


Key tools for Python project dependency management are Pip and Poetry. 1. Pip is suitable for small projects with requirements.txt. It installs dependencies through pip install -r requirements.txt, but it is difficult to separate the production and production environment. 2. Poetry is a more modern tool that automatically creates virtual environments, uses pyproject.toml and poetry.lock to accurately lock dependency versions, supports development of dependency markups (such as poetry add --dev pytest), and can build publishing packages. 3. Choose based on project complexity: Use Pip for simple scripts, and recommend Poetry for professional projects to improve stability and reproducibility.
Python project dependency management is a key part of the development process, especially when teams collaborate or deployed to different environments. Using tools like Pip and Poetry can help you more clearly control the various library versions required by the project, avoiding problems such as environmental chaos and version conflicts.

What is project dependency?
Simply put, dependencies are the third-party libraries necessary for your project to run. For example, if you write a web application and use Flask, then Flask is one of your dependencies. Sometimes these dependencies also have their own dependencies (called sub-dependencies), and it is easy to make mistakes when managed manually. At this time, tools are needed to help.

Pip requirements.txt: The most basic approach
If you are just starting to get involved in Python project management, you may have used pip install -r requirements.txt
.
- All packages and versions that need to be installed are listed in the
requirements.txt
file, such as:flask==2.3.0 requests>=2.28.1
Advantages : Simple and direct, suitable for small projects or quick testing.

Disadvantages : It cannot handle the separation of development dependencies and production dependencies well, and does not support functions such as automatic creation of virtual environments.
Tips: Use
pip freeze > requirements.txt
to export all dependencies of the current environment, but be aware that this method will write all installed packages into it, which may contain content you do not want.
Poetry: A more modern way of dependency management
Poetry is a dependency management and packaging tool designed specifically for Python. It not only helps you manage dependencies, but also helps you build and publish your own packages.
Installation and initialization
You can install Poetry through the officially recommended method:
curl -sSL https://install.python-poetry.org | python3 -
Then run in the project root directory:
poetry init
This will guide you to create a pyproject.toml
file that records the basic information and dependencies of the project.
Adding dependencies is simple
Want to add a dependency? Run directly:
poetry add flask
Poetry will automatically download the latest version and update pyproject.toml
and a lock file called poetry.lock
. The latter ensures that you install the exact same version combination on different machines.
Separate the dependency
Some packages are only used in the development stage, such as pytest and black. Poetry allows you to specifically tag them as "dev" dependencies:
poetry add --dev pytest
This allows you to choose not to install these dependencies when deploying a production environment:
poetry install --no-dev
How to choose Pip or Poetry?
This problem actually depends on the size and complexity of your project:
- If you just write a small script or use it for teaching, Pip plus requirements.txt is enough.
- If you want to better manage dependency trees, lock versions, or even prepare for package releases, then use Poetry.
In addition, Poetry also supports generation of traditional distribution formats such as setup.py and wheel, and it is easier to integrate CI/CD processes.
In general, whether it is Pip or Poetry, the key is to establish a clear dependency management process. Don't wait until it is launched to find that a certain version has changed and causes the program to report an error. Using these tools well can make your project more stable and reproducible.
Basically that's it.
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