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partials are incredibly useful. For instance, in a 'pipe-lined' sequence of function calls (in which the returned value from one function is the argument passed to the next). Sometimes a function in such a pipeline requires a single argument, but the function immediately upstream from it returns two values. In this scenario, <code>functools.partial</code> might allow you to keep this function pipeline intact. Here's a specific, isolated example: suppose you want to sort some data by each data point's distance from some target: <pre><code># create some data import random as RND fnx = lambda: RND.randint(0, 10) data = [ (fnx(), fnx()) for c in range(10) ] target = (2, 4) import math def euclid_dist(v1, v2): x1, y1 = v1 x2, y2 = v2 return math.sqrt((x2 - x1)**2 + (y2 - y1)**2) </code></pre> To sort this data by distance from the target, what you would like to do of course is this: <pre><code>data.sort(key=euclid_dist) </code></pre> but you can't--the sort method's key parameter only accepts functions that take a single argument. so re-write <code>euclid_dist</code> as a function taking a single parameter: <pre><code>from functools import partial p_euclid_dist = partial(euclid_dist, target) </code></pre> <code>p_euclid_dist</code> now accepts a single argument, <pre><code>>>> p_euclid_dist((3, 3)) 1.4142135623730951 </code></pre> so now you can sort your data by passing in the partial function for the sort method's key argument: <pre><code>data.sort(key=p_euclid_dist) # verify that it works: for p in data: print(round(p_euclid_dist(p), 3)) 1.0 2.236 2.236 3.606 4.243 5.0 5.831 6.325 7.071 8.602 </code></pre> Or for instance, one of the function's arguments changes in an outer loop but is fixed during iteration in the inner loop. By using a partial, you don't have to pass in the additional parameter during iteration of the inner loop, because the modified (partial) function doesn't require it. <pre><code>>>> from functools import partial >>> def fnx(a, b, c): return a + b + c >>> fnx(3, 4, 5) 12 </code></pre> create a partial function (using keyword arg) <pre><code>>>> pfnx = partial(fnx, a=12) >>> pfnx(b=4, c=5) 21 </code></pre> you can also create a partial function with a positional argument <pre><code>>>> pfnx = partial(fnx, 12) >>> pfnx(4, 5) 21 </code></pre> but this will throw (e.g., creating partial with keyword argument then calling using positional arguments) <pre><code>>>> pfnx = partial(fnx, a=12) >>> pfnx(4, 5) Traceback (most recent call last): File "<pyshell#80>", line 1, in <module> pfnx(4, 5) TypeError: fnx() got multiple values for keyword argument 'a' </code></pre> another use case: writing distributed code using python's <code>multiprocessing</code> library. A pool of processes is created using the Pool method: <pre><code>>>> import multiprocessing as MP >>> # create a process pool: >>> ppool = MP.Pool() </code></pre> <code>Pool</code> has a map method, but it only takes a single iterable, so if you need to pass in a function with a longer parameter list, re-define the function as a partial, to fix all but one: <pre><code>>>> ppool.map(pfnx, [4, 6, 7, 8]) </code></pre>
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1. POHow does the functools partial work in Python?
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1. COis there any practical use of this function somewher
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2. CO@user1865341 added two exemplarly use cases to my answer
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