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Изворен канал @pythonotes · Post #396 · 9 окт.

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

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@venturevillagewall · Post #4166 · 16.02.2025 г., 13:00

Nippon Steel Hit by Ransomware Attack 💻 Nippon Steel faces serious breach from BianLian, stealing 500GB of sensitive data. The attackers disclosed private info including financial data and personal details of top executives. With over 113,000 employees and $57.5B annual revenue, Nippon Steel is a key player in the steel industry worldwide. The hack adds to the company's challenges in 2025. 📌 For more details, visit Financial Times. #NipponSteel#BianLian#CyberSecurity#DataBreach#Ransomware#SteelIndustry#Japan#TechNews

Crypto M - Crypto News

@CryptoM · Post #65151 · 11.04.2026 г., 13:05

🚀 Lakeview Loan Servicing Reaches $26 Million Settlement Over Data Breach Lakeview Loan Servicing has agreed to a proposed $26 million settlement following a data breach that impacted 2.53 million individuals in the United States. According to NS3.AI, the lawsuit alleges that unauthorized actors gained access to the company's systems, potentially exposing names, Social Security numbers, financial account details, and other personal information. While Lakeview denies any wrongdoing, eligible class members may receive compensation, credit monitoring, and identity protection if the settlement is approved. #DataBreach#Settlement#Privacy#IdentityProtection#FinancialServices#CyberSecurity#USNews

Crypto M - Crypto News

@CryptoM · Post #64880 · 10.04.2026 г., 06:24

🚀 Security Concerns Arise Over LLM Agent API Routers On April 10, Solayer founder @Fried_rice highlighted on social media the growing reliance of large language model (LLM) agents on third-party API routers, which distribute tool call requests to multiple upstream providers. According to BlockBeats, these routers operate as application layer proxies and can access each JSON payload in plaintext during transmission. However, no provider currently enforces encryption integrity protection between the client and upstream models. A study tested 28 paid routers purchased from platforms like Taobao, Xianyu, and Shopify independent sites, along with 400 free routers collected from public communities. The findings revealed that one paid router and eight free routers were actively injecting malicious code. Additionally, two routers deployed adaptive evasion triggers, 17 accessed AWS Canary credentials owned by researchers, and one stole ETH from a private key held by researchers. Further poisoning studies demonstrated that seemingly harmless routers could also be exploited. A leaked OpenAI key was used to generate 100 million GPT-5.4 tokens and over seven Codex sessions. Weaker bait configurations resulted in 2 billion billing tokens, 99 credentials across 440 Codex sessions, and 401 sessions running autonomously in YOLO mode. The research team developed an experimental proxy named Mine, capable of executing all four types of attacks on four public proxy frameworks. They also verified three client defense strategies: fault lock strategy gating, response-side anomaly screening, and append-only transparent logging. #LLM#API#Security#CyberSecurity#Malware#DataBreach#Encryption#Proxy#AI#MachineLearning#ETH

Crypto M - Crypto News

@CryptoM · Post #65165 · 11.04.2026 г., 14:20

🚀 Heart South Reports Potential Data Breach Affecting Thousands Heart South has announced that approximately 46,666 individuals may have been affected by a data breach, with patient information from its network appearing on the dark web. According to NS3.AI, the company has been unable to verify if any specific individual's data was compromised. Notifications regarding the potential breach began being distributed in April 2026. #HeartSouth#databreach#patientdata#darkweb#NS3AI#privacy#cybersecurity#datasecurity#breachnotification#April2026