About

In December 2024, I joined Jeremy Howard's new course, Solve It With Code, by fast.ai. This unique program introduces a fresh approach to coding that combines iterative problem-solving with AI. It emphasizes building foundational skills without requiring a background in data structures or computer science. The course focuses on using Python (with minimal external libraries) and teaches an engineering technique that integrates AI as a collaborative tool (source).

This repository contains my solutions to the Advent of Code 2023 challenges, crafted using the engineering process taught in the course. Beyond the solutions, you can see how each solution was developed in dialog with the AI. The solutions are organized in the solutions folder, the dialogues in the dialogues folder, and the input data for each challenge is stored in the data folder.

Note: The input data for each challenge differs by user. If you are using this project as a template for your own solutions, you will need to log in to the Advent of Code website to download your personal puzzle input data and use it to replace the existing files in the ./data/ folder. To update the table of challenges, read these instructions below.

Table of Challenges

Day	Challenge	Solution Code	Solution Dialog	Time Complexity	Space Complexity	Challenge Link
1	Trebuchet?!	link	link	O(n * m)	O(1)	adventofcode.com
2	Cube Conundrum	Unsolved	-	-	-	adventofcode.com
3	Gear Ratios	Unsolved	-	-	-	adventofcode.com
4	Scratchcards	Unsolved	-	-	-	adventofcode.com
5	If You Give A Seed A Fertilizer	Unsolved	-	-	-	adventofcode.com
6	Wait For It	Unsolved	-	-	-	adventofcode.com
7	Camel Cards	Unsolved	-	-	-	adventofcode.com
8	Haunted Wasteland	Unsolved	-	-	-	adventofcode.com
9	Mirage Maintenance	Unsolved	-	-	-	adventofcode.com
10	Pipe Maze	Unsolved	-	-	-	adventofcode.com
11	Cosmic Expansion	Unsolved	-	-	-	adventofcode.com
12	Hot Springs	Unsolved	-	-	-	adventofcode.com
13	Point of Incidence	Unsolved	-	-	-	adventofcode.com
14	Parabolic Reflector Dish	Unsolved	-	-	-	adventofcode.com
15	Lens Library	Unsolved	-	-	-	adventofcode.com
16	The Floor Will Be Lava	Unsolved	-	-	-	adventofcode.com
17	Clumsy Crucible	Unsolved	-	-	-	adventofcode.com
18	Lavaduct Lagoon	Unsolved	-	-	-	adventofcode.com
19	Aplenty	Unsolved	-	-	-	adventofcode.com
20	Pulse Propagation	Unsolved	-	-	-	adventofcode.com
21	Step Counter	Unsolved	-	-	-	adventofcode.com
22	Sand Slabs	Unsolved	-	-	-	adventofcode.com
23	A Long Walk	Unsolved	-	-	-	adventofcode.com
24	Never Tell Me The Odds	Unsolved	-	-	-	adventofcode.com
25	Snowverload	Unsolved	-	-	-	adventofcode.com

Repository Structure

.
├── Dockerfile.readme               <- Defines the Docker environment for generating this README.md file
├── Dockerfile.data                 <- Defines the Docker environment for downloading the advent of code data
├── README.md                       <- You are reading this right now
├── README.template                 <- Template for dynamically generating the README file
├── challenges.json                 <- Metadata about Advent of Code 2023 challenges
├── download_data.py                <- Script to download the Advent of Code data
├── download_data_using_docker.sh   <- Runs download_data.py inside a Docker container
├── generate_readme.py              <- Script to generate the README dynamically
├── generate_readme_using_docker.sh <- Runs generate_readme.py inside a Docker container
├── requirements.txt                <- Lists the Python dependencies for the project
├── data                            <- Contains input and sample data for challenges
│   ├── dayXX_input.txt             <- Main input data for each challenge, downloaded using the downloader
│   ├── dayXX_sample.txt            <- Sample input manually extracted from the challenge description for testing
│   └── dayXX_test.txt              <- Additional test data you may want to add yourself
├── dialogues                       <- Contains the solution dialog as Juptyer notebooks
│   ├── XX_*.ipynb                  <- Juptyer notebooks for each challenge day XX=01,...,25
└── solutions                       <- Contains Python solution scripts for each challenge
    └── XX_*.py                     <- Python scripts containing the solutions for each challenge day XX=01,...,25

---

Setup

To set up the project on your local machine, follow these steps:

• Clone this repository.
• Ensure that Docker is installed and running on your system.

How to Run the Advent of Code Data Downloader

Advent of code has different input data for each user. This means you need to download your personal input data to solve the challenges. The following describes how you can download the data for all 26 days almost automatically. You need to do this only once.

Preparation

• Create a .env file in the project root and add the following line to it:

AOC_SESSION=<insert_your_session_key_here>

This file holds your session key, which is required to download the data. The next section describes how you can get the session key to insert into the .env file.

How to Obtain Your Session Key

1. Log in to the Advent of Code website.
2. Open your browser's developer tools (right-click anywhere on the page and select "Inspect" or press F12).
3. Navigate to the "Application" tab (in Chrome) or "Storage" tab (in Firefox).
4. Locate the "Cookies" section and click on adventofcode.com.
5. Find the cookie named session and copy its value.
6. Paste this value into your .env file as the AOC_SESSION variable.

Running the Data Downloader

1. Make the Bash Script Executable

Run the following command to make the script executable:

chmod +x ./download_data_using_docker.sh

2. Build and Run the Docker Container

Run the following command:

./download_data_using_docker.sh

• This will build the Docker image and run the download_data.py script inside the container.
• The script will download the Advent of Code data for the specified day and year.

3. Verify the Output

Once the container execution is finished, the downloaded data files day*_input.txt will be available in ./data/ folder.

---

Generating this README

Generating the README.md file updates the cells of the challenges table based on the metadata from the challenges.json file the content (!) of the solution files automatically.

Note: The time and space complexity are extracted from the solution files by looking for lines that start with Time complexity: and Space complexity: respectively. Please ensure that these lines are present in your solution files as well. Here are some valid examples:

"""
...
Time complexity: O(...)
Space complexity: O(...)
...
"""

or

...
# Time complexity: O(...)
...
# Space complexity: O(...)
...

To generate the README.md file, follow these steps:

1. Make the Bash Script Executable

Run the following command to make the script executable:

chmod +x ./generate_readme_using_docker.sh

2. Build and Run the Docker Container

./generate_readme_using_docker.sh

• This will build the Docker image each time it is run to avoid file caching issues.
• It will then run the Docker container to execute the generate_readme.py script, which generates the README.md file and overwrites the exiting README.md file in your local directory.

3. Verify the Output

Once the container execution is finished, you should see the updated README.md file in the same directory where you ran the script.