Django 6.1 has been released, introducing model field fetch modes, database-level delete options for ForeignKey.on_delete, and dictionary-based email settings. Django 6.0 moves to security-only support until April 2027. Critical security releases Django 6.0.8 and 5.2.17 patch high-severity spatial lookup flaws, DoS risks, and potential XSS in admin URLField — upgrade immediately. The Django Software Foundation is hiring its first Executive Director (US-based, applications due September 14). Python 3.15.0 RC1 is available for testing, alongside bug-fix releases 3.14.7 and 3.13.15. DjangoCon US 2026 runs August 24–28 in Chicago. Additional links cover integrating Vite with Django, a performance comparison of time-machine vs freezegun for date mocking, and a new modern REST framework for Django with async support.
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What are the new features in Django 6.1?
Django 6.1 introduces model field fetch modes, database-level delete options for ForeignKey.on_delete, and dictionary-based email settings. Django 6.0 is now out of mainstream support and will receive only security and data loss fixes until April 2027, making it important to plan an upgrade to 6.1 before that deadline. Developers planning the Django 6.1 upgrade track breaking changes and ecosystem compatibility on daily.dev.
What vulnerabilities were fixed in Django 6.0.8 and 5.2.17?
Django 6.0.8 and 5.2.17 fix high-severity spatial lookup flaws that could write files or make network requests, denial-of-service risks in language and geometry handling, and potential XSS from unsafe admin URLField values. Both releases are rated high-severity and should be applied as soon as possible. Teams running Django in production watch for security advisories like these on daily.dev.
How does time-machine compare to freezegun for mocking dates in Python tests?
time-machine is 100 to 200 times faster than freezegun across two project sizes. The difference comes from algorithmic complexity: time-machine operates in O(1) while freezegun degrades at O(n) as the number of mocked objects grows, making time-machine the better choice for large test suites. Python developers choosing between testing utilities for date mocking find comparisons like this on daily.dev.