testing-python
Write and evaluate effective Python tests using pytest.
Skill by benchflow-ai
Install
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About
Use cases: design, testing, writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
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Files it touches
~/.claude/skills/testing-python
What's inside
- Skill name
testing-python- Description
- Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.
- License
- Apache-2.0
- Instructions
- 217 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Writing Effective Python Tests
## Core Principles
Every test should be **atomic**, **self-contained**, and test **single functionality**. A test that tests multiple things is harder to debug and maintain.
## Test Structure
### Atomic unit tests
Each test should verify a single behavior. The test name should tell you what's broken when it fails. Multiple assertions are fine when they all verify the same behavior.
```python
# Good: Name tells you what's broken
def test_user_creation_sets_defaults():
user = User(name="Alice")
assert user.role == "member"
assert user.id is not None
assert user.created_at is not None
# Bad: If this fails, what behavior is broken?
def test_user():
user = User(name="Alice")
assert user.role == "member"
user.promote()
assert user.role == "admin"
assert user.can_delete_others()
```
### Use parameterization for variations of the same concept
```python
import pytest
@pytest.mark.parametrize("input,expected", [
("hello", "HELLO"),
("World", "WORLD"),
("", ""),
("123", "123"),
])
def test_uppercase_conversion(input, expected):
assert input.upper() == expected
```
### Use separate tests for different functionality
Don't parameterize unrelated behaviors. If the test logic differs, write separate tests.
## Project-Specific Rules
### No async markers needed
This project uses `asyncio_mode = "auto"` globally. Write async tests without decorators:
```python
# Correct
async def test_async_operation():
result = await some_async_function()
assert result == expected
# Wrong - don't add this
@pytest.mark.asyncio
async def test_async_operation():
...
```
### Imports at module level
Put ALL imports at the top of the file:
```python
# Correct
import pytest
from fastmcp import FastMCP
from fastmcp.client import Client
async def test_something():
mcp = FastMCP("test")
...
# Wrong - no local imports
async def test_something():
from fastmcp import FastMCP # Don't do this
...
```
### Use in-memory transport for testing
Pass FastMCP servers directly to clients:
```python
from fastmcp import FastMCP
from fastmcp.client import Client
mcp = FastMCP("TestServer")
@mcp.tool
def greet(name: str) -> str:
return f"Hello, {name}!"
async def test_greet_tool():
async with Client(mcp) as client:
result = await client.call_tool("greet", {"name": "World"})
assert result[0].text == "Hello, World!"
```
Only use HTTP transport when explicitly testing network features.
### Inline snapshots for complex data
Use `inline-snapshot` for testing JSON schemas and complex structures:
```python
from inline_snapshot import snapshot
def test_schema_generation():
schema = generate_schema(MyModel)
assert schema == snapshot() # Will auto-populate on first run
```From benchflow-ai/skillsbench, Apache-2.0.
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Signals
- Stars
- 1,870
- Forks
- 372
- Open issues
- 50
- Last commit (this folder)
- Jan 16, 2026 (9 months ago)
- Last release
- Jun 14, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/benchflow-ai/skillsbench
- Website
- www.skillsbench.ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
testing-python skill. Agent Mart. https://agentmart.dev/skills/benchflow-ai-testing-python (last updated 2026-10-24)