一键在 Manus 中运行任何 Skill

write-tests

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分支7

更新时间2026年3月31日 17:42

Write or update unit tests for changed code, following project conventions and ensuring coverage meets the 80% threshold.

安装

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在 Manus 中运行

来源

JetBrains

JetBrains/databao-cli

打开 GitHub 仓库查看创作者相关仓库

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在 Manus 中运行

Write Tests

Steps

1. Identify what to test

Read the source module(s). Focus on:

Public functions and CLI command handlers
Branches: error paths, edge cases, validation
New or changed behavior

Skip: third-party internals, Streamlit UI, trivial pass-throughs.

2. Locate or create test file

Tests in tests/ mirror source modules:

Source	Test file
`src/databao_cli/commands/init.py`	`tests/test_init.py`
`src/databao_cli/commands/build.py`	`tests/test_build.py`
`src/databao_cli/mcp/tools/<name>.py`	`tests/test_mcp.py`
`src/databao_cli/commands/datasource/add.py`	`tests/test_add_datasource.py`

Add to existing file when possible.

3. Conventions

pytest only, no unittest.TestCase.
Use project_layout fixture for project dirs, tmp_path for filesystem.
CLI: click.testing.CliRunner, import cli from databao_cli.__main__.
One behavior per test: test_<action>_<scenario>.
Return type -> None on all test functions.
Mock external I/O, not internal modules.

4. Write tests (Arrange/Act/Assert)

Specific assertions over truthiness. Include context:

assert result.exit_code == 0, f"Expected success but got: {result.output}"

5. Run and verify

uv run pytest tests/test_<module>.py -v
make test-cov-check

Repeat until 80% threshold met.

6. Lint

Run make check. Fix ruff/mypy errors in test code.

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name	write-tests
description	Write or update unit tests for changed code, following project conventions and ensuring coverage meets the 80% threshold.

Write Tests

Steps

1. Identify what to test

Read the source module(s). Focus on:

Public functions and CLI command handlers
Branches: error paths, edge cases, validation
New or changed behavior

Skip: third-party internals, Streamlit UI, trivial pass-throughs.

2. Locate or create test file

Tests in tests/ mirror source modules:

Source	Test file
`src/databao_cli/commands/init.py`	`tests/test_init.py`
`src/databao_cli/commands/build.py`	`tests/test_build.py`
`src/databao_cli/mcp/tools/<name>.py`	`tests/test_mcp.py`
`src/databao_cli/commands/datasource/add.py`	`tests/test_add_datasource.py`

Add to existing file when possible.

3. Conventions

pytest only, no unittest.TestCase.
Use project_layout fixture for project dirs, tmp_path for filesystem.
CLI: click.testing.CliRunner, import cli from databao_cli.__main__.
One behavior per test: test_<action>_<scenario>.
Return type -> None on all test functions.
Mock external I/O, not internal modules.

4. Write tests (Arrange/Act/Assert)

Specific assertions over truthiness. Include context:

assert result.exit_code == 0, f"Expected success but got: {result.output}"

5. Run and verify

uv run pytest tests/test_<module>.py -v
make test-cov-check

Repeat until 80% threshold met.

6. Lint

Run make check. Fix ruff/mypy errors in test code.