


Python Subprocess Readlines() Hangs
Problem Statement:
When attempting to stream a Ruby file line by line in Python using the subprocess module, the readlines() call blocks indefinitely, preventing further execution.
Cause:
This issue can arise when using the pty module on a non-Linux operating system to simulate a pseudo terminal. pty is a Linux-specific library, and its behavior on other systems is not guaranteed.
Solutions:
1. Use Pexpect:
Pexpect is a cross-platform library designed for automating interactive applications. It provides a high-level interface for sending and receiving data over a pseudo terminal.
import pexpect pexpect.run("ruby ruby_sleep.rb", logfile=sys.stdout)
2. Use Stdbuf:
Stdbuf can be used to enable line buffering in non-interactive mode, allowing output to be flushed on every line.
proc = Popen(['stdbuf', '-oL', 'ruby', 'ruby_sleep.rb'], bufsize=1, stdout=PIPE, stderr=STDOUT, close_fds=True) for line in iter(proc.stdout.readline, b''): print(line) proc.stdout.close() proc.wait()
3. Use Pty from Standard Library (for Linux):
import errno import os import pty from subprocess import Popen, STDOUT master_fd, slave_fd = pty.openpty() # provide tty to enable line-buffering on Ruby's side proc = Popen(['ruby', 'ruby_sleep.rb'], stdin=slave_fd, stdout=slave_fd, stderr=STDOUT, close_fds=True) os.close(slave_fd) try: while 1: try: data = os.read(master_fd, 512) except OSError as e: if e.errno != errno.EIO: raise break # EIO means EOF on some systems else: if not data: # EOF break print('got ' + repr(data)) finally: os.close(master_fd) if proc.poll() is None: proc.kill() proc.wait() print("This is reached!")
The above is the detailed content of Why Does Python's `subprocess.readlines()` Hang When Streaming Ruby Output, and How Can I Fix It?. For more information, please follow other related articles on the PHP Chinese website!

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

Solution to permission issues when viewing Python version in Linux terminal When you try to view Python version in Linux terminal, enter python...

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

SublimeText3 Chinese version
Chinese version, very easy to use

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

SublimeText3 Linux new version
SublimeText3 Linux latest version