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test-sdk

Precio sin confirmar★ 86 Estrellas de GitHubRegistro actualizado · 7 sept 2026agent-skill

Resumen

End-to-end test the scrapegraph-py v2 SDK against the live API using a user-provided API key. Exercises every public method on both ScrapeGraphAI (sync) and AsyncScrapeGraphAI (async), including the crawl/monitor/history namespaces. Use when the user asks to "test the SDK", "run full SDK tests", or validate a release candidate. NEVER push directly to main — all changes go via a feature branch + PR.

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Test the scrapegraph-py v2 SDK end-to-end

Hard rules

DO NOT push directly to main. main is the protected release branch. If changes are needed, create a feature branch and open a PR. Never git push origin main, never force-push to main, never self-merge.
Never hardcode or commit the API key. Accept it from the user at runtime. Pass it via the SGAI_API_KEY env var or the ScrapeGraphAI(api_key=...) constructor. Do not write it to any file, log, or commit.
Do not modify production config (env.py, release workflows, pyproject.toml version) as part of testing.

Required input

Ask the user for their ScrapeGraph API key before doing anything else:

I need a ScrapeGraph API key to run the live SDK tests. Please paste it (I will use it in-process only and will not write it to disk or commit it).

Export it for the session only:

export SGAI_API_KEY="<user-provided-key>"

Scope — the v2 SDK surface

The SDK exposes two top-level classes in scrapegraph_py:

ScrapeGraphAI (sync) — from scrapegraph_py.client
AsyncScrapeGraphAI (async) — from scrapegraph_py.async_client

Note: there is no smartscraper, markdownify, or agentic_scraper method. Those names are stale. Use the endpoints below — they mirror the Playground (Scrape, Extract, Search, Crawl, Monitor).

Endpoints to exercise

Endpoint	Sync method	Async method
Scrape	`client.scrape(...)`	`await aclient.scrape(...)`
Extract	`client.extract(...)`	`await aclient.extract(...)`
Search	`client.search(...)`	`await aclient.search(...)`
Crawl	`client.crawl.start(...)`	`await aclient.crawl.start(...)`
Monitor	`client.monitor.create(...)`	`await aclient.monitor.create(...)`
Credits	`client.credits()`	`await aclient.credits()`

Namespace sub-methods (cover the full lifecycle)

client.crawl — start, get, stop, resume, delete
client.monitor — create, list, get, update, pause, resume, activity, delete
client.history — list, get (supporting, not shown in Playground)

The async client exposes the same namespaces under the same attribute names, with async methods. health() and close() also exist as utility methods — call health() as a sanity check at the start of the run.

Scope — test the WHOLE SDK

Every public method above must be exercised against the live API on both ScrapeGraphAI and AsyncScrapeGraphAI. Do not mock.

For each call:

Use a minimal valid payload (e.g. https://example.com + trivial prompt).
Record the response type, that it matches the returned Pydantic model / ApiResult, and any surfaced error.
For crawl / monitor: after start/create, also exercise get, then stop/pause+resume, then delete so the full lifecycle is covered and no test artifacts are left behind.
Call credits() before and after the full run so the user can see credit consumption.

Procedure

Confirm the working directory is clean (git status). If not, stop and ask the user.
Confirm you're not on main. If making commits, branch first: git checkout -b test/sdk-smoke-YYYYMMDD. Running tests without committing does not require a branch.
Install deps: uv sync.
Run the existing unit tests first: uv run pytest tests/ -v. Fix any failures before live testing.
Write a throwaway script (e.g. scripts/smoke_sdk.py) that:
- Imports ScrapeGraphAI and AsyncScrapeGraphAI from scrapegraph_py.
- Calls every top-level method and every namespace method listed above, on both clients.
- Prints a compact table: method | sync ok | async ok | notes.
Run it: uv run python scripts/smoke_sdk.py.
Delete the throwaway script. Do not commit it.
Report a summary: which methods passed, which failed, credits consumed, and any suspicious response shapes.

If you find a bug

Branch: git checkout -b fix/<short-description>.

Fix it. Then run the full pre-commit suite from CLAUDE.md:

uv run ruff format src tests
uv run ruff check src tests --fix
uv build
uv run pytest tests/ -v

Commit with a fix: prefix (keeps the semantic-release bump at patch).
Push the branch and open a PR. Do not merge to main yourself.

Reminders to surface to the user

Live tests consume API credits. Confirm before running.
If any method returns a 4xx/5xx, report it verbatim — do not retry silently more than once.
If the user's key is invalid or rate-limited, stop and tell them; do not swap in any other key.

Ver fuente ↗

Metadatos del archivo

name: test-sdk
description: End-to-end test the scrapegraph-py v2 SDK against the live API using a user-provided API key. Exercises every public method on both ScrapeGraphAI (sync) and AsyncScrapeGraphAI (async), including the crawl/monitor/history namespaces. Use when the user asks to "test the SDK", "run full SDK tests", or validate a release candidate. NEVER push directly to main — all changes go via a feature branch + PR.

Ver texto original

---
name: test-sdk
description: End-to-end test the scrapegraph-py v2 SDK against the live API using a user-provided API key. Exercises every public method on both ScrapeGraphAI (sync) and AsyncScrapeGraphAI (async), including the crawl/monitor/history namespaces. Use when the user asks to "test the SDK", "run full SDK tests", or validate a release candidate. NEVER push directly to main — all changes go via a feature branch + PR.
---

# Test the scrapegraph-py v2 SDK end-to-end

## Hard rules

1. **DO NOT push directly to `main`.** `main` is the protected release branch. If changes are needed, create a feature branch and open a PR. Never `git push origin main`, never force-push to main, never self-merge.
2. **Never hardcode or commit the API key.** Accept it from the user at runtime. Pass it via the `SGAI_API_KEY` env var or the `ScrapeGraphAI(api_key=...)` constructor. Do not write it to any file, log, or commit.
3. **Do not modify production config** (`env.py`, release workflows, `pyproject.toml` version) as part of testing.

## Required input

Ask the user for their ScrapeGraph API key before doing anything else:

> I need a ScrapeGraph API key to run the live SDK tests. Please paste it (I will use it in-process only and will not write it to disk or commit it).

Export it for the session only:

```bash
export SGAI_API_KEY="<user-provided-key>"
```

## Scope — the v2 SDK surface

The SDK exposes two top-level classes in `scrapegraph_py`:

- `ScrapeGraphAI` (sync) — from `scrapegraph_py.client`
- `AsyncScrapeGraphAI` (async) — from `scrapegraph_py.async_client`

> Note: there is **no** `smartscraper`, `markdownify`, or `agentic_scraper` method. Those names are stale. Use the endpoints below — they mirror the Playground (Scrape, Extract, Search, Crawl, Monitor).

### Endpoints to exercise

| Endpoint | Sync method | Async method |
|----------|-------------|--------------|
| Scrape   | `client.scrape(...)`            | `await aclient.scrape(...)`            |
| Extract  | `client.extract(...)`           | `await aclient.extract(...)`           |
| Search   | `client.search(...)`            | `await aclient.search(...)`            |
| Crawl    | `client.crawl.start(...)`       | `await aclient.crawl.start(...)`       |
| Monitor  | `client.monitor.create(...)`    | `await aclient.monitor.create(...)`    |
| Credits  | `client.credits()`              | `await aclient.credits()`              |

### Namespace sub-methods (cover the full lifecycle)

- `client.crawl` — `start`, `get`, `stop`, `resume`, `delete`
- `client.monitor` — `create`, `list`, `get`, `update`, `pause`, `resume`, `activity`, `delete`
- `client.history` — `list`, `get` *(supporting, not shown in Playground)*

The async client exposes the same namespaces under the same attribute names, with `async` methods. `health()` and `close()` also exist as utility methods — call `health()` as a sanity check at the start of the run.

## Scope — test the WHOLE SDK

Every public method above must be exercised against the live API on both `ScrapeGraphAI` and `AsyncScrapeGraphAI`. Do not mock.

For each call:
- Use a minimal valid payload (e.g. `https://example.com` + trivial prompt).
- Record the response type, that it matches the returned Pydantic model / `ApiResult`, and any surfaced error.
- For `crawl` / `monitor`: after `start`/`create`, also exercise `get`, then `stop`/`pause`+`resume`, then `delete` so the full lifecycle is covered and no test artifacts are left behind.
- Call `credits()` before and after the full run so the user can see credit consumption.

## Procedure

1. Confirm the working directory is clean (`git status`). If not, stop and ask the user.
2. Confirm you're not on `main`. If making commits, branch first: `git checkout -b test/sdk-smoke-YYYYMMDD`. Running tests without committing does not require a branch.
3. Install deps: `uv sync`.
4. Run the existing unit tests first: `uv run pytest tests/ -v`. Fix any failures before live testing.
5. Write a throwaway script (e.g. `scripts/smoke_sdk.py`) that:
   - Imports `ScrapeGraphAI` and `AsyncScrapeGraphAI` from `scrapegraph_py`.
   - Calls every top-level method and every namespace method listed above, on both clients.
   - Prints a compact table: method | sync ok | async ok | notes.
6. Run it: `uv run python scripts/smoke_sdk.py`.
7. Delete the throwaway script. Do not commit it.
8. Report a summary: which methods passed, which failed, credits consumed, and any suspicious response shapes.

## If you find a bug

- Branch: `git checkout -b fix/<short-description>`.
- Fix it. Then run the full pre-commit suite from `CLAUDE.md`:
  ```bash
  uv run ruff format src tests
  uv run ruff check src tests --fix
  uv build
  uv run pytest tests/ -v
  ```
- Commit with a `fix:` prefix (keeps the semantic-release bump at patch).
- Push the branch and open a PR. **Do not merge to main yourself.**

## Reminders to surface to the user

- Live tests consume API credits. Confirm before running.
- If any method returns a 4xx/5xx, report it verbatim — do not retry silently more than once.
- If the user's key is invalid or rate-limited, stop and tell them; do not swap in any other key.

Revisar el código fuente

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Licencia: MIT
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Revisar antes de instalar: Evitar instalación automática

Licencia: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 86 GitHub stars
Stars/forks activity: 86 stars, 17 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

Indexado

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente: ScrapeGraphAI/scrapegraph-py
Licencia: MIT
Versión: 1.0.0
Último push de GitHub: 31 jul 2026
Registro actualizado: 7 sept 2026
Ruta de instrucciones: .claude/skills/test-sdk/SKILL.md @ 04750f848740

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

60/100

Prometedor

Confianza

61/100

Solo sandbox

Auditoría

73/100

Requiere revisión

Abrir auditoría completa Ver informe de evaluación

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 86 GitHub stars
Stars/forks activity: 86 stars, 17 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Resultados: —

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    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
  "agent_contract": {
    "task_input": "Use test-sdk in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 69/100 Manual review",
      "Audit: 73/100 Needs review",
      "Safety: 33/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "scrapegraphai-test-sdk (test-sdk)",
      "install_command": "npx skills add ScrapeGraphAI/scrapegraph-py --skill test-sdk",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "scrapegraphai-test-sdk",
      "task": "Use test-sdk in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/scrapegraphai-test-sdk",
    "api": "https://www.openagentskill.com/api/agent/skills/scrapegraphai-test-sdk",
    "audit": "https://www.openagentskill.com/skills/scrapegraphai-test-sdk/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=scrapegraphai-test-sdk&task=Use%20test-sdk%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20test-sdk%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20test-sdk%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/scrapegraphai-test-sdk/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/scrapegraphai-test-sdk"
  }
}

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Creador: ScrapeGraphAI
Fuente: ScrapeGraphAI/scrapegraph-py
Indexado por: Índice comunitario de OpenAgentSkill

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