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# 01 — Roadmap: Zero → Python SME (Automation + Dashboards + Excel/SQL/SolarWinds)
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Generated: **Monday, February 16, 2026, 2:11 PM (America/Detroit)**
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## What “Python SME” means (concrete outcomes)
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By the end, you can:
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- Build **reliable automation tools** that run unattended (scheduled tasks) and are safe to rerun.
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- Build **repeatable reporting pipelines**: Excel → transform → SQL → dashboard/report.
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- Integrate with **SolarWinds Orion** via API (read metrics, alerts; write/ack where permitted).
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- Ship **internal web GUIs / dashboards** for non-technical teammates.
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- Use modern team standards: **virtual environments, dependency pinning, formatting, linting, tests, logging, packaging**.
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- Teach others: docs, examples, code reviews, patterns, “pitfall” guidance.
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## The optimal learning order (why this order)
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1. **Foundations**: logic + reading code + debugging (otherwise everything else is random memorization).
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2. **Professional workflow**: venv/pip, git, lint/format, tests, logging (so you don’t build fragile scripts).
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3. **Data + IO**: files + Excel (fastest path to real business value).
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4. **SQL**: data persistence + reporting pipeline.
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5. **SolarWinds**: apply APIs + query language + auth + data modeling.
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6. **Dashboards**: UI + data access patterns + caching + security basics.
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7. **CI/CD + packaging**: how you ship repeatably (even if corporate is locked down, you will understand it).
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## Time model (flexible)
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- Baseline: **6–8 hours/week**
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- Typical: **9–12 months** to “team-trusted SME” if you consistently ship small tools.
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- Faster path: 10–12 hours/week + weekly capstone increments.
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You progress by **deliverables**, not by time spent.
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---
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# Phase 0 — Setup (Week 1)
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**Goal:** Your environment is predictable and professional.
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Do: **[03_SETUP_WINDOWS11.md](./03_SETUP_WINDOWS11.md)** (exact steps)
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Deliverables:
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- A folder called `python_sme/` with:
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- `templates/` (project template)
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- `notes/` (your learning notes)
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- `projects/` (each project gets its own folder)
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- You can:
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- create a venv
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- install packages with pip
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- run a script
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- run tests
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---
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# Phase 1 — Foundations (Weeks 2–6)
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**Goal:** You can read and write basic programs without copying blindly.
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Study backbone:
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- **Automate the Boring Stuff (3rd ed)** (Ch. 1–11) citeturn0search12turn0search19
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- Python tutorial for reinforcement (esp. functions, modules) citeturn0search1
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What you must master:
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- Types: int/float/str/bool/None
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- Data structures: list/dict/set/tuple
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- Control: if/elif/else, for/while, break/continue
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- Functions: parameters, return values, “small composable functions”
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- Debugging: reading tracebacks, printing, using VS Code debugger
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- Files: read/write text safely (encoding), paths, directories
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Deliverables:
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- 12–20 “micro scripts” (each 30–120 lines) that do one thing well
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- A personal “pitfalls” note (truthiness, mutability, off-by-one)
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Guide: **[04_FOUNDATIONS.md](./04_FOUNDATIONS.md)**
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---
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# Phase 2 — Professional workflow (Weeks 7–10)
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**Goal:** Your code is usable by others (consistent, tested, logged).
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# 01 - Roadmap: Zero Experience -> Python SME (Enterprise Automation and Dashboards)
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Home: [README](./README.md)
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Core:
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- `venv` + `pip` + dependency pinning citeturn0search5turn0search9
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- `pyproject.toml` as the single config hub citeturn2search1
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- Lint/format: Ruff + Black citeturn0search2
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- Tests: pytest citeturn2search2
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- Logging: Python logging module
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## Who this is for
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- You have zero coding, scripting, or programming experience.
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- You need practical outcomes in an enterprise operations environment.
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- You learn best by doing real work, not passive studying.
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## What you will build
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- Reliable Python automations for files, Excel, SQL, and monitoring data.
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- Repeatable ETL workflows using MSSQL as a reporting backbone.
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- SolarWinds Orion and DPA data ingestion jobs.
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- Browser-based dashboards for non-technical stakeholders.
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Deliverables:
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- A reusable **tool template**:
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- `src/` layout
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- CLI entrypoint
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- config loading
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- structured logging
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- tests
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- lint/format scripts
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## Prerequisites
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- Windows 11 machine.
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- Permission to install Python and VS Code.
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- Access path for MSSQL credentials (non-SSO SQL auth is supported in this plan).
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- Read-only API access to Orion and DPA to start.
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Guide: **[09_QUALITY_TOOLING.md](./09_QUALITY_TOOLING.md)** + **[02_GLOSSARY.md](./02_GLOSSARY.md)**
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## Program overview (8-10 hrs/week default)
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- Phase 0 (Week 1): environment setup and first script.
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- Phase 1 (Weeks 2-6): Python foundations.
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- Phase 2 (Weeks 7-10): quality tooling and team-ready workflow.
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- Phase 3 (Weeks 11-16): file and Excel automation.
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- Phase 4 (Weeks 17-22): SQL-first ETL pipelines.
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- Phase 5 (Weeks 23-28): Orion and DPA integration.
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- Phase 6 (Weeks 29-38): dashboard delivery for browser users.
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- Phase 7 (Weeks 39+): release process, governance, and handoff maturity.
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---
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## Step-by-step lab pack
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# Phase 3 — Files + Excel reporting (Weeks 11–16)
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**Goal:** Immediate business value: repeatable reporting from spreadsheets.
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Tools:
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- `pathlib`, `csv`, `json`
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- `openpyxl` (Excel) and optionally `pandas` (transformations)
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Capstone Project A: **Excel Merger + Validator + Report**
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- Input: folder of Excel files
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- Output: `Master_Report.xlsx` + `Master_Report.csv`
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- Features:
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- schema validation (required columns)
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- normalization (header mismatches)
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- highlight “Critical” rows
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- separate “Critical” tab
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- logs + error summary
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- safe reruns (versioned output)
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### Phase 0 - Setup (Week 1)
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Weekly outcome:
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- Local Python environment works reliably.
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Guide: **[05_AUTOMATION_FILES_EXCEL.md](./05_AUTOMATION_FILES_EXCEL.md)**
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---
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Minimum deliverables:
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- `python --version` works.
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- `.venv` created and activated.
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- First script runs.
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- First test passes.
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# Phase 4 — SQL integration (Weeks 17–22)
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**Goal:** Build “data pipelines” rather than “one-off reports”.
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Done means done:
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- You can repeat setup in a fresh folder without guessing.
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Tools:
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- SQL basics: SELECT/JOIN/GROUP BY
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- Python DB access (pyodbc and/or SQLAlchemy)
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- Migrations concept (optional early, important later)
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Fail/recover guidance:
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- If activation fails, use the troubleshooting section in [03_SETUP_WINDOWS11.md](./03_SETUP_WINDOWS11.md).
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Capstone Project B: **Ingest + Transform + Load**
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- Read Excel/CSV → validate → write to SQL staging → promote to reporting table
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- Idempotency key (reruns don’t duplicate)
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- Reject file output (bad rows)
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### Phase 1 - Foundations (Weeks 2-6)
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Weekly outcomes:
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- Week 2: variables, types, conditionals.
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- Week 3: loops and collections.
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- Week 4: functions and modular thinking.
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- Week 5: file IO and paths.
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- Week 6: debugging and code reading.
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Guide: **[06_SQL.md](./06_SQL.md)**
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---
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Minimum deliverables:
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- 15 micro-scripts.
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- One debugging diary file.
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# Phase 5 — SolarWinds Orion integration (Weeks 23–28)
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**Goal:** Automate monitoring/reporting workflows using Orion data.
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You will learn:
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- Orion platform API basics (SWIS, SWQL concepts)
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- Read nodes/interfaces/alerts/events
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- Produce “daily health” reports
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- (If allowed) acknowledge/annotate alerts
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Done means done:
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- You can explain each script out loud in plain language.
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References:
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- Orion SDK repo citeturn0search23
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- orionsdk-python client citeturn0search3
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Fail/recover guidance:
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- If stuck, reduce problem size and rebuild with toy data.
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Capstone Project C: **SolarWinds Daily Ops Report**
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- Pull top alerts, down interfaces, capacity metrics
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- Output: Excel + HTML dashboard page
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- Optional: push summary to email/Teams webhook
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### Phase 2 - Quality and workflow (Weeks 7-10)
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Weekly outcomes:
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- toolchain setup, formatting, linting, tests, logging.
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Guide: **[07_SOLARWINDS_ORION.md](./07_SOLARWINDS_ORION.md)**
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Minimum deliverables:
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- reusable project template with `pyproject.toml`, tests, logging, and README.
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---
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Done means done:
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- Any teammate can run your tool using documented steps.
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# Phase 6 — Web GUIs / Dashboards (Weeks 29–38)
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**Goal:** Put your reports behind a usable internal UI.
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Fail/recover guidance:
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- If tooling feels heavy, keep features tiny and run checks per feature.
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Recommended order for beginners:
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1. **Streamlit** (fastest to working dashboards) citeturn1search0turn1search14
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2. **Dash** (more “app-like” dashboards; strong data grids) citeturn1search1
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3. **FastAPI** (when you need a real backend API) citeturn1search2
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### Phase 3 - Files and Excel automation (Weeks 11-16)
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Weekly outcomes:
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- robust ingestion of multiple spreadsheets with validation.
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Capstone Project D: **Ops Dashboard**
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- Tabs: Excel reports, SQL summaries, SolarWinds health
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- Filters: customer/site, date range, severity
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- Caching to avoid hammering SolarWinds/SQL
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- Auth strategy appropriate for your environment (documented)
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Minimum deliverables:
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- Capstone A baseline complete.
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Done means done:
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- malformed inputs are rejected safely with clear logs.
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Fail/recover guidance:
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- Start with a 2-file sample dataset and scale gradually.
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### Phase 4 - SQL ETL (Weeks 17-22)
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Weekly outcomes:
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- clean table design and idempotent pipeline loads.
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Minimum deliverables:
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- staging and reporting tables + ETL job + daily summary query.
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Done means done:
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- rerunning ETL does not duplicate records.
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Fail/recover guidance:
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- freeze schema changes until test dataset passes end-to-end.
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### Phase 5 - Orion and DPA integration (Weeks 23-28)
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Weekly outcomes:
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- read-only ingestion from Orion and DPA into cache tables.
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Minimum deliverables:
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- one daily ingestion job from each source.
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Guide: **[08_DASHBOARDS.md](./08_DASHBOARDS.md)**
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Done means done:
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- data contract documented, ingestion stable, errors logged.
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---
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Fail/recover guidance:
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- enforce read-only endpoints first and short polling windows.
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# Phase 7 — Shipping: CI/CD + Packaging + Governance (Weeks 39+)
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**Goal:** Make your work easy to run, update, audit, and hand off.
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### Phase 6 - Dashboard delivery (Weeks 29-38)
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Weekly outcomes:
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- browser-consumable dashboard with filters and exports.
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You will learn (plain-English definitions in glossary):
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- CI/CD (automate test/build/release) citeturn1search3turn1search10
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- PyPI and “internal package indexes” citeturn2search0turn2search7
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- Packaging and distribution options citeturn2search3
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Minimum deliverables:
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- working dashboard with data freshness indicator.
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Deliverables:
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- A “release checklist”
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- A “deployment modes” guide: zip deploy vs wheel vs internal index
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- A “security baseline”: secrets, least privilege, dependency hygiene
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Done means done:
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- non-technical user can answer core ops questions without SQL access.
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Guide: **[11_CHECKLISTS.md](./11_CHECKLISTS.md)** + **[02_GLOSSARY.md](./02_GLOSSARY.md)**
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Fail/recover guidance:
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- fallback to SQL-only cache mode when source APIs are slow.
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---
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### Phase 7 - Shipping and governance (Weeks 39+)
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Weekly outcomes:
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- release process, support runbook, handoff standards.
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# How you will be evaluated (by your team)
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You become the SME when you can consistently:
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- take ambiguous automation/reporting requests
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- clarify requirements
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- deliver tools with:
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- good defaults
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- safe behavior
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- logs + tests
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- docs
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- predictable deploy/run steps
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Minimum deliverables:
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- release checklist and operational runbook.
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Next: **[03_SETUP_WINDOWS11.md](./03_SETUP_WINDOWS11.md)**
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Done means done:
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- another engineer can operate and troubleshoot your tools.
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Fail/recover guidance:
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- capture every incident and convert it into checklist updates.
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## Milestone gates
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- Gate A: setup + first script + first passing test.
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- Gate B: Capstone A supports safe reruns and rejects.
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- Gate C: SQL ETL is idempotent and logged.
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- Gate D: Orion/DPA ingestion proof into MSSQL cache.
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- Gate E: browser dashboard available to stakeholders.
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## If you fall behind (catch-up plan)
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1. Keep only one active project at a time.
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2. Finish minimum deliverables before adding features.
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3. Switch to 45-minute sessions with explicit goals.
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4. Use Hybrid mode until momentum returns.
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## Learning-style options (Play/Build/Dissect/Teach-back)
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- Play: tweak example scripts and observe behavior changes.
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- Build: implement full milestone checklists exactly.
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- Dissect: read unfamiliar scripts and annotate line-by-line intent.
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- Teach-back: explain one concept weekly to another person or a written journal.
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## Expected output
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- A complete progression from beginner to enterprise-capable Python practitioner.
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- A portfolio of capstones tied to your real data systems.
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## Break/fix drills
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- Break path assumptions by renaming input folders.
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- Break schema assumptions by removing required columns.
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- Break API assumptions by forcing timeout values.
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## Troubleshooting
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- If learning stalls: reduce scope, keep daily continuity, and ship smaller increments.
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- If project complexity spikes: return to the previous gate and stabilize.
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## Mastery check
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You are ready to advance when you can:
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- describe your current phase deliverable in one sentence,
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- run it end-to-end,
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- explain where it fails and how to recover.
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## Primary Sources
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- [Python Tutorial](https://docs.python.org/3/tutorial/)
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- [Automate the Boring Stuff](https://automatetheboringstuff.com/3e/)
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- [pytest getting started](https://docs.pytest.org/en/stable/getting-started.html)
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## Optional Resources
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- [Exercism Python](https://exercism.org/tracks/python)
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- [Real Python](https://realpython.com/tutorials/python/)
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## Next
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Go to [03_SETUP_WINDOWS11.md](./03_SETUP_WINDOWS11.md).

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