File: class/Extras/Code/Misc/gendemo.py

"""
================================================================================
Demonstrate the many mutations of generators though the years...
(Copyright M. Lutz 2015)

Contents:
1) In 2.3+: original model - yield
2) In 2.5+: sends (plus throws, closes)
3) In 3.3+: returns and subgenerators
4) In 3.5+: asynch/await (plus asyncio in 3.4)

This is a supplement to the book "Learning Python".  Its first few sections'
code runs under both Python 2.X and 3.X, but later code requires recent 3.X.
Generators and coroutines in Python: 

 -Have seen a volatile and even tortured evolution, that likely qualifies
  as thrashing

 -Have advanced and obscure usage modes that are not widely used by most
  Python programmers

 -In advanced roles, are more in the realm of application programming 
  than language, as they entail concurrent programming techniques.  

However, they have recently spawned new syntax that can regrettably make 
them a required topic for all users and learners of the core language.
================================================================================
"""

#
# See also: expression equivalent, in 2.4+
#

>>> for x in (i ** 2 for i in range(4)):    # Automatically yields values
...     print(x)                            # But defs can use full statements
...
0
1
4
9
>>>



#===============================================================================
# 1) In 2.3+: original model - yield
#     
# A def with a "yield" statement automatically supports the iteration 
# protocol: yielded values are returned for next().  This suffices for
# simple task switching: see http://learning-python.com/books/async1.py.
#===============================================================================


>>> def a(N):                      # YIELD VALS ONLY
...     for i in range(N):         # Suspend and resume just after yield
...         yield i ** 2           # Result of caller's next() or send()
...

>>> G = a(4)                       # Manual iteration: iteration protocol
>>> next(G)                        # Yielded values recieved at top by caller
0
>>> next(G)
1
>>> next(G)
4
>>> next(G)
9
>>> next(G)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

>>> for top in a(4): print(top)    # Automatic iteration: all contexts
...                                # Calls next() * N, catches exception
0
1
4
9
>>>



# 
# Example: classic producer/consumer model
# See also task switcher link above for a more general model
# Threads + thread queues achieve similar effect without manual yields
#

>>> queue = []                        # Shared object and global name
>>> def produce(N):
...     for i in range(N):
...         queue.append(i ** 2)
...         yield                     # Suspend, yield control to consume()
...
>>> def consume(N):
...     for i in produce(N):          # Start or resume produce() on each loop
...         res = queue.pop()
...         print(res)
...
>>> consume(4)
0
1
4
9
>>>



#===============================================================================
# 2) In 2.5+: sends (plus throws and closes, not shown)
# 
# The caller can resume a generator and pass it a value via G.send(X):  
# X becomes the result of the "yield" expression inside the generator.
#=============================================================================== 


>>> def a(N):                   # YIELD VALS + GET SENT VALS
...    for i in range(N): 
...        X = yield i ** 2     # X is result of caller's send()
...        print('gen:', X)     # Display X after resumed
...



#
# Iterate manually
#

>>> G = a(4)                    # Create generator

>>> G.send(77)                  # Must start with next(), not send()
TypeError: can't send non-None value to a just-started generator

>>> top = next(G)               # Start generator: to first yield
>>> top                         # Yielded iteration value in caller
0

>>> top = G.send(77)            # 77 sent to suspended yield expression
gen: 77                         # Sent value printed in generator
>>> top                         # Yielded iteration value in caller
1

>>> top = G.send(88)            # 88 sent to suspended yield expression
gen: 88                         # Sent value printed in generator
>>> top                         # Yielded iteration value in caller
4

>>> top = next(G)
gen: None                       # No value (default None) sent by next()
>>> top                         # Final yielded iteration value
9

>>> G.send(99)                  # Resume a(), a() exits, no new value
gen: 99
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>>



#
# Iterate with loops
#

>>> for x in a(4): print('top:', x)     # next() sends default None to a()
...
top: 0
gen: None
top: 1
gen: None
top: 4
gen: None
top: 9
gen: None

>>> G = a(4)                            # Send explicit values to a()
>>> v = next(G)
>>> print(v)
0
>>> while True:
...     v = G.send('Spam' * (v+1))
...     print('top:', v)
...
gen: Spam
top: 1
gen: SpamSpam
top: 4
gen: SpamSpamSpamSpamSpam
top: 9
gen: SpamSpamSpamSpamSpamSpamSpamSpamSpamSpam
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
StopIteration
>>>



#
# Example: using sent value inside a generator
# Yielded values can influence the caller's next action
# Sent values can influence the generator's next iteration
#

>>> def a(N):
...     X = True
...     for i in range(N):
...         if X:
...             result = i ** 2
...         else:
...             result = 1 / float(i)
...         X = yield result
...

>>> G = a(4)
>>> next(G)             # Generator runs up to first yield and suspends
0
>>> G.send(False)       # Suspended yield resumed, returns sent value 
1.0
>>> G.send(True)        # Sent value always impacts _next_ iteration
4
>>> G.send(False)
0.3333333333333333
>>> G.send(True)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>>



#===============================================================================
# 3) In 3.3+: returns and subgenerators
#    
# A "return X" is allowed in generators: X is attached to the StopIteration
# exception and becomes the result of a "yield from" subgenerator expression,
# which also propagates sent and yielded values to and from subgenerators.
#===============================================================================


C:\Code> py -3.5  # 3.3 and later

>>> def a(N):                           # YIELD VALS + RETURN RESULT
...     for i in range(N):
...         yield i ** 2                # yield: result of iterations
...     return 'SPAM'                   # return: result of "yield from" expression
...

>>> def b(N):
...     print('before...')
...     res = yield from a(N)           # Exports subgenerator iteration results
...     print('after...', res)          # res is "return" value (or None by default)
...

>>> for x in a(4): print('top:', x)     # Iterate through subgenerator directly
...
top: 0
top: 1
top: 4
top: 9
>>>

>>> for x in b(4): print('top:', x)     # Iterate through subgenerator indirectly
...
before...
top: 0
top: 1
top: 4
top: 9
after... SPAM
>>>

>>> G = a(4)
>>> try:
...     while True: next(G)
... except StopIteration as E:          # Catch return value in exception handler
...     print(E.value)
...
0
1
4
9
SPAM
>>>



>>> b(4)                                # Generators are nothing till started
<generator object b at 0x00...B65990>

>>> def a(N):
...     for i in range(N):
...         yield i ** 2                # Returns None by default (as usual)
...
>>> for x in b(4): print('top:', x)     # b() delegates to the new a()
...
before...
top: 0
top: 1
top: 4
top: 9
after... None
>>>



#
# DRUMROLL PLEASE... (all behavior combined)
#

>>> def a(N):                           # YIELD VALS + GET SENT VALS + RETURN RESULT
...     for i in range(N):
...         X = yield i ** 2            # X is result of highest send()
...         print('gen:', X)            # Display X after resumed
...     return 'SPAM'                   # return: result of "yield from" expression
...

>>> def b(N):
...     print('before...')
...     res = yield from a(N)           # Exports subgenerator iteration results
...     print('after...', res)          # res is "return" value (or None by default)
...



#
# Iterate manually
#

>>> G = b(4)         # Create generator
>>> next(G)          # Start: to first yield in b() then a(), 0 passed up to top
before...
0
>>> G.send(77)       # 77 sent to b() then a(), a() yields 1 to b() then top
gen: 77
1
>>> G.send(88)       # ditto, but sends 88 and receives 4
gen: 88
4
>>> next(G)          # next() sends default None, a() yields 9 to b() then top
gen: None
9
>>> G.send(99)       # Send 99 to a(), a() exits + returns 'SPAM' to b(), b() exits
gen: 99
after... SPAM
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>>



#
# Iterate with loops
#

>>> for x in b(4): print('top:', x)     # next() sends default None to a() via b()
...
before...
top: 0
gen: None
top: 1
gen: None
top: 4
gen: None
top: 9
gen: None
after... SPAM

>>> G = b(4)                            # Send explicit values to a() via b()
>>> v = next(G)
before...
>>> v
0
>>> while True:
...     v = G.send('Eggs' * (v+1))
...     print('top:', v)
...
gen: Eggs
top: 1
gen: EggsEggs
top: 4
gen: EggsEggsEggsEggsEggs
top: 9
gen: EggsEggsEggsEggsEggsEggsEggsEggsEggsEggs
after... SPAM
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
StopIteration
>>>



#
# Example: using sent values inside a subgenerator
# Both "yield" and "yield from" require "()" unless alone on right of "="
#

>>> def a(N):
...     sum = 0
...     for i in range(N):
...         sum += i + (yield i)        # Add on i plus sent value
...     return sum                      # (0+1+2+3) + (10+20+30+40)
...
>>> def b(N):
...     res = yield from a(N)           # Get subgenerator return value
...     return float(res)               # Return float conversion here
...
>>> G = b(4)
>>> next(G)                             # Run to first yield in a()
0
>>> G.send(10)                          # Send 10 to suspended yield
1
>>> G.send(20)
2
>>> G.send(30)
3
>>> G.send(40)                          # Send 40, a() exits, b() exits
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration: 106.0
>>>



>>> ^Z
C:\Code> py -3.2                        # Return allowed in generators in 3.3+ only
>>> def a():
...     for i in range(4):
...         yield i ** 2
...     return 'SPAM'
...
SyntaxError: 'return' with argument inside generator



#===============================================================================
# 4) In 3.5+: asynch/await (plus asyncio in 3.4)
#  
# New "async" and "await" core language syntax attempts to distinguish some 
# coroutine roles, by adding an entirely new and incompatible model.  
#
# This new model in 3.5:
#
#   -Builds on ideas in the new "asyncio" standard library module in 3.4 
#   -Which builds on the subgenerators added in 3.3
#   -Which builds on the extended generators of 2.5
#   -Which assumes the original model of 2.3 (and 2.4)
#
# For details, see:
#
#   -The PEP for change 0492
#   -Python 3.5's documentation 
#   -http://learning-python.com/books/python-changes-2014-plus.html#coroutines
#   -Or your local priest...
#===============================================================================


# This space intentionally left blank



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