Copy-on-write friendly Python garbage collection
At Instagram, we have the world’s largest deployment of the Django web framework, which is written entirely in Python. We began using Python early on because of its simplicity, but we’ve had to do many hacks over the years to keep it simple as we’ve scaled. Last year we tried dismissing the Python garbage collection (GC) mechanism (which reclaims memory by collecting and freeing unused data), and
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
1
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
GitHub - pympler/pympler: Development tool to measure, monitor and analyze the memory behavior of Python objects in a running Python application.
http://www.aminus.net/wiki/Dowser
GitHub - pytries/marisa-trie: Static memory-efficient Trie-like structures for Python based on marisa-trie C++ library.
Which Python memory profiler is recommended?