Python Intermediate

Capture and share your project dependencies.

Keep API keys and passwords out of your code with environment variables and python-dotenv.

Put the whole module together: venv, dependencies, secrets, and project layout from zero.

Work with dates and times using Python's built-in datetime module.

Calculate durations and add/subtract time.

Convert dates to strings with strftime and strings to dates with strptime.

Naive vs aware datetimes, UTC, and the golden rule of timestamps.

Combine parsing, date arithmetic, and comparisons to compute a Duolingo-style streak.

Read tabular data from CSV files using Python's csv module.

Write data to CSV files using Python's csv module.

The read-process-write pattern: filter rows, sort them, and survive messy data.

Totals per category, counts per key — defaultdict and Counter turn rows into answers.

Read a messy sales CSV, aggregate per product, and write a clean summary file.

Clients, servers, HTTP, and status codes — the vocabulary of the web, before any code.

Make your first HTTP requests with the requests library.

Fetch and navigate JSON data, pass query parameters, and send auth headers.

Send data to APIs with POST, and meet PUT, PATCH, and DELETE.

Timeouts, connection errors, bad statuses, retries — write API code that survives the real internet.

A real CLI tool against a live public API: fetch, rank, and display a user's repositories — robustly.

Use assert to verify assumptions and catch bugs early.

Write organised test cases using Python's built-in unittest framework.

Write and run tests with pytest — the framework the industry actually uses.

Arrange-Act-Assert, edge cases, and the habits that separate useful suites from decorative ones.

Write a real pytest suite — happy path, boundaries, error cases, and a bug hunt.

Create clean data models with @dataclass.

Define a fixed set of named constants with Python enums.

Work with file system paths as objects — the modern replacement for path strings.

Structural pattern matching — Python 3.10's answer to sprawling if/elif chains.

Generics, unions, None-handling, and mypy — type hints as a real engineering tool.

dataclasses + enums + pathlib + match + type hints, composed into one clean data layer.

iter(), next(), and the iterable-vs-iterator distinction that explains a whole class of bugs.

Implement __iter__ and __next__ yourself — and learn when a class beats the generators you already know.

Chain lazy stages into assembly lines that process gigabytes in constant memory.

count, cycle, chain, zip_longest, pairwise — the standard library's iterator building blocks.

A generator pipeline + Counter + itertools, pointed at a server log too big to load.

Build a command-line weather app on the OpenWeatherMap API — keys, params, JSON, and robust errors.

A CLI expense tracker with a dataclass model, CSV persistence, and grouped summaries.

Tame a messy Downloads folder — pathlib, an Enum category map, dry-run safety, and collision handling.

An interactive quiz game from a CSV question bank — plus a persistent high-score file and a pytest suite.