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Package Management
Python dependency management and packaging in one tool
★ 4.5
Virtual Environment Manager
★ 4.6
pip install poetrypip install virtualenvpip install poetrypip install virtualenvPython data engineers use Poetry to standardize project setup across the team — running `poetry install` from a cloned repo installs all pinned dependencies in an isolated virtual environment in one step, eliminating environment drift between machines. The `poetry add pandas==2.0` command adds a package, resolves its transitive dependencies against the full graph, and updates `poetry.lock` atomically, preventing the 'it works on my machine' problem. For pipeline projects with separate concerns, `poetry add --group dev pytest great-expectations` keeps test and quality tooling out of the production install. Teams publishing internal data libraries to a private PyPI registry use `poetry publish --repository private-pypi` to handle build and upload in a single authenticated step.
Python data engineers use virtualenv to isolate pipeline dependencies on shared servers and development machines — each project gets its own environment with pinned library versions, preventing conflicts between pipelines that depend on different versions of pandas or SQLAlchemy. Most modern projects use `python -m venv` (built-in) or Poetry instead.
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