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How to Execute External Commands in Python

Learn how to execute external commands in Python using the subprocess module. Complete guide covering subprocess.run(), Popen(), security best practices, and real-world examples for automation and system administration.

#command-line-interface #python-automation #python-programming #python-subprocess #security-best-practices #shell-command-execution #system-administration

10/19/2025, 08:44 PM

Question

How do I execute an external command within Python as if I had typed it directly in a shell or command prompt?

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To execute an external command within Python as if you had typed it directly in a shell or command prompt, you should use the subprocess module from Python’s standard library, with subprocess.run() being the most recommended approach for modern Python (3.5+). This method allows you to run shell commands, capture their output, handle errors, and manage input/output streams effectively. While older methods like os.system() exist, the subprocess module provides better control, security, and flexibility for executing external commands.

Basic Command Execution Methods
Recommended Approach: subprocess.run()
Advanced Options with subprocess.Popen()
Security Considerations and Best Practices
Handling Output and Errors
Real-World Examples
Common Use Cases

Basic Command Execution Methods

Python offers several approaches to execute external commands, each with different capabilities and use cases.

The Recommended subprocess Module

The subprocess module is the modern, flexible approach for running external commands in Python. It was introduced to replace older methods like os.system() and os.popen(), offering better security and control.

Legacy Approach: os.system()

The os.system() function is the oldest method for executing shell commands:

python

import os
# Execute a simple command
result = os.system('ls -l')

However, as noted in the DigitalOcean tutorial, “os.system() function works fine. But it’s not recommended way to execute shell commands.” The main limitations include:

No way to capture command output
Limited error handling
Security vulnerabilities with shell injection
Blocking behavior

Alternative: os.popen()

Another legacy method is os.popen(), which allows you to read or write to the command’s standard input/output:

python

import os
# Get command output
output = os.popen('ls -l').read()

But as discussed on Reddit, for scripts where you need to run shell commands and get their output, subprocess.run() is the preferred modern approach.

Recommended Approach: subprocess.run()

subprocess.run() is the most versatile and recommended method for executing external commands in Python 3.5 and later.

Basic Usage

python

import subprocess

# Simple command execution
result = subprocess.run(['ls', '-l'])

With Shell Commands

When you need to use shell features like pipes, wildcards, or variables:

python

import subprocess

# Execute through shell (use with caution)
result = subprocess.run('ls -l | grep .py', shell=True)

As the Python official documentation explains: “If args is a string, the string specifies the command to execute through the shell. This means that the string must be formatted exactly as it would be when typed at the shell prompt.”

Key Parameters

The subprocess.run() function accepts several important parameters:

Parameter	Description	Example
`args`	Command to execute	`['ls', '-l']` or `'ls -l'`
`shell`	Use shell command	`shell=True`
`capture_output`	Capture stdout/stderr	`capture_output=True`
`text`	Decode output as text	`text=True`
`check`	Raise on non-zero exit	`check=True`
`timeout`	Command timeout	`timeout=30`
`cwd`	Working directory	`cwd='/path/to/dir'`
`env`	Environment variables	`env={'VAR': 'value'}`

Example with Output Capture

python

import subprocess

# Capture command output
result = subprocess.run(['ls', '-l'], capture_output=True, text=True)

print(f"Return code: {result.returncode}")
print(f"Output:\n{result.stdout}")
print(f"Errors:\n{result.stderr}")

Advanced Options with subprocess.Popen()

For more complex scenarios requiring non-blocking execution or direct process interaction, subprocess.Popen() provides the most powerful options.

Basic Popen Usage

python

import subprocess

# Start process without waiting
process = subprocess.Popen(['ls', '-l'])
print(f"Process PID: {process.pid}")

# Wait for completion
return_code = process.wait()

Interactive Process Management

One key advantage of Popen is its non-blocking nature:

python

import subprocess
import time

# Start process and continue doing other work
process = subprocess.Popen(['sleep', '5'])
print("Process started, continuing with other work...")

# Do other tasks
time.sleep(1)
print("Other task completed")

# Wait for process to finish
return_code = process.wait()
print(f"Process completed with code: {return_code}")

Process Communication

Popen allows direct communication with the process:

python

import subprocess

# Process with input/output
process = subprocess.Popen(
    ['python', '-c', 'print(input().upper())'], 
    stdin=subprocess.PIPE, 
    stdout=subprocess.PIPE, 
    text=True
)

# Send input and get output
output, _ = process.communicate('hello world')
print(output)  # Output: HELLO WORLD

Pipeline Construction

As mentioned in the Stack Overflow discussion, Popen allows chaining commands similar to shell pipelines:

python

import subprocess

# Create pipeline equivalent to "dmesg | grep hda"
p1 = subprocess.Popen(['dmesg'], stdout=subprocess.PIPE)
p2 = subprocess.Popen(['grep', 'hda'], stdin=p1.stdout, stdout=subprocess.PIPE)
p1.stdout.close()
output = p2.communicate()[0]
print(output.decode())

Security Considerations and Best Practices

When executing external commands in Python, security should be a primary concern.

Shell Injection Risks

Using shell=True with untrusted input creates security vulnerabilities:

python

# DANGEROUS - vulnerable to shell injection
user_input = "file.txt; rm -rf /"
subprocess.run(f"cat {user_input}", shell=True)  # Security risk!

Safer Alternatives

Always prefer passing arguments as a list when possible:

python

# SAFE - no shell injection risk
user_input = "file.txt; rm -rf /"
subprocess.run(['cat', user_input])  # Safe!

Input Validation

For commands requiring shell features, validate and sanitize input:

python

import shlex

# Safer shell usage with input validation
user_input = "file.txt"
if not any(char in user_input for char in [';', '|', '&', '$']):
    subprocess.run(['cat', user_input], shell=True)
else:
    print("Invalid input detected")

Principle of Least Privilege

Run commands with the minimum necessary permissions. Consider using sudo only when absolutely required and always with specific commands.

Handling Output and Errors

Proper handling of command output and errors is crucial for robust Python scripts.

Return Code Checking

python

import subprocess

# Check return code
result = subprocess.run(['ls', '/nonexistent'], capture_output=True, text=True)

if result.returncode != 0:
    print(f"Command failed with error: {result.stderr}")
else:
    print(f"Command succeeded:\n{result.stdout}")

Using check_call() and check_output()

For convenience, subprocess offers specialized functions:

python

import subprocess

# Raises exception on failure
subprocess.check_call(['ls', '-l'])

# Captures output and raises on failure
output = subprocess.check_output(['ls', '-l'], text=True)
print(output)

Timeout Handling

python

import subprocess
import time

try:
    # Timeout after 5 seconds
    result = subprocess.run(['sleep', '10'], timeout=5)
except subprocess.TimeoutExpired:
    print("Command timed out")
    # Handle timeout case

Real-time Output Streaming

For long-running commands, you may want to process output in real-time:

python

import subprocess

process = subprocess.Popen(
    ['ping', '-c', '5', 'example.com'],
    stdout=subprocess.PIPE,
    stderr=subprocess.PIPE,
    text=True
)

for line in process.stdout:
    print(line.strip())

Real-World Examples

Let’s explore practical examples demonstrating external command execution in common scenarios.

System Information Gathering

python

import subprocess

def get_system_info():
    # Get disk usage
    disk_info = subprocess.run(['df', '-h'], capture_output=True, text=True).stdout
    
    # Get uptime
    uptime = subprocess.run(['uptime'], capture_output=True, text=True).stdout
    
    # Get memory usage
    memory = subprocess.run(['free', '-h'], capture_output=True, text=True).stdout
    
    return {
        'disk_usage': disk_info,
        'uptime': uptime,
        'memory_usage': memory
    }

# Usage
info = get_system_info()
print(info['disk_usage'])

File Operations Automation

python

import subprocess
import os

def organize_files(source_dir):
    """Organize files by extension"""
    extensions = {}
    
    for filename in os.listdir(source_dir):
        if os.path.isfile(os.path.join(source_dir, filename)):
            ext = filename.split('.')[-1].lower()
            if ext not in extensions:
                extensions[ext] = []
            extensions[ext].append(filename)
    
    # Create directories and move files
    for ext, files in extensions.items():
        dir_path = os.path.join(source_dir, ext)
        os.makedirs(dir_path, exist_ok=True)
        
        for filename in files:
            subprocess.run(['mv', os.path.join(source_dir, filename), dir_path])

# Usage
organize_files('/path/to/files')

Network Operations

python

import subprocess

def check_network_connectivity(host):
    """Check if host is reachable"""
    result = subprocess.run(['ping', '-c', '3', host], capture_output=True, text=True)
    
    if result.returncode == 0:
        print(f"{host} is reachable")
        return True
    else:
        print(f"{host} is not reachable")
        return False

# Usage
check_network_connectivity('google.com')

Git Operations

python

import subprocess

def get_git_commit_history(repo_path, limit=5):
    """Get recent git commit history"""
    os.chdir(repo_path)
    result = subprocess.run(
        ['git', 'log', f'--pretty=format:%h - %an : %s', f'--max-count={limit}'],
        capture_output=True,
        text=True
    )
    
    return result.stdout.split('\n')

# Usage
commits = get_git_commit_history('/path/to/repo')
for commit in commits:
    print(commit)

Common Use Cases

External command execution in Python is essential for many automation and system administration tasks.

System Administration

System administrators frequently use Python to automate routine tasks:

python

import subprocess
import time

def monitor_disk_usage():
    """Monitor disk usage and alert if over 90%"""
    result = subprocess.run(['df', '-h'], capture_output=True, text=True)
    lines = result.stdout.split('\n')[1:]  # Skip header
    
    for line in lines:
        if line.strip():
            parts = line.split()
            usage = parts[4]  # Usage percentage
            filesystem = parts[5]
            
            # Extract percentage number
            usage_percent = int(usage.replace('%', ''))
            
            if usage_percent > 90:
                print(f"WARNING: {filesystem} is {usage_percent}% full")

# Run every hour
while True:
    monitor_disk_usage()
    time.sleep(3600)

Data Processing Pipelines

Python scripts can orchestrate complex data processing pipelines:

python

import subprocess

def process_large_dataset(input_file, output_file):
    """Process large dataset using external tools"""
    # Step 1: Compress the file
    subprocess.run(['gzip', input_file])
    compressed_file = f"{input_file}.gz"
    
    # Step 2: Extract and process with awk
    processed_data = subprocess.run(
        ['zcat', compressed_file, '|', 'awk', '{print $1, $3}'],
        shell=True,
        capture_output=True,
        text=True
    )
    
    # Step 3: Save results
    with open(output_file, 'w') as f:
        f.write(processed_data.stdout)
    
    # Clean up
    subprocess.run(['rm', compressed_file])

# Usage
process_large_dataset('large_data.txt', 'processed_data.txt')

Development Automation

Automate development tasks with Python:

python

import subprocess
import os

def run_tests_and_deploy():
    """Run tests and deploy if successful"""
    # Run tests
    test_result = subprocess.run(['pytest'], capture_output=True, text=True)
    
    if test_result.returncode == 0:
        print("All tests passed. Deploying...")
        
        # Build application
        subprocess.run(['npm', 'run', 'build'])
        
        # Deploy to server
        subprocess.run(['scp', '-r', 'dist/', 'user@server:/var/www/'])
        
        print("Deployment completed successfully")
    else:
        print("Tests failed. Deployment aborted.")
        print(test_result.stdout)
        print(test_result.stderr)

# Usage
run_tests_and_deploy()

Security Scanning

Automated security scanning using external tools:

python

import subprocess
import json

def scan_vulnerabilities(target):
    """Run vulnerability scan using nmap"""
    # Run nmap scan
    scan_result = subprocess.run(
        ['nmap', '--script=vuln', target],
        capture_output=True,
        text=True
    )
    
    # Parse results (simplified example)
    vulnerabilities = []
    for line in scan_result.stdout.split('\n'):
        if 'VULNERABLE' in line:
            vulnerabilities.append(line.strip())
    
    return {
        'target': target,
        'vulnerabilities': vulnerabilities,
        'scan_output': scan_result.stdout
    }

# Usage
scan_results = scan_vulnerabilities('192.168.1.1')
print(json.dumps(scan_results, indent=2))

Conclusion

Executing external commands in Python is a powerful capability that enables automation, system administration, and integration with existing tools and workflows. Here are the key takeaways:

Use subprocess.run() as your primary method - This modern approach (Python 3.5+) provides the best balance of simplicity, flexibility, and control for most use cases.
Prevent shell injection - Always pass commands as lists when possible, and only use shell=True when necessary for shell features like pipes or wildcards.
Handle errors properly - Check return codes, capture output, and implement timeout handling to create robust automation scripts.
Choose the right tool for the job - While subprocess.run() is recommended for most cases, understand when to use subprocess.Popen() for non-blocking operations or complex process management.
Leverage existing tools - Python excels at orchestrating external tools and utilities, allowing you to create powerful automation solutions that combine Python’s flexibility with specialized command-line tools.

By mastering external command execution in Python, you can unlock tremendous potential for automation, system administration, and integration tasks across various domains and use cases.

Sources

How to handle command output and errors in Python subprocess?What are the security risks of executing shell commands in Python?How to create a pipeline of commands using subprocess in Python?When should I use subprocess.run() vs subprocess.Popen() in Python?How to execute commands with elevated privileges in Python?How to timeout a command execution in Python subprocess?

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How to Execute External Commands in Python

Contents

Basic Command Execution Methods

The Recommended subprocess Module

Legacy Approach: os.system()

Alternative: os.popen()

Recommended Approach: subprocess.run()

Basic Usage

With Shell Commands

Key Parameters

Example with Output Capture

Advanced Options with subprocess.Popen()

Basic Popen Usage

Interactive Process Management

Process Communication

Pipeline Construction

Security Considerations and Best Practices

Shell Injection Risks

Safer Alternatives

Input Validation

Principle of Least Privilege

Handling Output and Errors

Return Code Checking

Using check_call() and check_output()

Timeout Handling

Real-time Output Streaming

Real-World Examples

System Information Gathering

File Operations Automation

Network Operations

Git Operations

Common Use Cases

System Administration

Data Processing Pipelines

Development Automation

Security Scanning

Conclusion

Sources