[B! Python][python][GC] xefのブックマーク

How fast can the RPython GC allocate?

While working on a paper about allocation profiling in VMProf I got curious about how quickly the RPython GC can allocate an object. I wrote a small RPython benchmark program to get an idea of the order of magnitude. The basic idea is to just allocate an instance in a tight loop: class A(object): pass def run(loops): # preliminary idea, see below for i in range(loops): a = A() a.i = i The RPython

xef 2025/06/16

Python
GC

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Dismissing Python Garbage Collection at Instagram

By dismissing the Python garbage collection (GC) mechanism, which reclaims memory by collecting and freeing unused data, Instagram can run 10% more efficiently. Yes, you heard it right! By disabling GC, we can reduce the memory footprint and improve the CPU LLC cache hit ratio. If you’re interested in knowing why, buckle up! How We Run Our Web ServerInstagram’s web server runs on Django in a multi

xef 2017/01/21

Python
GC

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Generational GC in Python and Ruby - Pat Shaughnessy

Both the Ruby and Python garbage collectors handle old and young objects differently. Last week I wrote up the my first half of my notes from a presentation I did at RuPy called “Visualizing Garbage Collection in Ruby and Python.” I explained how standard Ruby (also known as Matz’s Ruby Interpreter or MRI) uses a garbage collection (GC) algorithm called mark and sweep, the same basic algorithm dev

xef 2013/11/08

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Visualizing Garbage Collection in Ruby and Python - Pat Shaughnessy

Note: This post is based on a presentation I just did at RuPy in Budapest. Instead of just posting my slides I thought it would be more useful if I wrote it down as a blog post while it’s still fresh in my mind. You can also watch the video recording of the presentation. FYI I’m planning to do a similar presentation at RubyConf, except I’ll remove the Python info, and instead compare how GC works