Things I’ve built.
Problems I’ve solved.

Preparing weekly team updates required manually reviewing Jira tickets and compiling progress across projects, operational tasks, and change requests. This tool automates that collection and produces a consistent report.

The approach was to turn Jira activity into a report that follows how the team discusses its work. The tool retrieves tickets for configured team members, captures ongoing work and items closed within the previous seven days, and groups them into completed changes, changes in progress, projects, and business-as-usual tasks. It includes owners, statuses, descriptions, and selected latest comments, then exports a dated text report. Packaging it as a Windows executable makes it easier to run without a separate Python installation.

• Python
• Jira Cloud REST API
• JQL
• Requests
• JSON configuration
• PyInstaller

Earlier versions also included HTML reports and Gmail/email experiments.

A Python automation that brings ServiceNow change requests into Jira and keeps their workflow statuses aligned. It helps technical operations teams track work across both platforms with less duplicate administration.

When changes are managed in ServiceNow but team activity is tracked in Jira, maintaining both systems creates extra work. Details must be copied, records linked and statuses updated manually.

The approach keeps ServiceNow as the source of truth and uses each change number to connect records across the two platforms. Missing Jira tasks are created automatically, while existing tasks receive workflow status updates.

Separating the platform connections from the main workflow makes the integration easier to understand and maintain.

1. Retrieves assigned ServiceNow changes that are active or were completed within the previous seven days.
2. Searches Jira for the corresponding change number.
3. Creates missing Jira tasks with a description and link to the original ServiceNow record.
4. Updates Jira workflow statuses as the source changes progress.
5. Repeats the check periodically.

The integration runs one way—from ServiceNow to Jira. Existing Jira tasks receive status updates; their descriptions and other details are not continually synchronised.

• Python
• ServiceNow Table API
• Jira REST API
• JQL
• Requests
• JSON configuration

Reduces repeated ticket entry, helps keep change statuses consistent and gives team members a direct link to the original record. Time savings have not been measured.

Think4 brings search-result collection, historical records and ranking comparisons into one workflow. It is designed to help businesses and marketing teams explore local search visibility and competitor rankings over time.

Monitoring search visibility manually means repeating searches, recording positions, visiting websites and comparing results with earlier observations. As the number of services and locations grows, this becomes difficult to maintain consistently.

The approach separates collection from analysis. A Python collector gathers search results and saves webpage HTML, while a database retains timestamped ranking observations for the dashboard.

Keeping historical records makes comparisons possible across collection runs, rather than relying on the latest search alone.

1. Loads configured searches combining service categories and Australian locations.
2. Retrieves organic Google results through the Serper API.
3. Retains the first result for each domain and records its search position.
4. Stores timestamped observations in MySQL and downloads webpage HTML separately.
5. Provides dashboard filters, ranking charts, movement comparisons and trend views.

The dashboard reads database history. Saved HTML captures support separate inspection; they are not complete offline copies of websites.

• Python
• Serper API
• Requests
• MySQL
• PHP
• JavaScript
• Chart.js
• JSON
• Git
• GitHub

The project supports 63 configured searches and preserves historical search results and saved webpage files. It demonstrates a repeatable approach to collecting search observations and comparing visibility over time.

Potential benefits include less manual recordkeeping and easier ranking comparisons. Time savings and commercial outcomes have not been measured.

Net Explorer brings network discovery, topology drawings and physical infrastructure documentation into one browser workspace.

It helps engineers understand device connections, inspect supported network protocols, and document equipment across geographic locations, rooms, racks and cabinets.

Network documentation often involves collecting information from individual devices and copying it into separate diagrams, spreadsheets and equipment records.

These documents can become inconsistent as networks change, making troubleshooting and handover more difficult.

The approach combines repeatable network observations with editable documentation. A collector gathers device information, while users review discovered connections, arrange drawings and add physical details.

Uncertain results remain visible for review. Failed polls retain the last successful snapshot, with stale information labelled.

1. Connects the browser workspace to a local or remote collector.
2. Registers network devices and configures read-only SNMP access.
3. Collects device identities, interfaces, neighbours, traffic counters and supported protocol information.
4. Interprets observations to build topology and protocol views.
5. Combines discovered information with user-maintained locations, racks and room layouts.
6. Exports drawings and workspace data for documentation and handover.

Supported views include Spanning Tree, HSRP, OSPF and EtherChannel. Export formats include SVG, PNG, DXF and diagrams.net.

• Node.js
• JavaScript
• Express
• HTML
• CSS
• SNMP
• Leaflet
• OpenStreetMap
• JSON storage
• Custom drawing exporters

Testing tools include the Node test runner, jsdom, Playwright and GNS3.

Saved workspaces, drawings, exports and test records demonstrate the prototype’s collection and documentation capabilities.

The practical benefit is less repeated transcription and a shared workspace for logical connections and physical infrastructure. Time savings and production-scale performance have not been measured.