Python Virtual Environments

📋 Daftar Isi

Mengapa Virtual Environment?
venv — Built-in Virtual Env
pip dan requirements.txt
pip-tools — Dependency Pinning
Poetry — Modern Package Manager
Conda — Data Science Environment
uv — Ultra-fast Package Manager
pyproject.toml — Modern Config
Workflow Sehari-hari
Virtual Env + Docker
Best Practices
Quiz Pemahaman

1. Mengapa Virtual Environment?

Bayangkan kamu mengerjakan dua proyek: Proyek A memerlukan requests==2.28 sedangkan Proyek B memerlukan requests==2.31. Jika kamu menginstal keduanya secara global, akan terjadi konflik versi. Virtual environment menyelesaikan masalah ini.

Masalah Tanpa Virtual Environment

⚠️ Masalah Dependency Hell

Tanpa virtual environment, semua package terinstal di satu tempat global. Jika Proyek A butuh Django 4.2 dan Proyek B butuh Django 3.2, kamu tidak bisa keduanya terinstal bersamaan. Satu-satunya solusi adalah meng-uninstall dan install ulang setiap kali ganti proyek — sangat merepotkan dan rentan error.

Apa Itu Virtual Environment?

Aspek	Penjelasan
Definisi	Environment Python terisolasi dengan package dan dependency sendiri
Isolasi	Setiap venv memiliki folder `site-packages` sendiri
Python Version	Bisa menggunakan versi Python yang berbeda per proyek
No Conflict	Package di satu proyek tidak mempengaruhi proyek lain
Reproducible	Bisa di-share via `requirements.txt` untuk replikasi

Diagram: Virtual Environment Architecture

Virtual Environment Architecture

Perbandingan Tools

Tool	Type	Keunggulan	Cocok Untuk
`venv`	Built-in	Sederhana, tidak perlu install	Proyek sederhana
`pip`	Built-in	Package installer standar	Package management dasar
`pip-tools`	Third-party	Dependency pinning, reproducible	Proyek production
`Poetry`	Third-party	All-in-one (env + package + build + publish)	Library/app development
`Conda`	Third-party	Multi-language, binary packages	Data science, ML
`uv`	Third-party	Sangat cepat (Rust-based)	Semua proyek (modern)

2. venv — Built-in Virtual Environment

venv adalah modul standar Python untuk membuat virtual environment. Sudah included sejak Python 3.3, tidak perlu instalasi tambahan.

Membuat Virtual Environment

Terminal — venv Basics

# ===== Membuat virtual environment =====

# Nama konvensi: .venv atau venv
python3 -m venv .venv

# Dengan Python versi spesifik
python3.11 -m venv .venv
python3.12 -m venv .venv

# Dengan pip versi terbaru
python3 -m venv --upgrade-deps .venv

# Tanpa pip (hemat space)
python3 -m venv --without-pip .venv

# ===== Mengaktifkan virtual environment =====

# Linux / macOS:
source .venv/bin/activate

# Windows (Command Prompt):
.venv\Scripts\activate.bat

# Windows (PowerShell):
.venv\Scripts\Activate.ps1

# Windows (Git Bash):
source .venv/Scripts/activate

# ===== Setelah aktif, prompt berubah =====
# (.venv) user@machine:~/project$

# ===== Verifikasi =====
which python    # → /home/user/project/.venv/bin/python
which pip       # → /home/user/project/.venv/bin/pip
python --version

# ===== Deactivate =====
deactivate

# ===== Menghapus virtual environment =====
rm -rf .venv         # Linux/Mac
rmdir /s /q .venv    # Windows

Struktur Virtual Environment

Terminal — venv Structure

Diagram: # Struktur folder venv (Linux/macOS):

/"No. Struktur folder venv (Linux/macOS):"/
bin/
/"activate"/
/"activate.csh"/
/"activate.fish"/
python
python3
pip
/"include/"/
lib/
/"python3.11/"/
/"site-packages/  No."/
pip/
/"setuptools/"/
...
/"pyvenv.cfg"/
share/
/"Scripts/"/
/"activate.bat"/
/"activate.ps1"/
/"python.exe"/
pip.exe
Lib/
/"site-packages/"/
/"Include/"/
/"pyvenv.cfg"/
tcl/

💡 Tips

Tambahkan .venv/ ke .gitignore agar virtual environment tidak masuk ke repository. Setiap developer bisa membuat venv sendiri dari requirements.txt.

3. pip dan requirements.txt

pip adalah package installer standar untuk Python. Digunakan bersama requirements.txt untuk mengelola dependency.

pip Commands

Terminal — pip Commands

# ===== Instalasi packages =====

# Instal package terbaru
pip install requests

# Instal versi spesifik
pip install requests==2.31.0

# Instal dengan batasan versi
pip install "requests>=2.28,<3.0"
pip install "django~=4.2"      # Compatible release (>=4.2, ==4.*)
pip install "flask>=3.0"       # Minimum version

# Instal dari git
pip install git+https://github.com/user/repo.git
pip install git+https://github.com/user/repo.git@branch-name
pip install git+https://github.com/user/repo.git@v1.0.0

# Instal dari local directory
pip install ./my-package/
pip install -e ./my-package/   # Editable mode (development)

# Instal beberapa packages sekaligus
pip install requests flask sqlalchemy

# ===== Upgrade dan Uninstall =====

# Upgrade package
pip install --upgrade requests
pip install -U requests

# Upgrade pip itu sendiri
pip install --upgrade pip

# Uninstall
pip uninstall requests

# ===== List dan Info =====

# List semua package terinstal
pip list

# List dengan format columns
pip list --format=columns

# List outdated packages
pip list --outdated

# Info tentang package
pip show requests

# ===== Requirements File =====

# Generate requirements.txt dari environment saat ini
pip freeze > requirements.txt

# Instal dari requirements.txt
pip install -r requirements.txt

# Instal dari requirements.txt dengan upgrade
pip install -r requirements.txt --upgrade

# ===== Cache =====

# Lihat cache
pip cache info

# Hapus cache
pip cache purge

requirements.txt Best Practices

Text — requirements.txt

# requirements.txt — Production (pinned versions)
# Untuk reproducible builds

# Web framework
django==4.2.13
djangorestframework==3.15.2

# Database
psycopg2-binary==2.9.9
sqlalchemy==2.0.31

# HTTP
requests==2.32.3
httpx==0.27.0

# Task queue
celery==5.4.0
redis==5.0.7

# Testing
pytest==8.2.2
pytest-django==4.8.0
pytest-cov==5.0.0

# Development
ruff==0.5.0
mypy==1.10.0
ipython==8.25.0

Text — requirements.in (unpinned)

# requirements.in — Base requirements (unpinned)
# Digunakan dengan pip-tools untuk generate pinned requirements.txt

django>=4.2,<5.0
djangorestframework>=3.15
psycopg2-binary>=2.9
sqlalchemy>=2.0
requests>=2.28
httpx>=0.27
celery>=5.4
redis>=5.0

# Dev dependencies (opsional, pisahkan ke requirements-dev.in)
pytest
pytest-django
ruff
mypy

Constraints dan Layering

Terminal — Requirements Layers

# Pisahkan dependency berdasarkan environment:

# requirements-base.txt    — shared dependencies
# requirements.txt         — production (includes base)
# requirements-dev.txt     — development (includes base + testing tools)
# requirements-test.txt    — testing only

# Contoh requirements-dev.txt:
# -r requirements.txt
pytest>=8.0
pytest-cov>=5.0
ruff>=0.5
mypy>=1.10
ipython>=8.0
debugpy>=1.8

# Menggunakan constraint file
# constraints.txt: membatasi versi tanpa menginstall
# django==4.2.13
# sqlalchemy==2.0.31

pip install -r requirements.txt -c constraints.txt

# Instal requirements-dev
pip install -r requirements-dev.txt

4. pip-tools — Dependency Pinning

pip-tools menyediakan workflow yang lebih baik untuk mengelola dependency dengan memisahkan antara requirement yang diinginkan (unpinned) dan requirement yang di-resolve (pinned).

Terminal — pip-tools

# ===== Instalasi pip-tools =====
pip install pip-tools

# ===== Workflow pip-tools =====

# 1. Buat requirements.in (input — apa yang kamu butuhkan)
# requirements.in:
# django>=4.2
# requests>=2.28
# sqlalchemy>=2.0

# 2. Compile ke requirements.txt (output — resolved, pinned)
pip-compile requirements.in
# Menghasilkan requirements.txt dengan versi exact + hash
# django==4.2.13 (via django>=4.2)
# requests==2.32.3 (via requests>=2.28)
# sqlalchemy==2.0.31 (via sqlalchemy>=2.0)
# ... beserta semua transitive dependencies

# 3. Sync environment dengan requirements.txt
pip-sync requirements.txt
# Menginstall yang kurang, menghapus yang tidak perlu

# ===== Advanced pip-tools =====

# Compile dengan upgrade semua
pip-compile --upgrade requirements.in

# Compile dengan upgrade package tertentu
pip-compile --upgrade-package django requirements.in

# Output ke file berbeda
pip-compile requirements.in -o requirements.txt

# Dev dependencies
pip-compile requirements-dev.in -o requirements-dev.txt

# Generate dengan hashes (untuk security)
pip-compile --generate-hashes requirements.in

# Sync dari multiple requirements files
pip-sync requirements.txt requirements-dev.txt

# ===== pip-tools Configuration (pyproject.toml) =====
# [tool.pip-tools]
# generate-hashes = true
# allow-unsafe = false
# strip-extras = true

Diagram: pip-tools Workflow

pip-sync
(install +
uninstall)
.venv/
(ter-sync)
PIP-TOOLS WORKFLOW
requirements.in requirements.txt
django>=4.2 compile→ django==4.2.13
requests>=2 requests==2.32.3
sqlalchemy>2 sqlalchemy==2.0.31
certifi==2024.6.2
(apa yang kamu mau) urllib3==2.2.2
... (20+ transitive)
▼
▼

5. Poetry — Modern Package Manager

Poetry adalah all-in-one tool untuk dependency management, virtual environment, building, dan publishing Python packages. Ini menjadi standar de facto untuk proyek Python modern.

Instalasi dan Setup

Terminal — Poetry Install

# ===== Instalasi Poetry =====

# Linux / macOS / WSL
curl -sSL https://install.python-poetry.org | python3 -

# Windows (PowerShell)
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -

# Atau via pip (kurang recommended)
pip install poetry

# Verifikasi
poetry --version

# ===== Konfigurasi =====
# Membuat venv di dalam project folder (recommended)
poetry config virtualenvs.in-project true

# Lihat semua konfigurasi
poetry config --list

# ===== Membuat Project Baru =====
poetry new my-project
# Menghasilkan:
# my-project/
# ├── pyproject.toml
# ├── README.md
# ├── my_project/
# │   └── __init__.py
# └── tests/
#     └── __init__.py

# Inisialisasi di project yang sudah ada
cd existing-project
poetry init

Dependency Management dengan Poetry

Terminal — Poetry Dependencies

# ===== Menambah dependencies =====

# Add production dependency
poetry add requests
poetry add "django>=4.2,<5.0"
poetry add sqlalchemy@^2.0

# Add dev dependency
poetry add --group dev pytest ruff mypy
poetry add -G dev pytest

# Add optional dependency
poetry add --group optional redis

# ===== Menghapus dependencies =====
poetry remove requests
poetry remove --group dev pytest

# ===== Install semua dependencies =====
poetry install

# Install tanpa dev dependencies
poetry install --only main

# Install hanya dev
poetry install --only dev

# ===== Update dependencies =====
# Update semua
poetry update

# Update package tertentu
poetry update requests

# ===== Lock file =====
# poetry.lock otomatis dibuat/diupdate
# SELALU commit poetry.lock ke git!

# Re-resolve semua dependencies
poetry lock

# Lock tanpa update
poetry lock --no-update

# ===== List dependencies =====
poetry show
poetry show --tree        # Dengan dependency tree
poetry show --outdated    # Package yang bisa diupdate

# ===== Export ke requirements.txt =====
poetry export -f requirements.txt --output requirements.txt
poetry export -f requirements.txt --without-hashes -o requirements.txt

pyproject.toml dengan Poetry

TOML — pyproject.toml

[tool.poetry]
name = "my-awesome-project"
version = "1.0.0"
description = "Deskripsi project kamu"
authors = ["Budi Santoso <budi@email.com>"]
license = "MIT"
readme = "README.md"
repository = "https://github.com/user/my-project"
keywords = ["python", "tutorial"]
packages = [{include = "my_project"}]

[tool.poetry.dependencies]
python = "^3.11"
django = "^4.2"
djangorestframework = "^3.15"
requests = "^2.31"
sqlalchemy = "^2.0"
celery = {version = "^5.4", extras = ["redis"]}
redis = "^5.0"
gunicorn = {version = "^22.0", optional = true}

[tool.poetry.group.dev.dependencies]
pytest = "^8.2"
pytest-cov = "^5.0"
pytest-django = "^4.8"
ruff = "^0.5"
mypy = "^1.10"
ipython = "^8.25"

[tool.poetry.group.docs.dependencies]
sphinx = "^7.3"
sphinx-rtd-theme = "^2.0"

[tool.poetry.scripts]
myproject = "my_project.cli:main"

[tool.poetry.plugins."my_project.plugins"]
myplugin = "my_project.plugins:MyPlugin"

[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

Poetry Commands Lengkap

Terminal — Poetry Commands

# ===== Virtual Environment =====
poetry env info              # Info tentang venv
poetry env list              # List semua venv
poetry env use python3.11    # Ganti Python version
poetry env remove .venv      # Hapus venv

# ===== Running =====
poetry run python script.py  # Jalankan script di venv
poetry run pytest            # Jalankan pytest di venv
poetry run python -m mymodule

# Shell di dalam venv
poetry shell
# Sekarang semua command berjalan di venv
exit  # Keluar dari shell

# ===== Building dan Publishing =====
# Build package
poetry build
# Menghasilkan dist/my_project-1.0.0.tar.gz dan .whl

# Publish ke PyPI
poetry publish

# Build + Publish
poetry publish --build

# Publish ke private repository
poetry config repositories.private https://private.pypi.org/simple/
poetry publish -r private

# ===== Check dan Versioning =====
poetry check                  # Validasi pyproject.toml
poetry version                # Lihat versi
poetry version patch          # 1.0.0 → 1.0.1
poetry version minor          # 1.0.0 → 1.1.0
poetry version major          # 1.0.0 → 2.0.0

6. Conda — Data Science Environment

Conda adalah package dan environment manager yang sangat populer di kalangan data scientist. Berbeda dengan pip yang hanya mengelola Python packages, Conda bisa mengelola packages dari berbagai bahasa (C, C++, R, dll).

Instalasi Miniconda

Terminal — Conda Install

# ===== Instalasi Miniconda (recommended, lebih ringan dari Anaconda) =====

# Linux
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

# macOS
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh
bash Miniconda3-latest-MacOSX-arm64.sh

# Windows: Download installer dari https://docs.conda.io/en/latest/miniconda.html

# Verifikasi
conda --version
conda info

# ===== Konfigurasi =====
# Auto-activate base environment (optional)
conda config --set auto_activate_base false

# Tambah channel
conda config --add channels conda-forge
conda config --set channel_priority strict

Conda Environment Management

Terminal — Conda Environments

# ===== Membuat Environment =====

# Buat env dengan Python versi spesifik
conda create -n myproject python=3.11

# Buat env dengan beberapa packages
conda create -n datascience python=3.11 numpy pandas scikit-learn jupyter

# Buat env dari file
conda env create -f environment.yml

# Buat env di folder spesifik
conda create --prefix ./envs python=3.11

# ===== Mengaktifkan / Deactivate =====
conda activate myproject
conda deactivate

# ===== List Environments =====
conda env list
# atau
conda info --envs

# ===== Install / Update / Remove Packages =====
# Install
conda install numpy pandas matplotlib
conda install -c conda-forge scikit-learn
conda install "numpy>=1.24,<2.0"

# Update
conda update numpy
conda update --all

# Remove
conda remove numpy

# ===== Export / Import Environment =====
# Export ke YAML
conda env export > environment.yml
conda env export --no-builds > environment.yml  # Tanpa build numbers

# Export hanya packages yang diinstall secara eksplisit
conda env export --from-history > environment.yml

# Import dari YAML
conda env create -f environment.yml

# Update existing env dari YAML
conda env update -f environment.yml --prune

# ===== YAML File =====
# environment.yml:
# name: myproject
# channels:
#   - conda-forge
#   - defaults
# dependencies:
#   - python=3.11
#   - numpy>=1.24
#   - pandas>=2.0
#   - scikit-learn>=1.3
#   - pip:
#     - some-pip-package>=1.0

7. uv — Ultra-fast Package Manager

uv adalah package manager baru yang ditulis dalam Rust, menawarkan kecepatan 10-100x lebih cepat dari pip. Dikembangkan oleh tim Astral (pembuat Ruff).

Terminal — uv

# ===== Instalasi uv =====
# Linux / macOS
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Atau via pip
pip install uv

# Verifikasi
uv --version

# ===== Virtual Environment =====
# Buat venv dengan uv (sangat cepat!)
uv venv
uv venv --python 3.11
uv venv .venv --python 3.12

# ===== Install Packages =====
# Install packages (10-100x lebih cepat dari pip!)
uv pip install requests
uv pip install "django>=4.2" sqlalchemy

# Install dari requirements.txt
uv pip install -r requirements.txt

# Compile requirements
uv pip compile requirements.in -o requirements.txt

# Sync environment
uv pip sync requirements.txt

# ===== uv sebagai Python Manager =====
# Install Python versions
uv python install 3.11 3.12 3.13
uv python list

# ===== uv Project Management (v0.4+) =====
# Inisialisasi project
uv init my-project
cd my-project

# Tambah dependency
uv add requests
uv add "django>=4.2"
uv add --dev pytest ruff

# Remove dependency
uv remove requests

# Run command
uv run python script.py
uv run pytest

# Lock dependencies
uv lock

# Sync environment
uv sync

# ===== Benchmark =====
# pip install (dengan cache): ~10 detik
# uv pip install (dengan cache): ~0.3 detik
# Perbedaan sangat signifikan untuk CI/CD!

💡 Mengapa uv?

uv ditulis dalam Rust dan menggunakan parallel downloading + caching yang sangat efisien. Untuk CI/CD pipeline yang perlu menginstal dependencies berkali-kali, uv bisa menghemat waktu build secara drastis. uv juga bisa menggantikan pip, pip-tools, dan bahkan virtualenv.

8. pyproject.toml — Modern Configuration

pyproject.toml adalah file konfigurasi standar modern untuk proyek Python (PEP 518, PEP 621). Menggantikan setup.py, setup.cfg, requirements.txt untuk banyak kasus.

TOML — pyproject.toml Lengkap

# pyproject.toml — Standalone (tanpa Poetry)
[project]
name = "my-project"
version = "1.0.0"
description = "Deskripsi project"
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.11"
authors = [
    {name = "Budi Santoso", email = "budi@email.com"},
]
keywords = ["python", "web", "api"]
classifiers = [
    "Development Status :: 4 - Beta",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
]

# Dependencies
dependencies = [
    "django>=4.2,<5.0",
    "djangorestframework>=3.15",
    "requests>=2.28",
    "sqlalchemy>=2.0",
]

# Optional dependencies
[project.optional-dependencies]
dev = [
    "pytest>=8.0",
    "pytest-cov>=5.0",
    "ruff>=0.5",
    "mypy>=1.10",
]
docs = [
    "sphinx>=7.3",
    "sphinx-rtd-theme>=2.0",
]
all = [
    "my-project[dev,docs]",
]

# Entry points / CLI
[project.scripts]
myproject = "my_project.cli:main"

# URLs
[project.urls]
Homepage = "https://github.com/user/my-project"
Documentation = "https://my-project.readthedocs.io"
Repository = "https://github.com/user/my-project"
Issues = "https://github.com/user/my-project/issues"

# ===== Build System =====
[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.backends._legacy:_Backend"

# ===== Tool Configurations =====

# Ruff (linter + formatter)
[tool.ruff]
target-version = "py311"
line-length = 100

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP", "B", "A", "SIM"]

# Pytest
[tool.pytest.ini_options]
testpaths = ["tests"]
python_files = "test_*.py"
addopts = "-v --tb=short --cov=my_project"

# MyPy
[tool.mypy]
python_version = "3.11"
strict = true
warn_return_any = true
warn_unused_configs = true

# Coverage
[tool.coverage.run]
source = ["my_project"]
omit = ["tests/*"]

[tool.coverage.report]
exclude_lines = [
    "pragma: no cover",
    "if TYPE_CHECKING:",
    "if __name__ == .__main__.",
]

9. Workflow Sehari-hari

Workflow Standar dengan venv + pip

Terminal — Daily Workflow

# ===== Setup Awal Project =====
mkdir my-project && cd my-project
git init

# Buat virtual environment
python3 -m venv .venv
source .venv/bin/activate   # Linux/Mac
# .venv\Scripts\activate    # Windows

# Buat file standar
touch README.md
echo ".venv/" >> .gitignore
echo "__pycache__/" >> .gitignore
echo "*.pyc" >> .gitignore

# Install dependencies
pip install django pytest ruff
pip freeze > requirements.txt

# ===== Daily Development =====
# Aktivasi (setiap buka terminal baru)
source .venv/bin/activate

# Install package baru
pip install new-package
pip freeze > requirements.txt  # Update requirements!
git add requirements.txt
git commit -m "Add new-package dependency"

# ===== Join Project yang Sudah Ada =====
git clone https://github.com/user/project.git
cd project
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

# ===== Deployment Preparation =====
pip install -r requirements.txt
python manage.py test          # Jalankan test
ruff check .                   # Lint check
python manage.py collectstatic # Django specific

Workflow dengan Poetry

Terminal — Poetry Workflow

# ===== Setup Awal =====
poetry new my-project
cd my-project
git init

# Tambah dependencies
poetry add django requests sqlalchemy
poetry add --group dev pytest ruff mypy

# ===== Daily Development =====
# Tidak perlu aktivasi manual — poetry handle semuanya!
poetry run python manage.py runserver
poetry run pytest
poetry run ruff check .

# Atau masuk ke shell
poetry shell
python manage.py runserver
pytest
exit

# Tambah dependency baru
poetry add httpx
# Poetry otomatis update pyproject.toml dan poetry.lock!

# Commit ke git
git add pyproject.toml poetry.lock
git commit -m "Add httpx dependency"

# ===== Join Project =====
git clone https://github.com/user/project.git
cd project
poetry install
# Poetry baca pyproject.toml + poetry.lock, install semua!

# ===== Update Dependencies =====
poetry update              # Update semua
poetry update requests     # Update satu package
poetry show --outdated     # Cek yang bisa diupdate

10. Virtual Env + Docker

Dockerfile — Docker + venv

# ===== Dockerfile dengan venv =====
FROM python:3.11-slim

WORKDIR /app

# Buat virtual environment
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

# Install dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy application
COPY . .

# Run
CMD ["python", "app.py"]

# ===== Dockerfile dengan Poetry =====
FROM python:3.11-slim

WORKDIR /app

# Install Poetry
RUN pip install poetry && \
    poetry config virtualenvs.in-project true

# Copy dependency files
COPY pyproject.toml poetry.lock ./

# Install dependencies (tanpa dev)
RUN poetry install --only main --no-interaction

# Copy application
COPY . .

# Activate venv
ENV PATH="/app/.venv/bin:$PATH"

CMD ["python", "app.py"]

# ===== Multi-stage build (lebih kecil) =====
FROM python:3.11-slim AS builder

WORKDIR /app
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

FROM python:3.11-slim AS runtime

WORKDIR /app
COPY --from=builder /opt/venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

COPY . .
CMD ["python", "app.py"]

# ===== docker-compose.yml =====
# version: "3.8"
# services:
#   app:
#     build: .
#     volumes:
#       - .:/app
#     ports:
#       - "8000:8000"
#     environment:
#       - DATABASE_URL=postgresql://user:pass@db:5432/mydb
#   db:
#     image: postgres:15
#     environment:
#       - POSTGRES_PASSWORD=pass

11. Best Practices

Golden Rules

Rule	Penjelasan
🔥 SELALU gunakan venv	Jangan pernah install package ke system Python secara global
📌 Pin versi di production	Gunakan exact versions (`==`) di requirements.txt
🔒 Commit lock files	`poetry.lock` dan `requirements.txt` harus masuk git
🚫 Jangan commit venv	Selalu tambahkan `.venv/` ke `.gitignore`
📋 Pisahkan deps	Pisahkan production deps dan dev deps
🔄 Update berkala	Jalankan `pip-audit` atau `pip list --outdated` secara berkala

Text — .gitignore

# .gitignore — Python project

# Virtual environments
.venv/
venv/
env/
ENV/

# Python
__pycache__/
*.py[cod]
*$py.class
*.so
*.egg-info/
dist/
build/
*.egg

# IDE
.vscode/
.idea/
*.swp
*.swo

# OS
.DS_Store
Thumbs.db

# Environment variables
.env
.env.local

# Coverage
.coverage
htmlcov/

# Mypy
.mypy_cache/

# Ruff
.ruff_cache/

# Pytest
.pytest_cache/

# Jupyter
.ipynb_checkpoints/

Kapan Menggunakan Tool Apa?

Decision Guide

# ===== Decision Tree =====
#
# Kamu membuat apa?
# │
# ├── 📚 Library yang akan di-publish ke PyPI?
# │   └── → Poetry atau Hatchling
# │
# ├── 🌐 Web application / API?
# │   └── → venv + pip-tools (atau Poetry)
# │
# ├── 📊 Data Science / Machine Learning?
# │   └── → Conda (atau mamba)
# │
# ├── 🤖 Script / Automation?
# │   └── → venv + pip (simplest)
# │
# ├── ⚡ Performance-critical CI/CD?
# │   └── → uv (sangat cepat)
# │
# └── 🏢 Enterprise / Tim besar?
#     └── → Poetry (atau PDM) + Docker
#
# ===== Quick Reference =====
#
# Tool       │ Buat Venv │ Install │ Lock │ Build │ Publish
# ───────────┼───────────┼─────────┼──────┼───────┼────────
# venv+pip   │ ✅        │ ✅      │ ❌    │ ❌     │ ❌
# pip-tools  │ ❌        │ ✅      │ ✅    │ ❌     │ ❌
# Poetry     │ ✅        │ ✅      │ ✅    │ ✅     │ ✅
# Conda      │ ✅        │ ✅      │ ❌    │ ❌     │ ❌
# uv         │ ✅        │ ✅      │ ✅    │ ✅     │ ❌
# PDM        │ ✅        │ ✅      │ ✅    │ ✅     │ ✅