#13094: merge with 3.2.
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7d48669085
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@ -206,6 +206,58 @@ an imported module. This clutter would defeat the usefulness of the ``global``
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declaration for identifying side-effects.
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Why do lambdas defined in a loop with different values all return the same result?
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----------------------------------------------------------------------------------
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Assume you use a for loop to define a few different lambdas (or even plain
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functions), e.g.::
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squares = []
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for x in range(5):
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squares.append(lambda: x**2)
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This gives you a list that contains 5 lambdas that calculate ``x**2``. You
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might expect that, when called, they would return, respectively, ``0``, ``1``,
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``4``, ``9``, and ``16``. However, when you actually try you will see that
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they all return ``16``::
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>>> squares[2]()
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16
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>>> squares[4]()
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16
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This happens because ``x`` is not local to the lambdas, but is defined in
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the outer scope, and it is accessed when the lambda is called --- not when it
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is defined. At the end of the loop, the value of ``x`` is ``4``, so all the
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functions now return ``4**2``, i.e. ``16``. You can also verify this by
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changing the value of ``x`` and see how the results of the lambdas change::
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>>> x = 8
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>>> squares[2]()
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64
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In order to avoid this, you need to save the values in variables local to the
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lambdas, so that they don't rely on the value of the global ``x``::
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squares = []
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for x in range(5):
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squares.append(lambda n=x: n**2)
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Here, ``n=x`` creates a new variable ``n`` local to the lambda and computed
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when the lambda is defined so that it has the same value that ``x`` had at
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that point in the loop. This means that the value of ``n`` will be ``0``
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in the first lambda, ``1`` in the second, ``2`` in the third, and so on.
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Therefore each lambda will now return the correct result::
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>>> squares[2]()
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4
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>>> squares[4]()
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16
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Note that this behaviour is not peculiar to lambdas, but applies to regular
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functions too.
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How do I share global variables across modules?
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------------------------------------------------
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