DLMDSPWP01 — Programming with Python: Curve-Fitting Assignment

Author: Alen Nukovic — IU International University of Applied Sciences, M.Sc. Artificial Intelligence Module: DLMDSPWP01 — Programming with Python Submission target: June 2026

This repository contains the implementation accompanying the written assignment for the module Programming with Python (DLMDSPWP01). It selects the four best-fitting ideal functions from a pool of fifty for four training datasets using the least-squares criterion, validates test points against the chosen functions using a √2 deviation factor, persists all data in a SQLite database via SQLAlchemy, and visualises the results with Bokeh.

Repository Structure

dlmdspwp01-curve-fitting/
├── src/                Source code
│   ├── exceptions.py   Custom exception hierarchy
│   ├── data_loader.py  CSV loaders (inheritance hierarchy)
│   ├── database.py     SQLAlchemy ORM models and engine setup
│   ├── analysis.py     Ideal-function selector & test-point mapper
│   ├── visualization.py Bokeh plotting
│   └── main.py         End-to-end orchestrator
├── tests/              pytest unit tests
├── data/               Input CSVs (train.csv, ideal.csv, test.csv)
├── docs/               LaTeX manuscript of the written assignment
├── notebooks/          Exploratory notebooks (not part of submission)
├── pyproject.toml      Project metadata and dependencies
└── README.md           This file

Setup

python3.11 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"

Run

python -m src.main

This produces:

• output/results.db — SQLite database with three tables.
• output/plot.html — interactive Bokeh visualisation.

Tests

pytest

Style

Code follows PEP 8 (Python Enhancement Proposal 8). Style is enforced via ruff check src/.