python-testing

A set of Python testing practices for pytest, a tool that runs automated checks on Python code. It covers test-driven development (TDD), where tests are written before the code, along with fixtures, mocks, parameterized tests, and coverage checks.

In plain words
What is it for?
Use it when writing Python code, designing or reviewing test suites, checking coverage, or setting up testing tools.
Why use it?
It helps catch errors early and shows which parts of the code are not tested. The TDD process also gives a clear cycle for writing and improving code.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/zte-aicloud/co-omnispec/python-testing
Any agent
npx skills add ZTE-AICloud/Co-OmniSpec --skill python-testing
Clone the repo
git clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpec

Made for: Claude Code, Codex.

Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,420 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.04420
Opus 5 $0.00012 $0.02210
Sonnet 5 $0.00005 $0.00884
Haiku 4.5 $0.00002 $0.00442

Measured 2d ago against content hash b304a8c503af, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-testing scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.get("https://api.example.com")
Origin

Copies of this mod

7 near-identical copies found in the catalogue:

omni-dsdd/skills/python-testing/SKILL.md · 817 lines

How it starts

The opening of the file, as written. The whole thing — 817 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Testing Patterns

Comprehensive testing strategies for Python applications using pytest, TDD methodology, and best practices.

When to Activate

  • Writing new Python code (follow TDD: red, green, refactor)
  • Designing test suites for Python projects
  • Reviewing Python test coverage
  • Setting up testing infrastructure

Core Testing Philosophy

Test-Driven Development (TDD)

Always follow the TDD cycle:

  1. RED: Write a failing test for the desired behavior
  2. GREEN: Write minimal code to make the test pass
  3. REFACTOR: Improve code while keeping tests green
# Step 1: Write failing test (RED)
def test_add_numbers():
    result = add(2, 3)
    assert result == 5

# Step 2: Write minimal implementation (GREEN)
def add(a, b):
    return a + b

# Step 3: Refactor if needed (REFACTOR)

Coverage Requirements

  • Target: 80%+ code coverage
  • Critical paths: 100% coverage required
  • Use pytest --cov to measure coverage
pytest --cov=mypackage --cov-report=term-missing --cov-report=html

pytest Fundamentals

Basic Test Structure

import pytest

def test_addition():
    """Test basic addition."""
    assert 2 + 2 == 4

def test_string_uppercase():
    """Test string uppercasing."""
    text = "hello"
    assert text.upper() == "HELLO"

def test_list_append():
    """Test list append."""
    items = [1, 2, 3]
    items.append(4)
    assert 4 in items
    assert len(items) == 4

Assertions

# Equality
assert result == expected

# Inequality
assert result != unexpected

# Truthiness
assert result  # Truthy
assert not result  # Falsy
assert result is True  # Exactly True
assert result is False  # Exactly False
assert result is None  # Exactly None

# Membership
assert item in collection
assert item not in collection

# Comparisons
assert result > 0
assert 0 <= result <= 100

# Type checking
assert isinstance(result, str)

# Exception testing (preferred approach)
with pytest.raises(ValueError):
    raise ValueError("error message")

# Check exception message
with pytest.raises(ValueError, match="invalid input"):
    raise ValueError("invalid input provided")

# Check exception attributes
with pytest.raises(ValueError) as exc_info:
    raise ValueError("error message")
assert str(exc_info.value) == "error message"

Read the full file on GitHub · 817 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 817 lines · 24 tokens per session scan A b304a8c503af

Subscribe to this mod's changes

python-testing is a skill published in the GitHub repository ZTE-AICloud/Co-OmniSpec (54 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 4,420 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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