Weather Data (Day 25)

Reading CSV weather data in Python, first with the built-in csv library and then with pandas. It is the day-25 assignment of Udemy's 100 Days of Code: The Complete Python Pro Bootcamp. The lectures read the weather of one week from weather_data.csv, collect the temperatures as whole numbers, and then show how pandas does the same in one line: a table is a DataFrame and a column of it is a Series. They convert both to a dictionary and a list, compute the average and the maximum temperature, select rows by a condition (the row of Monday, the row of the hottest day, Monday's temperature in Fahrenheit), create a DataFrame from a dictionary, and export it to a CSV file.

The csv part has no runtime dependencies; pandas is an optional extra. The code keeps the names of the lectures (data, temperatures, temp_list, data_dict, average_temp, monday, to_dict, to_list, mean, max, to_csv) so that you can compare it with your own solution.

Status: in progress. The project foundation (configuration, constants, documentation settings and continuous integration) is in place; the readers and the analysis follow in the next milestones, see docs/project-plan.md.

Requirements

• Python 3.13 or newer.
• git, to clone the repository.
• Optional: Doxygen to build the source documentation.
• No runtime dependencies. pandas (the optional extra pandas) is needed for the second half of the lectures and is installed by the dev extra, together with the development tools (pytest, ruff, mypy).

Set up

Clone the repository, then create a local virtual environment .venv in its root, upgrade pip and install the project with its development tools. The .venv folder is ignored by git.

git clone https://git.tirsystem.com/Tirsvad-Udemy-100-days-of-code/025-weather.git
cd 025-weather

Windows powershell

python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"

If PowerShell refuses to run the activation script, allow scripts for this window only with Set-ExecutionPolicy -Scope Process -ExecutionPolicy RemoteSigned and activate again.

Linux debian

Debian 13 or newer ships Python 3.13. On older releases install Python 3.13 separately.

sudo apt install python3 python3-venv
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"

MacOS

brew install python@3.13
python3.13 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"

To install only what the csv part needs, leave out the extras: python -m pip install -e .. To add pandas without the development tools use python -m pip install -e ".[pandas]".

Run

With the virtual environment active, the program that prints the results of the lectures is added in a later milestone (python -m weather); until then the package can be imported:

python -c "from weather import constants; print(constants.DATA_FILE)"

Run the tests

The tests write only into temporary folders.

pytest

The same checks that continuous integration runs:

python -m pytest
python -m ruff check src tests
python -m ruff format --check src tests
python -m mypy

Continuous integration

.gitea/workflows/ci.yml runs on Gitea Actions on every push and on every pull request. It sets up Python 3.13, upgrades pip, installs .[dev], then runs pytest, ruff (lint and format check) and mypy. It does not build the source documentation: run doxygen Doxyfile yourself, as the next section shows.

The workflow lives in .gitea/workflows and not in .github/workflows, so GitHub does not run it and pushing to a GitHub mirror needs no workflow permission.

Build the source documentation

The source is documented with Doxygen comments and the Doxyfile in the root. Install Doxygen (winget install DimitriVanHeesch.Doxygen on Windows, sudo apt install doxygen on Debian, brew install doxygen on macOS), then:

doxygen Doxyfile

The HTML is written to build/doxygen/index.html. A warning fails the build.

Project layout

.
├── .gitea/workflows/ci.yml    continuous integration (Gitea Actions)
├── docs/                      business case, plan, milestones, reviews
├── src/weather/               the package
│   ├── __init__.py
│   └── constants.py           every constant of the lectures
├── tests/                     pytest tests (conftest.py runs every test in a
│                              temporary folder)
├── Doxyfile                   source documentation settings
├── LICENSE
├── pyproject.toml             project configuration
└── README.md

License

GNU Affero General Public License v3.0 only. See LICENSE.