Development Skill
Angular Migration
Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and…
$15
Python Testing Patterns
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven…
A comprehensive pytest toolkit for building test suites that are trustworthy, isolated, and fast: covering fixtures, mocking, parameterization, async tests, property-based testing, and database tests. It applies the Arrange-Act-Assert structure and a Shift-Left mindset so bugs get caught at commit time, not in production. The payoff is a suite you actually trust, with low flakiness and meaningful coverage instead of vanity percentages.
$15 one-time
Add to a kit → Prices include 20% VAT. · Forged on real agency work · one-time, no lock-in
- Type Skill
- Category Development
- Delivery Email · instant
- License One-time
Inside the run · no black box
See the actual work before you buy it.
The skill builds a pytest suite as a layered system, not a pile of test files. This is the order it works in and the gates it enforces:
- Structure every test as Arrange-Act-Assert with descriptive behavior names (test_login_fails_with_invalid_password), organized into test_unit, test_integration and test_e2e directories
- Design fixtures by scope economics: session scope for expensive resources like DB engines, function scope plus cleanup for isolation, shared fixtures in conftest.py, in-memory SQLite sessions for model tests
- Collapse duplicate cases with parametrize, covering valid, invalid and edge inputs in one table per function instead of five near-identical tests
- Isolate external dependencies: unittest.mock with patch for HTTP and third-party APIs (asserting call arguments, not just results), monkeypatch for env vars and attributes, tmp_path for filesystem work
- Classify with markers (slow, integration, xfail for known bugs) so daily development runs the fast subset and CI runs the full matrix across Python versions
- Gate the pipeline on coverage and properties: cov-fail-under threshold in CI, plus hypothesis property-based tests that fire hundreds of generated inputs at invariants ordinary examples miss
One power source. 6 lines out.
python-testing-patterns · core
core active · 6 lines
- ✓ write isolated unit tests
Write isolated unit tests with the AAA pattern
- ✓ build fixtures with the
Build fixtures with the right scope (function/module/session)
- ✓ mock external apis and d…
Mock external APIs and dependencies cleanly
- ✓ parameterize tests to co…
Parameterize tests to cover many inputs without duplication
- ✓ test async code and conc…
Test async code and concurrent operations
- ✓ run property-based tests
Run property-based tests with Hypothesis to find edge cases
Yours to keep.
Drag time forward. Watch what stays.
Forever
That's what owning means.
The rented stack
ai writing tool: subscription
expired · access lostanalytics suite: subscription
expired · access lostdesign platform: subscription
expired · access lost(nothing left)
Your forge
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Catch bugs at commit time, where a fix costs a fraction of a production fix
license: perpetual -
Keep tests independent so a failure points to the real cause, not shared state
license: perpetual -
Discover edge cases automatically with property-based invariants instead of hand-picked cases
license: perpetual -
Run fast feedback locally and full suites in CI using test markers
license: perpetual
subscriptions expire · deeds don't
Everything in the box.
Pick a piece up. Watch it work.
pytest fundamentals: assertions, pytest.raises, fixtures with setup/teardown
6 parts · one working system · ships instantly by email
This wasn't forged for everyone.
- Not for you if you'd rather rent a tool than own one.
- Not for you if you want someone else to run your stack.
- Not for you if you're happy guessing.
Python developers who want a reliable, maintainable test suite with strong isolation, smart mocking, and meaningful coverage rather than brittle, flaky tests.
then this was forged for you.Works with
Universal by design: these run in any AI. Delivered in the open Agent Skills + MCP format (native in Claude); ChatGPT, Gemini, Cursor and Copilot adapt the same files their own way.
- Claude Native format
- ChatGPT Adapts via open standards
- Gemini Adapts via open standards
- Cursor Adapts via open standards
- Copilot Adapts via open standards
Catch what's on your mind.
the air is clear. nothing between you and the forge.
catch a spark: the forge will answer
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Does this cover async code and database tests, or just plain unit tests?
It goes well beyond unit tests: async testing with pytest.mark.asyncio, in-memory database tests with SQLAlchemy fixtures and constraint checks, property-based testing with Hypothesis, and parameterized integration patterns. The AAA structure holds across all of them.
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How does it keep a growing suite from turning flaky?
Isolation is the core mechanism: fixtures scoped correctly (function, module, session), shared state pushed into conftest, external dependencies mocked with unittest.mock and monkeypatch, so a failure points to a real cause. Test markers split fast local feedback from the full CI matrix.
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If coverage hits the cov-fail-under bar, does that mean my code is well tested?
No. Coverage percentage is explicitly treated as a floor, not proof of quality; a line can be executed without its behavior being asserted. That is why the kit pushes property-based invariants and meaningful assertions over chasing a vanity number.
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How is it delivered?
By email right after purchase: ready to run, downloaded instantly, no setup wait.
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One-time or subscription?
A one-time purchase; no subscription or hidden fees. VAT (20%) is included.
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Can I get a refund?
As a digital product, it can’t be refunded once downloaded. That’s why we show exactly what’s inside and who it’s for, right here.