Stop Comparing Age and Height
Right, so you’ve got arithmetic operators working and maths calculations sorted haven’t you. Addition, subtraction, multiplication, division, that whole bit. Now we’re getting to something that catches loads of people out when they start making decisions in their network scripts – python comparison operators.
Python for Network Engineers Blog 14: Arithmetic Operators
Now here’s where most Python courses completely cock it up again. They’ll have you comparing ages to see who’s oldest or comparing heights to see who’s tallest or working out which test score is highest. I’m sitting there thinking, that’s lovely mate but I’ve got interface utilisation to check, VLAN ranges to validate, and device uptime to compare. How’s comparing people’s ages going to help me write proper network monitoring logic then?
Thing is, I made this exact mistake when I started. Few years back, was trying to write a script to check if interface utilisation was above our threshold limits. Had to compare current bandwidth usage against maximum capacity, check if error rates were acceptable, that sort of thing. Kept getting the logic wrong because I didn’t understand which comparison operator to use when. Spent ages manually checking values instead of letting Python do the comparisons. Complete waste of time.
Few months later, needed to build monitoring logic that would alert when network performance dropped below acceptable levels. Thought there’s got to be a better way than manually checking every metric every time.
Found someone who explained python comparison operators properly, this one actually used networking examples. Made much more sense straight away. Instead of comparing student test scores, I’m checking if bandwidth_usage > threshold_limit and error_rate < acceptable_level.
So anyway, let’s do python comparison operators properly using network stuff that matters.
What Python Comparison Operators Actually Are
Right so python comparison operators are symbols that tell Python to compare two values and give you a True or False answer. Greater than, less than, equal to, that sort of thing. Dead useful for making decisions in network monitoring and validation scripts.
Python gives you six comparison operators to work with:
# Basic comparison operators for network monitoring
bandwidth_usage = 850 # Current usage in Mbps
link_capacity = 1000 # Link capacity in Mbps
error_threshold = 0.01 # 1% error threshold
current_errors = 0.005 # Current error rate
# Comparison operators return True or False
overloaded = bandwidth_usage > link_capacity # False (850 > 1000)
at_capacity = bandwidth_usage == link_capacity # False (850 == 1000)
under_capacity = bandwidth_usage < link_capacity # True (850 < 1000)
acceptable_errors = current_errors <= error_threshold # True (0.005 <= 0.01)
high_errors = current_errors >= error_threshold # False (0.005 >= 0.01)
errors_ok = current_errors != error_threshold # True (0.005 != 0.01)
print(f"Link overloaded: {overloaded}")
print(f"At capacity: {at_capacity}")
print(f"Under capacity: {under_capacity}")
print(f"Acceptable errors: {acceptable_errors}")
print(f"High errors: {high_errors}")
print(f"Errors within range: {errors_ok}")
See? Network comparisons that actually matter. Not working out who scored highest on a maths test.
Now here’s something quite clever about python comparison operators that I didn’t know when I started. You can chain them together to check ranges and multiple conditions. Dead useful for checking if values fall within acceptable network parameters.
Had this come up last month actually. Was building a script to validate VLAN configurations. Needed to check if VLAN IDs were in the valid range (1-4094), interface speeds were sensible, that sort of thing. Python’s comparison chaining made the validation logic much cleaner than doing multiple separate checks.
Why This Matters for Network Engineers
Look, networking’s absolutely stuffed with thresholds and limits, isn’t it? Bandwidth thresholds, error rate limits, VLAN ranges, port counts. Everything needs checking against acceptable values.
Understanding python comparison operators properly means you can build proper decision-making logic into your scripts. Makes your monitoring much more reliable when you’re checking network performance or validating configurations.
# Real network threshold checking
interface_stats = {
"name": "GigabitEthernet0/1",
"speed_mbps": 1000,
"input_mbps": 750,
"output_mbps": 680,
"input_errors": 23,
"output_errors": 15,
"total_packets": 1500000
}
# Calculate current metrics
total_usage = interface_stats["input_mbps"] + interface_stats["output_mbps"]
utilisation_percent = (total_usage / interface_stats["speed_mbps"]) * 100
error_rate = (interface_stats["input_errors"] + interface_stats["output_errors"]) / interface_stats["total_packets"]
# Set thresholds
utilisation_warning = 80 # 80% utilisation warning
utilisation_critical = 95 # 95% utilisation critical
error_rate_threshold = 0.01 # 1% error rate threshold
# Use comparison operators for monitoring logic
if utilisation_percent >= utilisation_critical:
status = "CRITICAL"
elif utilisation_percent >= utilisation_warning:
status = "WARNING"
else:
status = "OK"
error_status = "HIGH" if error_rate > error_rate_threshold else "ACCEPTABLE"
print(f"Interface: {interface_stats['name']}")
print(f"Utilisation: {utilisation_percent:.1f}% - {status}")
print(f"Error rate: {error_rate:.4f} - {error_status}")
But here’s where people get confused. When do you use which comparison operator for different network scenarios?
Basic Comparison Operators
This catches people out constantly. Which operator do you use for different types of network validation?
Simple rule I use. Equal (==) for exact matches like VLAN IDs and device types. Greater/less than for thresholds and capacity checks. Not equal (!=) for filtering out unwanted values.
# Equality comparison - exact matches
vlan_sales = 10
vlan_engineering = 20
current_vlan = 10
is_sales_vlan = current_vlan == vlan_sales # True
is_eng_vlan = current_vlan == vlan_engineering # False
# Greater than - capacity and threshold checks
current_bandwidth = 850
link_capacity = 1000
warning_threshold = 800
exceeds_capacity = current_bandwidth > link_capacity # False
exceeds_warning = current_bandwidth > warning_threshold # True
# Less than - checking minimums and limits
min_uptime_hours = 24
current_uptime = 18
uptime_acceptable = current_uptime > min_uptime_hours # False
# Greater than or equal - inclusive thresholds
critical_temp = 70
current_temp = 70
temp_critical = current_temp >= critical_temp # True
# Less than or equal - maximum limits
max_vlans = 4094
allocated_vlans = 4094
within_vlan_limit = allocated_vlans <= max_vlans # True
# Not equal - filtering and exclusions
device_type = "switch"
excluded_type = "router"
include_device = device_type != excluded_type # True
print(f"Sales VLAN: {is_sales_vlan}")
print(f"Exceeds warning: {exceeds_warning}")
print(f"Uptime acceptable: {uptime_acceptable}")
print(f"Temperature critical: {temp_critical}")
print(f"Within VLAN limit: {within_vlan_limit}")
print(f"Include device: {include_device}")
There we go. Basic comparisons that handle most of your network validation logic.
Got caught out by this early on actually. Had a script that was checking interface speeds using greater than when I should have been using greater than or equal. Kept missing interfaces that were exactly at the speed I was looking for. Spent ages debugging before I realised the comparison was excluding valid results. Proper embarrassing that was.
String Comparisons for Network Data
Right so here’s something that confused the hell out of me when I started. Python can compare strings just like numbers, but the rules are different. Dead useful for device names, interface types, status checking.
String Equality and Inequality
Most common string comparisons in networking:
# Device status checking
interface_status = "up"
expected_status = "up"
problem_status = "down"
interface_ok = interface_status == expected_status # True
interface_down = interface_status == problem_status # False
needs_attention = interface_status != expected_status # False
print(f"Interface OK: {interface_ok}")
print(f"Interface down: {interface_down}")
print(f"Needs attention: {needs_attention}")
# Device type validation
device_model = "CSR1000v"
router_models = ["CSR1000v", "ASR1000", "ISR4000"]
switch_models = ["Cat9300", "Cat9400", "Cat9500"]
is_router = device_model in router_models # True (using 'in' operator)
is_switch = device_model in switch_models # False
# String comparison for filtering
hostname = "SW1-ACCESS"
location_prefix = "SW1"
matches_location = hostname.startswith(location_prefix) # True
print(f"Device is router: {is_router}")
print(f"Device is switch: {is_switch}")
print(f"Matches location: {matches_location}")
Brilliant. String comparisons are perfect for device categorisation and status checking.
Alphabetical Comparisons
Sometimes useful for sorting device names or checking ranges:
# Device naming validation
device_names = ["SW1-ACCESS", "SW2-ACCESS", "SW3-DIST", "R1-EDGE"]
# Check if device names are in alphabetical order
first_device = device_names[0]
last_device = device_names[-1]
alphabetically_first = first_device < last_device # True (R1 < SW1)
# VLAN name comparisons for sorting
vlan_names = ["SALES", "ENGINEERING", "GUEST", "MANAGEMENT"]
sorted_vlans = sorted(vlan_names) # Uses < operator internally
print(f"First comes before last: {alphabetically_first}")
print(f"Sorted VLANs: {sorted_vlans}")
# IP address string comparison (be careful with this!)
ip1 = "192.168.1.10"
ip2 = "192.168.1.2"
# This gives wrong result because it's alphabetical, not numeric!
wrong_comparison = ip1 > ip2 # True, but 10 < 2 numerically
print(f"Wrong IP comparison: {wrong_comparison}")
print("Don't compare IP addresses as strings!")
Watch out for IP address comparisons. Strings compare alphabetically, not numerically.
Chaining Comparison Operators
Now here’s something brilliant about python comparison operators that most people don’t know. You can chain them together to check ranges in one go.
# Range checking with chained comparisons
vlan_id = 150
valid_vlan_range = 1 <= vlan_id <= 4094 # True
interface_utilisation = 75
normal_range = 10 <= interface_utilisation <= 80 # True
port_number = 22
ssh_ports = 22 <= port_number <= 22 # True (exactly 22)
# Temperature monitoring
cpu_temp = 65
normal_temp_range = 20 <= cpu_temp <= 70 # True
# Bandwidth validation
allocated_bandwidth = 500
available_bandwidth = 800
valid_allocation = 0 < allocated_bandwidth <= available_bandwidth # True
print(f"Valid VLAN: {valid_vlan_range}")
print(f"Normal utilisation: {normal_range}")
print(f"SSH port: {ssh_ports}")
print(f"Normal temperature: {normal_temp_range}")
print(f"Valid bandwidth allocation: {valid_allocation}")
# Multiple conditions in one check
error_count = 5
uptime_hours = 48
acceptable_interface = 0 <= error_count <= 10 and uptime_hours >= 24
print(f"Interface acceptable: {acceptable_interface}")
Great stuff. Chained comparisons make range checking much cleaner than multiple separate checks.
Common Python Comparison Operators Cock-ups
Let me tell you about cock-ups I see network engineers make when learning python comparison operators. Made most of these myself at some point.
Confusing assignment with equality is a massive one:
# Wrong - using assignment instead of comparison
vlan_id = 10
# if vlan_id = 20: # This would be an error - you can't assign in an if statement
# Right - using equality comparison
if vlan_id == 20:
print("VLAN 20")
else:
print(f"VLAN {vlan_id}")
# Single = assigns a value
# Double == compares values
Single equals assigns. Double equals compares. Different things entirely.
Comparing different data types bit me badly once:
# Wrong - comparing string with number
port_number_str = "22" # String from user input
ssh_port = 22 # Integer
# This comparison will always be False!
wrong_comparison = port_number_str == ssh_port # False ("22" != 22)
print(f"Wrong comparison result: {wrong_comparison}")
# Right - convert to same type first
correct_comparison = int(port_number_str) == ssh_port # True
print(f"Correct comparison result: {correct_comparison}")
# Or convert the other way
string_comparison = port_number_str == str(ssh_port) # True
print(f"String comparison result: {string_comparison}")
Always make sure you’re comparing the same data types. String “22” is not the same as integer 22.
Floating point precision catches people out constantly:
# Floating point precision problems
bandwidth_1 = 0.1 + 0.2
bandwidth_2 = 0.3
# This might not work as expected!
direct_comparison = bandwidth_1 == bandwidth_2 # Might be False due to precision
print(f"0.1 + 0.2 = {bandwidth_1}")
print(f"Expected: {bandwidth_2}")
print(f"Direct comparison: {direct_comparison}")
# Better way - use tolerance for floating point comparisons
tolerance = 0.0001
close_enough = abs(bandwidth_1 - bandwidth_2) < tolerance
print(f"Close enough comparison: {close_enough}")
# Or round the values
rounded_comparison = round(bandwidth_1, 2) == round(bandwidth_2, 2)
print(f"Rounded comparison: {rounded_comparison}")
Floating point numbers can have tiny precision errors. Use tolerance or rounding for comparisons.
Actually Useful Applications
Thing is, once you get python comparison operators sorted, loads of networking tasks become much easier. Let me show you some practical applications.
Network device health monitoring:
# Device health checker using comparison operators
def check_device_health(device_stats):
health_report = {}
# CPU utilisation check
cpu_ok = device_stats["cpu_percent"] <= 80
cpu_critical = device_stats["cpu_percent"] >= 95
if cpu_critical:
health_report["cpu_status"] = "CRITICAL"
elif not cpu_ok:
health_report["cpu_status"] = "WARNING"
else:
health_report["cpu_status"] = "OK"
# Memory utilisation check
memory_ok = device_stats["memory_percent"] <= 85
health_report["memory_status"] = "OK" if memory_ok else "WARNING"
# Temperature check
temp_normal = 20 <= device_stats["temperature"] <= 70
health_report["temp_status"] = "OK" if temp_normal else "CRITICAL"
# Uptime check
min_uptime = 24 # 24 hours minimum
uptime_ok = device_stats["uptime_hours"] >= min_uptime
health_report["uptime_status"] = "OK" if uptime_ok else "WARNING"
# Overall health
all_ok = all(status == "OK" for status in health_report.values())
health_report["overall"] = "HEALTHY" if all_ok else "NEEDS_ATTENTION"
return health_report
# Example device data
device_data = {
"hostname": "SW1-ACCESS",
"cpu_percent": 45,
"memory_percent": 60,
"temperature": 55,
"uptime_hours": 72
}
health = check_device_health(device_data)
print(f"Device: {device_data['hostname']}")
for metric, status in health.items():
print(f" {metric}: {status}")
Brilliant. Comprehensive health checking with comparison operators.
VLAN configuration validation:
# VLAN validator using comparison operators
def validate_vlan_config(vlan_config):
validation_results = {}
for vlan_id, vlan_info in vlan_config.items():
vlan_results = {}
# VLAN ID range check
valid_id = 1 <= vlan_id <= 4094
vlan_results["valid_id"] = valid_id
# VLAN name check
has_name = vlan_info["name"] != "" and vlan_info["name"] is not None
vlan_results["has_name"] = has_name
# Port count check
reasonable_ports = 0 <= vlan_info["port_count"] <= 48
vlan_results["reasonable_ports"] = reasonable_ports
# Status check
valid_status = vlan_info["status"] in ["active", "suspended"]
vlan_results["valid_status"] = valid_status
# Overall VLAN validity
all_valid = all(vlan_results.values())
vlan_results["overall_valid"] = all_valid
validation_results[vlan_id] = vlan_results
return validation_results
# Example VLAN configuration
vlans = {
10: {"name": "SALES", "port_count": 24, "status": "active"},
20: {"name": "ENGINEERING", "port_count": 12, "status": "active"},
5000: {"name": "INVALID", "port_count": 100, "status": "unknown"}, # Invalid
30: {"name": "", "port_count": 8, "status": "suspended"} # Missing name
}
validation = validate_vlan_config(vlans)
for vlan_id, results in validation.items():
print(f"VLAN {vlan_id}:")
for check, result in results.items():
status = "PASS" if result else "FAIL"
print(f" {check}: {status}")
Fantastic. VLAN validation made systematic with comparison operators.
Interface monitoring with thresholds:
# Interface threshold monitoring
def monitor_interfaces(interface_data, thresholds):
alerts = []
for interface in interface_data:
name = interface["name"]
# Utilisation checking
utilisation = interface["utilisation_percent"]
if utilisation >= thresholds["critical_utilisation"]:
alerts.append(f"{name}: CRITICAL utilisation {utilisation}%")
elif utilisation >= thresholds["warning_utilisation"]:
alerts.append(f"{name}: WARNING utilisation {utilisation}%")
# Error rate checking
error_rate = interface["error_rate"]
if error_rate > thresholds["max_error_rate"]:
alerts.append(f"{name}: High error rate {error_rate:.4f}")
# Speed validation
expected_speed = interface["expected_speed"]
actual_speed = interface["actual_speed"]
if actual_speed < expected_speed:
alerts.append(f"{name}: Speed mismatch - expected {expected_speed}, got {actual_speed}")
# Duplex checking
if interface["duplex"] != "full":
alerts.append(f"{name}: Not full duplex - {interface['duplex']}")
return alerts
# Monitoring thresholds
thresholds = {
"warning_utilisation": 70,
"critical_utilisation": 90,
"max_error_rate": 0.01
}
# Interface data
interfaces = [
{"name": "Gi0/1", "utilisation_percent": 85, "error_rate": 0.005,
"expected_speed": 1000, "actual_speed": 1000, "duplex": "full"},
{"name": "Gi0/2", "utilisation_percent": 95, "error_rate": 0.02,
"expected_speed": 1000, "actual_speed": 100, "duplex": "half"},
{"name": "Gi0/3", "utilisation_percent": 45, "error_rate": 0.001,
"expected_speed": 1000, "actual_speed": 1000, "duplex": "full"}
]
alerts = monitor_interfaces(interfaces, thresholds)
if alerts:
print("Interface Alerts:")
for alert in alerts:
print(f" {alert}")
else:
print("All interfaces normal")
Great stuff. Comprehensive interface monitoring with comparison-based logic.
Real Network Examples
Let me show you actual scenarios where python comparison operators matter.
Network capacity planning validation:
# Capacity planning validator
def validate_capacity_plan(current_data, planned_growth, limits):
validation_report = {}
# Calculate projected requirements
projected_users = current_data["users"] * (1 + planned_growth["user_growth"])
projected_bandwidth = current_data["bandwidth_gbps"] * (1 + planned_growth["bandwidth_growth"])
projected_ports = current_data["ports_used"] + planned_growth["additional_ports"]
# Validate against limits
validation_report["users_within_limit"] = projected_users <= limits["max_users"]
validation_report["bandwidth_within_limit"] = projected_bandwidth <= limits["max_bandwidth_gbps"]
validation_report["ports_within_limit"] = projected_ports <= limits["max_ports"]
# Check growth percentages are reasonable
reasonable_user_growth = 0 <= planned_growth["user_growth"] <= 0.5 # Max 50% growth
reasonable_bandwidth_growth = 0 <= planned_growth["bandwidth_growth"] <= 1.0 # Max 100% growth
validation_report["reasonable_user_growth"] = reasonable_user_growth
validation_report["reasonable_bandwidth_growth"] = reasonable_bandwidth_growth
# Calculate headroom
user_headroom = (limits["max_users"] - projected_users) / limits["max_users"]
bandwidth_headroom = (limits["max_bandwidth_gbps"] - projected_bandwidth) / limits["max_bandwidth_gbps"]
port_headroom = (limits["max_ports"] - projected_ports) / limits["max_ports"]
# Check if we have sufficient headroom (at least 20%)
sufficient_headroom = all([
user_headroom >= 0.2,
bandwidth_headroom >= 0.2,
port_headroom >= 0.2
])
validation_report["sufficient_headroom"] = sufficient_headroom
validation_report["projections"] = {
"users": projected_users,
"bandwidth_gbps": projected_bandwidth,
"ports": projected_ports
}
return validation_report
# Current network state
current = {
"users": 150,
"bandwidth_gbps": 2.5,
"ports_used": 120
}
# Planned growth
growth = {
"user_growth": 0.3, # 30% more users
"bandwidth_growth": 0.4, # 40% more bandwidth
"additional_ports": 50 # 50 more ports
}
# Network limits
limits = {
"max_users": 250,
"max_bandwidth_gbps": 5.0,
"max_ports": 240
}
capacity_validation = validate_capacity_plan(current, growth, limits)
print("Capacity Planning Validation:")
for check, result in capacity_validation.items():
if check != "projections":
status = "PASS" if result else "FAIL"
print(f" {check}: {status}")
print(f"\nProjected Requirements:")
for metric, value in capacity_validation["projections"].items():
print(f" {metric}: {value}")
Brilliant. Complete capacity validation using comparison operators.
IP address allocation checker:
# IP allocation validation
def validate_ip_allocations(subnets, allocations):
validation_results = {}
for subnet_name, subnet_info in subnets.items():
subnet_results = {}
# Check if subnet has allocations
if subnet_name in allocations:
allocated_ips = allocations[subnet_name]
# Count allocated IPs
allocated_count = len(allocated_ips)
available_ips = subnet_info["usable_hosts"]
# Utilisation checks
utilisation = allocated_count / available_ips
subnet_results["under_80_percent"] = utilisation <= 0.8
subnet_results["under_95_percent"] = utilisation <= 0.95
subnet_results["not_full"] = allocated_count < available_ips
# Check for valid IP ranges
network_start = subnet_info["first_ip"]
network_end = subnet_info["last_ip"]
valid_ips = all(network_start <= ip <= network_end for ip in allocated_ips)
subnet_results["all_ips_valid"] = valid_ips
# Check for duplicates
no_duplicates = len(allocated_ips) == len(set(allocated_ips))
subnet_results["no_duplicates"] = no_duplicates
subnet_results["allocation_count"] = allocated_count
subnet_results["utilisation_percent"] = utilisation * 100
else:
# No allocations for this subnet
subnet_results["has_allocations"] = False
subnet_results["allocation_count"] = 0
subnet_results["utilisation_percent"] = 0
validation_results[subnet_name] = subnet_results
return validation_results
# Subnet definitions (simplified as integers for this example)
subnets = {
"SALES": {"first_ip": 100, "last_ip": 199, "usable_hosts": 100},
"ENGINEERING": {"first_ip": 200, "last_ip": 299, "usable_hosts": 100},
"GUEST": {"first_ip": 300, "last_ip": 349, "usable_hosts": 50}
}
# Current allocations
allocations = {
"SALES": [101, 102, 103, 104, 105, 150, 151, 152], # 8 IPs
"ENGINEERING": [201, 202, 203, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260], # 14 IPs
"GUEST": [301, 302, 303, 304, 305] # 5 IPs
}
ip_validation = validate_ip_allocations(subnets, allocations)
for subnet, results in ip_validation.items():
print(f"\nSubnet {subnet}:")
for check, result in results.items():
if isinstance(result, bool):
status = "PASS" if result else "FAIL"
print(f" {check}: {status}")
else:
print(f" {check}: {result}")
Fantastic. IP allocation tracking with comparison-based validation.
PCEP Requirements for Comparison Operators
The PCEP exam covers specific aspects of python comparison operators that you need to understand properly.
You need to know all six comparison operators and their behavior:
# All comparison operators with networking examples
a = 1000 # Link speed in Mbps
b = 1000 # Another link speed
equal_to = a == b # True - speeds are equal
not_equal = a != b # False - speeds are equal
greater_than = a > b # False - not greater
less_than = a < b # False - not less
greater_equal = a >= b # True - equal counts as greater-or-equal
less_equal = a <= b # True - equal counts as less-or-equal
print(f"Equal: {equal_to}")
print(f"Not equal: {not_equal}")
print(f"Greater than: {greater_than}")
print(f"Less than: {less_than}")
print(f"Greater or equal: {greater_equal}")
print(f"Less or equal: {less_equal}")
All comparison operators return boolean values (True or False).
Understanding comparison precedence with other operators:
# Comparison operators have lower precedence than arithmetic
result1 = 5 + 3 > 7 # True (calculated as (5 + 3) > 7, which is 8 > 7)
result2 = 10 / 2 == 5 # True (calculated as (10 / 2) == 5, which is 5.0 == 5)
result3 = 2 * 3 <= 6 # True (calculated as (2 * 3) <= 6, which is 6 <= 6)
print(f"5 + 3 > 7: {result1}")
print(f"10 / 2 == 5: {result2}")
print(f"2 * 3 <= 6: {result3}")
# Use brackets for clarity
clear_result = (5 + 3) > 7 # Same as above but more explicit
print(f"Clear result: {clear_result}")
Arithmetic operations happen before comparisons.
Comparison chaining behavior:
# Chained comparisons work left to right
vlan_id = 100
valid_range = 1 <= vlan_id <= 4094 # True
# This is equivalent to:
equivalent = (1 <= vlan_id) and (vlan_id <= 4094)
print(f"Chained comparison: {valid_range}")
print(f"Equivalent comparison: {equivalent}")
# Chaining with different operators
temperature = 65
normal_range = 20 < temperature <= 70 # True (20 < 65 <= 70)
print(f"Temperature in normal range: {normal_range}")
Chained comparisons are evaluated as logical AND operations.
Why This All Actually Matters
Look, understanding python comparison operators properly is fundamental to any decision-making logic you’ll write for network automation. Device monitoring, configuration validation, threshold checking – they all depend on comparing values correctly.
Get python comparison operators wrong and your monitoring logic will be unreliable. Status checks will miss problems, threshold alerts won’t trigger properly, validation scripts will let invalid configurations through. Get them right and you can build robust decision-making into all your network scripts.
The key thing is using python comparison operators for actual network conditions. Bandwidth thresholds, error rate limits, device status checking, configuration validation. Not comparing test scores or people’s ages that have nothing to do with networking.
Understanding comparison operators means your network scripts can make proper decisions automatically. From simple threshold checking to complex validation logic. Makes you much more effective at building reliable network monitoring and automation.
That’s python comparison operators sorted properly. You understand all six operators, when to use each one, and how to avoid common comparison cock-ups. Much better than generic examples that teach you nothing useful for actual networking work.
External Link: Python Expressions Documentation – official Python documentation for comparison operators and chaining
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