Multi-Device Show Command

Multi-Device Show Command Collection¶

"From One to Many — Evolve Your Script for Production Scale"¶

In Tutorial #1, you built a script that connects to a single device and exports data to Excel. That's a great start, but real network automation needs to handle multiple devices.

In this tutorial, we'll build on your existing script and evolve it to:

Read device inventory from a CSV file
Loop through multiple devices
Handle errors gracefully (one device failing doesn't stop the others)
Export results to Excel with one sheet per device

This is how you transition from a proof-of-concept to a production-ready tool!

🎯 What You'll Learn¶

By the end of this tutorial, you'll understand:

✅ How to manage device inventory using CSV files
✅ How to loop through multiple devices efficiently
✅ Why per-device error handling is critical
✅ How to combine multi-device data into a single Excel file
✅ How to provide user feedback during long operations
✅ The difference between "fail-fast" and "continue-on-error" patterns

📋 Prerequisites¶

Required Knowledge¶

✅ Completed Tutorial #1 — This builds directly on that script
✅ Basic understanding of CSV files
✅ Comfortable with Python loops and error handling

Required Software¶

# Same libraries as Tutorial #1
pip install netmiko pandas openpyxl

Required Access¶

Multiple Cisco devices (2 or more) with:
SSH enabled
Same credentials (or we'll show you how to handle different credentials)
Reachable from your workstation

🔄 Evolution from Tutorial #1¶

Here's what we're changing:

Tutorial #1 (Single Device)	Tutorial #2 (Multi-Device)
Device details hardcoded in script	Device list in external CSV file
Connects to one device	Loops through multiple devices
Script stops if connection fails	Continues to next device on error
One Excel file, one device	One Excel file, multiple sheets (one per device)
Password entered once	Password entered once, used for all devices

🔧 The Complete Script¶

Here's the full multi-device script. We'll break down what changed below.

"""
Multi-Device Netmiko Script: Show Version to Excel
Description: Connects to multiple Cisco devices from CSV inventory and exports to Excel
Author: Nautomation Prime
"""

# Import required libraries
from netmiko import ConnectHandler
import pandas as pd
import getpass
import csv

# Get password once (used for all devices)
device_password = getpass.getpass('Enter device password: ')

def read_inventory(csv_file):
    """
    Read device inventory from CSV file

    Args:
        csv_file: Path to CSV file containing device information

    Returns:
        List of device dictionaries ready for Netmiko
    """
    devices = []

    try:
        with open(csv_file, 'r') as file:
            reader = csv.DictReader(file)
            for row in reader:
                device = {
                    'device_type': row['device_type'],
                    'host': row['host'],
                    'username': row['username'],
                    'password': device_password,
                    'secret': row.get('secret', ''),  # Optional enable password
                }
                devices.append(device)

        print(f"✓ Loaded {len(devices)} device(s) from {csv_file}")
        return devices

    except FileNotFoundError:
        print(f"✗ Error: Could not find file '{csv_file}'")
        return []
    except KeyError as e:
        print(f"✗ Error: Missing required column in CSV: {e}")
        return []

def collect_from_device(device):
    """
    Connect to a single device and collect show version data

    Args:
        device: Dictionary with connection parameters

    Returns:
        Tuple of (hostname, dataframe) or (hostname, None) on error
    """
    hostname = device['host']

    try:
        print(f"  Connecting to {hostname}...")
        connection = ConnectHandler(**device)

        # Send show command with TextFSM parsing
        output = connection.send_command('show version', use_textfsm=True)

        # Check if parsing was successful
        if isinstance(output, list) and len(output) > 0:
            df = pd.DataFrame(output)
            connection.disconnect()
            print(f"  ✓ Success: {hostname} - {len(output)} row(s) collected")
            return (hostname, df)
        else:
            connection.disconnect()
            print(f"  ⚠ Warning: {hostname} - TextFSM parsing returned no data")
            return (hostname, None)

    except Exception as e:
        print(f"  ✗ Failed: {hostname} - {str(e)}")
        return (hostname, None)

def main():
    """Main function to orchestrate multi-device collection"""

    # Define inventory file
    inventory_file = 'devices.csv'

    print("=" * 60)
    print("Multi-Device Show Version Collection")
    print("=" * 60)

    # Read device inventory
    devices = read_inventory(inventory_file)

    if not devices:
        print("No devices to process. Exiting.")
        return

    # Collect data from all devices
    print(f"\nCollecting data from {len(devices)} device(s)...\n")

    results = {}
    for device in devices:
        hostname, df = collect_from_device(device)
        if df is not None:
            results[hostname] = df

    # Export results to Excel
    if results:
        excel_file = 'multi_device_show_version.xlsx'

        print(f"\n{'=' * 60}")
        print(f"Exporting to Excel: {excel_file}")

        # Create Excel writer object
        with pd.ExcelWriter(excel_file, engine='openpyxl') as writer:
            for hostname, df in results.items():
                # Excel sheet names have a 31-character limit
                sheet_name = hostname[:31]
                df.to_excel(writer, sheet_name=sheet_name, index=False)
                print(f"  ✓ Sheet created: {sheet_name}")

        print(f"\n✓ Successfully exported {len(results)} device(s) to {excel_file}")
        print(f"{'=' * 60}")
    else:
        print("\n✗ No data collected. No Excel file created.")

# Script entry point
if __name__ == "__main__":
    main()

📄 Create Your Inventory File¶

Before running the script, create a CSV file named devices.csv in the same directory:

devices.csv¶

device_type,host,username,secret
cisco_ios,192.168.1.1,admin,
cisco_ios,192.168.1.2,admin,
cisco_ios,192.168.1.3,admin,
cisco_nxos,192.168.1.10,admin,

Column Explanations:

device_type: The Netmiko device type (cisco_ios, cisco_nxos, cisco_xr, etc.)
host: IP address or hostname of the device
username: SSH username
secret: Enable password (leave blank if not needed)

Important Notes:

The CSV must have a header row with these exact column names
All devices should use the same password (you'll enter it once when the script runs)
If devices have different passwords, see the "Advanced Variations" section below

📖 What Changed - Line by Line¶

Let's focus ONLY on what's different from Tutorial #1. I won't re-explain concepts you already learned.

New Import¶

import csv

What it does: Imports Python's built-in CSV library.

Why: We need to read device information from the CSV file. Python's csv module makes this easy and handles edge cases like quoted values and different delimiters.

Password Handling Change¶

Tutorial #1:

'password': getpass.getpass('Enter password: '),

Tutorial #2:

device_password = getpass.getpass('Enter device password: ')

What changed: We now capture the password in a variable BEFORE defining devices.

Why: We only want to prompt for the password once, then reuse it for all devices. In Tutorial #1, the password was part of the device dictionary. Now we store it separately and assign it to each device as we process the CSV.

New Function: `read_inventory()`¶

This function is completely new. Let's break it down:

def read_inventory(csv_file):
    """
    Read device inventory from CSV file

    Args:
        csv_file: Path to CSV file containing device information

    Returns:
        List of device dictionaries ready for Netmiko
    """

What it does: Defines a function that reads our CSV file and returns a list of device dictionaries.

Why: Functions make code reusable and testable. By separating the "read CSV" logic from the "connect to devices" logic, we can easily swap to a different inventory source later (like a database or API).

The triple-quoted docstring documents what the function does, what parameters it expects, and what it returns. This is a Python best practice.

devices = []

What it does: Creates an empty list to store device dictionaries.

Why: We'll loop through the CSV rows and append each device to this list.

try:
    with open(csv_file, 'r') as file:

What it does: Opens the CSV file for reading using a context manager (with).

Why:

The try block catches errors if the file doesn't exist
The with statement automatically closes the file when done, even if an error occurs
'r' means "read mode"

reader = csv.DictReader(file)

What it does: Creates a CSV reader that converts each row into a dictionary.

Why: DictReader automatically uses the first row as column headers. Each subsequent row becomes a dictionary where keys are column names. This is much easier to work with than positional indexes.

For example, if a CSV row is:

1	`cisco_ios,192.168.1.1,admin,`

DictReader converts it to:

{
    'device_type': 'cisco_ios',
    'host': '192.168.1.1',
    'username': 'admin',
    'secret': ''
}

for row in reader:

What it does: Loops through each row in the CSV (after the header).

Why: We need to process each device one at a time.

device = {
    'device_type': row['device_type'],
    'host': row['host'],
    'username': row['username'],
    'password': device_password,
    'secret': row.get('secret', ''),
}

What it does: Creates a device dictionary in the format Netmiko expects.

Why: This dictionary structure is identical to Tutorial #1, but now we're building it from CSV data instead of hardcoding it.

Important detail:

row['device_type'] gets the value from the CSV
device_password uses the password we captured at the start
row.get('secret', '') safely gets the secret, defaulting to empty string if the column is missing

devices.append(device)

What it does: Adds this device dictionary to our list.

Why: We're building a list of all devices to process.

print(f"✓ Loaded {len(devices)} device(s) from {csv_file}")
return devices

What it does: Prints a success message and returns the list of devices.

Why: User feedback! It's important to confirm how many devices were loaded before starting connections.

except FileNotFoundError:
    print(f"✗ Error: Could not find file '{csv_file}'")
    return []

What it does: Catches the error if the CSV file doesn't exist.

Why: If the file is missing, we want a friendly error message, not a Python traceback. Returning an empty list allows the script to exit gracefully.

except KeyError as e:
    print(f"✗ Error: Missing required column in CSV: {e}")
    return []

What it does: Catches errors if required CSV columns are missing.

Why: If someone forgets the device_type column, this provides a clear error message instead of a confusing crash.

New Function: `collect_from_device()`¶

This function wraps the connection logic from Tutorial #1 but adds error handling.

def collect_from_device(device):
    """
    Connect to a single device and collect show version data

    Args:
        device: Dictionary with connection parameters

    Returns:
        Tuple of (hostname, dataframe) or (hostname, None) on error
    """

What it does: Defines a function that handles ONE device.

Why: By putting the connection logic in a function, we can easily call it in a loop for multiple devices. The function returns either (hostname, DataFrame) on success or (hostname, None) on failure.

hostname = device['host']

What it does: Stores the device IP/hostname for easier reference.

Why: We use hostname multiple times in print statements, so storing it in a variable makes code cleaner.

try:
    print(f"  Connecting to {hostname}...")
    connection = ConnectHandler(**device)

What it does: Attempts to connect to the device, wrapped in error handling.

Why: The try block is CRITICAL for multi-device operations. If this device fails, we want to:

Log the error
Continue to the next device

Without try/except, one failed device would crash the entire script!

Note the indentation in the print statement: The leading spaces make output more readable when processing multiple devices.

output = connection.send_command('show version', use_textfsm=True)

if isinstance(output, list) and len(output) > 0:
    df = pd.DataFrame(output)
    connection.disconnect()
    print(f"  ✓ Success: {hostname} - {len(output)} row(s) collected")
    return (hostname, df)

What it does: Same logic as Tutorial #1, but now returns a tuple.

Why: We return (hostname, df) so the main script knows which device this data came from. This is essential for creating separate Excel sheets later.

else:
    connection.disconnect()
    print(f"  ⚠ Warning: {hostname} - TextFSM parsing returned no data")
    return (hostname, None)

What it does: Handles the case where TextFSM parsing fails.

Why: Unlike Tutorial #1 where we printed raw output, here we just log a warning and return None. This keeps the script moving through other devices.

except Exception as e:
    print(f"  ✗ Failed: {hostname} - {str(e)}")
    return (hostname, None)

What it does: Catches ANY error during connection or command execution.

Why: This is the "continue-on-error" pattern. Instead of crashing, we:

Log which device failed and why
Return None to indicate failure
Let the script continue to the next device

Common errors this catches:

Authentication failures
Timeouts
Device unreachable
SSH not enabled

Updated `main()` Function¶

The main function now orchestrates the entire multi-device operation.

inventory_file = 'devices.csv'

What it does: Defines the CSV filename.

Why: Having this at the top of main() makes it easy to change if you want to use a different filename.

print("=" * 60)
print("Multi-Device Show Version Collection")
print("=" * 60)

What it does: Prints a header banner.

Why: Visual feedback. The "=" * 60 creates a 60-character line of equals signs for a nice separator.

devices = read_inventory(inventory_file)

if not devices:
    print("No devices to process. Exiting.")
    return

What it does: Reads the CSV and exits if no devices were loaded.

Why: If the CSV is missing or empty, there's no point continuing. This is defensive programming—check preconditions before doing work.

results = {}
for device in devices:
    hostname, df = collect_from_device(device)
    if df is not None:
        results[hostname] = df

What it does: Loops through all devices and stores successful results in a dictionary.

Why:

results = {} creates an empty dictionary
For each device, we call collect_from_device() which returns (hostname, dataframe)
We use Python's tuple unpacking: hostname, df = collect_from_device(device)
if df is not None checks if collection succeeded
results[hostname] = df stores the DataFrame with the hostname as the key

This builds a dictionary like:

{
    '192.168.1.1': DataFrame(...),
    '192.168.1.2': DataFrame(...),
    '192.168.1.3': DataFrame(...)
}

Excel Export with Multiple Sheets¶

This is the biggest change from Tutorial #1!

if results:

What it does: Only exports if we have at least one successful result.

Why: If all devices failed, don't create an empty Excel file.

with pd.ExcelWriter(excel_file, engine='openpyxl') as writer:

What it does: Creates an Excel writer object using a context manager.

Why:

ExcelWriter allows us to write multiple sheets to one Excel file
engine='openpyxl' specifies which library to use (same one Tutorial #1 uses)
The with statement ensures the file is properly saved when done

for hostname, df in results.items():

What it does: Loops through our results dictionary.

Why: results.items() gives us both the key (hostname) and value (DataFrame) for each successful device.

sheet_name = hostname[:31]

What it does: Truncates the hostname to 31 characters.

Why: Excel has a limitation—sheet names cannot exceed 31 characters. If your hostname is longer, this prevents an error by only taking the first 31 characters.

df.to_excel(writer, sheet_name=sheet_name, index=False)

What it does: Writes this device's DataFrame to its own sheet.

Why:

writer is the Excel file we opened above
sheet_name=sheet_name names the sheet after the device
index=False prevents pandas from adding row numbers

Key difference from Tutorial #1: We're calling to_excel() multiple times (once per device), all writing to the same writer object. This creates multiple sheets in one file!

print(f"  ✓ Sheet created: {sheet_name}")

What it does: Confirms each sheet was created.

Why: Real-time feedback during export. For 50 devices, this shows progress.

print(f"\n✓ Successfully exported {len(results)} device(s) to {excel_file}")

What it does: Prints final success summary.

Why: Confirms how many devices were exported and where to find the file.

🚀 How to Run the Script¶

Step 1: Create the Inventory CSV¶

Create devices.csv with your device information:

device_type,host,username,secret
cisco_ios,10.1.1.1,admin,
cisco_ios,10.1.1.2,admin,
cisco_ios,10.1.1.3,admin,

Important: Save this file in the same directory as your Python script.

Step 2: Save the Script¶

Save the complete script as multi_device_show_version.py

Step 3: Run the Script¶

1	`python multi_device_show_version.py`

Step 4: Enter Your Password¶

When prompted:

1	`Enter device password:`

Type your password (it won't be displayed) and press Enter.

Step 5: Watch the Progress¶

You'll see output like:

============================================================
Multi-Device Show Version Collection
============================================================
✓ Loaded 3 device(s) from devices.csv

Collecting data from 3 device(s)...

  Connecting to 10.1.1.1...
  ✓ Success: 10.1.1.1 - 1 row(s) collected
  Connecting to 10.1.1.2...
  ✓ Success: 10.1.1.2 - 1 row(s) collected
  Connecting to 10.1.1.3...
  ✗ Failed: 10.1.1.3 - Authentication failed

============================================================
Exporting to Excel: multi_device_show_version.xlsx
  ✓ Sheet created: 10.1.1.1
  ✓ Sheet created: 10.1.1.2

✓ Successfully exported 2 device(s) to multi_device_show_version.xlsx
============================================================

Notice that even though device 10.1.1.3 failed, the script continued and exported the two successful devices!

📊 Example Excel Output¶

Open multi_device_show_version.xlsx and you'll see:

Multiple sheet tabs at the bottom (one per device)
Each sheet contains that device's show version data
Sheet names match the device IPs/hostnames

🔄 Trying Different Commands¶

Just like Tutorial #1, you can change the command:

# Change this line:
output = connection.send_command('show version', use_textfsm=True)

# To this:
output = connection.send_command('show ip interface brief', use_textfsm=True)

And update the filename:

excel_file = 'multi_device_interfaces.xlsx'

🎓 Key Concepts Learned¶

Congratulations! You've learned critical production automation patterns:

1. External Inventory Management¶

Instead of hardcoding devices, you now use CSV files. This means:

Non-programmers can update the device list
Easy to maintain as your network grows
Can generate the CSV from other systems (CMDB, monitoring tools, etc.)

2. Continue-on-Error Pattern¶

One device failing doesn't stop the entire job. This is essential for production automation where you might have:

Devices undergoing maintenance
Occasional network blips
Devices with different credential requirements

3. Per-Device Error Handling¶

Each device operation is isolated in a try/except block, providing:

Clear logging of which device failed and why
Ability to collect partial results
Easier troubleshooting

4. Data Aggregation¶

Multiple device results combined into one Excel file with multiple sheets. This is much better than:

Dozens of separate files
Having to manually combine data
Losing track of which device is which

5. User Feedback¶

Progress indicators during long operations keep users informed:

CSV load confirmation
Per-device connection status
Export progress
Final summary

🐛 Troubleshooting¶

"Could not find file 'devices.csv'"¶

Cause: The CSV file isn't in the same directory as the script.

Solution:

Check the CSV file exists
Make sure it's in the same folder as your Python script
Or use an absolute path: inventory_file = 'C:/path/to/devices.csv'

Some Devices Fail with "Authentication failed"¶

Cause: Those devices have different credentials.

Solution: See "Advanced Variations" below for per-device passwords.

Excel Sheet Name is Cut Off¶

Cause: Hostname longer than 31 characters (Excel limit).

Solution: This is expected behavior. The script automatically truncates to 31 characters. If you need full hostnames, you could:

Add a column in the sheet with the full hostname
Create a mapping file
Use shorter hostnames in your CSV

No Data Collected (All Devices Failed)¶

Troubleshooting steps:

Verify you can manually SSH to at least one device
Check the error messages—common issues:
Wrong password
Wrong device_type in CSV
Devices unreachable
Test with just one device in the CSV first

🚀 Advanced Variations¶

Different Passwords Per Device¶

If devices have different passwords, modify the CSV and script:

devices.csv with passwords:

1
2
3

device_type,host,username,password,secret
cisco_ios,10.1.1.1,admin,password1,
cisco_ios,10.1.1.2,admin,password2,

Modified script (don't prompt for password):

# Remove this line:
# device_password = getpass.getpass('Enter device password: ')

# In read_inventory(), change this:
'password': row['password'],  # Get from CSV instead

Security Warning: Storing passwords in CSV is NOT recommended for production. Consider using a vault like HashiCorp Vault, CyberArk, or encrypted files.

Separate Excel Files Per Device¶

If you prefer individual files instead of multiple sheets:

# Replace the Excel export section with:
for hostname, df in results.items():
    excel_file = f"{hostname}_show_version.xlsx"
    df.to_excel(excel_file, index=False, sheet_name='Show Version')
    print(f"  ✓ Created: {excel_file}")

Add Timestamp to Filename¶

To avoid overwriting previous runs:

from datetime import datetime

# Add at the top of main():
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
excel_file = f'multi_device_show_version_{timestamp}.xlsx'

This creates files like: multi_device_show_version_20260215_143022.xlsx

Filter Devices from CSV¶

Only process specific devices:

# After loading devices:
devices = [d for d in devices if d['device_type'] == 'cisco_ios']
print(f"Filtered to {len(devices)} IOS device(s)")

🎯 Next Steps¶

You've now mastered multi-device automation! Ready for the next challenge?

Continue Learning with These Tutorials:

Configuration Backup (Complete the Beginner Path)
Save device configurations to disk
Build timestamped archives for version control
Understand data persistence patterns
Nornir Fundamentals (Intermediate)
Learn a powerful framework for scaling automation
Understand how industries run automation at scale
Multi-threaded device operations (10x speed improvement)
Enterprise Config Backup with Nornir (Intermediate)
See the backup pattern scaled to production
Integration with structured logging and error handling
Real-world patterns used in enterprise deployments

Study Production Code:
Deep Dives — Review complete production tools
Access Switch Audit — Learn parallel device collection and PoE intelligence
CDP Network Audit — Study threading, configuration, and jump host support

Ready to Deploy?
Script Library — Deploy pre-built tools based on these patterns
Credential vaulting with HashiCorp Vault
Event-driven automation and webhooks
GitOps workflows and CI/CD integration
Container deployment and orchestration
Deep Dives — Study production-grade tools:
CDP Network Audit — Multi-threaded topology discovery
Access Switch Audit — Parallel port health collection
Enhance This Script — Practice by adding:
Progress bars (using the tqdm library)
Logging to file with the logging module
Retry logic for failed devices
Different commands for different device types
Export to CSV in addition to Excel

💡 Production Readiness Checklist¶

Want to use this script in production? Consider these enhancements:

🟡 Intermediate Level (Coming Soon in Tutorials)¶

🔴 Expert Level (Coming Soon in Tutorials)¶

These topics are covered in our Intermediate and Expert tutorials!

💬 What You've Accomplished¶

Impressive! You've evolved from a single-device script to a multi-device automation tool. You now understand:

✅ CSV inventory management
✅ Looping through devices
✅ Continue-on-error patterns
✅ Multi-sheet Excel export
✅ User feedback during operations
✅ Defensive programming techniques

This foundation prepares you for enterprise automation scenarios where resilience and scale matter.

← Back to Beginner Tutorials | Continue to Tutorial #3 →

Multi-Device Show Command