# 🐍 Mastering Python Algorithms Tutorial By [@alesanchezr](https://twitter.com/alesanchezr) and [other contributors](https://github.com/4GeeksAcademy//master-python-programming-exercises/graphs/contributors) at [4Geeks Academy](http://4geeksacademy.co/) *Estas instrucciones [están disponibles en 🇪🇸 español](https://github.com/4GeeksAcademy/master-python-programming-exercises/blob/master/README.es.md) :es:* After you finish the begginers, functions, and loop series, this series will really prepare you for your next job or any other programming challenge. Practice everything there is to know to build algorithms with Python, from intermediate to hard challenges. The entire tutorial is 👆 interactive and ✅ auto-graded. These exercises were built in collaboration, we need you! If you find any bugs or misspellings, please contribute and report them. ## One click installation (recommended): You can open these exercises in just a few seconds by clicking: [Open in Codespaces](https://codespaces.new/?repo=4GeeksAcademy/master-python-programming-exercises) (recommended) or [Open in Gitpod](https://gitpod.io#https://github.com/4GeeksAcademy/master-python-programming-exercises). > Once you have VSCode open the LearnPack exercises should start automatically. If exercises don't run automatically you can try typing on your terminal: `$ learnpack start` ## Local Installation 1. Make sure you have [LearnPack](https://learnpack.co) installed, node.js version 14+, and Python version 3+. This is the command to install LearnPack: ```bash npm i @learnpack/learnpack@2.1.20 -g && learnpack plugins:install @learnpack/python@1.0.0 ``` 2. Clone or download this repository in your local environment. ```bash $ git clone https://github.com/4GeeksAcademy/master-python-programming-exercises.git $ cd master-python-programming-exercises ``` > Note: Once you finish downloading, you will find an "exercises" folder that contains all the exercises within. 3. Start the tutorial/exercises by running the following command at the same level your learn.json file is: ```bash $ pip3 install pytest==6.2.5 pytest-testdox mock $ learnpack start ``` ## How are the exercises organized? Each exercise is a small Python application containing the following files: 1. **app.py:** represents the entry Python file that will be executed by the computer. 2. **README.md:** contains exercise instructions. 3. **test.py:** you don't have to open this file, it contains the testing script for the exercise. > Note: The exercises have automatic grading, but it's very rigid and strict, my recommendation is to not take the tests too serious and use them only as a suggestion, or you may get frustrated. ## Contributors Thanks goes to these wonderful people ([emoji key](https://github.com/kentcdodds/all-contributors#emoji-key)): 1. [Alejandro Sanchez (alesanchezr)](https://github.com/alesanchezr), contribution: (coder) 💻, (idea) 🤔, (build-tests) ⚠️, (pull-request-review) 👀, (build-tutorial) ✅, (documentation) 📖 2. [Paolo (plucodev)](https://github.com/plucodev), contribution: (bug reports) 🐛, (coder) 💻, (translation) 🌎 3. [Marco Gómez (marcogonzalo)](https://github.com/marcogonzalo), contribution: (bug reports) 🐛, (translation) 🌎 This project follows the [all-contributors](https://github.com/kentcdodds/all-contributors) specification. Contributions of any kind are welcome! This and many other exercises are built by students as part of the 4Geeks Academy [Coding Bootcamp](https://4geeksacademy.com/us/coding-bootcamp) by [Alejandro Sánchez](https://twitter.com/alesanchezr) and many other contributors. Find out more about our [Full Stack Developer Course](https://4geeksacademy.com/us/coding-bootcamps/part-time-full-stack-developer), and [Data Science Bootcamp](https://4geeksacademy.com/us/coding-bootcamps/datascience-machine-learning).