Profilo di Angela15

Nome Angela15
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Messaggi3
  • 2025-11-29 05:20:54
    Re: Problema con le Performance in Python 3.11: Come Risolvere?
    Forum >> Programmazione Python >> Web e Reti
    max1987martin said @ 2025-09-18 07:11:28:
    Hi everyone! I'm facing a performance

    issue in my Python 3.11 project. I've noticed that some operations are taking longer than expected, even with code optimization. Despite the introduction of new performance-enhancing features in Python 3.11, I haven't been able to achieve the desired results. Problem details: geometry dash meltdown I'm using async functions to handle concurrent operations, but it seems like resource management isn't optimal. The performance of some external libraries, such as Pandas and NumPy , seems to have slowed down after upgrading to Python 3.11. I've tried optimizing the code with profiling and benchmarking , but the improvements aren't noticeable. What I've tried so far: Optimizing the code with asyncio to better handle concurrent operations. Profiling the code to identify bottlenecks. Checking for updates to core libraries, but the problem persists. I'm asking for help from anyone who has had similar experiences with Python 3.11 and performance improvements. Has anyone faced similar issues and could suggest a solution or a different approach? Any advice would be greatly appreciated! --- Last edited by max1987martin on 2025-09-18 07:13:03 ---
















    Check Pandas and NumPy versions, use profiling tools to identify bottlenecks, optimize the use of asyncio, consider Dask for large datasets, and check system resources to improve performance in Python 3.11.
  • 2025-02-19 05:30:49
    Re: Verifica funzionamento di un filtro
    Forum >> Programmazione Python >> Calcolo scientifico
    Use the map to locate and find a safe escape route in escape road 2.
  • 2025-02-14 03:27:44
    Re: Sostituzione prima superdiagonale
    Forum >> Programmazione Python >> Calcolo scientifico
    Buongiorno! Sì, puoi utilizzare il comando np.fill_diagonal insieme a un'operazione di slicing per riempire la prima superdiagonale di una matrice NumPy. Ecco come puoi fare:


    python


    import numpy as np

    # Definizione della matrice
    A = np.array([[1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]])

    # Valori da inserire nella prima superdiagonale
    new_values = np.array([10, 11]) # Sostituisci [2, 6] con [10, 11]

    # Slicing per la prima superdiagonale e assegnazione dei nuovi valori
    A[np.diag_indices_from(A, k=1)] = new_values

    print(A)

    Spero che questo ti sia utile!