TGINSIGHT SIMILAR POSTS
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: #tradingstrategy
@CryptoM · Post #65210 · 12.04.2026 г., 02:09
🚀 Analyst Discusses Stop-Loss Adjustment Strategy An analyst, @ai_9684xtpa, posted on X about the rationale behind adjusting a stop-loss point to $73,500. The adjustment was made to prevent precise liquidation, and the analyst noted that the price nearly reached this adjusted level. #StopLoss#TradingStrategy#MarketAnalysis#RiskManagement#PriceAdjustment#Investing
@CryptoM · Post #64661 · 09.04.2026 г., 13:04
🚀 Bitcoin's Current Volatility May Present a Generational Buying Opportunity Cryptocurrency analyst Ali Martinez recently shared an analysis on the X platform, suggesting that instead of debating whether Bitcoin has hit its bottom, attention should be focused on whether the current volatility presents a 'generational buying opportunity.' According to Odaily, Martinez identifies key 'value zones' for the current cycle based on long-term trend lines, on-chain liquidity, and cost distribution indicators. The UTXO Realized Price Distribution (URPD) indicates a significant concentration of holdings between $63,111 and $70,685, forming the primary support band. If Bitcoin falls below $63,111, the market may enter a liquidity vacuum. From a long-term perspective, Bitcoin is nearing a critical ascending trend line from the past decade, approximately between $56,000 and $60,000. Historically, this position has often marked the accumulation phase before significant price increases. In more extreme scenarios, the CVDD indicator suggests a structural bottom around $47,960, while the MVRV 0.8 range at approximately $43,647 indicates a market in an 'extreme pain' phase, typically associated with exhaustion of selling pressure. In the event of a black swan event, prices could briefly dip to an extreme range of around $36,657. Based on these zones, Martinez employs a dollar-cost averaging (DCA) strategy, gradually increasing positions across different support bands to reduce overall holding costs. He believes the market is currently in a phase of low sentiment, but potential opportunities are gradually emerging. #Bitcoin#Cryptocurrency#CryptoTrading#MarketAnalysis#Volatility#InvestmentOpportunity#DCA#OnChainAnalysis#CryptoMarket#TradingStrategy#BTC
@venturevillagewall · Post #3926 · 20.01.2025 г., 04:00
Melania Meme Token Debuts on Major Exchanges Centralized exchanges like MEXC, BingX, Gate, and Bitget list Melania Meme (MELANIA) token. The token's economic model: 35% team share (30-day lock), 20% treasury, 20% community, 15% public offering, 10% liquidity. Major transaction: an address bought 3.8M MELANIA for 800k USDC, now with a profit of $38.6M. Read more: Wu Blockchain News #Crypto#MemeToken#MELANIA#TrumpProject#Dogecoin#Bitcoin#Profit#Exchanges#Trading#Finance#USDC#MarketAnalysis#Tokenomics#Investment#TradingStrategy#Speculation#ProfitableAddresses#MarketTrends#Blockchain#Web3#VC
@ss7trader · Post #29955 · 26.02.2026 г., 22:28
Binary trading isn't gambling if you have the right tools. 📈 Watch how Pro Thunder V12 identifies the signal on MT5 before I even open the broker. No repainting, no delay, just pure accuracy. #binaryoptions#pocketoption#quotex#tradingstrategy#mt5#forexsignals#otctrading#daytrading#prothunderv12#fintok#wealthbuilding#tradingtips#makemoneyonline#investing2026
@venturevillagewall · Post #4198 · 20.02.2025 г., 10:00
Traders Face Major Losses with LIBRA Coin Nansen research reveals that 86% of LIBRA coin traders lost money, totaling $251 million in investor losses. Meanwhile, insiders profited over $100 million from the token issuance. For more details, visit CoinDesk. #LIBRA#Argentina#Crypto#Investors#Losses#Trading#Nansen#Market#Finance#Tokens#Wealth#Volatility#DeFi#Research#Blockchain#Memecoin#VC#Funds#Loss#Insiders#TradingStrategy
@venturevillagewall · Post #3760 · 31.12.2024 г., 13:00
XRP Market Insights and Predictions 📉 Current XRP Price: $2.16 with a $123B market cap. Trading volume: $2.21B. 📊Consolidation Phase: Support at $2.1, resistance at $2.5. RSI: 49.81 | Stochastic: 26.35 | CCI: -95.21. Mixed signals overall, MACD suggests bearish sentiment. 🔄Short-term Downtrend: Testing support at $2.115; resistance at $2.22 - $2.25. EMAs indicate sell signals for 10- and 20-periods. 📈Bullish/ Bearish Scenarios: Break above $2.25 targets $2.5; break below $2.1 targets $1.9. Traders should implement tight stop-losses. Full analysis details can be read here. #XRP#Crypto#MarketAnalysis#TradingStrategy#Investing#TechnicalAnalysis#PricePrediction#Bullish#Bearish#Support#Resistance#EMAs#MACD#RSI#Stochastic#CCI#Volume#Traders#Bulls#Bears#Consolidation