https://github.com/josephmachado/data-engineering-interview-series
Repository for Data Engineering Interview Series
https://github.com/josephmachado/data-engineering-interview-series
data-structures dataengineering interview
Last synced: 16 days ago
JSON representation
Repository for Data Engineering Interview Series
- Host: GitHub
- URL: https://github.com/josephmachado/data-engineering-interview-series
- Owner: josephmachado
- License: mit
- Created: 2024-08-12T10:54:07.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-10-17T19:43:09.000Z (7 months ago)
- Last Synced: 2025-04-15T02:57:57.308Z (16 days ago)
- Topics: data-structures, dataengineering, interview
- Language: Jupyter Notebook
- Homepage: https://www.startdataengineering.com/post/de_interview_dsa/
- Size: 203 KB
- Stars: 29
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
* [Data Engineering Interview Series Posts](#data-engineering-interview-series-posts)
* [Prerequisites](#prerequisites)
* [Setup](#setup)
* [Option 1: Github codespaces (Recommended)](#option-1-github-codespaces-recommended)
* [Option 2: Run locally](#option-2-run-locally)
This is a repo that contains all the code for my **"Data Engineering Interview Series"**.
## Data Engineering Interview Series Posts
1. [Data Engineering Interview Series #1: Data Structures and Algorithms](https://www.startdataengineering.com/post/de_interview_dsa/)
## Prerequisites
1. Sign up for a Github account.
## Setup
You have two options to run the exercises in this repo
### Option 1: Github codespaces (Recommended)
:exclamation: Codespaces has limited free tier per month.
Steps:
1. Create [Github codespaces with this link](https://github.com/codespaces/new?skip_quickstart=true&machine=basicLinux32gb&repo=841408842&ref=main&geo=UsEast).
2. Now open the [./DSA/dsa_prep.ipynb](./DSA/dsa_prep.ipynb) (or any ipynb) and it will open in a Jupyter notebook interface. You will be asked for your kernel choice, choose `Python Environments` and then `python3.10.13 Global`.
### Option 2: Run locally
Steps:
1. Clone this repo, cd into the cloned repo
2. Start a virtual env and install requirements.
3. Start Jupyter lab and run the `ipynb` notebooks.
```bash
git clone https://github.com/josephmachado/data-engineering-interview-series.git
cd data-engineering-interview-series
python -m venv ./env # create a virtual env
source env/bin/activate # use virtual environment
pip install -r requirements.txt
jupyter lab
```