7.09.2025 состоялся релизPithon 3.14!
На фоне хайпа про NoGIL всё позабыли про другие фичи. Особенно про Multiple Interpreters, который обещает изоляцию процессов но с эффективностью потоков! На сколько действительно это будет эффективно мы узнаем позже, потому что сейчас это лишь первый релиз с ограничениями и недоработками.
Но что там про NoGIL? Теперь этот режим не экспериментальный, а официально поддерживаемый, но опциональный.
Чтобы запустить без GIL нужна специальная сборка. И перед стартом нужно объявить переменную PYTHON_GIL=0
Для вас я собрал готовый репозиторий где достаточно запустить скрпит, который всё сделает:
▫️ соберет релизный Python 3.14 в новый Docker-образ
▫️ запустит тесты в контейнере (GIL, NoGIL, MultiInterpreter)
▫️ распечатает результаты
Тест очень простой, усложняйте сами)
Вот какие результаты у меня:
=== Running ThreadPoolExecutor GIL ON
TOTAL TIME: 45.48 seconds
=== Running ThreadPoolExecutor GIL OFF
TOTAL TIME: 6.14 seconds
=== Running basic Thread GIL ON
TOTAL TIME: 45.54 seconds
=== Running basic Thread GIL OFF
TOTAL TIME: 4.74 seconds
=== Running with Multi Interpreter
TOTAL TIME: 18.30 seconds
Если сравнивать GIL и NoGIL, то на мои 32 ядра прирост х7-x10 (почему не х32? 🤷). При этом нам обещают что скорости будут расти с новыми релизами.
Режим без GIL похож (визуально) на async, тоже параллельно, тоже не по порядку. Но это не IO! и от того некоторый диссонанс в голове 😵💫, нас учили не так!
Интересно, что чистый Thread работает быстрей чем ThreadPoolExecutor без GIL.
Ну и где-то плачет один адепт мульти-интерпретаторов😭 Теперь нужно искать где они могут пригодиться с такой-то скоростью. Скорее всего своя область применения найдется.
Отдельно я затестил память и вот что вышло на 32 потока:
ThreadPoolExecutor GIL ON
305.228 MB
ThreadPoolExecutor GIL OFF
500.176 MB
basic Thread GIL ON
90.668 MB
basic Thread GIL OFF
472.444 MB
with Multi Interpreter
1267.788 MB
Пока не знаю как к этому относиться)
В целом - радует направление развития!
#release
Dear Colleagues, I am thrilled to announce that I have successfully passed the AI Governance Professional certification exam from the International Association of Privacy Professionals (AIGP/IAPP).
This comprehensive exam covered a wide range of topics, from the technological foundations of AI systems and their lifecycles to the ethical, risk management, and legal considerations surrounding the development and deployment of AI systems.
I am committed to continuing my learning in this area and sharing news and valuable resources with you.
#IAPP#AIGP
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This streamlined version is highly practical, designed to address the current responsibilities AI governance professionals encounter, not merely theoretical questions. Furthermore, Domains III and IV now separate the roles of developers and deployers, a crucial distinction reflecting how laws and standards are evolving in the field.
By balancing legal and technical insights, the new AIGP BoK solidifies its standing as the essential credential for those committed to responsible AI governance.
#AIGP#AIGovernance#LegalTech#ResponsibleAI#IAPP
IAPP Releases Comprehensive Report on AI Governance in Practice
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#AI#AIGovernance#DataPrivacy#IAPP#AIGP
ISO Releases Free AI Governance Standard
The International Organization for Standardization (ISO), a prominent NGO known for creating industry standards, has made the important ISO/IEC 22989 standard publicly available for free. This standard addresses a wide range of AI governance topics, providing valuable guidelines for the responsible development and deployment of AI technologies.
ISO/IEC 22989 covers essential aspects of AI governance, including ethical considerations, risk management, and compliance requirements. It provides standardized concepts and terminology to help stakeholders understand and adopt AI technology effectively. This document is designed for a wide audience, including both experts and non-practitioners, offering insights into AI’s interdisciplinary nature, which encompasses computer science, data science, natural sciences, humanities, mathematics, and social sciences.
By making this standard freely accessible, ISO aims to promote the widespread adoption of responsible AI practices, ensuring that AI systems are trustworthy, robust, resilient, reliable, accurate, safe, secure, and private.
You can find ISO/IEC 22989 and other publicly avalable standards here.
#ISO#AIGovernance#AIGP#AI#Ethics#AICompliance#Technology#Innovation