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  2. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    In the merge sort algorithm, this subroutine is typically used to merge two sub-arrays A[lo..mid], A[mid+1..hi] of a single array A. This can be done by copying the sub-arrays into a temporary array, then applying the merge algorithm above. [1] The allocation of a temporary array can be avoided, but at the expense of speed and programming ease.

  3. Dask (software) - Wikipedia

    en.wikipedia.org/wiki/Dask_(software)

    Due to Python’s Global Interpreter Lock, local threads provide parallelism only when the computation is primarily non-Python code, which is the case for Pandas DataFrame, Numpy arrays or other Python/C/C++ based projects. Local process A multiprocessing scheduler leverages Python’s concurrent.futures.ProcessPoolExecutor to execute computations.

  4. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  5. Timsort - Wikipedia

    en.wikipedia.org/wiki/Timsort

    Timsort has been Python's standard sorting algorithm since version 2.3 (since version 3.11 using the Powersort merge policy [5]), and is used to sort arrays of non-primitive type in Java SE 7, [6] on the Android platform, [7] in GNU Octave, [8] on V8, [9] Swift, [10] and inspired the sorting algorithm used in Rust.

  6. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    Suppose that such an algorithm existed, then we could construct a comparison-based sorting algorithm with running time O(n f(n)) as follows: Chop the input array into n arrays of size 1. Merge these n arrays with the k-way merge algorithm. The resulting array is sorted and the algorithm has a running time in O(n f(n)).

  7. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    Numpy is one of the most popular Python data libraries, and TensorFlow offers integration and compatibility with its data structures. [66] Numpy NDarrays, the library's native datatype, are automatically converted to TensorFlow Tensors in TF operations; the same is also true vice versa. [ 66 ]

  8. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    The Nial example of the inner product of two arrays can be implemented using the native matrix multiplication operator. If a is a row vector of size [1 n] and b is a corresponding column vector of size [n 1]. a * b;

  9. Merge (version control) - Wikipedia

    en.wikipedia.org/wiki/Merge_(version_control)

    Manual merging is also required when automatic merging runs into a change conflict; for instance, very few automatic merge tools can merge two changes to the same line of code (say, one that changes a function name, and another that adds a comment). In these cases, revision control systems resort to the user to specify the intended merge result.