Skip to main content

A package to suggest activities based on mood.

Project description

chugthiskoolaid

Team members: Hao Yang, Yukun Dong, Jess, YifanZzzz

TABLE OF CONTENTS

  1. Description
  2. PyPI Page
  3. Installation
  4. Virtual Environment & Dependencies
  5. Usage Examples
  6. Contributing

Description

A package that generates “Mood Suggester” messages, programming wisdom, or absurd advice when called.

PyPI Page

You can find the package here:

Installation

You can import the Mood Suggester package into your projects using pip. Below is how to install the package:

1. Install the package from PyPI

pip install mood_suggester

2. Import the functions in your Python code

from mood_suggester import recommend_activity, recommend_book, recommend_movie, recommend_music

Virtual Environment & Dependencies

how to configure and run all parts of your project for any developer on any platform how to set up any environment variables and import any starter data into the database, as necessary, for the system to operate correctly when run. 1️⃣ Clone the Repository

git clone https://github.com/software-students-spring2025/3-python-package-chugthiskoolaid/tree/main
cd mood-suggester

2️⃣ Create a Virtual Environment

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run Tests

pytest tests/

5️⃣ Build the Package

python setup.py sdist bdist_wheel

Usage Examples

see example.py

recommend_activity:

How are you feeling now? (happy/sad/stressed/bored/motivated/angry): bored

🎉 activity: Solve a puzzle, play a board game, or try an escape room challenge

recommend_book:

How are you feeling now? (happy/sad/stressed/bored/motivated/angry): happy

📖 book: The Hundred-Year-Old Man Who Climbed Out the Window and Disappeared – Jonas Jonasson

recommend_movie:

How are you feeling now? (happy/sad/stressed/bored/motivated/angry): angry

🍽 movie: The Revenant

recommend_music:

How are you feeling now? (happy/sad/stressed/bored/motivated/angry): bored

🎵 music: Young Folks - Peter Bjorn and John

Contributing

We welcome contributions! Here’s how you can help:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mood_recommender-0.1.1.tar.gz (21.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mood_recommender-0.1.1-py3-none-any.whl (21.5 kB view details)

Uploaded Python 3

File details

Details for the file mood_recommender-0.1.1.tar.gz.

File metadata

  • Download URL: mood_recommender-0.1.1.tar.gz
  • Upload date:
  • Size: 21.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.13

File hashes

Hashes for mood_recommender-0.1.1.tar.gz
Algorithm Hash digest
SHA256 4a3962455fa80850f71d427b46c446843d4c99e7ea9ca88481d091bf42f4acbd
MD5 5381663d1e533527206e54dda9faf7bc
BLAKE2b-256 fa30a4008891b1d5e2850c1a2b2d40a97b3249870753c80187b7a77aed70dbd9

See more details on using hashes here.

File details

Details for the file mood_recommender-0.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for mood_recommender-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4dd857fd4a1affedac636c8546c11566dc211310ff51d908035b7dfee6f3afc6
MD5 9492d7cfb0e43213cbe4ab42f046768a
BLAKE2b-256 d770dcbf622926e76835b707742c89d408de3c51e5c3653b6a2b5b530872f014

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page