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Commit 8977566

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edoardob90edoardob90
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‎.flake8

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per-file-ignores =
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binder/ipython_config.py:E266

‎.github/workflows/build-docker-image.yml

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---
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name: Build Tutorial Container
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on:
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push:
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branches:
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- main
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paths-ignore:
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- '*.md'
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- slides/**
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- images/**
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- .gitignore
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workflow_dispatch:
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jobs:
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repo2docker:
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runs-on: ubuntu-latest
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permissions:
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packages: write
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steps:
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- name: checkout files in repo
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uses: actions/checkout@main
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- name: update jupyter dependencies with repo2docker
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uses: jupyterhub/repo2docker-action@master
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with:
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DOCKER_USERNAME: ${{ github.actor }}
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DOCKER_PASSWORD: ${{ secrets.GITHUB_TOKEN }}
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DOCKER_REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}
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FORCE_REPO2DOCKER_VERSION: jupyter-repo2docker==2023.06.0

‎.gitignore

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.DS_Store
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*_files/
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*.html
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.idea/

‎.mypy.ini

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[mypy]
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; Do not warn about missing return statements
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warn_no_return = False
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; Show error messages in context
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show_error_context = True
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; Allow untyped definitions and calls
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disallow_untyped_defs = False
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disallow_untyped_calls = False
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; Disable import errors
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disable_error_code = import

‎.pre-commit-config.yaml

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- id: isort
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args: [--profile, black, --filter-files]
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- repo: https://github.com/PyCQA/autoflake
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rev: v2.2.0
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rev: v2.2.1
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hooks:
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- id: autoflake
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- repo: https://github.com/asottile/pyupgrade
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rev: v3.9.0
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rev: v3.14.0
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hooks:
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- id: pyupgrade
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args: [--py38-plus]
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- repo: https://github.com/psf/black
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rev: 23.7.0
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rev: 23.9.1
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hooks:
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- id: black
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language_version: python3 # Should be a command that runs python3.6+
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- repo: https://github.com/PyCQA/flake8
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rev: 6.0.0
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rev: 6.1.0
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hooks:
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- id: flake8
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args: [--count, --show-source, --statistics]
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- pyflakes
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- tryceratops
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v1.4.1
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rev: v1.5.1
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hooks:
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- id: mypy
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additional_dependencies:
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hooks:
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- id: yamlfmt
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- repo: https://github.com/asottile/setup-cfg-fmt
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rev: v2.4.0
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rev: v2.5.0
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hooks:
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- id: setup-cfg-fmt
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- repo: https://github.com/kynan/nbstripout

‎README.md

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# python-tutorial
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3-
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/empa-scientific-it/python-tutorial.git/main?labpath=index.ipynb)
4-
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/empa-scientific-it/python-tutorial.git/main?labpath=index.ipynb) [![Build Docker container](https://github.com/empa-scientific-it/python-tutorial/actions/workflows/build-docker-image.yml/badge.svg)](https://github.com/empa-scientific-it/python-tutorial/actions/workflows/build-docker-image.yml)
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## Run the tutorial on your computer
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### 0. Prerequisites
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You have two ways in which you can run the tutorial **locally**.
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### 1. With a `conda` environment
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#### 0. Prerequisites
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To run the tutorial locally, you should first install [conda](https://docs.conda.io/en/latest/miniconda.html) (or [mamba](https://mamba.readthedocs.io/en/latest/installation.html)).
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It is also suggested that you have a recent version of `git`. Check out [how to install `git`](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) on your operating system.
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### 1. Download the material
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#### 1. Download the material
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Go to the directory on your machine where you want to download the material and clone the repository:
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Extract the archive in a directory of your choice.
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### 2. Create a dedicated environment
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#### 2. Create a dedicated environment
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Enter the tutorial folder with
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> If you are on Windows and using Command Prompt or the PowerShell, please make sure to adjust the paths in the commands above accordingly.
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Then activate the environment with
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```console
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conda activate python-tutorial
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```
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conda env update -f binder/environment.yml
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```
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### 3. Launch the tutorial via Jupyter
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#### 3. Launch the tutorial via Jupyter
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Finally, launch JupyterLab with
65+
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```console
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jupyter lab
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```
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To update the existing environment, run
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```console
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conda env update -f environment.yml
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```
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### 2. With Docker
77+
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> **Note**
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>
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> The following instructions are for Windows. With minor changes, the steps work on macOS or Linux as well.
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1. Install Docker Desktop: First, you need to install Docker Desktop on your Windows machine. You can download it from the official Docker website: https://www.docker.com/products/docker-desktop.
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2. Create a folder: Open File Explorer and create a new folder where you want to save the tutorial's materials. For example, you could create a folder called "python-tutorial" on your Desktop.
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3. Open PowerShell: Once Docker Desktop is installed, open PowerShell on your Windows machine. You can do this by pressing the "Windows" key and typing "PowerShell" in the search bar.
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4. Pull the Docker image: In PowerShell, run the following command to pull the "empascientificit/python-tutorial" Docker image:
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```console
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docker pull ghcr.io/empa-scientific-it/python-tutorial:latest
92+
```
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5. Run the Docker container: Once the image is downloaded, run the following command to start a Docker container from the image:
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```console
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docker run -p 8888:8888 --name python_tutorial -v /path/to/python-tutorial:/home/jovyan/work ghcr.io/empa-scientific-it/python-tutorial:latest jupyter lab --ip 0.0.0.0 --no-browser
98+
```
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Replace `/path/to/python-tutorial` with the path to the folder you created in step 2, for example `C:/Users/yourusername/Desktop/python-tutorial`.
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> **Note**
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>
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> The above command will **mirror** the content of your local folder (e.g., `C:/Users/yourusername/Desktop/python-tutorial`) to the `work/` folder **inside the container**. In this way, every file or folder you copy or create into `work/` will be saved on your machine, and will remain there **even if you stop Docker**.
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6. Access the Jupyter Notebook: Open a web browser and navigate to `http://localhost:8888/lab`. You should see the Jupyter Notebook interface. Enter the token provided in the PowerShell console to access the notebook. Alternatively, you can directly click on the link that appears in the PowerShell after the container has started.
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You can now use the Jupyter in the Docker container to run the python-tutorial. When you're done, you can stop the container by pressing `Ctrl+C` in the PowerShell console.
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> **Note**
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>
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> If you want to restart the container, you can simply run the command `docker container start python_tutorial`.

‎binder/environment.yml

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channels:
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- conda-forge
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dependencies:
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- python
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- python=3.10
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- pip
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- pip:
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- numpy

‎binder/ipython_config.py

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# Configuration file for ipython.
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c = get_config() # noqa
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c = get_config() # noqa # type: ignore
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# ------------------------------------------------------------------------------
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# InteractiveShellApp(Configurable) configuration

‎magic_example.ipynb

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"%%ipytest\n",
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"# or %%ipytest test_module_name\n",
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"\n",
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"len('a')\n",
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"def solution_power2(x: int) -> int:\n",
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" print('hi')\n",
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" len('b')\n",
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" print(len('bb'))\n",
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" return x ** 2\n",
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"len('aaa')"
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" return x * 2"
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]
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},
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{

‎tutorial/tests/test_control_flow.py

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return True
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def reference_solution_find_factors(num: int) -> List[int]:
143+
def reference_find_factors(num: int) -> List[int]:
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"""Dumb way to find the factors of an integer"""
145145
if is_prime(num):
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return [1, num]
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@pytest.mark.parametrize("num", [350, 487, 965, 816, 598, 443, 13, 17, 211])
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def test_find_factors(num: int, function_to_test) -> None:
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assert function_to_test(num) == reference_solution_find_factors(num)
152+
assert function_to_test(num) == reference_find_factors(num)
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#
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)
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def reference_solution_find_pair(nums: List[int]) -> int:
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def reference_find_pair(nums: List[int]) -> int:
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"""Reference solution (part 1)"""
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complements = {}
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for num in nums:
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@pytest.mark.parametrize("nums", [nums_1, nums_2])
175175
def test_find_pair(nums: List[int], function_to_test) -> None:
176-
assert function_to_test(nums) == reference_solution_find_pair(nums)
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assert function_to_test(nums) == reference_find_pair(nums)
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179-
def reference_solution_find_triplet_slow(nums: List[int]) -> int:
179+
def reference_find_triplet_slow(nums: List[int]) -> int:
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"""Reference solution (part 2), O(n^3)"""
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n = len(nums)
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for i in range(n - 2):
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return nums[i] * nums_2[j] * nums[k]
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189-
def reference_solution_find_triplet(nums: List[int]) -> int:
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def reference_find_triplet(nums: List[int]) -> int:
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"""Reference solution (part 2), O(n^2)"""
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n = len(nums)
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for i in range(n - 1):
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@pytest.mark.parametrize("nums", [nums_1, nums_2])
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def test_find_triplet(nums: List[int], function_to_test) -> None:
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assert function_to_test(nums) == reference_solution_find_triplet(nums)
204+
assert function_to_test(nums) == reference_find_triplet(nums)
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207207
#
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# Exercise 3: Cats with hats
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#
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212-
def reference_solution_cats_with_hats() -> int:
212+
def reference_cats_with_hats() -> int:
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"""Solution with dictionaries"""
214214
cats = {i: False for i in range(1, 101)}
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224224
def test_cats_with_hats(function_to_test) -> None:
225-
assert function_to_test() == reference_solution_cats_with_hats()
225+
assert function_to_test() == reference_cats_with_hats()
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#
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241241
trees_1, trees_2 = (parse_data(f"trees_{num}.txt") for num in (1, 2))
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243243

244-
def reference_solution_toboggan_p1(
245-
trees_map: List[List[int]], right: int, down: int
246-
) -> int:
244+
def reference_toboggan_p1(trees_map: List[List[int]], right: int, down: int) -> int:
247245
"""Reference solution (part 1)"""
248246
start, trees, depth, width = [0, 0], 0, len(trees_map), len(trees_map[0])
249247
while start[0] < depth:
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262260
def test_toboggan_p1(
263261
trees_map: List[List[int]], right: int, down: int, function_to_test
264262
) -> None:
265-
assert function_to_test(trees_map, right, down) == reference_solution_toboggan_p1(
263+
assert function_to_test(trees_map, right, down) == reference_toboggan_p1(
266264
trees_map, right, down
267265
)
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269267

270-
def reference_solution_toboggan_p2(
271-
trees_map: List[List[int]], slopes: Tuple[Tuple[int]]
272-
) -> int:
268+
def reference_toboggan_p2(trees_map: List[List[int]], slopes: Tuple[Tuple[int]]) -> int:
273269
"""Reference solution (part 2)"""
274270
total = 1
275271
for right, down in slopes:
276-
total *= reference_solution_toboggan_p1(trees_map, right, down)
272+
total *= reference_toboggan_p1(trees_map, right, down)
277273
return total
278274

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@@ -293,6 +289,6 @@ def reference_solution_toboggan_p2(
293289
def test_toboggan_p2(
294290
trees_map: List[List[int]], slopes: Tuple[Tuple[int]], function_to_test
295291
) -> None:
296-
assert function_to_test(trees_map, slopes) == reference_solution_toboggan_p2(
292+
assert function_to_test(trees_map, slopes) == reference_toboggan_p2(
297293
trees_map, slopes
298294
)

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