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update text in parallel-computing.rst
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content/parallel-computing.rst

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@@ -116,9 +116,9 @@ by the GIL, so they typically support actual multihreading during the execution.
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It might be a good idea to use multiple threads during calculations
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like matrix operations or frequency analysis.
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Depending on configuration, NumPy will often use multiple threads by default,
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but we can use the environment variable ``OMP_NUM_THREADS`` to set the number
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of threads manually in a Unix-like enviroment:
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Depending on the configuration, NumPy will often use multiple threads by default,
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and one can use the environment variable ``OMP_NUM_THREADS`` to set the number
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of threads manually by executing the following command in a terminal:
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.. code-block:: console
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