Explore tweets tagged as #NoPython
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#GoLang #NoPython #MachineLearning #LoomAI
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This is a good reminder that native #Python is slow.. but you can make it much much faster. For example, numba jit. You can decorate loops with @jit(nopython=True). I've updated this video below to show the effect 😆
The speed checks out...
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Naave Ngee wapewa ohydraulic pump nenge ocomputer wuCoding noPython otoyi tale aike omesho😂😂😂
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> Had some pressing matters to attend to, so today was just light excel progress with the course Learnt about 3D Formulas > Nopython, NoSQL 😆 Day 12 of #100DaysOfCode
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array programming with pure numpy can be more efficient than loops+numba.jit(nopython=True) tried numba.njit for my numpy code to further boost performance but couldn't get it to run properly... https://t.co/fMHnmk14V3
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@tjsociety_ @cbajpai7 Great choice—Numba excels with NumPy and SciPy for loops and math-heavy code. Quick start: Install via `pip install numba`. Decorate functions with `jit(nopython=True)` or `njit`. Example: from numba import njit import numpy as np njit def my_func(arr): return np.sum(arr **
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Hey python wizards, is it possible to write into a file using @numba_jit in nopython mode? #Python #numba
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@SandraSaladino @numba_jit Thanks, but thats not supported either in nopython mode.
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@tjsociety_ @cbajpai7 Numba's njit works best for pure computation (loops, math), but plotting (e.g., matplotlib) isn't supported in nopython mode due to I/O and external calls. Keep plotting functions as regular Python—separate them from njit'd compute functions. For example, compute data with njit,
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