@ethereumglobalnews · Post #1090 · 19.10.2025 г., 12:58
🤣#Web3News#CryptoSight 🤔#Coinglass 數據【 近 7 日内已有近 22,000 枚 BTC ,自中心化交易所撤出 】 #BTC 流出引發市場對資金去向與潛在行情變動的高度關注 #Web3
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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
Пребарај: #coinglass
@ethereumglobalnews · Post #1090 · 19.10.2025 г., 12:58
🤣#Web3News#CryptoSight 🤔#Coinglass 數據【 近 7 日内已有近 22,000 枚 BTC ,自中心化交易所撤出 】 #BTC 流出引發市場對資金去向與潛在行情變動的高度關注 #Web3
@CryptoM · Post #65182 · 11.04.2026 г., 16:55
🚀 Ethereum Price Movements Could Trigger Significant Liquidations Ethereum's price fluctuations could lead to substantial liquidations on major centralized exchanges. According to ChainCatcher, data from Coinglass indicates that if Ethereum surpasses $2,346, the cumulative liquidation of short positions could reach $893 million. Conversely, if Ethereum falls below $2,135, the liquidation of long positions could total $877 million. #Ethereum#Crypto#PriceMovements#Liquidations#CryptoTrading#Coinglass#ChainCatcher#ShortPositions#LongPositions#Cryptocurrency#ETH
@CryptoM · Post #64985 · 10.04.2026 г., 12:56
🚀 Ethereum Price Movements Could Trigger Significant Liquidations Ethereum's price fluctuations could lead to substantial liquidations on major centralized exchanges. According to ChainCatcher, Coinglass data indicates that if Ethereum falls below $2,082, the liquidation intensity for long positions could reach $974 million. Conversely, if Ethereum surpasses $2,299, the liquidation intensity for short positions could amount to $855 million. #Ethereum#PriceMovements#Liquidations#CentralizedExchanges#Coinglass#ChainCatcher#LongPositions#ShortPositions#ETH
@CryptoM · Post #64988 · 10.04.2026 г., 12:58
🚀 Hyperliquid Platform Whale Holdings Reach $3.721 Billion, Data Shows Hyperliquid platform whales currently hold positions valued at $3.721 billion, according to ChainCatcher. Data from Coinglass reveals that long positions account for $1.902 billion, representing 51.13% of the total holdings, while short positions amount to $1.818 billion, making up 48.87%. The long positions have incurred a loss of $6.8165 million, whereas the short positions have gained $17.7438 million. Notably, a whale address identified as 0xa5b0..41 has engaged in a 15x leveraged long position on ETH at a price of $2,148.7, currently showing an unrealized profit of $2.6246 million. #Hyperliquid#WhaleHoldings#ChainCatcher#Coinglass#LongPositions#ShortPositions#ETH#LeveragedPosition#Crypto#UnrealizedProfit
@CryptoM · Post #65366 · 13.04.2026 г., 02:44
🚀 Hyperliquid Whale Positions Reach $3.745 Billion, Data Shows Hyperliquid platform's whale positions currently total $3.745 billion, according to ChainCatcher. Coinglass data reveals that long positions account for $1.91 billion, representing 50.98% of the total, while short positions amount to $1.836 billion, making up 49.02%. The long positions have incurred a loss of $12.4197 million, whereas the short positions have gained $19.721 million. Notably, a whale address 0xa5b0..41 has taken a 15x leveraged long position on ETH at a price of $2,148.7, with an unrealized profit of $3.7797 million. #Hyperliquid#WhalePositions#ChainCatcher#Coinglass#LongPositions#ShortPositions#ETH#LeveragedPositions#UnrealizedProfit#Crypto
@CryptoM · Post #65338 · 13.04.2026 г., 00:45
🚀 Ethereum Price Movements Could Trigger Significant Liquidations Ethereum's price fluctuations could lead to substantial liquidations on major centralized exchanges. According to ChainCatcher, Coinglass data indicates that if Ethereum surpasses $2,309, the cumulative liquidation intensity of short positions on mainstream centralized exchanges will reach $798 million. Conversely, if Ethereum falls below $2,093, the cumulative liquidation intensity of long positions will amount to $581 million. #Ethereum#PriceMovements#Liquidations#CentralizedExchanges#CryptoTrading#Coinglass#ChainCatcher#ShortPositions#LongPositions#CryptoMarket#ETH
@CryptoM · Post #65184 · 11.04.2026 г., 16:56
🚀 Hyperliquid Whale Positions Reach $3.905 Billion Hyperliquid platform's whale positions have reached a total of $3.905 billion, according to ChainCatcher. Data from Coinglass reveals that long positions account for $1.992 billion, representing 51.01% of the total, while short positions amount to $1.913 billion, making up 48.99%. The profit and loss for long positions stands at $29.0862 million, whereas short positions show a loss of $13.7305 million. Notably, a whale address, 0xa5b0..41, has engaged in a 15x leveraged long position on ETH at a price of $2,148.7, currently showing an unrealized profit of $6.6987 million. #Hyperliquid#WhalePositions#Billion#ChainCatcher#Coinglass#LongPositions#ShortPositions#ETH#LeveragedPosition#ProfitLoss
@CryptoM · Post #65035 · 10.04.2026 г., 15:05
🚀 Bittensor Experiences Significant Market Value Loss Following Covenant AI Departure Bittensor's market value dropped by nearly $900 million after Covenant AI announced its departure from the network. According to NS3.AI, CryptoSlate data revealed that TAO, Bittensor's native token, fell 27% from $338 to $285 within approximately two hours before slightly recovering to $294. CoinGlass data indicated that the event led to $11 million in long liquidations. The split has highlighted a governance dispute between Covenant AI founder Sam Dare and Bittensor co-founder Jacob Steeves. #Bittensor#MarketValueLoss#CovenantAI#TAO#Crypto#NS3AI#CryptoSlate#CoinGlass#Liquidations#GovernanceDispute#SamDare#JacobSteeves
@CryptoM · Post #65295 · 12.04.2026 г., 15:15
🚀 Crypto Analyst Manya Releases Research Tool Rankings Crypto analyst manya has released a ranking of personal research tools. According to ChainCatcher, the rankings categorize tools into different levels based on their effectiveness. The S-tier includes Dune and frontrun.pro, while the A-tier features Coinglass, RootData, Drop, MetaSleuth, and DefiLlama. B-tier tools comprise Arkham, Bubblemaps, Dexscreener, Surf, Nansen, and CoinMarketCap. C-tier tools include Cryptorank and others. #CryptoAnalyst#ResearchTools#CryptoRanking#Dune#frontrunpro#Coinglass#RootData#Drop#MetaSleuth#DefiLlama#Arkham#Bubblemaps#Dexscreener#Surf#Nansen#CoinMarketCap#Cryptorank