Python 2 to 3 Program Playbook
Migrate remaining Python 2 codebases to Python 3 as a coordinated program. Raise test coverage first, automate conversion, then modernize idioms and add type hints before cutting over.
Python 2 reached end of life years ago, yet long-lived backend systems still run it. This program migrates those codebases to Python 3, treating the move as a chance to modernize idioms and add type safety rather than a mechanical port. Strong test coverage is the foundation that makes the migration safe.
Phase-by-Phase
Inventory and Test Coverage. Catalog every Python 2 codebase and its third-party dependencies, flagging packages with no Python 3 release. Raise test coverage to a level where behavior changes will be detected; the migration is only as safe as the tests that guard it.
Automated Conversion. Run automated 2to3 conversion as a starting point, then fix what tooling cannot: the str/bytes split, integer division, dictionary view changes, and removed standard-library modules. A CI gate blocks Python 2 syntax from re-entering the codebase.
Modernization and Typing. Add type hints, adopt f-strings, dataclasses, and context managers, and upgrade dependencies to current versions. Static analysis in CI catches type and security issues introduced during the rewrite.
Cutover and Cleanup. Remove __future__ imports and six-style compatibility shims, cut over runtimes with a canary rollout, and decommission Python 2 interpreters. The program ends when no Python 2 remains in build or runtime.
Team and Roles
An architect sets typing and dependency standards. Backend engineers do the conversion and modernization. QA owns the coverage baseline and regression validation. DevOps maintains the CI gate and runtime cutover.
Risks and Mitigations
The str/bytes distinction is the classic source of silent bugs; targeted tests around encoding boundaries catch them. Unmaintained dependencies may force replacement or vendoring, identified in the audit. Silent behavior changes (division, ordering) are caught by the coverage raised in phase one. Coordinate shared-library upgrades so apps migrate against a stable base.
Success Criteria
Success is high test coverage, current dependencies, improved deployment frequency, and better MTTR. No Python 2 interpreter should remain in production or CI.
Tooling
Use automated conversion tooling as a first pass, type checkers and linters in CI, Docker for runtime parity, and a Git-driven pipeline. Frameworks such as Django or FastAPI host the modernized services.