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--- other:python:misc_by_jyp [2023/11/29 11:32] – [Working with paths and filenames] Improved and added pathlib example jypeter
+++ other:python:misc_by_jyp [2023/12/08 16:36] – Added the efficient looping section jypeter
@@ Line 313: / Line 313: @@
 ['c', 'd', 'b', 'a']</code>
+===== Efficient looping with numpy, map and itertools =====
+<wrap hi>Big, nested, explicit loops should be avoided at all cost</wrap>, in order to reduce a script execution time!
+  * **''numpy'' arrays** should be used when dealing with //numerical data//
+    * **Masked arrays** can be used to deal with //special cases// and remove tests from loops
+  * The built-in [[https://docs.python.org/3/library/functions.html?highlight=map#map|map]] function (and similar functions like [[https://docs.python.org/3/library/functions.html?highlight=zip#zip|zip]], [[https://docs.python.org/3/library/functions.html?highlight=filter#filter|filter]], ...) can be used to efficiently apply a function (possibly a //simple// [[https://docs.python.org/3/tutorial/controlflow.html#lambda-expressions|lambda]] function) to all the elements of a list
+    * <code>>>> my_ints = [1, 2, 3]
+>>> map(str, my_ints)
+['1', '2', '3']
+>>> map(lambda ii: str(10*ii + 5), my_ints)
+['15', '25', '35']</code>
+  * The [[https://docs.python.org/3/library/itertools.html|itertools]] module defines many more fancy iterators that can be used for efficient looping
+    * Example: replacing nested loops with [[https://docs.python.org/3/library/itertools.html#itertools.product|product]]
+      * <code>>>> it.product('AB', '01')
+<itertools.product object at 0x2b35a7b5f100>
+>>> list(it.product('AB', '01'))
+[('A', '0'), ('A', '1'), ('B', '0'), ('B', '1')]
+>>> for c1, c2 in it.product('AB', '01'):
+...   print(c1 + c2)
+...
+A0
+A1
+B0
+B1
+>>> for c1, c2 in it.product(['A', 'B'], ['0', '1']):
+...   print(c1 + c2)
+...
+A0
+A1
+B0
+B1
+>>> for c1, c2, c3 in it.product('AB', '01', '$!'):
+...   print(c1 + c2 + c3, end=', ')
+...
+A0$, A0!, A1$, A1!, B0$, B0!, B1$, B1!,</code>
 ===== numpy related stuff =====