Python Course for Designers

Lesson 1 • Installing Python and Your Editor

Install Python and a code editor suited for design workflows. This foundation ensures every subsequent exercise runs without environment errors.

Lesson 2 • The Python Interactive Shell

Use the REPL to test expressions and explore Python behaviour instantly. Immediate feedback accelerates early concept absorption.

Lesson 3 • Navigating the Terminal

Learn essential command-line navigation to run scripts and manage files. Terminal fluency removes friction from all later coding tasks.

Lesson 1 • Variables and Assignment

Assign values to named variables and update them throughout a script. Variables are the primary way design data is tracked in code.

Lesson 2 • Core Data Types

Distinguish integers, floats, strings, and booleans and know when to use each. Correct type selection prevents calculation and logic errors.

Lesson 3 • Arithmetic and Comparison Operators

Perform calculations and compare values using Python operators. These operations underpin every layout calculation and conditional check.

Lesson 4 • Type Conversion

Convert between data types explicitly to avoid runtime errors. Designers frequently convert user input or file data into usable numeric values.

Lesson 1 • for Loops and Iteration

Iterate over sequences to process collections of design assets automatically. for loops eliminate manual repetition across files or data sets.

Lesson 2 • List Comprehensions

Build filtered or transformed lists in a single concise expression. Comprehensions replace verbose loops when generating asset lists or colour palettes.

Lesson 3 • Boolean Logic and Conditions

Combine conditions with and, or, and not to express complex rules. Logical operators are the building blocks of every branching decision.

Lesson 4 • if, elif, and else Statements

Branch script execution based on evaluated conditions. Conditional blocks let scripts respond differently to varied design inputs.

Lesson 1 • Defining and Calling Functions

Write functions with def and invoke them with arguments. Functions are the primary unit of reusable design automation logic.

Lesson 2 • Lambda Functions and Higher-Order Functions

Write concise anonymous functions and pass functions as arguments. These patterns enable compact sorting and filtering of design asset collections.

Lesson 3 • Scope and Variable Lifetime

Understand local and global scope to avoid naming conflicts. Scope awareness prevents subtle bugs in multi-function design scripts.

Lesson 4 • Parameters, Arguments, and Defaults

Control function flexibility using positional, keyword, and default parameters. Flexible signatures make functions adaptable to varied design contexts.

Lesson 1 • Tuples and Immutable Sequences

Use tuples to store fixed data such as RGB colour values or coordinate pairs. Immutability signals that data should not change after creation.

Lesson 2 • Choosing the Right Data Structure

Select the optimal structure based on access patterns and mutability needs. Correct choices improve script performance and code clarity.

Lesson 3 • Dictionaries and Key-Value Data

Map descriptive keys to values to represent structured design metadata. Dictionaries model style tokens, component properties, and asset catalogues.

Lesson 4 • Sets and Unique Collections

Eliminate duplicates and perform set operations on design asset collections. Sets efficiently identify unique tags, fonts, or colour values.

Lesson 1 • Reading and Writing Text Files

Open files with the with statement and read or write content safely. Text file I/O is the foundation for processing design briefs and logs.

Lesson 2 • Working with CSV Data

Parse and generate CSV files using Python's csv module. CSV is the standard format for exporting and importing design asset spreadsheets.

Lesson 3 • Working with JSON Data

Serialise and deserialise JSON to exchange design tokens and configuration data. JSON is the dominant format for design system data interchange.

Lesson 4 • File System Navigation with pathlib

Traverse directories, build paths, and manage files using pathlib. Path manipulation is essential for batch-processing folders of design assets.

Lesson 1 • try, except, and finally Blocks

Wrap risky operations in try blocks and handle exceptions gracefully. Exception handling prevents scripts from crashing on missing files or bad input.

Lesson 2 • Raising and Creating Exceptions

Raise built-in exceptions and define custom ones for domain-specific errors. Custom exceptions make design tool errors descriptive and actionable.

Lesson 3 • Understanding Python Errors

Identify syntax, runtime, and logic errors from tracebacks. Accurate error diagnosis is the first step toward fast, effective debugging.

Lesson 4 • Writing Defensive and Resilient Code

Validate inputs, set safe defaults, and log errors to build scripts that survive real-world conditions. Resilient scripts require minimal manual intervention.

Lesson 1 • Generating Colour Palette Reports

Extract colour data from a JSON token file and produce a formatted text report. This project applies dictionaries, file I/O, and string formatting together.

Lesson 2 • Creating a Simple CLI Design Tool

Accept user arguments from the command line to make scripts flexible and reusable. CLI tools are the standard delivery format for design automation utilities.

Lesson 3 • Automating Asset Renaming Workflows

Build a script that renames design files according to a naming convention. This project integrates file I/O, string formatting, and error handling.

Lesson 4 • Packaging and Sharing Your Scripts

Organise scripts into a distributable package with a README and requirements file. Proper packaging lets teammates install and run tools without setup friction.