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Изворен канал @pythonotes · Post #32 · 7 фев.

Скорее всего уже слышали, что складывать строки через + это плохая практика. Падение производительности, и всё такое. Без лишних слов, давайте измерять: from timeit import timeit def t1(): # складываем 10 строк через + из переменной t = 'text' for _ in range(1000): s = t + t + t + t + t + t + t + t + t def t2(): # склеиваем список строк через метод join arr = ['text'] * 10 for _ in range(1000): s = ''.join(arr) def t3(): # складываем через + но не из переменной а непосредственно инлайн объекты for _ in range(1000): s = 'text' + 'text' + 'text' + ... # всего 10 раз Теперь каждую строку склейки запустим по 10М раз >>> timeit(t1, number=10000) 0.21951690399964718 >>> timeit(t2, number=10000) 1.4978306379998685 >>> timeit(t3, number=10000) 0.2213820789993406 Хм, а нам говорили что через "+" это плохо и медленно ))) 😁 Тут стоит учитывать, что речь идёт о склейке множества длинных строк. Давайте изменим условия: def t4(): t = 'text'*100 for _ in range(1000): s = t + t + t + t + t + t + t + t + t def t5(): arr = ['text'*100] * 10 for _ in range(1000): s = ''.join(arr) def t6(): for _ in range(1000): s = 'text'*100 + 'text'*100 + ... # всего 10 раз >>> timeit(t4, number=10000) 12.795130728000004 >>> timeit(t5, number=10000) 2.642637542999182 >>> timeit(t6, number=10000) 0.2184546610005782 Вот, уже другой разговор, сразу видна разница, в среднем в 6 раз. Но погодите, почему последний тест t6() по скорости такой же как и t3()? Ведь строки теперь в 100 раз длиннее! Это вопросы оптимизации кода, какие простые изменения ускоряют или замедляют выполнение программы. Мы столкнулись с примером обхода обращения к переменной. Например, именно так работает директива #define в С++, во время компиляции подставляя значение переменной вместо ссылки на неё. В Python это тоже работает, но часто ли вы сможете встретить такой способ работы со строками? К сожалению, способ почти только теоретический. В целом, тесты показали то, что мы хотели. Делаем выводы самостоятельно. Полный листинг 🌍 #tricks

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AI & Law

@ai_and_law · Post #768 · 19.02.2026 г., 08:04

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🇺🇸U.S. Department of Labor Launches Federal AI Literacy Framework The U.S. Department of Labor has introduced the United States’ first federal-level AI literacy framework, a voluntary initiative aimed at guiding AI literacy programs across government, the public workforce, and education systems. The framework defines AI literacy as a foundational set of competencies enabling responsible use and evaluation of AI technologies, with a primary focus on generative AI as a core workplace tool. It is intended as a baseline understanding rather than specialized training for AI developers. Designed for broad application, the framework encourages tailored programs for different roles and contexts. It outlines benefits for workers (independent skill-building and adaptation to AI-enabled environments), employers (responsible deployment and workforce transition), and education providers (curriculum design and competency assessment). Although nonbinding, it is expected to influence private-sector training initiatives in the U.S. and abroad. The document emphasizes that AI literacy requirements will evolve with technological change, labor market developments, and implementation feedback. #AIRegulation#AILiteracy#GenerativeAI#PublicPolicy

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AI & Law

@ai_and_law · Post #819 · 04.05.2026 г., 07:04

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🇿🇦South Africa Withdraws AI Policy Over Hallucinated Sources South Africa has withdrawn its draft national AI policy after discovering that at least 6 of its 67 academic citations were AI-generated and referred to non-existent journal articles. Communications Minister Solly Malatsi stated that the most plausible explanation is the inclusion of unverified AI-generated references, calling the lapse a failure that “compromised the integrity and credibility” of the policy. The draft policy had proposed establishing a national AI commission, an AI ethics board, and a regulatory authority, alongside incentives such as tax breaks and grants to support AI infrastructure. The issue was identified after News24 found fabricated citations, later confirmed by journal editors. The policy will be revised before being reissued, and the minister indicated there would be consequences for those responsible. The case highlights risks of using generative AI in policy drafting without verification. A Nature study cited in the report found that over 2.5% of academic papers in 2025 contained at least one potentially hallucinated reference, up from 0.3% in 2024, amounting to more than 110,000 papers. #AIRegulation#AIethics#Hallucinations#PublicPolicy#AIGovernance

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AI & Law

@ai_and_law · Post #809 · 20.04.2026 г., 07:04

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🇿🇦South Africa Publishes Draft National AI Policy South Africa’s Minister of Communications and Digital Technologies, Solly Malatsi, released a draft national AI policy for a 60-day public consultation. The proposal outlines the creation of several institutions, including a National AI Commission, an AI Ethics Board, an AI Regulatory Authority, and a National AI Safety Institute to coordinate governance and oversight. The draft introduces safety requirements for AI systems, including mandatory human rights and gender impact assessments, human intervention mechanisms, and obligations to ensure “sufficient explainability” and “sufficient transparency” for high-risk systems used in the public sector. #AIRegulation#AIethics#PublicPolicy#AISafety#SouthAfrica

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