Python | Automation | Backend | Systems Integration | IoT / R&D
I build software and automation that connect systems, data and hardware.
My public portfolio is built from independent, synthetic projects that demonstrate backend services, resilient API workflows, data pipelines, operational dashboards and hardware-software lab foundations without exposing employer code, customer data or private infrastructure.
- Python automation and backend-oriented tooling.
- Systems integration and resilient API workflows.
- Data processing, ETL and relational persistence.
- Windows diagnostics, IoT, embedded systems and hardware-software integration.
- Applied AI in progress, starting with measurable deterministic baselines.
All public repositories are independent portfolio implementations. They do not contain employer source code, real operational data, private endpoints, credentials, real logs, internal rules, customer identifiers or proprietary architecture.
| Project | Problem | Stack | Differentiator |
|---|---|---|---|
| support-operations-intelligence-platform | Turn noisy operational events into incidents and follow-up actions. | Python, FastAPI, SQLAlchemy, SQLite/PostgreSQL | Database-backed rules, retryable actions, scheduled health sweep, audit history and security automation. |
| operations-automation-platform | Model a backend automation platform with production-style layering. | Python, FastAPI, PostgreSQL, SQLAlchemy, Alembic | Service/repository layers, migrations, Docker Compose, RBAC, audit trail and synthetic automation rules. |
| resumable-api-batch-extractor | Extract paginated API data without losing progress after failures. | Python, httpx, SQLite, NDJSON | Cursor checkpoints, bounded retries and idempotent output with a synthetic API simulator. |
| usb-serial-driver-diagnostics-lab | Diagnose Windows USB serial, driver and COM-port failure modes. | Python, pyserial, Windows/PnP, JSON/HTML reports | Hardware-free simulations plus controlled live probing, VID/PID handling and actionable troubleshooting reports. |
| cellular-gnss-tracker-lab | Model cellular/GNSS tracker resilience without private firmware or real APNs. | ESP32 concepts, modem AT commands, GNSS, Python tooling | State machine, retry/recovery flows, synthetic logs and explicit simulation-first validation. |
| can-j1939-firmware-sniffer-lab | Build a public CAN/J1939 sniffer lab around firmware and host-side tooling. | ESP32, MCP2515, CAN/J1939, Python | Extended CAN ID parsing, PGN/source/destination filters, firmware skeleton, statistics and CSV/JSON export. |
For a concise technical catalog of all 15 main projects, see PORTFOLIO.md.
- api-integration-playground: resilient integration behavior under auth refresh, pagination, retries, timeout, rate-limit and normalization scenarios.
- data-etl-automation-lab: operational data processing with validation, deduplication, manifest output and relational persistence.
- flask-operations-dashboard-lab: browser dashboard with SLA calculations, queue workload metrics and actionable JSON endpoints.
- iot-serial-diagnostics-tool: simulation-first serial diagnostics with baud rate, timeout, health checks, evidence capture and optional real port inventory.
- j1939-can-bench-reader: synthetic CAN/J1939 parser for 29-bit identifier decomposition and PGN logic.
- esp32-iot-integration-lab: public ESP32 lab structure for UART, RFID, CAN, GNSS, Cellular and future MQTT using generic docs and synthetic logs.
- ai-log-triage-lab: synthetic log triage with typed deterministic baseline, structured output, labeled dataset and evaluation metrics.
- python-support-automation-simulator: synthetic support queue workflow with SQLAlchemy, SQLite and audit trail.
- linux-python-service-operations-lab: Linux-focused service operations lab with FastAPI health checks, systemd unit, dedicated service user, environment file, structured logs and safe Bash automation.
The main portfolio repositories include:
- GitHub Issues, feature branches and Pull Requests.
- Published flagship repositories validated through GitHub Actions on 2026-08-22.
- GitHub Actions CI with Ruff, PyTest and coverage.
- ShellCheck and Linux service operations evidence where relevant.
- CodeQL, dependency review and Dependabot on the main projects.
- Professional READMEs with Mermaid diagrams and quick-start commands.
- Architecture docs, ADRs and short contribution guides where they add signal.
- Synthetic datasets and examples.
- Security notes and disclaimers.
- Branch protection on the strongest portfolio repositories.
- Docker where it adds value.
- PostgreSQL 16.15 validated through Docker Compose in
operations-automation-platform.
For publication status and safe LinkedIn/resume claims, see PORTFOLIO_EXECUTION_STATUS.md.
Current: Python FastAPI Flask SQLAlchemy PostgreSQL SQLite Docker Docker Compose Linux systemd Bash ShellCheck PyTest Ruff GitHub Actions REST APIs httpx ETL Windows USB Serial ESP32 GNSS MCP2515 CAN/J1939
Learning path: Applied AI LLM comparison MQTT CI maturity test coverage expansion
- support-operations-intelligence-platform
- operations-automation-platform
- python-support-automation-simulator
- usb-serial-driver-diagnostics-lab
- cellular-gnss-tracker-lab
- can-j1939-firmware-sniffer-lab
- esp32-iot-integration-lab
- iot-serial-diagnostics-tool
- j1939-can-bench-reader
Course repositories and earlier experiments remain available, but the projects above are the primary portfolio signal.
- GitHub: @guilherme-lacerda-tech