Dependency management, version pinning, and virtual environments often become a source of frustration in Python projects. Different machines install different versions, requirements files become messy, and package conflicts pop up unexpectedly.
This is exactly where Poetry steps in — a modern tool that brings structure, consistency, and automation to Python development.
In this guide, you’ll learn everything you need to start using Poetry confidently.
What You Will Learn
- How to create new Python projects with Poetry
- How to manage virtual environments
- How to read and configure pyproject.toml
- How to pin dependency versions
- Why poetry.lock is essential
- How to use the most important Poetry commands
- How to add Poetry to an existing project
What Is Dependency Management?
Every Python project depends on external packages — FastAPI, NumPy, Pandas, SQLAlchemy, Requests, and many more.
Dependency management ensures that:
- the correct versions are installed
- these versions are compatible with each other
- every team member uses the same versions
Without proper dependency management, projects become unstable and unpredictable.
Poetry solves all of this elegantly.
What Is Poetry?
Poetry is a modern dependency and package management tool designed to simplify the entire Python project lifecycle.
Its goal is to make Python development:
- consistent
- standardized
- secure
- reproducible
Poetry manages dependencies, virtual environments, packaging, and publishing — all through a single tool.
Starting a Project With Poetry
Poetry provides two ways to start a project depending on your needs.
1. Creating a New Project
If you want a clean, best-practice project scaffold:
poetry new project-name
This generates a ready-to-use structure:
project-name/
│
├── project_name/
│ └── __init__.py
│
├── tests/
│ └── __init__.py
│
├── pyproject.toml
└── README.md
- Adding Poetry to an Existing Project If you already have a project folder:
poetry init
Poetry will ask you a few questions and create a pyproject.toml file.
It does not change your existing folder structure — which gives you full control.
You can now add dependencies:
poetry add fastapi
poetry add --dev pytest
What Is pyproject.toml?
pyproject.toml is the modern, universal configuration file for Python projects.
It replaces multiple legacy files:
- setup.py
- setup.cfg
requirements.txt
Inside this file you’ll find:Project name and version
Dependencies
Python version
Dev dependencies
Build system information
Example:
[tool.poetry]
name = "pos-backend"
version = "0.1.0"
authors = ["Mehmet Ali Tilgen"]
[tool.poetry.dependencies]
python = "^3.11"
fastapi = "^0.115.0"
[tool.poetry.dev-dependencies]
pytest = "^7.0"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
What Is the poetry.lock File?
poetry.lock records the exact versions of all dependencies — including transitive ones.
Why is this important?
✔ Everyone on the team uses the same versions
✔ Local, CI/CD, and production environments become identical
✔ Builds become deterministic
✔ Updates are safe and intentional
You should never edit this file manually; Poetry maintains it automatically.
Essential Poetry Commands
Add a dependency
poetry add fastapi
Add a development dependency
poetry add --dev pytest
Activate the virtual environment
poetry shell
Run any command inside the environment
poetry run python main.py
Update all dependencies
poetry update
These commands cover 95% of practical use cases.
Conclusion
Poetry is more than a dependency manager — it’s a powerful ecosystem that brings order and professionalism to Python development. By unifying project setup, versioning, virtual environments, and builds under a single workflow, Poetry helps you:
- avoid conflicts
- maintain stable projects
- collaborate more effectively
- reproduce environments easily Whether you're building backend services, data pipelines, or web applications, Poetry will significantly improve your development experience.
See you in the next article!
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