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Python開発環境構築手順(VSCode, Docker, Poetry, isort, black, flake8, pytest)

Last updated at Posted at 2022-11-19

はじめに

  • Python開発環境を整備し直したときのメモです
  • コードはこちらに配置しています

どういう開発環境を作るか

  • VSCode・Docker上で実行する(ローカルでの実行を想定)
  • パッケージ管理はPoetryを利用する
  • linter, formatterはisort, black, flake8を利用する
    • コマンドだけでなくVSCodeからも利用する
  • テストはpytestを利用する
  • Jupyter Notebookも利用可能にしておく

セットアップ手順

事前準備【ローカル】

  • VSCode・Dockerのインストール
  • VSCode拡張機能Remote Developmentのインストール

設定ファイルの配置

  • (参考)フォルダ構成
.
├── .devcontainer
│   └── devcontainer.json
├── .vscode
│   ├── launch.json
│   └── settings.json
├── Dockerfile
├── pyproject.toml
├── src
│   └── sample.py
└── tests
    └── test_sample.py
.devcontainer/devcontainer.json
{
    "name": "Python39docker",
    "dockerFile": "../Dockerfile",
    "extensions": [
        "ms-python.python",
        "ms-python.vscode-pylance",
        "njpwerner.autodocstring",
        "mosapride.zenkaku",
        "streetsidesoftware.code-spell-checker"
    ],
    "forwardPorts": [8888]
}
.vscode/launch.json
{
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python39docker",
            "type": "python",
            "request": "launch",
            "program": "${file}",
            "console": "internalConsole"
        }
    ]
}
.vscode/settings.json
{
    //isort
    "editor.codeActionsOnSave": {
        "source.organizeImports": true
    },
    //black
    "editor.formatOnSave": true,
    "python.formatting.provider": "black",
    //flake8
    "python.linting.lintOnSave": true,
    "python.linting.enabled": true,
    "python.linting.pylintEnabled": false,
    "python.linting.flake8Enabled": true,
    //autoDocstring
    "autoDocstring.docstringFormat": "google"
}
Dockerfile
FROM python:3.9

# install python package
COPY pyproject.toml ./
RUN pip install poetry
RUN poetry config virtualenvs.create false \
    && poetry install --no-root

# mount dir
RUN mkdir -p /opt/mnt
WORKDIR /opt/mnt

# expose port
EXPOSE 8888
  • pyproject.toml
    • packages: sys.pathに自動的に含まれるようになる(tests配下からのパスなどで利用する)
    • (参考)その設定、pyproject.tomlに全部書けます
    • まず手動で poetry add pandas とかで試してからファイルに追記する
pyproject.toml
[tool.poetry]
name = "sample"
version = "0.1.0"
description = ""
authors = ["Your Name <you@example.com>"]
packages = [
    { include = "src" },
]

[tool.poetry.dependencies]
python = "^3.9"
pandas = "^1.5.1"
isort = "^5.10.1"
black = "^22.10.0"
pyproject-flake8 = "^5.0.4.post1"
pytest = "^7.2.0"
jupyterlab = "^3.5.0"

[tool.isort]
profile = "black"
line_length = 120

[tool.black]
line-length = 120

[tool.flake8]
max-line-length = 120
ignore = "E203,"

[tool.pytest.ini_options]
testpaths = ["tests",]
  • src/sample.py
    • サンプルコード
    • (参考)pytest
src/sample.py
import sys


def is_prime(n: int) -> bool:
    if n <= 1:
        return False

    if n == 2:
        return True

    if n % 2 == 0:
        return False

    i = 3

    while i * i <= n:
        if n % i == 0:
            return False

        i += 2

    return True

if __name__ == '__main__':
    args = sys.argv
    n = int(args[1])
    print(is_prime(n))
  • tests/test_sample.py
    • サンプルのテストコード
    • (参考)pytest
tests/test_sample.py
from src.sample import is_prime


def test_is_prime():
    assert not is_prime(1)
    assert is_prime(2)
    assert is_prime(3)
    assert not is_prime(4)
    assert is_prime(5)
    assert not is_prime(6)
    assert is_prime(7)
    assert not is_prime(8)
    assert not is_prime(9)
    assert not is_prime(10)

コンテナ起動・接続

  • コンテナ起動
$ docker build -t python39docker .
$ docker run -itd -v $(pwd):/opt/mnt -p 18888:8888 python39docker
  • コンテナにVSCodeからの接続
    • VSCode左下のリモートウィンドウ → Attach to Running Container

→ コンテナ側のVSCodeが起動するので、開発する

その他

  • linter, formatter実行
$ poetry run isort src tests
$ poetry run black src tests
$ poetry run flake8 src tests
  • テスト実行
# packageを読み込んでパス設定
$ poetry install
# テスト実行
$ poetry run pytest src tests
  • Jupyter Notebook起動
$ jupyter notebook --allow-root --port=8888 --ip=0.0.0.0 &
# jupyter lab --allow-root --port=8888 --ip=0.0.0.0 &
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