termidy/ccar-f-practice
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Practice code for the CCAR-F course: ShopAssist in Python on the Claude API, plus the Udemy labs
개요
Companion code for the practice lessons of the course. Each practice lesson is recorded in VS Code against the real Claude API, and this repository holds the project you see on screen, so you can run every step yourself. .env holds one line, ANTHROPIC_API_KEY=...; every script loads it with python-dotenv. Some lessons also need Claude Code installed and logged in. The scripts use the current API: claude-sonnet-5-5, output_config={"effort": "low"}, structured outputs through output_config.format, and the mcp package 2.x for the MCP server. If something returns a 400, check the model id and the SDK version first (anthropic>=1.12). The order IDs the tools know are ORD-12345678 (a jacket, delivered 20 days ago) and ORD-87654321 (a lamp, delivered 45 days ago). Everything else returns found: false, which is data, not an error. shopassist/.trace/ is the small observer you see beside the editor in the videos. sitecustomize.py logs every HTTP exchange of the Anthropic client to trace.
README
원문 README의 일부입니다. 원문 보기.
CCAR-F practice: ShopAssist in code
Companion code for the practice lessons of the Claude Certified Architect - Foundations (CCAR-F) course. Each practice lesson is recorded in VS Code against the real Claude API, and this repository holds the project you see on screen, so you can run every step yourself.
| Folder | What it is |
|---|---|
shopassist/ |
The practice project: one small Python script per lesson, all built on the same fictional support assistant, ShopAssist. Needs an Anthropic API key. |
starting-points/ |
The “before” version of the files that a lesson edits on screen, so you can replay the edits yourself. |
labs/ |
Jupyter notebooks to practise without an API key. |
Setup
git clone https://github.com/termidy/CCAR-F-practice.git
cd CCAR-F-practice/shopassist
python3 -m venv .venv && source .venv/bin/activate # Python 3.10+
pip install -r requirements.txt
cp .env.example .env # put your key in .env, never in the code
.env holds one line, ANTHROPIC_API_KEY=...; every script loads it with python-dotenv. Some lessons also need Claude Code installed and logged in.
The scripts use the current API: claude-sonnet-5-5, output_config={"effort": "low"}, structured outputs through
output_config.format, and the mcp package 2.x for the MCP server. If something returns a 400, check the model id and the SDK
version first (anthropic>=1.12).
The lessons
In the order of the course.
| Lesson | File(s) | What you run |
|---|---|---|
| First request in code | first_request.py |
python first_request.py - one messages.create, then content, stop_reason and usage; lower max_tokens to 20 and watch the reply get cut |
| The conversation lives in your code | conversation.py |
python conversation.py - the messages list is the only memory |
| A chat UI talks to your script | app.py, static/index.html |
uvicorn app:app --port 8000, open http://127.0.0.1:8000/ |
| System prompt rules vs code rules | rules.py (start: starting-points/p04_rules.start.py) |
python rules.py - a prompt rule is a request, a code rule is a guarantee |
| Evaluate a prompt change on a test set | evaluate.py |
python evaluate.py - two system prompts, same cases, scored by code and by a model grader |
| Your first tool call, end to end | tool_call.py |
python tool_call.py - tools=, stop_reason == "tool_use", run the function, send tool_result back |
| Schema-valid output from Claude | extract.py |
python extract.py - output_config.format with a JSON schema |
| Validate, then retry with the error | validate.py (start: starting-points/p08_validate.start.py) |
python validate.py - schema-valid is not business-valid; send the exact error back and retry, up to three attempts |
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