devashishmaurya/opd

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1. Identify the project type and purpose

- This is a lightweight Python-based “tool” whose sole purpose is to generate OPD (out‑patient department) slips and prescriptions by reading data from a Google Sheet, applying a rendering template (render.yaml), and producing PDF outputs (prescription.pdf, slip reports).

2. Analyze the file structure

- Top‑level scripts and modules:

• app.py  – The main entry point / orchestrator

• report.py – PDF/report‐generation logic

• google_sheet.py – Google Sheets API client wrapper

• sheetUtil.py – Utility functions for parsing & transforming sheet data

• test.py – Unit/integration tests

• get-pip.py – Bootstrap pip installer (one‐off helper)

- Configuration & assets:

• render.yaml – Template definitions (fields, layout, styling)

• requirements.txt – Dependency list

• prescription.pdf – Sample output or static asset

- README.md simply notes “opd slips,” confirming the PDF generation focus.

3. Key external dependency

- Google Sheets API

4. Main components to show in the diagram

a. Client/Trigger

• CLI or scheduler that invokes app.py

b. Configuration Loader

• render.yaml reader

c. Google Sheets Service

• google_sheet.py calling Google API

d. Data Processing Layer

• sheetUtil.py transforms raw rows into domain objects

e. Report Generation Layer

• report.py uses domain objects + template to render PDF

f. Output Store

• File system (local folder) or downstream distribution

g. Tests

• test.py (can be shown off to the side)

5. Relationships & data flow

- Arrow from CLI → app.py

- From app.py → Configuration Loader (reads render.yaml)

- app.py → Google Sheets Service → external Google API

- Raw data → sheetUtil.py → normalized data

- Normalized data + template → report.py → PDF output

- PDF output → local file system (prescription.pdf, slip_NNN.pdf)

6. Architectural patterns & principles

- Single‐process, layered‐architecture script

- Separation of concerns: API client, utilities, report generation, configuration

- Config driven (render.yaml) to support template changes without code edits

7. Diagram‐drawing guidelines

- Use boxes/containers for each major component:

• App Orchestrator (app.py)

• Config Loader (render.yaml)

• Google Sheets Client (google_sheet.py)

• Data Transformer (sheetUtil.py)

• PDF Generator (report.py)

• Output Store (local FS)

- Use directional arrows to show sequence & data flow:

1) CLI → App

2) App → Config & Sheets Client

3) Sheets Client → Google API

4) Sheet Data → Data Transformer

5) Transformed Data + Template → PDF Generator

6) PDF → Output Store

- Color‑code or shape‑code:

• Blue rectangles for internal modules

• Green cylinder for external Google Sheets API

• Yellow document icon for render.yaml

• Grey folder icon for output storage

- Label each arrow with the artifact passing along (e.g., “raw rows,” “domain objects,” “PDF bytes”).

8. Tailoring for this tool

- Emphasize the core functionality (data read → transform → PDF write).

- Show extensibility point: if tomorrow you add another output format or input source, that becomes another box branching off the Data Transformer.

9. Final notes

- Be exhaustive but keep it simple: you don’t need multiple microservices—just clearly separate the responsibilities.

- Use a canvas tool (Draw.io, Lucidchart) with containers, connectors, and a legend explaining your colors/shapes.

By following these steps and visually grouping the configuration, API client, processing, and output modules, you’ll produce a clear, accurate system‐design diagram tailored to the OPD‐slip generator project.

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