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Pygame was originally written by Pete Shinners to replace PySDL after its development stalled. [2] [8] It has been a community project since 2000 [9] and is released under the free software GNU Lesser General Public License [5] (which "provides for Pygame to be distributed with open source and commercial software" [10]).
Since 7 October 2024, Python 3.13 is the latest stable release, and it and, for few more months, 3.12 are the only releases with active support including for bug fixes (as opposed to just for security) and Python 3.9, [55] is the oldest supported version of Python (albeit in the 'security support' phase), due to Python 3.8 reaching end-of-life.
Sometimes, a critical part of the program can be re-written in a different programming language that gives more direct access to the underlying machine. For example, it is common for very high-level languages like Python to have modules written in C for greater speed. Programs already written in C can have modules written in assembly.
Self-modifying code is quite straightforward to implement when using assembly language.Instructions can be dynamically created in memory (or else overlaid over existing code in non-protected program storage), [1] in a sequence equivalent to the ones that a standard compiler may generate as the object code.
Modern programming languages like Java therefore implement a memory model. The memory model specifies synchronization barriers that are established via special, well-defined synchronization operations such as acquiring a lock by entering a synchronized block or method. The memory model stipulates that changes to the values of shared variables ...
In computer science, manual memory management refers to the usage of manual instructions by the programmer to identify and deallocate unused objects, or garbage.Up until the mid-1990s, the majority of programming languages used in industry supported manual memory management, though garbage collection has existed since 1959, when it was introduced with Lisp.
In programming language theory, lazy evaluation, or call-by-need, [1] is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which avoids repeated evaluations (by the use of sharing).
On 21 March 2017, the PyPy project released version 5.7 of both PyPy and PyPy3, with the latter introducing beta-quality support for Python 3.5. [25] On 26 April 2018, version 6.0 was released, with support for Python 2.7 and 3.5 (still beta-quality on Windows). [26] On 11 February 2019, version 7.0 was released, with support for Python 2.7 and ...