FlyPython: Learn to ship Python with AI coding agents

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Real projects; your agent does the typing, verify.py decides when you're done.

Challenge courses with objective verification. Pick a folder from courses/, solve the contract in TASK.md with your coding agent as the tool, and prove it with verify.py — which prints a claim code per checkpoint. Prefer a guided path? COURSE.md still runs an agent-taught mode, and paths/ sequences courses into badge routes. Continue on flypython.com.

FlyPython is a practical, bilingual repository for writing good Python and turning it into products people can rely on. It combines AI-coding methods, task playbooks, runnable examples, reusable templates, and reviewed primary sources for APIs, automation, agents, Skills, and MCP.

It is not a beginner link dump. The goal is to help you move from “the agent wrote code” to “a user outcome is verified.” The repository owns the reviewed source content and data; flypython.com turns pinned versions into a browsable learning experience.

Current release: v0.1.2 — see CHANGELOG.md; release and delivery status is tracked in the repository-to-website operating model.

Start in three minutes

You need a coding agent that can run commands and reach the network (Claude Code, the Codex app, Cursor, GitHub Copilot in VS Code, DeepSeek Harness, Kimi Code, or ZCode — chat-only web AIs cannot run these courses). Install the FlyPython Skill in your agent, then paste this one sentence:

Read https://flypython.com/skills/flypython/SKILL.md and start the FlyPython course da-eda.

The agent authorizes you with a one-time link (you never hand it a password), fetches the course files itself — you download nothing — and drives the challenges with you. New to driving an agent? Start with the tool course for your agent: Hands-on Python with Claude Code, Codex app, Cursor, GitHub Copilot, DeepSeek Harness, Kimi Code, or ZCode.

Maintainers can still reproduce an example locally without any agent:

git clone https://github.com/flypythoncom/python.git
cd python
python examples/product-slug/verify.py starter --expect-failure
python examples/product-slug/verify.py solution

Verify and record a course

In the course folder, run python verify.py after each change. It tests only starter/ and reports every checkpoint:

• [open] — the task is unfinished.
• [passed] — the tests pass and verify.py prints a claim code.
• [pending] — a reflection checkpoint: answer that lesson's questions, then run python verify.py --attest l01 (repeat for each completed reflection) to get its [attested] code.

Submit only [passed] and [attested] codes through your agent or the dashboard. check --json is the versioned v2 interface; progress --json remains for older signed-receipt integrations.