path / filename
save_data(filepath, content)
# Verify all files created
assert len(list(tmp_path.iterdir())) == 3
# Verify contents
for filename, expected_content in files.items():
filepath = tmp_path / filename
assert load_data(filepath) == expected_content
```
## Pattern 9: Custom Fixtures and Conftest
```python
# conftest.py
"""Shared fixtures for all tests."""
import pytest
@pytest.fixture(scope="session")
def database_url():
"""Provide database URL for all tests."""
return "postgresql://localhost/test_db"
@pytest.fixture(autouse=True)
def reset_database(database_url):
"""Auto-use fixture that runs before each test."""
# Setup: Clear database
print(f"Clearing database: {database_url}")
yield
# Teardown: Clean up
print("Test completed")
@pytest.fixture
def sample_user():
"""Provide sample user data."""
return {
"id": 1,
"name": "Test User",
"email": "test@example.com"
}
@pytest.fixture
def sample_users():
"""Provide list of sample users."""
return [
{"id": 1, "name": "User 1"},
{"id": 2, "name": "User 2"},
{"id": 3, "name": "User 3"},
]
# Parametrized fixture
@pytest.fixture(params=["sqlite", "postgresql", "mysql"])
def db_backend(request):
"""Fixture that runs tests with different database backends."""
return request.param
def test_with_db_backend(db_backend):
"""This test will run 3 times with different backends."""
print(f"Testing with {db_backend}")
assert db_backend in ["sqlite", "postgresql", "mysql"]
```
## Pattern 10: Property-Based Testing
```python
# test_properties.py
from hypothesis import given, strategies as st
import pytest
def reverse_string(s: str) -> str:
"""Reverse a string."""
return s[::-1]
@given(st.text())
def test_reverse_twice_is_original(s):
"""Property: reversing twice returns original."""
assert reverse_string(reverse_string(s)) == s
@given(st.text())
def test_reverse_length(s):
"""Property: reversed string has same length."""
assert len(reverse_string(s)) == len(s)
@given(st.integers(), st.integers())
def test_addition_commutative(a, b):
"""Property: addition is commutative."""
assert a + b == b + a
@given(st.lists(st.integers()))
def test_sorted_list_properties(lst):
"""Property: sorted list is ordered."""
sorted_lst = sorted(lst)
# Same length
assert len(sorted_lst) == len(lst)
# All elements present
assert set(sorted_lst) == set(lst)
# Is ordered
for i in range(len(sorted_lst) - 1):
assert sorted_lst[i] <= sorted_lst[i + 1]
```
## Testing Database Code
```python
# test_database_models.py
import pytest
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker, Session
Base = declarative_base()
class User(Base):
"""User model."""
__tablename__ = "users"
id = Column(Integer, primary_key=True)
name = Column(String(50))
email = Column(String(100), unique=True)
@pytest.fixture(scope="function")
def db_session() -> Session:
"""Create in-memory database for testing."""
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(engine)
SessionLocal = sessionmaker(bind=engine)
session = SessionLocal()
yield session
session.close()
def test_create_user(db_session):
"""Test creating a user."""
user = User(name="Test User", email="test@example.com")
db_session.add(user)
db_session.commit()
assert user.id is not None
assert user.name == "Test User"
def test_query_user(db_session):
"""Test querying users."""
user1 = User(name="User 1", email="user1@example.com")
user2 = User(name="User 2", email="user2@example.com")
db_session.add_all([user1, user2])
db_session.commit()
users = db_session.query(User).all()
assert len(users) == 2
def test_unique_email_constraint(db_session):
"""Test unique email constraint."""
from sqlalchemy.exc import IntegrityError
user1 = User(name="User 1", email="same@example.com")
user2 = User(name="User 2", email="same@example.com")
db_session.add(user1)
db_session.commit()
db_session.add(user2)
with pytest.raises(IntegrityError):
db_session.commit()
```
## CI/CD Integration
```yaml
# .github/workflows/test.yml
name: Tests
on: [push, pull_request]
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
pip install -e ".[dev]"
pip install pytest pytest-cov
- name: Run tests
run: |
pytest --cov=myapp --cov-report=xml
- name: Upload coverage
uses: codecov/codecov-action@v3
with:
file: ./coverage.xml
```
## Configuration Files
```ini
# pytest.ini
[pytest]
testpaths = tests
python_files = test_*.py
python_classes = Test*
python_functions = test_*
addopts =
-v
--strict-markers
--tb=short
--cov=myapp
--cov-report=term-missing
markers =
slow: marks tests as slow
integration: marks integration tests
unit: marks unit tests
e2e: marks end-to-end tests
```
```toml
# pyproject.toml
[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = ["test_*.py"]
addopts = [
"-v",
"--cov=myapp",
"--cov-report=term-missing",
]
[tool.coverage.run]
source = ["myapp"]
omit = ["*/tests/*", "*/migrations/*"]
[tool.coverage.report]
exclude_lines = [
"pragma: no cover",
"def __repr__",
"raise AssertionError",
"raise NotImplementedError",
]
```
+4 -3
View File
@@ -7,6 +7,8 @@ permissions:
jobs:
build_arch:
runs-on: archlinux
outputs:
version: ${{ steps.pkg_version.outputs.version }}
steps:
- name: Checkout Current Repo
@@ -22,8 +24,7 @@ jobs:
- name: Extract package version
id: pkg_version
run: |
PKGFILE=$(ls external/*.pkg.tar.zst)
PKGVERSION=$(basename "$PKGFILE" | sed 's/^rscli-git-\(r[^ ]*\)-.*$/\1/')
PKGVERSION=$(pacman -Qp external/*.pkg.tar.zst | awk '{print $2}')
echo "PKGVERSION=$PKGVERSION" >> $GITHUB_ENV
echo "version=$PKGVERSION" >> $GITHUB_OUTPUT
- name: Upload Artifact
@@ -45,7 +46,7 @@ jobs:
path: ./dist
- name: Create Git Tag
run: |
VERSION=$(ls dist/*.pkg.tar.zst | sed 's/^rscli-git-\(r[^ ]*\)-.*$/\1/')
VERSION="${{ needs.build_arch.outputs.version }}"
git tag "$VERSION"
git push origin "$VERSION"
echo "VERSION=$VERSION" >> $GITHUB_ENV
+37
View File
@@ -0,0 +1,37 @@
# AGENTS.md
## Project Overview
- **Project**: rscli - Python CLI for a social network API
- **Entry point**: `rcli` command (defined in pyproject.toml as `rscli.main:app`)
- **Python version**: >= 3.14
- **Dependencies**: prettytable, requests, typer
## Running the CLI
```bash
rcli --help # Show commands
rcli version # Show version
rcli login # Login to API
rcli api_uri <url> # Set API URI
```
## Configuration
- Config stored at: `~/.config/rs-cli/config.json`
- Contains: `token`, `API_URI`
## Development
- Install locally: `pip install -e .` or use `uv pip install -e .`
- Project uses **uv** for dependency management (see uv.lock)
## CI/Build
- Gitea workflows in `.gitea/workflows/build.yml`
- Builds Arch Linux package (.pkg.tar.zst)
- Publishes releases to Gitea
## Available Skills
- python-patterns
- python-testing-patterns
- python-executor
## Notes
- No test suite currently exists in the repo
- Config class supports dot-notation paths (e.g., `config.get("token")`)
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{
"version": 1,
"skills": {
"python-executor": {
"source": "inferen-sh/skills",
"sourceType": "autoskills-registry",
"computedHash": "bd2d874c27788964fadf03c0840049de0409407f06f883ee90886164cb22ef69"
},
"python-patterns": {
"source": "affaan-m/everything-claude-code",
"sourceType": "autoskills-registry",
"computedHash": "5c344cc64b19a9a7aecb9b5fa977175acd8e55a169f86901d28eb57c637869b4"
},
"python-testing-patterns": {
"source": "wshobson/agents",
"sourceType": "autoskills-registry",
"computedHash": "07b87d62993c0b6159a91d18fc8723b7f4c13d5000c0984266c207493ce641ff"
}
}
}