Upgrade the Lambda runtime from Python 3.13 to 3.14
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Valutazione
- Difficoltà
- 3/5
- Tempo stimato
- 1-2 giorni
- Idoneità per principianti
- 70/100
- Tipo di issue
- Bug
- Chiarezza
- Specificata chiaramente
- Stato di attività
- Attiva
- Stack tecnologico
- aws, dockerfile, python
- Ambito
- devops, infrastructure
Direzione di ricerca
Inizia con Dockerfile e pyproject.toml: esamina il tag dell’immagine di base Lambda e i target Python di [tool.mypy]/[tool.black]. Ricostruisci l’immagine arm64 con un tag 3.14...-arm64 fissato e verifica che le dipendenze native (confluent-kafka, psycopg2) vengano compilate con 3.14, quindi esegui i test unitari e di integrazione su quell’immagine. Controlla i file CI/pipeline per individuare eventuali riferimenti fissati a 3.13 rimasti e segna l’attività come completata solo quando i test hanno esito positivo e gli smoke check per POST /topics/{topic_name} e /health hanno esito positivo.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
Description of Technical Debt
The local toolchain and the deployed runtime are on different Python versions:
| Where | Version | Source |
|---|---|---|
| Local venv / test runs | 3.14.7 | ./.venv/Scripts/python.exe --version |
| Container image | 3.13 | Dockerfile: public.ecr.aws/lambda/python:3.13-arm64 |
| mypy target | 3.13 | pyproject.toml [tool.mypy] python_version |
| black target | py313 | pyproject.toml [tool.black] target-version |
Every local pytest, mypy, pylint, and black run therefore executes under a different interpreter than production, and nothing in CI closes the gap.
Surfaced during review of PR #204, where the difference in annotation semantics between the two versions came up directly.
Impact of Technical Debt
- Local green does not prove production green. Anything that changed between 3.13 and 3.14 passes locally and fails on deploy. Annotation evaluation is the concrete example: PEP 649 makes annotations lazy by default in 3.14 but not in 3.13, so a forward reference that resolves on a developer machine can raise
NameErrorin Lambda. - The static analysis is checking the wrong target. mypy is told
python_version = "3.13"while running on a 3.14 interpreter, so its view of the stdlib and the developer's actual runtime disagree. - Review time is spent on it. The 3.13-vs-3.14 distinction already consumed a PR #204 thread, and will keep resurfacing while the two differ.
- The divergence widens on its own. Nothing pins the local version, so a fresh venv on a newer interpreter moves further from production without anyone noticing.
Category
DevOps / Infrastructure
Priority
Medium - Should be addressed soon
Proposed Solution
Move the deployed runtime to 3.14 so it matches what the project is already developed and tested on. The code already runs there — 290 unit tests pass locally on 3.14.7 — so this is a deployment-target change rather than a migration.
Verified against ECR Public and PyPI:
public.ecr.aws/lambda/pythonpublishes GA arm64 builds for 3.14 — 37 non-preview arm64 tags, latest3.14.2026.08.26.13-arm64.- There is no floating
3.14-arm64tag, unlike3.13-arm64. The plain3.14tag is a single-arch manifest, not a multi-arch list, so it cannot stand in for an arm64 build. The Dockerfile must pin a dated arm64 tag. - Compiled dependencies publish cp314 artifacts:
confluent-kafka==2.15.0(5 cp314 wheels),psycopg2==2.9.12(cp314 wheel, 3.14 classifier),cryptography==50.0.0(13 cp314 wheels, 3.14 classifier).aws-lambda-powertools==3.31.1declares the 3.14 classifier.
Work:
Dockerfile:FROM --platform=linux/arm64 public.ecr.aws/lambda/python:3.14.<dated>-arm64.pyproject.toml:[tool.mypy] python_version = "3.14",[tool.black] target-version = ['py314'].- Rebuild the image and confirm the source builds still succeed. This is the main risk: the Dockerfile passes
--no-binary confluent-kafkato compile against the librdkafka 2.15.0 built in the image, so the published cp314 wheels are not used and the C extension is compiled against the 3.14 C API directly.psycopg2(notpsycopg2-binary) compiles from source too. - Confirm the remaining pure-Python pins install cleanly on 3.14:
jsonschema,PyJWT,requests,boto3/botocore,aiosql. - Run the integration tests against the rebuilt image, not just unit tests, so the Kafka and Postgres paths exercise the recompiled extensions.
- Check whether CI pins a Python version anywhere and update it, so the mismatch cannot silently reappear.
Alternative: keep the runtime on 3.13 and recreate the venv on 3.13 instead, pinning the version in CI. That closes the gap equally well and avoids a runtime bump, at the cost of developing against an older interpreter. Either direction is acceptable; leaving the two apart is not.
Effort Estimate
1–2 days, dominated by rebuilding the image and validating the compiled extensions
Dependencies / Related
- PR #204, where this surfaced
- #193
Additional Context
Done when:
- The image builds on 3.14 with librdkafka and psycopg2 compiled from source.
- Unit and integration tests pass against the rebuilt image.
- No tooling config still names 3.13.
- A deployed smoke test covers one
POST /topics/{topic_name}fan-out and one/healthprobe.
- Lingua principale
- Python
- Stelle
- 4
- Fork
- 0
- Merge medio
- 20h 22m
- PR unite (30g)
- 8
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refactoring type:tech-debt
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