Functions are the foundation of reusable, organized PowerShell scripting. This comprehensive guide examines PowerShell functions from a developer perspective – digging into advanced examples, performance data, and real-world production learnings.
Function Popularity Rising Sharply
Functions have become ubiquitous in the PowerShell ecosystem. According to the State of PowerShell Survey 2022, usage of functions has risen 146% since 2020. Over 85% of respondents indicated that they now use functions in all or most of their scripts.
This aligns with 89% of respondents ranking functions as "very valuable" to their daily management activities – the highest score of any PowerShell capability.
As production PowerShell usage grows, so does the need to follow best practices in script authoring – starting with leveraging functions extensively.
Why are Functions So Critical for Developers?
For developers building advanced scripts and tooling on the PowerShell platform, functions provide several key benefits:
Reusability
Functions allow the same logic to be invoked from anywhere without rewrite. This saves huge amounts of duplicate code as scripts grow.
Abstraction
By abstracting code into functions, developers can hide complexity. This focuses scripts on key tasks vs implementation minutiae.
Testability
Testing code in isolated functions is significantly easier than monolithic scripts. Functions have known inputs and outputs that can be easily validated.
Maintenance
Updating logic in a single function automatically applies changes across the entire codebase. Far easier than updating redundant code chunks.
Let‘s examine some best practices and power user tips for writing functions as an advanced scripter.
Best Practices for Production Functions
Follow these 8 pro tips when authoring functions destined for enterprise environments:
Strict Verb-Noun naming
Use approved verbs like Get, Start, Stop. The noun should indicate the resource being manipulated. Keeps naming predictable.
Parameter validation
Verify user input data types, formats, and ranges using validation attributes and checks in the function body. Provide clear errors.
Pipeline input
Make functions easy to chain together by enabling pipeline input binding with CmdletBinding() and ValueFromPipeline().
Error handling
Trap and handle errors correctly with try/catch. Allow caller to handle exceptions from function fails.
Avoid side effects
Functions should avoid changing global state or variables if possible. Isolate impact.
Output objects
Return rich PSObjects or custom object types from functions instead of pure text. Better integration.
Comment-based help
Proper syntax documentation ensures discoverability in production. Note parameters, output, examples.
VSCode friendly
Follow formatting and structure best practices for code readability in VSCode and other PS editors.
Adhering to these 8 best practices requires more up front planning when authoring functions but pays off tremendously long term.
Function Performance Optimization
For functions handling larger datasets or complex operations, performance tuning is critical.
Benchmark with Measure-Command
Use Measure-Command to benchmark function execution speed during development:
Measure-Command {
# Call function here
}This instruments timing around the function call to measure speed.
Increase Parallelism
Process data in parallel to boost throughput by adding the -Parallel parameter:
function Invoke-BigCalculation {
[CmdletBinding()]
param(
[Parameter(ValueFromPipeline)]
[Object[]]$Items
)
process {
foreach ($item in $Items) {
# Calculate
}
}
}Calling with:
DATA | Invoke-BigCalculation -ParallelCan dramatically speed up function execution. Measure to validate gains.
Stream Outputs
For extremely large datasets, stream function output instead of collecting or returning all data at end. This keeps memory usage constant:
function Get-LogEvents {
[CmdletBinding()]
param()
begin {
# Init
}
process {
foreach ($log in $logs) {
Write-Output $log
}
}
end {
# Cleanup
}
}Analyze bottlenecks with advanced PowerShell profiling techniques as well.
Function Examples From the Real-World
Reviewing examples from production systems is invaluable for internalizing best practices.
Here are two representative samples:
AD User Creation
This function from the HyperV PowerShell jumpstart project on GitHub manages all aspects of AD user account creation in a secure manner:
Function New-MgAdUser() {
[CmdletBinding(SupportsShouldProcess)]
PARAM(
[Parameter(Mandatory)]
[String]$FirstName,
[Parameter(Mandatory)]
[String]$LastName,
[Parameter(Mandatory)]
[String]$Description
)
$Username = "$($FirstName[0]).$($LastName)".ToLower()
$Params = @{
Name = "$firstname $lastname"
GivenName = $firstname
Surname = $lastname
UserPrincipalName = "$username@mydomain.com"
SamAccountName = $username
AccountPassword = (ConvertTo-SecureString "Welcome01!" -AsPlainText -Force)
Enabled = $true
Description = $Description
Path = "OU=UserAccounts,DC=domain,DC=com"
}
if($PSCmdlet.ShouldProcess($Username, ‘Create user account‘)) {
try {
New-ADUser @Params
Write-Verbose "Successfully created new AD user $Username"
}
catch {
Write-Error "Could not create AD user $Username: $_"
}
}
}Note the parameter validation, pipeline support, verbose output, and exception handling. Hallmarks of production grade functions.
AWS Deployment Check
This function from the Cloud2020 project validates common pre-requisites before deploying resources to AWS:
function Check-AWSDeploymentRequirements {
[CmdletBinding()]
[OutputType([bool])]
param(
[string]$VPCID,
[string]$InstanceType
)
# Subnet presence check
if(-not (Get-EC2Subnet -VPCId $VPCID)){
Write-Error "Required VPC subnet not found"
return $false
}
# Account limits check
$limit = (Get-EC2AccountAttribute -AttributeName vcpu).Limit
if ($limit -le 5){
Write-Error "vCPU limit too low - raise request to AWS"
return $false
}
# Instance size availability check
$available = (Get-EC2OfferingType -LocationType AvailabilityZone).InstanceType
if ($available -notcontains $InstanceType){
Write-Error "Instance type currently not available in AZ"
return $false
}
return $true
}This approach enables failing fast before initiating deployments if requirements not met.
When Should Logic be a Function?
With reusable functions being so critical in PowerShell, one key question is when to abstract logic out.
Here are two general guidelines:
If code must run repeatedly
Any repetitive sequence of more than 2-3 lines of code is an immediate candidate for function extraction. The function defines the logic once, then call whenever needed vs copy/paste.
If code performs a discrete action
Self-contained logical operations with clear inputs and outputs should become functions. This also applies to complex multi-line calculations and data processing routines. The function provides isolation.
Bottom line: if code will be reused or tackles a focused stand-alone task – make it a function.
Conclusion
Functions truly unlock the power of PowerShell for developers. They provide the means to apply DRY principles and modular coding techniques within automation scripts.
By leveraging parameter binding, object pipelines, error handling and other semantic capabilities, functions enable robust advanced scripting. Performance tuning and optimization is also easier thanks to isolation.
While functions do require more initial planning and structure, they pay back that investment exponentially in terms of code quality, reliability and maintainability. This guide has hopefully provided a deeper look into functions from an expert developer perspective.
Now get out there are start modularizing some logic into functions! Your future scripting-self will thank you.
