


Calling Python Scripts with User Input Using Subprocess
In Python, you may encounter a scenario where you want to execute a script (referred to as "a.py") that prompts the user for input and produces a JSON-formatted output. To automate the execution of this script from another script (named "b.py") using Python's subprocess module, follow these steps:
Import the necessary modules:
<code class="python">import os import sys from subprocess import check_output</code>
Determine the path to the script you want to execute ("a.py"):
<code class="python">script_path = os.path.join(get_script_dir(), 'a.py')</code>
Use the check_output() function to execute "a.py" and provide it with input:
<code class="python">output = check_output([sys.executable, script_path], input='\n'.join(['query 1', 'query 2']), universal_newlines=True)</code>
This command does the following:
- Provides "query 1" and "query 2" as input to the script.
- Executes the script using the Python interpreter specified by sys.executable.
- Captures the output of the script in the 'output' variable.
By providing input in this manner, you are effectively simulating user interaction with the script. The output can now be used as needed in your "b.py" script.
Additional Alternatives
- Import and Call Function: You can import the "a.py" module and call its functions directly, providing input and retrieving results.
- Use Multiprocessing: If query processing is CPU-intensive, consider using multiprocessing to run each query in a separate process for improved performance.
The above is the detailed content of How to Automate User Input and Retrieve JSON Output from Python Scripts with subprocess?. For more information, please follow other related articles on the PHP Chinese website!

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

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

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

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

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 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

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

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

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

Atom editor mac version download
The most popular open source editor

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