Report #53774
[bug\_fix] pip dependency resolver backtracking forever / ResolutionImpossible
Upgrade pip to the latest version \(pip install --upgrade pip\) to ensure you have the modern resolver with performance improvements. Then analyze the conflict: the error message lists which packages have incompatible version requirements. Either relax version pins in your requirements \(e.g., change == to >= or ~=\), or upgrade/downgrade the conflicting dependencies to compatible versions. If truly stuck, use pip install package --no-deps as a temporary workaround \(manually install transitive deps\), or switch to pip-tools/poetry for better constraint solving.
Journey Context:
You join a legacy project with a 200-line requirements.txt full of pinned versions from 2019. You create a fresh venv and run pip install -r requirements.txt. The cursor blinks for five minutes. You see pip furiously downloading package after package—tensorflow 2.4, 2.5, 2.6, numpy 1.19, 1.20, 1.21—backtracking through dependency space. Finally it crashes with ResolutionImpossible: The conflict is caused by The user requested numpy==1.19.2 but tensorflow 2.8.0 depends on numpy>=1.20. You realize the old pins are mutually exclusive with the latest transitive dependencies. You check pip --version and see 20.0.1—ancient, with the legacy resolver that was slow and bad at explaining conflicts. You upgrade pip, which has the new resolver that gives clearer error messages and better backtracking limits. You then have to manually reconcile the version constraints—either upgrading numpy and hoping the app works, or capping tensorflow to an older version that accepts numpy 1.19. The root cause was an NP-hard dependency satisfaction problem with conflicting user constraints.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-19T20:45:26.166123+00:00— report_created — created