Python RPA自动化工具包

3. Install Dependencies

```bash pip install -U uv uv pip install -r requirements.txt # Full (GUI)

or: uv pip install -r requirements-nogui.txt # Headless

or: uv pip install -r requirements-docker.txt # Docker

<details>
<summary>Custom install — pick only what you need</summary>

See requirements/ directory for all available groups: ai-deepseek.txt, ai-gemini.txt, ai-ollama.txt, database.txt, excel-data.txt, mcp.txt, ocr.txt, web-automation.txt, etc.

</details>

1. Install Python 3.14

Download from python.org. On Windows, check "Add Python to PATH".

2. Install wxPython (GUI only)

<details> <summary>Python 3.14 requires a development snapshot (click to expand)</summary>

The stable release (4.2.x on PyPI) does not support Python 3.14. Download a 4.3.0-alpha .whl from wxpython.org/Phoenix/snapshot-builds matching your platform:

```bash

Build & Docker

```bash

Docker — Background service (headless, port 8866)

./build/script/docker_build_bg.sh # build + export tar ./build/script/docker_build_bg.sh --run # build + start container ./build/script/docker_build_bg.sh --no-tar # build only ./build/script/docker_build_bg.sh --push repo:tag # push to registry ./build/script/docker_build_bg.sh --dirty # use working dir (skip git archive)

Docker — Web App (port 5555)

./build/script/docker_build_webapp.sh # build + export tar ./build/script/docker_build_webapp.sh --run # build + start container ./build/script/docker_build_webapp.sh --dirty # use working dir (skip git archive) ```

Note: Build scripts default to git archive mode — only git-tracked and staged files are included in the Docker context. Use --dirty to include all working directory files (relies on .dockerignore).

Deploy to NAS

```bash

Deploy BG image (scp + docker load + start container)

./build/script/deploy_bg_to_nas.sh ./build/script/deploy_bg_to_nas.sh --no-start # only transfer + load ./build/script/deploy_bg_to_nas.sh --keep-tar # don't delete remote tar

Deploy Webapp image

./build/script/deploy_webapp_to_nas.sh

Quick Start

Screenshots

Refresh funnel routes (reset + reconfigure)

sudo ./build/script/tailscale_funnel_refresh.sh

Run pipeline and exit

python PETP_background.py --run-pipeline DAILY_REPORT --no-http

Run pipeline with initial data

python PETP_background.py --run-pipeline MY_PIPELINE --init-data '{"param":"value"}' --no-http

MCP & AI Integration

PETP exposes executions as MCP tools via Streamable-HTTP on port 8866.

🔒 Auth is fail-closed. When http_request_token is unset in petpconfig.yaml, every protected endpoint (/petp/*, /mcp) returns 501 Not Configured. Set a token before exposing the server (e.g. via Tailscale Funnel). Send it as Authorization: Bearer <token> on every request.

🔒 Security hardening (Phase 2 P0). - CMD processor: defaults to shlex.split (no shell). Set shell="yes" only for trusted commands needing pipes/redirects. - Dynamic _fn / lambda_* parameters: run in a sandbox with __import__, open, eval, exec, compile removed. Whitelisted modules: re, json, datetime, math. - Encrypted password salt: override the public default by setting env PETP_SALT or writing ~/.petp/secret (POSIX mode 0600). The default salt is logged with a WARNING — cryptocode ciphertext is not actually secret unless you set a custom salt.

Performance (headless/Docker): - Shared thread pool for concurrent tool calls (no per-request executor overhead) - Static execution cache — zero filesystem I/O after startup (no stat/mtime checks) - Processor class pre-loading on server start (eliminates cold-start latency) - Real-time task-level SSE progress notifications during long-running tools/call - Cached outputSchema parsing (same tool re-called without re-parsing mcp_desc JSON)

Built-in MCP Tools:

Claude Code / Cursor / any MCP client:

{
  "mcpServers": {
    "petp": {
      "type": "http",
      "url": "http://localhost:8866/mcp"
    }
  }
}

HTTP API (no MCP client needed):

```bash

Trigger pipeline (sync)

curl -X POST http://localhost:8866/petp/exec \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"action":"pipeline","params":{"pipeline":"MY_PIPELINE"},"wait_for_result":"true"}'

Trigger pipeline (async — poll with /petp/result)

curl -X POST http://localhost:8866/petp/exec \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"action":"pipeline","params":{"pipeline":"MY_PIPELINE"},"wait_for_result":"false"}' ```

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Troubleshooting

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