Python 3.8

Python 3.8
Name	Python 3.8
Developer	Guido van Rossum, Python Software Foundation
Initial release	October 14, 2019
Latest release	3.8.16
Programming language	C, Python
Operating system	Cross-platform
License	Python Software Foundation License

Python 3.8 Python 3.8 is a major release of the Python family published by the Python Software Foundation. It introduced language syntax changes, standard library enhancements, and performance improvements that influenced projects from Dropbox deployments to Instagram services and academic projects at Massachusetts Institute of Technology. The release cycle overlapped governance and tooling efforts involving contributors from organizations such as Microsoft, Google, and the Open Source Initiative.

History and release timeline

Development for the release proceeded under steering by core developers including contributors associated with Guido van Rossum, the Python Software Foundation, and experts from Red Hat, IBM, Intel Corporation, Facebook, and NVIDIA. Milestone discussions took place at conferences like PyCon US, EuroPython, and SciPy meetings, with decisions influenced by proposals reviewed on the Python Enhancement Proposal process and implemented during sprints at events such as EuroPython Sprint Weekend and PyCon AU. The initial alpha builds were published in early 2019, followed by release candidates and the final release on October 14, 2019; subsequent maintenance releases continued into the 3.8.x series with backports coordinated by the Python Security Response Team and package maintainers from Debian, Ubuntu, Fedora Project, and Arch Linux.

New features and language changes

Significant syntax and semantics changes were introduced, including the walrus operator (assignment expressions) from PEP 572, positional-only parameters from PEP 570, and f-string support enhancements via PEP 498 discussions; these changes were debated in committees and at summits attended by representatives from Microsoft Research, Google Research, Dropbox, Quansight, and academia such as University of California, Berkeley and University of Cambridge. The walrus operator affected code patterns used by projects like NumPy, Pandas, Django, and Flask and influenced tutorials at Codecademy and Coursera offerings. Other changes touched core constructs used in systems developed by NASA, European Space Agency, and financial firms including Goldman Sachs.

Library and standard library updates

The standard library received updates to modules such as asyncio, typing, concurrent.futures, and statistics, with new APIs and optimizations that benefitted scientific stacks including SciPy, Matplotlib, and scikit-learn. Secure hashing and TLS improvements aligned with practices from OpenSSL and integrations used by GitHub, Bitbucket, and GitLab continuous integration pipelines. Packaging and installer behavior changes impacted distribution tools like pip, setuptools, wheel and binary distributions maintained by Anaconda (company) and ActiveState. Documentation revisions were coordinated with resources at Read the Docs and tutorials from Real Python and O'Reilly Media.

Performance and implementation details

Interpreter-level optimizations in the CPython implementation included faster method calls, improved handling of frame evaluation, and tweaks to the garbage collector that affected latency-sensitive services at companies such as Netflix, Spotify, and Dropbox. Work on the interpreter involved contributors from PyPy and discussions referencing virtual machine research from institutions like Carnegie Mellon University and Stanford University. Build and test tooling incorporated continuous integration from Travis CI, CircleCI, and Jenkins used across open source repositories on GitHub and Bitbucket.

Compatibility and upgrade considerations

Upgrading to this release required attention to deprecated behaviors and bytecode changes impacting applications maintained by enterprises including Salesforce, IBM, Oracle Corporation, and government projects such as those at NASA Jet Propulsion Laboratory. Dependency management with ecosystems like RubyGems and Node.js ecosystems was discussed at cross-language conferences like FOSDEM and the Linux Foundation events. Enterprise distributions such as Red Hat Enterprise Linux, Ubuntu, and SUSE provided guidance for system administrators and DevOps teams from firms like Accenture and Capgemini.

Reception and usage

Adoption was tracked by package index metrics maintained by PyPI and by surveys from organizations such as the Python Software Foundation and Stack Overflow, and discussed in media outlets like The New York Times technology sections, Wired (magazine), and The Register. Open source projects including Django, Flask, TensorFlow, PyTorch, and Home Assistant evaluated compatibility, while education platforms at Harvard University, Massachusetts Institute of Technology, and Stanford University updated curricula. Industry adoption patterns were analyzed by research firms like Gartner and Forrester Research.

Security and maintenance updates

Maintenance releases in the 3.8.x series addressed vulnerabilities reported via the CERT Coordination Center and managed by the Python Security Response Team in coordination with vendors such as Microsoft, Red Hat, Canonical (company), and cloud providers including Amazon Web Services, Google Cloud Platform, and Microsoft Azure. Backporting and support decisions referenced policies used by projects like Debian Long Term Support and advisories published by US-CERT and national computer emergency response teams such as CERT-EU.

Category:Python (programming language) releases