How to Properly Read stdout from a Subprocess Using Asyncio in Python

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http://youtube.com/watch?v=J-Pwrbu7kz4

Learn how to effectively read `stdout` from a subprocess in Python using Asyncio. This guide provides a clear solution to common buffering issues encountered while working with asynchronous processes. • --- • This video is based on the question https://stackoverflow.com/q/78251320/ asked by the user 'Black Jack' ( https://stackoverflow.com/u/21455692/ ) and on the answer https://stackoverflow.com/a/78251685/ provided by the user 'mudskipper' ( https://stackoverflow.com/u/23578988/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. • Visit these links for original content and any more details, such as alternate solutions, comments, revision history etc. For example, the original title of the Question was: Asyncio: how to read stdout from subprocess? • Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... • The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. • If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. • --- • Understanding the Problem: Reading stdout from a Subprocess in Asyncio • When programming in Python, you might encounter the need to communicate with a subprocess. This can include tasks like starting a process, stopping it, and retrieving its output. Recently, a common issue has arisen where developers struggle to read the stdout of a subprocess using the Asyncio library. • Consider the case of a simple stopwatch written in Python. The stopwatch continuously increments a counter and prints the current time to stdout. However, many have found it challenging to capture this output effectively using Asyncio, leading to frustrating empty byte strings. • In this guide, we'll explore the problem and provide a well-structured solution to ensure you can read output from a subprocess using Asyncio. • • The Stopwatch Code • Here's a quick look at the stopwatch code: • [[See Video to Reveal this Text or Code Snippet]] • This code initializes a stopwatch that prints an incrementing number every second. • • Subprocess Manager with Asyncio • The provided code for the RobotManager class is intended to manage the stopwatch process: • [[See Video to Reveal this Text or Code Snippet]] • While this code sets the stage for handling the subprocess, it encounters problems when trying to read the output because of buffering issues associated with stdout. • • Solution to Reading stdout Correctly • The key issue here involves buffering with the subprocess output. Most notably, the default behavior of Python can result in the output being buffered, which prevents real-time reading of the data from stdout. Here’s a detailed solution to ensure you can read from the subprocess effectively. • Step 1: Modify Command to Prevent Output Buffering • You can prevent output from being buffered by running Python with the -u option (unbuffered mode): • Change the command in the RobotManager as follows: • [[See Video to Reveal this Text or Code Snippet]] • Step 2: Update the stop() Method to Continuously Read Output • To capture all output while the subprocess is running, you need to continuously read from the stdout. Here’s the modified stop() method: • [[See Video to Reveal this Text or Code Snippet]] • Step 3: Adding Helpful Print Statements • Introducing print statements can significantly help in debugging. Add outputs that indicate when the stopwatch starts and stops: • [[See Video to Reveal this Text or Code Snippet]] • • Conclusion • By utilizing these modifications, you should be able to seamlessly read the stdout of a subprocess in Python using Asyncio without the frustration of empty outputs. Implementing the -u flag helps eliminate buffering issues, while continuously reading the output ensures you capture all relevant data. • With this knowledge, you can now manage subprocesses more effectively in your Asyncio applications!

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