How to Build a Custom PowerShell Debug VisualizerDebug visualizers are tools that help developers inspect complex objects during debugging by presenting them in a more readable, structured, or interactive form. In PowerShell, objects are rich and often nested; a custom debug visualizer can save time, reduce errors, and make debugging more productive. This article walks through the process of building a custom PowerShell debug visualizer: planning, design, implementation, packaging, and usage examples.
Why build a custom PowerShell debug visualizer?
PowerShell objects can contain nested properties, collections, and custom types. The default console output or simple Format-Table/Format-List views can make it hard to quickly find the value you need. A visualizer can:
- Show nested objects as expandable trees.
- Present tables, charts, or diagrams for collections and metrics.
- Render HTML, JSON, or domain-specific visual formats.
- Provide interactive controls for filtering, searching, and copying data.
Use a custom visualizer when you frequently inspect a specific type (e.g., complex configuration objects, Azure resource objects, or custom DTOs) and want a faster, clearer view than raw textual output.
Overview of approaches
There are several ways to implement a PowerShell debug visualizer, each with trade-offs:
- Host an external GUI application and send objects to it (easiest to start, language-agnostic).
- Use a PowerShell module that opens a WPF/WinForms window in-process (good for tight integration on Windows).
- Implement a VS Code extension that renders visualizations in the Debug Console or a WebView (cross-platform, modern editor integration).
- Use a web-based visualizer: serve HTML/JS locally and open in a browser or WebView (flexible UI tech stack).
Which approach to choose depends on your target environment (Windows-only vs cross-platform), UX needs, and whether you want editor integration.
Plan the visualizer: requirements and user stories
Start by defining what the visualizer must do. Example user stories:
- As a developer, I want to inspect nested objects with collapsible nodes.
- As an operator, I want to visualize performance counters as charts.
- As a tester, I want to search and filter properties quickly.
- As a contributor, I want the visualizer to accept piped objects from PowerShell.
Decide key features: tree view, property inspector, JSON/Raw view, search, copy to clipboard, export (CSV/JSON), and optional live updates.
Serializing PowerShell objects reliably
PowerShell objects are often rich .NET objects, PSCustomObject, or hashtables. To send them to a visualizer you need a reliable serialization format.
Options:
- JSON (ConvertTo-Json): familiar and cross-platform, but default depth limit (2) requires setting -Depth.
- XML: useful for strongly typed .NET objects, but more verbose.
- Custom serialization: walk the object graph and emit a normalized structure.
Recommended pattern: build a normalization routine in PowerShell that converts objects into a JSON-serializable structure with explicit type metadata and controlled depth. Example considerations:
- Handle circular references by tracking visited object IDs.
- Preserve type names for custom renderers.
- Convert complex members (ScriptProperty, NoteProperty) into simple key-value pairs.
Minimal normalization example (conceptual):
function Normalize-Object { param($InputObject, $MaxDepth = 5, $Visited = @{}) if ($null -eq $InputObject) { return $null } $id = [RuntimeHelpers]::GetHashCode($InputObject) 2>$null if ($Visited.ContainsKey($id)) { return @{ __ref = $id } } if ($MaxDepth -le 0) { return $InputObject.ToString() } $Visited[$id] = $true if ($InputObject -is [System.Collections.IDictionary]) { $result = @{} foreach ($k in $InputObject.Keys) { $result[$k] = Normalize-Object -InputObject $InputObject[$k] -MaxDepth ($MaxDepth - 1) -Visited $Visited } return @{ __type = 'dictionary'; __value = $result } } if ($InputObject -is [System.Collections.IEnumerable] -and -not ($InputObject -is [string])) { $arr = @() foreach ($item in $InputObject) { $arr += (Normalize-Object -InputObject $item -MaxDepth ($MaxDepth - 1) -Visited $Visited) } return @{ __type = 'array'; __value = $arr } } # For objects: capture public properties $props = @{} foreach ($p in $InputObject | Get-Member -MemberType Properties) { try { $props[$p.Name] = Normalize-Object -InputObject ($InputObject.$($p.Name)) -MaxDepth ($MaxDepth - 1) -Visited $Visited } catch { $props[$p.Name] = "<error reading property>" } } return @{ __type = $InputObject.GetType().FullName; __props = $props } }
Option A — External GUI app (recommended starting point)
Build a small standalone application (C#, Electron, or web server + static site) that accepts normalized JSON and renders it.
High-level flow:
- PowerShell script serializes the object (Normalize-Object) and posts it to the visualizer over HTTP or writes to a temp file and launches the app.
- The app displays the object in an interactive tree, with search and detail panes.
Example stack choices:
- C# WPF/WinForms: native look on Windows, easy to embed .NET types.
- Electron / Node + React/Vue: cross-platform, rapid UI development.
- Lightweight Python + Flask serving a local page, opened in the default browser.
Example: simple local HTTP approach
- Visualizer runs a local HTTP server (localhost:PORT).
- PowerShell posts JSON via Invoke-RestMethod.
- Visualizer receives JSON and shows it in a tree control (e.g., using react-json-view).
PowerShell sender snippet:
$normalized = Normalize-Object -InputObject $MyComplexObject -MaxDepth 6 $json = $normalized | ConvertTo-Json -Depth 100 Invoke-RestMethod -Uri "http://localhost:5000/visualize" -Method Post -Body $json -ContentType "application/json"
Visualizer UI can use libraries:
- react-json-view for expandable JSON trees
- monaco-editor for raw/JSON view
- chart.js or d3 for charts
Option B — In-process PowerShell module with WPF (Windows only)
For tight integration without an external process, create a PowerShell module that opens a WPF window. This works well if your users run PowerShell Desktop on Windows.
Key points:
- Require STA thread for WPF (start with powershell.exe -STA or use Runspace).
- Use XAML to define UI with a TreeView, PropertyGrid-like panel, and search box.
- Convert normalized object to ObservableCollection for binding.
Simplified module sketch:
- Export a cmdlet Show-ObjectVisualizer that accepts -InputObject and opens a WPF window bound to the normalized data.
- Use Add-Type to load helper C# types if needed.
Example invocation:
Show-ObjectVisualizer -InputObject $myObj -Title "My Visualizer"
Be mindful of:
- Threading issues with remote sessions and background runspaces.
- Dependencies and signing requirements if distributing.
If your team uses VS Code, a Debug Visualizer implemented as an extension provides the best debugging UX: integrate with the debug adapter, add a custom view, and show a WebView panel.
High-level tasks:
- Create an extension scaffold (yo code).
- Add a command that registers a webview and listens for messages.
- From a debugging session or from a PowerShell extension hook, send serialized objects to the webview for rendering.
- Use the PowerShell extension’s Debug Adapter Protocol or write a companion script that posts objects to the extension via localhost.
Benefits:
- Runs on Windows/macOS/Linux.
- Uses modern web tech for UI.
- Can attach to breakpoints and visualize objects inline.
UI/UX design: what to show and how
Design the visualizer UI for quick comprehension:
- Left pane: collapsible tree of object structure.
- Right pane: selected node details — full type name, raw value, JSON, and actions (copy, export).
- Top toolbar: search, depth control, refresh, export.
- Optional: small inline charts for numeric arrays, timelines for time-series, or a table view toggle for uniform collections.
Use progressive disclosure: show summary values at higher levels (Count, Type, ToString) and let users drill down for details.
Example: Build a simple Electron-based visualizer
- Initialize Electron app (npm init, install electron, react).
- Create a POST endpoint using Express in the Electron main process.
- Render react-json-view in the renderer to show incoming JSON.
PowerShell side (sender):
$payload = Normalize-Object -InputObject $myObj -MaxDepth 6 | ConvertTo-Json -Depth 200 Invoke-RestMethod -Uri 'http://localhost:4000/visualize' -Method Post -Body $payload -ContentType 'application/json'
Electron main (simplified):
const { app, BrowserWindow } = require('electron'); const express = require('express'); const bodyParser = require('body-parser'); const server = express(); server.use(bodyParser.json({limit: '10mb'})); server.post('/visualize', (req, res) => { mainWindow.webContents.send('visualize', req.body); res.sendStatus(200); }); server.listen(4000); let mainWindow; app.whenReady().then(() => { mainWindow = new BrowserWindow({ webPreferences: { nodeIntegration: true, contextIsolation: false }}); mainWindow.loadURL('file://' + __dirname + '/index.html'); });
Renderer (React) listens for the ‘visualize’ event and updates state, showing react-json-view.
Security considerations
- Bind the server only to localhost to avoid remote access.
- If using temp files, place them in secure temp directories and remove after use.
- Validate incoming JSON before rendering to avoid injection attacks if you include HTML rendering.
- If distributing binaries, sign them and document required execution policies for PowerShell modules.
Packaging and distribution
- PowerShell module: include cmdlet, helper scripts, and optional bundled GUI executable. Publish to PowerShell Gallery.
- Electron app: package with Electron Forge or Electron Builder for Windows/macOS/Linux.
- VS Code extension: package as .vsix and publish to the Marketplace.
Provide clear install steps and a quick-start example that shows sending objects to the visualizer.
Example usage scenarios
- Inspecting Azure Resource Graph results: show resources in a table with expandable properties.
- Debugging complex configuration objects in DevOps pipelines.
- Visualizing test run results or diagnostic payloads as charts and tables.
Testing and maintenance
- Unit-test normalization logic against representative object graphs, including circular references and deep nesting.
- Integration test the full pipeline (PowerShell → visualizer).
- Document behavior for common types and known limitations.
Conclusion
A custom PowerShell debug visualizer can dramatically speed troubleshooting and understanding of complex objects. Start small—normalize objects and render them in an external UI—then iterate toward tighter editor integration or richer visualizations. Focus on robust serialization, simple UX for drill-down, and safe local hosting. With those building blocks you can create a tool that makes inspecting PowerShell objects fast, intuitive, and powerful.