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Add the validation layers that gate a merge — ty typing, Ruff linting, pytest coverage, structured logging, and the trivy, pip-audit, and gitleaks scans. Use when hardening code quality or wiring the mise run check task.
Add the validation layers that gate a merge — ty typing, Ruff linting, pytest coverage, structured logging, and the trivy, pip-audit, and gitleaks scans. Use when hardening code quality or wiring the mise run check task.
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To ensure software quality, reliability, and security through automated validation layers. This skill enforces Strict Typing (ty), Unified Linting (ruff), Comprehensive Testing (pytest), Structured Logging, and Supply-Chain Scanning (pip-audit, gitleaks, trivy).
uv; Tasks: miseEvery check below is a mise task, so the same command runs locally, in the git hook, and in CI. Never invoke the underlying tool by hand in a hook or a workflow — the task is the single definition.
| Task | Tool | What it proves |
|---|---|---|
check:format | dprint, validate-pyproject, ruff format --check, uv lock --check | Files and manifests are canonical and the lockfile is current. |
check:lint | ruff check | No lint violation, including the S (security) rules. |
check:types | ty check | Type annotations are consistent. |
check:vuln | pip-audit | No known CVE in the resolved Python dependencies. |
check:leaks | gitleaks | No secret in the staged change or the recent history. |
check:scan | trivy | No misconfiguration, leaked secret, or forbidden license in the tree. |
check:actions | actionlint, zizmor | Workflows are valid and not vulnerable. |
test | pytest | Behavior is covered and correct. |
mise run check runs the check:* tasks in parallel; mise run all chains format -> check -> test -> build and is the only gate anyone needs to remember.
Catch errors before they run.
ty (Astral type checker; pre-1.0, pin a compatible range such as ty>=0.0.69,<0.1). The mandated checker — do not use mypy.Any (unless absolutely necessary). Fully typed function signatures.ty does not yet model every dynamic library (MLflow, pandera, Pydantic). Silence the specific rule categories they trigger in [tool.ty.rules], with a comment saying why — never disable the checker wholesale.pandera schemas to validate DataFrame structures/types.pydantic for data modeling and runtime validation.ruff 0.16+ (replaces black, isort, pylint, flake8, bandit).noqa sparingly and with justification.pyproject.toml, with an explicit [tool.ruff.lint] select list. Ruff 0.16 expanded the default rule set from 59 to 413 rules, so a project that relies on the default set changes behavior on upgrade while an explicit select list does not..md files. Expect a one-time reformat of your documentation on the first run, and commit it.Verify behavior and prevent regressions.
Tool: pytest (9.x).
Structure: Mirror src/ in tests/.
src/pkg/mod.py -> tests/test_mod.py
Fixtures: Use tests/conftest.py for shared setup (mock data, temp paths).
Coverage: Measure with pytest-cov and set --cov-fail-under to the level the suite actually reaches, so any drop is a visible regression rather than slack under a round number.
Pattern: Use Given-When-Then in comments.
def test_pipeline_execution(input_data):
# Given: Valid input data
# When: The pipeline processes the data
# Then: The output content matches expectations
MLflow in tests: Point the tests at a SQLite tracking store, not the deprecated file store — but build it once. Creating a fresh MLflow SQLite database runs the full Alembic migration chain (measured at roughly 7 seconds per database), so a session-scoped fixture should migrate one template database and each test should shutil.copyfile it into its own tmp_path (roughly 0.07 seconds). Migrating per test turned a 34-second suite into a 339-second one.
Enable observability and debugging.
loguru, configured through a small logging service so sinks and levels stay configurable. The wider house standard for long-lived services is structlog; both emit structured records, so choose one per project and stay with it — running both splits the log stream and doubles the configuration surface.DEBUG: Low-level tracing (payloads, internal state).INFO: Key business events (Job started, Model saved).ERROR: Actionable failures (with stack traces).print in library code — Ruff's T20 rules enforce it.Protect the supply chain and runtime.
S (flake8-bandit) rules to detect unsafe patterns (e.g., eval, yaml.load) — this replaces standalone bandit, and runs inside check:lint.check:vuln runs pip-audit --skip-editable against the resolved environment; Dependabot opens the update pull requests on a weekly schedule.check:leaks runs gitleaks. Scan the staged change in the pre-commit hook (--staged) and the recent history in CI (--log-opts="--max-count=100"); a scheduled workflow rescans the full history weekly, because a secret committed and later removed is invisible to a shallow scan forever.check:scan runs trivy --config trivy.yaml fs . — one pass covering vulnerabilities, misconfigurations (Dockerfile, IaC), secrets, and license compliance. Two details matter: pass --config explicitly, or a TRIVY_CONFIG exported in a developer's shell silently overrides the committed policy; and use the fs subcommand, because trivy config only runs the misconfiguration scanner and quietly skips the rest.check:actions runs actionlint (syntax, shell) and zizmor (workflow security: injection, over-broad permissions, credential persistence).mise run check:types pass?mise run check:lint pass with an explicit select list?pytest successfully find modules in src/?check:lint (Ruff S), check:vuln, check:leaks, check:scan, and check:actions all pass?mise run all pass end to end?name: mlops-validation description: Add the validation layers that gate a merge — ty typing, Ruff linting, pytest coverage, structured logging, and the trivy, pip-audit, and gitleaks scans. Use when hardening code quality or wiring the mise run check task. license: MIT metadata: author: Médéric HURIER (Fmind) source: github.com/MLOps-Courses/mlops-coding-skills/tree/main/mlops-validation created: 2026-01-25 updated: 2026-08-10
---
name: mlops-validation
description: Add the validation layers that gate a merge — ty typing, Ruff linting, pytest coverage, structured logging, and the trivy, pip-audit, and gitleaks scans. Use when hardening code quality or wiring the mise run check task.
license: MIT
metadata:
author: Médéric HURIER (Fmind)
source: github.com/MLOps-Courses/mlops-coding-skills/tree/main/mlops-validation
created: 2026-01-25
updated: 2026-08-10
---
# MLOps Validation
## Goal
To ensure software quality, reliability, and security through automated validation layers. This skill enforces **Strict Typing** (`ty`), **Unified Linting** (`ruff`), **Comprehensive Testing** (`pytest`), **Structured Logging**, and **Supply-Chain Scanning** (`pip-audit`, `gitleaks`, `trivy`).
## Prerequisites
- **Language**: Python 3.14
- **Manager**: `uv`; **Tasks**: `mise`
- **Context**: Ensuring code quality before merge/deploy.
## Instructions
### 1. The Task Vocabulary
Every check below is a `mise` task, so the same command runs locally, in the git hook, and in CI. Never invoke the underlying tool by hand in a hook or a workflow — the task is the single definition.
| Task | Tool | What it proves |
| --------------- | ------------------------------------------------------------------------ | --------------------------------------------------------------------- |
| `check:format` | `dprint`, `validate-pyproject`, `ruff format --check`, `uv lock --check` | Files and manifests are canonical and the lockfile is current. |
| `check:lint` | `ruff check` | No lint violation, including the `S` (security) rules. |
| `check:types` | `ty check` | Type annotations are consistent. |
| `check:vuln` | `pip-audit` | No known CVE in the resolved Python dependencies. |
| `check:leaks` | `gitleaks` | No secret in the staged change or the recent history. |
| `check:scan` | `trivy` | No misconfiguration, leaked secret, or forbidden license in the tree. |
| `check:actions` | `actionlint`, `zizmor` | Workflows are valid and not vulnerable. |
| `test` | `pytest` | Behavior is covered and correct. |
`mise run check` runs the `check:*` tasks in parallel; `mise run all` chains `format` -> `check` -> `test` -> `build` and is the only gate anyone needs to remember.
### 2. Static Analysis (Typing & Linting)
Catch errors before they run.
1. **Typing**:
- **Tool**: `ty` (Astral type checker; pre-1.0, pin a compatible range such as `ty>=0.0.69,<0.1`). The mandated checker — do not use `mypy`.
- **Rule**: No `Any` (unless absolutely necessary). Fully typed function signatures.
- **Pragmatism**: `ty` does not yet model every dynamic library (MLflow, pandera, Pydantic). Silence the specific rule categories they trigger in `[tool.ty.rules]`, with a comment saying why — never disable the checker wholesale.
- **DataFrames**: Use `pandera` schemas to validate DataFrame structures/types.
- **Classes**: Use `pydantic` for data modeling and runtime validation.
1. **Linting & Formatting**:
- **Tool**: `ruff` 0.16+ (replaces black, isort, pylint, flake8, bandit).
- **Rule**: Zero tolerance for linter errors. Use `noqa` sparingly and with justification.
- **Config**: Centralize in `pyproject.toml`, with an explicit `[tool.ruff.lint] select` list. Ruff 0.16 expanded the _default_ rule set from 59 to 413 rules, so a project that relies on the default set changes behavior on upgrade while an explicit `select` list does not.
- **Markdown**: Ruff 0.16 also formats Python code blocks inside `.md` files. Expect a one-time reformat of your documentation on the first run, and commit it.
### 3. Testing Strategy
Verify behavior and prevent regressions.
1. **Tool**: `pytest` (9.x).
1. **Structure**: Mirror `src/` in `tests/`.
```text
src/pkg/mod.py -> tests/test_mod.py
```
1. **Fixtures**: Use `tests/conftest.py` for shared setup (mock data, temp paths).
1. **Coverage**: Measure with `pytest-cov` and set `--cov-fail-under` to the level the suite actually reaches, so any drop is a visible regression rather than slack under a round number.
1. **Pattern**: Use **Given-When-Then** in comments.
```python
def test_pipeline_execution(input_data):
# Given: Valid input data
# When: The pipeline processes the data
# Then: The output content matches expectations
```
1. **MLflow in tests**: Point the tests at a SQLite tracking store, not the deprecated file store — but build it once. Creating a fresh MLflow SQLite database runs the full Alembic migration chain (measured at roughly 7 seconds per database), so a session-scoped fixture should migrate one template database and each test should `shutil.copyfile` it into its own `tmp_path` (roughly 0.07 seconds). Migrating per test turned a 34-second suite into a 339-second one.
### 4. Structured Logging
Enable observability and debugging.
1. **Tool**: `loguru`, configured through a small logging service so sinks and levels stay configurable. The wider house standard for long-lived services is `structlog`; both emit structured records, so choose one per project and stay with it — running both splits the log stream and doubles the configuration surface.
1. **Format**: Use structured logging (JSON) in production for queryability.
1. **Levels**:
- `DEBUG`: Low-level tracing (payloads, internal state).
- `INFO`: Key business events (Job started, Model saved).
- `ERROR`: Actionable failures (with stack traces).
1. **Context**: Include context (Job ID, Model Version) in logs.
1. **Discipline**: No bare `print` in library code — Ruff's `T20` rules enforce it.
### 5. Security
Protect the supply chain and runtime.
1. **Code Scanning**: Enable Ruff `S` (flake8-bandit) rules to detect unsafe patterns (e.g., `eval`, `yaml.load`) — this replaces standalone `bandit`, and runs inside `check:lint`.
1. **Dependencies**: `check:vuln` runs `pip-audit --skip-editable` against the resolved environment; **Dependabot** opens the update pull requests on a weekly schedule.
1. **Secret Scanning**: `check:leaks` runs `gitleaks`. Scan the staged change in the pre-commit hook (`--staged`) and the recent history in CI (`--log-opts="--max-count=100"`); a scheduled workflow rescans the **full** history weekly, because a secret committed and later removed is invisible to a shallow scan forever.
1. **Filesystem Scanning**: `check:scan` runs `trivy --config trivy.yaml fs .` — one pass covering vulnerabilities, misconfigurations (Dockerfile, IaC), secrets, and license compliance. Two details matter: pass `--config` explicitly, or a `TRIVY_CONFIG` exported in a developer's shell silently overrides the committed policy; and use the `fs` subcommand, because `trivy config` only runs the misconfiguration scanner and quietly skips the rest.
1. **Workflow Scanning**: `check:actions` runs `actionlint` (syntax, shell) and `zizmor` (workflow security: injection, over-broad permissions, credential persistence).
1. **Secrets**: **NEVER** log secrets. Sanitize outputs.
## Self-Correction Checklist
- [ ] **Type Safety**: Does `mise run check:types` pass?
- [ ] **Lint Cleanliness**: Does `mise run check:lint` pass with an explicit `select` list?
- [ ] **Test Discovery**: Does `pytest` successfully find modules in `src/`?
- [ ] **Test Speed**: Is the MLflow store built once and copied, not migrated per test?
- [ ] **Log Format**: Are production logs serializing to JSON, from one logging library?
- [ ] **Security**: Do `check:lint` (Ruff `S`), `check:vuln`, `check:leaks`, `check:scan`, and `check:actions` all pass?
- [ ] **Gate**: Does `mise run all` pass end to end?
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
49/100
Needs review
Trust
55/100
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"api": "https://www.openagentskill.com/api/agent/skills/mlops-courses-mlops-validation",
"audit": "https://www.openagentskill.com/skills/mlops-courses-mlops-validation/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=mlops-courses-mlops-validation&task=Use%20mlops-validation%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20mlops-validation%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20mlops-validation%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/mlops-courses-mlops-validation/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/mlops-courses-mlops-validation"
}
}Listing source
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Do not auto-install
Audit
67/100
Needs review
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