EDIT: We are currently looking for a sponsor for a potential PEP.
Introduction
Hello everyone,
I’ve been looking into Python’s asynchronous generators and noticed a notable difference compared to synchronous generators: asynchronous generators currently do not allow return statements with values. If you try to use return value within an asynchronous generator, it results in a SyntaxError. I believe that permitting return statements with values in asynchronous generators could enhance their functionality and bring them in line with synchronous generators. Before considering drafting a PEP, I wanted to open up a discussion here to gather your thoughts, insights, and gauge the community’s interest in this idea. 
Motivation
In synchronous generators, it’s perfectly acceptable to use a return statement with a value. When the generator is exhausted, this value can be accessed through the StopIteration exception’s value attribute. This feature allows generators to convey a final result upon completion, which can be incredibly useful in various scenarios.
For example:
def gen():
total = 0
for i in range(5):
total += i
yield i
return total # Returns the sum of yielded numbers
g = gen()
for i in g:
print(i)
try:
next(g)
except StopIteration as e:
print(f"Total sum: {e.value}") # Outputs: Total sum: 10
However, when working with asynchronous generators, attempting to use return value raises a SyntaxError:
async def agen():
total = 0
for i in range(5):
total += i
yield i
return total # SyntaxError: 'async generator' can't have non-empty return value
I’d like to propose that we allow return statements with values in asynchronous generators. This change would enable them to return a final value upon completion, just like synchronous generators do.
Benefits
Allowing return statements with values in asynchronous generators would bring several advantages:
-
Consistency and Predictability: It would align the behavior of asynchronous generators with that of synchronous ones, making the language more consistent. This consistency simplifies the mental model for developers and eases the transition for those moving between synchronous and asynchronous code.
-
Expressive Power: With this change, asynchronous generators could convey a final result or status upon completion. This capability can be essential in many programming patterns, such as data processing pipelines where you might want to return a summary statistic after yielding a sequence of results.
-
Code Clarity and Maintainability: Developers would no longer need to rely on external variables, sentinels, or workarounds to pass back a final result. Using an explicit
return valuemakes the code cleaner and more maintainable.
Use Cases
To illustrate the potential benefits, here are some practical examples where allowing return statements with values in asynchronous generators would be helpful:
1. Data Processing Pipelines
Consider an asynchronous generator that processes data chunks and needs to return a final aggregated result, such as a total count or checksum.
async def process_data(stream):
total_bytes = 0
iterator = stream.__aiter__()
while True:
try:
chunk = await anext(iterator)
total_bytes += len(chunk)
yield chunk
except StopAsyncIteration:
break
return total_bytes # Proposed to be allowed
async def main():
stream = async_data_stream()
iterator = process_data(stream)
while True:
try:
chunk = await anext(iterator)
process(chunk)
except StopAsyncIteration as e:
print(f"Total bytes processed: {e.value}")
break
In this example, the asynchronous generator yields data chunks for processing and then returns the total number of bytes processed. This approach avoids the need for external variables to keep track of the total.
2. Asynchronous File Reading with Summary
Imagine reading lines from a file asynchronously and wanting to know the total number of lines read after processing.
async def read_lines(file_path):
line_count = 0
async with aiofiles.open(file_path, 'r') as f:
iterator = f.__aiter__()
while True:
try:
line = await anext(iterator)
line_count += 1
yield line
except StopAsyncIteration:
break
return line_count # Proposed to be allowed
async def main():
iterator = read_lines('data.txt')
while True:
try:
line = await anext(iterator)
process_line(line)
except StopAsyncIteration as e:
print(f"Total lines read: {e.value}")
break
Here, the generator yields each line for processing and returns the total line count upon completion, providing a clear and direct way to access this final result.
3. Database Query with Aggregated Result
Suppose you have an asynchronous generator fetching records from a database and you want to return a summary, like the total value of a certain field.
async def fetch_records(query):
total_value = 0
iterator = database.execute(query).__aiter__()
while True:
try:
record = await anext(iterator)
total_value += record.value
yield record
except StopAsyncIteration:
break
return total_value # Proposed to be allowed
async def main():
iterator = fetch_records('SELECT * FROM sales')
while True:
try:
record = await anext(iterator)
process_record(record)
except StopAsyncIteration as e:
print(f"Total sales value: {e.value}")
break
This pattern allows you to process each record individually while also obtaining an aggregate result at the end without extra steps.
Technical Considerations
To implement this feature, we would need to modify the StopAsyncIteration exception to include a value attribute, similar to StopIteration. The asynchronous iteration protocol would also require updates to handle the return value when the generator is exhausted.
One key aspect is ensuring backward compatibility. Existing asynchronous generators that don’t use return statements with values would continue to function as before. The change would be additive, and developers could opt-in to use the new feature as needed.
We’d also need to consider how asynchronous frameworks like asyncio handle these return values. Updating asyncio and other libraries to support the change would be part of the implementation process.
Potential Challenges
While this proposal offers benefits, there are some challenges to address:
-
Event Loop Adjustments: Event loops and asynchronous frameworks may need updates to support and propagate the return value from asynchronous generators. Ensuring these changes are seamless and don’t introduce regressions is important.
-
Error Handling: We need to be cautious with exception propagation to prevent unintended catching of
StopAsyncIterationexceptions with a value in user code. Aligning with the principles established in PEP 479 regarding exception handling in generators would be essential.
Seeking Feedback & A Sponsor
I’m interested in hearing your thoughts on this proposal:
Do you see value in allowing return statements with values in asynchronous generators? Are there potential pitfalls or unintended consequences we should consider? Would this change enhance your experience when working with asynchronous code in Python?
Your insights and feedback will be invaluable in refining this idea before deciding whether to draft a PEP.
References
