Requirements.txt to Poetry Converter
Stop manual migration. Instantly convert legacy requirements.txt into modern [tool.poetry.dependencies] blocks.
Our parser understands Version Specifiers (`==`, `>=`, `~=`), ignores comments, and strictly formats for pyproject.toml so you can run poetry install immediately.
Why Migrate to Poetry?
Legacy requirements.txt files are flat lists. They don't separate "Production" vs "Dev" dependencies, and they don't ensure deterministic builds (unless you manual freeze everything).
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✅ Deterministic Lockfiles:
Poetry generates a
poetry.lockfile satisfying all constraints, guaranteeing the exact same environment on Prod. - ✅ Dependency Resolution: Pip often installs conflicting versions. Poetry checks the graph *before* installing.
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✅ One Config to Rule Them All:
All metadata, scripts, and dependencies live in one
pyproject.toml.
Version Syntax: Pip vs Poetry
Poetry uses a different syntax (Semantic Versioning) than Pip. Our tool handles the translation for you.
Why Migrating to Poetry Fixes "It Works on My Machine"
For years, Python developers have relied on `requirements.txt`. It's simple, but it's dangerous. It doesn't distinguish between your *direct* dependencies (what you installed) and *sub-dependencies* (what your libraries need).
❌ The Pip Trap
If you install `pandas`, pip also installs `numpy`. If you later uninstall `pandas`, `numpy` stays behind, cluttering your environment (Ghost Dependencies).
Worse, `pip freeze > requirements.txt` locks *everything* together in one flat list, making upgrades a nightmare.
✅ The Poetry Way
Poetry uses `pyproject.toml` for your main tools and `poetry.lock` for the exact versions.
It knows that `pandas` *needs* `numpy`. If you remove pandas, it auto-cleans numpy. It resolves conflicts *before* installation, preventing broken builds.
Migration Guide: From Pip to Poetry
Initialize Poetry
Run `poetry init` in your project folder to create a blank `pyproject.toml`.
Convert Dependencies
Paste your `requirements.txt` into the tool above. Select all the TOML output.
Update pyproject.toml
Open your new `pyproject.toml` and paste the `[tool.poetry.dependencies]` block.
Install & Lock
Run `poetry install`. This generates the golden `poetry.lock` file. Commit this file!
Deep Dive: Caret (^) vs Tilde (~)
Poetry defaults to Caret requirements, which allows updates that do *not* modify the left-most non-zero digit. This is different from pip's `~=` (compatible release).
^1.2.3
Recommended
Allows: >=1.2.3, <2.0.0
Accepts new features (1.3.0) and patches (1.2.4), but blocks breaking changes (2.0.0). Ideal for libraries following SemVer.
~1.2.3
Strict
Allows: >=1.2.3, <1.3.0
Only accepts patch updates (1.2.4). Blocks new features (1.3.0). Use this if you are paranoid about stability.
Stop bloating your Prod with Test tools
In requirements.txt, you often mix `pytest`, `black`, and `mypy` with your app code. Or you maintain awkward `requirements-dev.txt` files.
Poetry solves this natively with Groups. Keep your production image tiny by only installing what runs the app.
What is "Dependency Hell"? (And how Poetry fixes it)
Imagine Library A needs `numpy<1.20` and Library B needs `numpy>=1.22`. If you use pip, it might install them in an order that breaks one of them.
The SAT Solver Solution
Poetry features a comprehensive dependency resolver. It maps out the entire graph of every single package before installing a single file. If a conflict exists (e.g., impossible version requirements), Poetry will fail explicitly and tell you exactly why, instead of letting you deploy a broken application.