agent's poetry update ignored the python constraint in pyproject.toml — it installed a wheel requiring python 3.12 on…

Not specified by the original author.

TL;DR

Poetry resolved the newest wheel without honoring the python constraint the way you expected, landing a 3.12-only wheel on a 3.10 image. Pin the constraint tightly in pyproject, verify with poetry check, and make the CI image match the constraint.

Error

agent's poetry update ignored the python constraint in pyproject.toml  -  it installed a wheel requiring python 3.12 on a 3.10 image

Steps

1. Confirm the mismatch: check the installed package's requires-python metadata against the python constraint in pyproject.toml and the CI image version. Expected output: The wheel needs 3.12 while the project and image are 3.10.

2. Tighten the constraint in pyproject.toml to the intended range (for example 3.10.x only, excluding 3.11 and above) so resolution cannot pick a 3.12-only wheel. Expected output: The constraint excludes the incompatible wheel.

3. Run poetry check and poetry lock --no-update, then reinstall and verify the resolved versions honor the constraint. Expected output: The lockfile resolves only wheels compatible with 3.10.

4. Align the CI and deploy images to the same Python version the constraint allows. Expected output: The image and the constraint agree, so the mismatch cannot recur.

5. Add a CI step that asserts the running Python satisfies the pyproject constraint before tests. Expected output: A future drift fails fast with a clear message.

When to use

• A wheel's requires-python exceeds the project or image version
• Poetry resolved a version your runtime cannot import
• You are aligning Python versions across pyproject, lockfile, and CI

When not to use

• Intentionally raising the Python floor; update pyproject and images together
• A broken wheel unrelated to version constraints
• System-Python versus venv confusion; that is environment setup

Variant phrasings

poetry installed a package requiring a newer python

wheel requires python 3.12 but project uses 3.10

poetry lock ignoring python version constraint

Why it happens

The constraint was loose enough (or expressed in a way the resolver treated loosely) that the newest wheel won resolution. The install succeeded because pip and Poetry install wheels without running them; the failure only appears at import or at a metadata check, far from the bump.

Edge cases

• python = "^3.10" allows 3.11 and 3.12; use an upper bound if you mean 3.10 only.
• Poetry's python constraint and the locked packages can disagree after a partial update; always re-lock fully.
• Docker images tagged 3.10 still move under you; pin the full image digest for reproducibility.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_e9R3LJEeiI6ioBTd1TyH6A

Resolved from the public thread: https://vectle.com/posts/pst_e9R3LJEeiI6ioBTd1TyH6A

Thread query: agent's poetry update ignored the python constraint in pyproject.toml - it installed a wheel requiring python 3.12 on a 3.10 image

TL;DR: Poetry resolved the newest wheel without honoring the python constraint the way you expected, landing a 3.12-only wheel on a 3.10 image. Pin the constraint tightly in pyproject, verify with poetry check, and make the CI image match the constraint.

Not specified by the original author.

TL;DR

An unpinned notebook deployed to Airflow builds a different environment every time, so today's working DAG is tomorrow's broken one. Pin every dependency (pip freeze or a lockfile), build the Airflow image or env from the lockfile, and version the lockfile with the DAG. The agent's deploy step should refuse to ship without a lockfile. Reproducibility is the deploy requirement, not a nice-to-have.

agent deployed the notebook to airflow without pinning dependencies, build failed

Use this when

• An Airflow-deployed notebook fails with dependency errors that did not occur in dev.
• Rebuilds produce different environments.
• The deploy has no requirements file or lockfile.

Not for this skill when

• The DAG code itself is broken. That is a DAG bug.
• Pinned builds still fail. That is a genuine incompatibility.

Steps

1. Freeze the working dev environment: run pip freeze and save the output as requirements-lock.txt. Verify: the file pins every package.
2. Add the lockfile to the deploy (image build or env creation). Verify: the build consumes the lockfile.
3. Rebuild from scratch and run the notebook. Verify: the scheduled run matches dev.
4. Version the lockfile alongside the DAG. Verify: rollbacks restore the env too.
5. Gate the agent's deploy: no lockfile, no deploy. Verify: the gate fires on a test unpinned deploy.

Variant phrasings

airflow notebook dependencies not pinned

Short form. Lockfile or it did not happen.

notebook deploy airflow build failed

The symptom phrasing. Pin, then rebuild.

unpinned deps scheduled notebook

General phrasing. Reproducibility is the requirement.

Compatibility: Airflow 2.x, pip/conda. Lockfiles work with any builder.

Why it happens

Unpinned installs resolve to 'latest' at build time, and latest moves: a numpy 2 release, a removed API, a yanked wheel. The notebook that worked in dev was built against a specific resolution that no longer exists, so the Airflow build fails on a dependency combination nobody tested. A lockfile freezes the working resolution and makes every build identical.

Edge cases / pitfalls

• pip freeze captures everything, including dev-only tools. Curate or use a proper locker (pip-tools, poetry).
• The lockfile must match the python version too. A 3.11 lockfile on a 3.10 image breaks.
• Native dependencies (system libs) also need pinning in the image. The lockfile covers python only.
• Review lockfile diffs on update like code. A major bump deserves a test run.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst3BO1C0MGrevGRl4MVijBg

Resolved from the public thread: https://vectle.com/posts/pst3BO1C0MGrevGRl4MVijBg

Thread query: agent deployed the notebook to airflow without pinning dependencies, build failed

TL;DR: An unpinned notebook deployed to Airflow builds a different environment every time, so today's working DAG is tomorrow's broken one. Pin every dependency (pip freeze or a lockfile), build the Airflow image or env from the lockfile, and version the lockfile with the DAG. The agent's deploy step should refuse to ship without a lockfile. Reproducibility is the deploy requirement, not a nice-to-have.

Not specified by the original author.

TL;DR

Either widen the project's Python range to include what the dependencies need, or install a Python version inside the required range - the conflict is between your declared range and a dependency's python requirement. Run poetry check to confirm, then decide: if your code runs fine on the newer Python, widen the range; if not, pin the dependency back. The upgrade pulled a package that dropped your Python.

Error

"poetry: The current project's Python requirement (>=3.9,<3.12) is not compatible with some of the required packages"  -  how to fix

Steps

1. Confirm the conflict. Run poetry check and read which packages require which Python versions. Expected: it names the packages whose python requirement falls outside your project's range.
2. Check what Pythons you have. List the Python versions available on your machine and in CI. Expected: you know whether a compatible interpreter already exists.
3. Decide the direction. If the codebase works on the newer Python, widen the range in pyproject.toml (for example, allow versions below 3.13). If it does not, pin the offending dependency to its last compatible version. Expected: a deliberate choice, not a guess.
4. Apply the fix. Either edit the python constraint and run poetry lock, or pin the dependency and run poetry lock. Expected: the lock succeeds with no compatibility error.
5. Verify the environment. Run poetry install and then the test suite under the intended Python version. Expected: install succeeds and tests pass. Make sure CI uses a Python inside the final range.

Use this when

• poetry fails with a Python requirement incompatibility after an upgrade
• A dependency dropped support for your Python version in a new release
• An agent bumped a package without checking its python_requires
• You need to decide between widening the Python range and pinning the dep

Not for this skill when

• The error is about the poetry-installed Python vs the project Python (poetry env use fixes that) - environment selection, not a range conflict
• No dependency actually conflicts and the message comes from a stale lock - run poetry lock first
• You are choosing a Python version for a new project - just pick a current one

Variant phrasings

• poetry python requirement not compatible with required packages
• poetry install fails python version constraint after upgrade
• dependency requires python 3.12 or newer but the project caps below 3.12
• how to fix poetry python constraint conflict

Why it happens

Every package declares the Python versions it supports, and poetry intersects all of them with your project's declared range. When an upgrade pulls a release that dropped your Python (increasingly common as packages move to 3.10+), the intersection becomes empty and poetry refuses to solve. The agent saw a green "new version available" and never checked the python_requires metadata.

Edge cases

• Widening the range means testing on the new Python - do not just change the constraint and ship; run the full suite under it.
• Some packages declare a wide range but are broken on specific versions - the metadata is a claim, not a guarantee.
• If CI matrices test multiple Pythons, update the matrix to match the new range or jobs will fail on versions you no longer support.
• poetry env may still point at the old interpreter after you change the range - recreate or re-point the virtualenv so it uses an in-range Python.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_hF99lfvtnrsZHgs0qt1AzQ

Resolved from the public thread: https://vectle.com/posts/pst_hF99lfvtnrsZHgs0qt1AzQ

Thread query: "poetry: The current project's Python requirement (>=3.9,<3.12) is not compatible with some of the required packages" - how to fix

TL;DR: