In Practice, Leveraging the "yield from" Syntax in Python 3.3

The "yield from" syntax, introduced in Python 3.3, offers a significant enhancement to the capabilities of generators and coroutines. It establishes a bidirectional connection between a caller and a sub-generator, enabling seamless communication in both directions.

Use Cases for "yield from"

Reading Data from Generators:

• This use case mimics the functionality of a for loop, but with the added convenience of propagating exceptions. For example:

def reader():
    for i in range(4):
        yield '<< %s' % i

def reader_wrapper(g):
    yield from g

wrap = reader_wrapper(reader())
for i in wrap:
    print(i)

# Result:
# << 0
# << 1
# << 2
# << 3

Sending Data to Coroutines:

• This scenario involves creating a coroutine that accepts data sent to it and writes it to a specified location, like a file or a socket. For example:

def writer():
    while True:
        w = (yield)
        print('>> ', w)

def writer_wrapper(coro):
    yield from coro

w = writer()
wrap = writer_wrapper(w)
wrap.send(None)  # Prime the coroutine
for i in range(4):
    wrap.send(i)

# Expected result:
# >>  0
# >>  1
# >>  2
# >>  3

Comparison to Micro-Threads

The yield from syntax shares some similarities with micro-threads in that it allows for suspending and resuming coroutines, creating a lightweight alternative to traditional threads. However, coroutines are more lightweight and have a lower memory overhead compared to micro-threads. They also run on the same thread, avoiding the issues associated with context switching in multi-threaded environments.