Python Engineering Lab

A learning-in-public project. I'm a software engineer consolidating my Python and backend fundamentals by implementing one engineering concept at a time — from scratch, by hand, understanding rather than copying — and writing down what I actually learned along the way.

The concepts aren't isolated exercises. Together they build one API — a workout / training tracker — that grows more capable with every step. Concept 01 is a bare REST endpoint; by concept 10 the same API validates input, is covered by tests, persists to a database, supports search, filtering and pagination, imports CSV files, runs scheduled background jobs, caches reads, and parses free-form text into workouts. Ten concepts, one growing codebase.

The project: a workout tracker API

The running example logs workouts — runs, swims, rides, badminton, strength sessions, rest days. A deliberately small domain, chosen so the engineering stays in focus. A few decisions recur throughout:

• A workout has a sport, and optionally a distance_km and duration_min.
• Different sports need different fields: a run needs both distance and duration; strength and badminton need only duration; a rest day needs neither ("conditional validation").
• Absent optional fields are stored as NULL / None, which forces careful handling of missing values throughout the stack.

How this lab works

• One concept per folder, numbered in order (01-..., 02-...).
• I write the first version myself before looking at any reference — the point is understanding, not copying.
• Each concept builds on the previous one's code; the API is cumulative.
• Each folder has its own README with run instructions and honest notes on what tripped me up and what I deliberately left for later.

Architecture

A theme that pays off repeatedly: separation of concerns. From concept 04 on, all database code lives in a db.py data-access layer, and the Flask routes call those functions rather than touching SQL directly. Routes handle HTTP; db.py handles storage. That split is what lets later concepts — like a background job reading the database from outside any request — reuse the same functions cleanly.

Getting started

You'll need Python 3.12 or newer.

git clone https://github.com/ajitagupta/python-engineering-lab.git
cd python-engineering-lab
python -m venv .venv
.venv\Scripts\activate          # macOS/Linux: source .venv/bin/activate

Then open the README inside whichever concept folder you want to run — each lists its own dependencies. Reading them in order shows the API take shape.

Roadmap

Each concept adds one capability to the same workout-tracker API.

Concept	What it adds	Skill	Folder
01 — REST API	List and create workouts over HTTP	Flask routes, HTTP methods, JSON	01-rest-api
02 — Validation & Error Handling	Reject bad input with clear errors	Validation, 400/404, conditional rules	02-validation-error-handling
03 — Pytest API Tests	A test suite proving the API works	pytest, test client, fixtures	03-pytest-api-tests
04 — SQLite Persistence	Store workouts in a database	SQL, a data-access layer, sqlite3	04-sqlite-persistence
05 — Search & Filtering	Filter by sport, distance, duration	Query parameters, dynamic SQL	05-search-filtering
06 — Pagination	Return results in pages with metadata	LIMIT/OFFSET, response metadata	06-pagination
07 — File Uploads	Bulk-import from CSV, all-or-nothing	Multipart uploads, CSV parsing	07-file-upload
08 — Background Scheduler	Log a summary periodically, on a timer	Scheduled jobs, background threads	08-background-scheduler
09 — Caching	Serve repeated reads from a cache	Cache strategies, invalidation	09-caching
10 — Data Parsing & Extraction	Parse free-form text into workouts	Regular expressions, extraction	10-data-parsing

All ten concepts complete. ✅

Tech

Python 3.12 · Flask — the web framework — and APScheduler for background jobs are the only third-party dependencies. Everything else is the standard library: SQLite (sqlite3), CSV parsing (csv, io), and regular expressions (re), plus pytest for tests. Dependencies were added only as each concept needed them.

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A finished learning project. Progress over speed — one concept genuinely understood beats five rushed.