Comparision between Generator and Nomal Iterator function

Comparision between Generator and Nomal Iterator function

Author: SanjayPradeeo

Generators/DiffBtwnGenratorsAndIterator.py

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+__author__ = 'Sanjay'
+
+# Differences between Generator function and a Normal Iterator function
+
+# Here is how a generator function differs from a normal function.
+#
+# Generator function contains one or more yield statement.
+
+# When called, it returns an object (iterator) but does not start execution immediately.
+
+# Methods like __iter__() and __next__() are implemented automatically. So we can iterate through the items using next().
+
+# Once the function yields, the function is paused and the control is transferred to the caller.
+
+# Local variables and their states are remembered between successive calls.
+
+# Finally, when the function terminates, StopIteration is raised automatically on further calls.
+
+
+def my_gen():
+    n = 1
+    print('This is printed first')
+    # Generator function contains yield statements
+    yield n
+
+    n += 1
+    print('This is printed second')
+    yield n
+
+    n += 1
+    print('This is printed at last')
+    yield n
+
+
+a = my_gen()
+print (a)
+next(a) # This is printed first
+next(a) # This is printed second
+next(a) # This is printed at last
+
+# next(a) # StopIteration because there's no more n value available to bring out.
+
+# One interesting thing to note in the above example is that, the value of variable n is remembered between each call.
+#
+# Unlike normal functions, the local variables are not destroyed when the function yields. Furthermore, the generator object can be iterated only once.
+#
+# To restart the process we need to create another generator object using something like a = my_gen().
+
+# Note: One final thing to note is that we can use generators with for loops directly.
+
+# Here you go ..
+
+for item in my_gen():
+    print (item)
+
+# Here's the output
+
+# This is printed first
+# 1
+# This is printed second
+# 2
+# This is printed at last
+# 3