Python 2.4

Python 2.4
Name	Python 2.4
Developer	Python Software Foundation
Released	2004-11-30
Latest release version	2.4.6
Operating system	Cross-platform
License	PSF License

Python 2.4

Python 2.4 is a legacy release of the Python programming language produced by the Python Software Foundation with lead contributions from developers associated with BeOpen and CNRI. Released in late 2004, the release followed precedents set by earlier versions and influenced subsequent implementations such as those maintained by the Open Source Initiative, vendors like Red Hat, Debian, and projects including Zope and Django. The release occurred amid broader open-source activity involving organizations like Mozilla Foundation, Apache Software Foundation, and corporate stakeholders such as Google, IBM, and Intel.

History and Release

The development cycle for this release involved contributors from consortiums and institutions such as University of California, Berkeley, MIT, Stanford University, and Cornell University, along with corporate contributors from Microsoft and Sun Microsystems. Announcements were discussed on mailing lists similar to those operated by GNU Project and referenced practices seen in projects like Linux kernel and FreeBSD. Influences from academic work at institutions including Massachusetts Institute of Technology, Princeton University, and Carnegie Mellon University were visible in design discussions, echoing efforts by teams behind Emacs, Vim, and tools originating at Bell Labs. The release timeline intersected with events and standards activity involving bodies such as IETF, W3C, and ECMA International.

New Features and Enhancements

This version introduced language features and library additions influenced by community discussions like those involving Guido van Rossum and contributors associated with Zope Corporation, ActiveState, and Digital Equipment Corporation. Key language-level additions drew conceptual parallels to work by researchers at University of Oxford, University of Cambridge, and ETH Zurich, and echoed features used in languages developed at Bell Labs and initiatives supported by DARPA. Enhancements were debated in forums reminiscent of governance by organizations such as OSI and incorporated ideas that had appeared in toolchains used by projects like Apache HTTP Server, PostgreSQL, and MySQL.

Library and Module Changes

The standard library received updates to modules commonly used in ecosystems maintained by projects including GNOME, KDE, and applications such as GIMP and Inkscape. Improvements to networking and parsing modules reflected interoperability concerns parallel to work at Cisco Systems, Juniper Networks, and vendors participating in IETF working groups. Cryptography- and security-related modules underwent changes considered by stakeholders like RSA Security, OpenSSL, and academic groups at Caltech and Harvard University. Packaging and distribution patterns were influenced by systems used by Debian Project, Fedora Project, and package maintainers at Canonical Ltd.

Compatibility and Deprecations

Compatibility guidance paralleled compatibility efforts found in projects such as Perl, Ruby, and PHP, and was relevant to enterprise adopters including Oracle Corporation, SAP SE, and HP. Deprecation notices were discussed in conjunction with large-scale software consumers like Yahoo!, eBay, and Facebook (then early-stage projects), and were relevant to build systems used by Autoconf, Automake, and CMake. Porting advice followed patterns similar to those used by developers migrating codebases across releases of GNU Compiler Collection and LLVM.

Performance and Implementation Details

Performance tuning referenced profiling approaches comparable to those used by teams at Google, Facebook, and Netflix, and optimization techniques popularized in academic venues such as ACM and IEEE conferences. Implementation notes reflected the C-based CPython interpreter maintained by the Python Software Foundation and interactions with runtimes and toolchains provided by GCC, Clang, and Microsoft Visual C++. Memory and CPU characteristics were of interest to system integrators at Amazon Web Services, Rackspace, and institutions running research clusters at Lawrence Berkeley National Laboratory and Argonne National Laboratory.

Adoption and Impact

Adoption of this release was notable among open-source projects and commercial vendors including Canonical Ltd., Red Hat, SUSE, and IBM; web frameworks and content management systems such as Plone, Django, and Trac referenced behavior from this era. Educational use at universities like Harvard University, Stanford University, and MIT contributed to workforce skills relevant to employers such as Goldman Sachs, Morgan Stanley, and Accenture. The release influenced software engineering practices observed at organizations including NASA, ESA, and research institutions like CERN and Los Alamos National Laboratory.

Category:Python versions