ClawPy: Minimal Single-File Python Implementation of OpenClaw with Experience Memory

✍️ OpenClawRadar📅 Published: March 12, 2026🔗 Source
ClawPy: Minimal Single-File Python Implementation of OpenClaw with Experience Memory
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What This Is

ClawPy is a minimal, single-file Python implementation of OpenClaw's autonomous task execution architecture. It runs directly in the terminal without heavy abstractions, focusing on raw prompt engineering, state machine logic, and subprocess execution.

Key Implementation Details

The script mirrors OpenClaw's core mechanics:

  • Recursive Task Tree: Maintains a tasks.txt state file that tracks incomplete tasks. The system reads this file, decides whether to execute tasks directly or decompose them (up to 4 levels deep), and automatically bubbles up "Completed" status.
  • Code Interpreter & Self-Healing: Uses custom XML tags (<python>) to write and run scripts locally. When execution hits a traceback, it catches the stderr, forces an <error> reflection tag to analyze the bug, and rewrites the code until it achieves Return Code 0.
  • Experience Memory System: Every time the agent successfully executes a script (explained via <msg> tags) or reflects on a crash (<error>), it appends that insight to an experience.txt file. When booted up again, the system injects truncated history of past mistakes and successes into the system prompt, preventing repetition of syntax or logical errors.
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Practical Use Cases

The developer built this for two main audiences:

  • People who want to learn exactly how the autonomous loop works under the hood without diving into a massive codebase
  • Data analysts and quants who want a lightweight agent to write and fix Pandas/financial scripts in their local environment

Important Security Note: The tool runs generated Python code directly on your machine, so the developer recommends running it in a safe environment or virtual machine.

The project is available on GitHub at https://github.com/EricChanBank/clawPy.git.

📖 Read the full source: r/openclaw

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👀 See Also