[Snyk] Security upgrade python from 3.13.1-alpine to 3.14.2-alpine

[kevin-benton]

Snyk has created this PR to fix 4 vulnerabilities in the dockerfile dependencies of this project.

Keeping your Docker base image up-to-date means you’ll benefit from security fixes in the latest version of your chosen image.

Snyk changed the following file(s):

• docker/umap/Dockerfile

We recommend upgrading to python:3.14.2-alpine, as this image has only 0 known vulnerabilities. To do this, merge this pull request, then verify your application still works as expected.

Vulnerabilities that will be fixed with an upgrade:

	Issue	Score
	Integer Overflow or Wraparound SNYK-ALPINE321-SQLITE-12675067	264
	CVE-2025-6965 SNYK-ALPINE321-SQLITE-11191065	263
	Integer Overflow or Wraparound SNYK-ALPINE321-SQLITE-9712340	161
	CVE-2025-26519 SNYK-ALPINE321-MUSL-8720634	139
	CVE-2025-26519 SNYK-ALPINE321-MUSL-8720634	139

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Important

• Check the changes in this PR to ensure they won't cause issues with your project.
• Max score is 1000. Note that the real score may have changed since the PR was raised.
• This PR was automatically created by Snyk using the credentials of a real user.

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Learn how to fix vulnerabilities with free interactive lessons:

🦉 Integer Overflow or Wraparound

[kevin-benton]

This upgrade to Python 3.14 introduces significant new features and a key breaking change.

Breaking Change:

• Code using return, break, or continue to exit a finally block will now raise a SyntaxError due to the implementation of PEP 765. [4, 9]

Major Change:

• Type annotations are now evaluated lazily by default (PEP 649). This may affect advanced frameworks or libraries that perform introspection on type hints and rely on eager evaluation. [1, 2, 10]

Source: What's New in Python 3.14 documentation
Recommendation: Review code for control flow statements (return, break, continue) inside finally blocks. Validate any code that relies on the specific timing of type annotation evaluation.

Notice 🤖: This content was augmented using artificial intelligence. AI-generated content may contain errors and should be reviewed for accuracy before use.