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# π Turorial y Ejercicios sobre Funciones de Python</h1>
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Creado por <ahref="https://twitter.com/alesanchezr">@alesanchezr</a> y <ahref="https://github.com/4GeeksAcademy/python-functions-programming-exercises/graphs/contributors">othors contribuyentes</a> en <ahref="http://4geeksacademy.com/">4Geeks Academy</a>
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# π Tutorial y Ejercicios sobre Funciones de Python</h1>
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Creado por <ahref="https://twitter.com/alesanchezr">@alesanchezr</a> y <ahref="https://github.com/4GeeksAcademy/python-functions-programming-exercises/graphs/contributors">otros contribuyentes</a> en <ahref="http://4geeksacademy.com/">4Geeks Academy</a>
Puedes empezar estos ejercicios en pocos segundos haciendo clic en: [Abrir en Codespaces](https://codespaces.new/?repo=4GeeksAcademy/python-functions-programming-exercises) (recomendado) o [Abrir en Gitpod](https://gitpod.io#https://github.com/4GeeksAcademy/python-functions-programming-exercises.git).
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> Una vez ya tengas abierto VSCode, los ejercicios de LearnPack deberΓan empezar automΓ‘ticamente; si esto no sucede puedes intentar empezar los ejercicios escribiendo este comando en tu terminal: `$ learnpack start`
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> Una vez ya tengas abierto VSCode, los ejercicios de LearnPack deberΓan empezar automΓ‘ticamente; si esto no sucede, puedes intentar empezar los ejercicios escribiendo este comando en tu terminal: `$ learnpack start`
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## InstalaciΓ³n local:
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1) AsegΓΊrate de instalar [learnpack](https://learnpack.co), `node.js` version 14+ y python version 3+. Este es el comando para instalar learnpack:
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1) AsegΓΊrate de instalar [LearnPack](https://learnpack.co), node.js version 14+ y Python version 3+. Este es el comando para instalar LearnPack:
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```sh
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```bash
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$ npm i learnpack -g && learnpack plugins:install learnpack-python
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```
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2) Clona o descarga este repositorio. Una vez que termines de descargar, encontrarΓ‘s un carpeta nueva con un subdirectorio "exercises" que contiene los ejercicios.
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2) Clona o descarga este repositorio. Una vez que termines de descargar, encontrarΓ‘s una carpeta nueva con un subdirectorio llamado "exercises" que contiene los ejercicios.
> Nota: Estos ejercicios tienen calificaciΓ³n automΓ‘tica. Los tests son muy rΓgidos y estrictos, mi recomendaciΓ³n es que no prestes demasiada atenciΓ³n a los tests y los uses solo como una sugerencia o podrΓas frustrarte.
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## Colaboradores
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Gracias a estas personas maravillosas ([emoji key](https://github.com/kentcdodds/all-contributors#emoji-key)):
@@ -82,4 +79,4 @@ Este proyecto sigue la especificaciΓ³n [all-contributors](https://github.com/ken
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Este proyecto sigue la especificaciΓ³n [all-contributors](https://github.com/kentcdodds/all-contributors). Β‘Todas las contribuciones son bienvenidas!
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Este y otros ejercicios son usados para [aprender a programar](https://4geeksacademy.com/es/aprender-a-programar/aprender-a-programar-desde-cero) por parte de los alumnos de 4Geeks Academy [Coding Bootcamp](https://4geeksacademy.com/us/coding-bootcamp) realizado por [Alejandro SΓ‘nchez](https://twitter.com/alesanchezr) y muchos otros contribuyentes. Conoce mΓ‘s sobre nuestros [Curso de ProgramaciΓ³n](https://4geeksacademy.com/es/curso-de-programacion-desde-cero?lang=es) para convertirte en [Full Stack Developer](https://4geeksacademy.com/es/coding-bootcamps/desarrollador-full-stack/?lang=es), o nuestro [Data Science Bootcamp](https://4geeksacademy.com/es/coding-bootcamps/curso-datascience-machine-learning).
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Este y otros ejercicios son usados para [aprender a programar](https://4geeksacademy.com/es/aprender-a-programar/aprender-a-programar-desde-cero) por parte de los alumnos de 4Geeks Academy [Coding Bootcamp](https://4geeksacademy.com/us/coding-bootcamp) realizado por [Alejandro SΓ‘nchez](https://twitter.com/alesanchezr) y muchos otros contribuyentes. Conoce mΓ‘s sobre nuestros [Cursos de ProgramaciΓ³n](https://4geeksacademy.com/es/curso-de-programacion-desde-cero?lang=es) para convertirte en [Full Stack Developer](https://4geeksacademy.com/es/coding-bootcamps/desarrollador-full-stack/?lang=es), o nuestro [Data Science Bootcamp](https://4geeksacademy.com/es/coding-bootcamps/curso-datascience-machine-learning).
These exercises were built in collaboration, we need you! If you find any bugs or misspellings, please contribute and report them.
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<!-- hide -->
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## One click installation (recommended):
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You can open these exercises in just a few seconds by clicking: [Open in Codespaces](https://codespaces.new/?repo=4GeeksAcademy/python-functions-programming-exercises) (recommended) or [Open in Gitpod](https://gitpod.io#https://github.com/4GeeksAcademy/python-functions-programming-exercises).
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> 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`
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> 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`
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## Local Installation
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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:
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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:
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```
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```bash
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$ npm i learnpack -g && learnpack plugins:install learnpack-python
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```
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2) Clone or download this repository. Once you finish downloading, you will find a new folder with a subdirectory "exercises" that contains all the exercises within.
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2) Clone or download this repository. Once you finish downloading, you will find a new folder with a subdirectory called "exercises" that contains all the exercises within.
3) Start the tutorial/exercises by running the following command from the root of the project:
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```sh
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```bash
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$ cd python-functions-programming-exercises
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$ pip install pytest==4.4.2 mock pytest-testdox
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$ learnpack start
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```
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<!-- endhide -->
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## How are the exercises organized?
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Each exercise is a small react application containing the following files:
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Each exercise is a small React application containing the following files:
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1.**app.py:** represents the entry python file that will be executed by the computer.
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1.**app.py:** represents the entry Python file that will be executed by the computer.
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2.**README.md:** contains exercise instructions.
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3.**test.py:** you don't have to open this file, it contains the testing script for the exercise.
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> Note: The exercises have automatic grading but its very rigid and string, my recomendation is to ignore the tests and use them only as a recomendation or you can get frustrated.
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> 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.
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## Contributors
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Thanks to these wonderful people ([emoji key](https://github.com/kentcdodds/all-contributors#emoji-key)):
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