pydatenyc 0.1.1

A CLI tool to recommend date ideas in NYC from activity, to a meal, to dessert based on user preferences, and can even recommend a pick up line for you!

PyDate in NYC

An easy date generator that gives you activities, meals, desserts, and even pick up lines!

Installation

Usage

Once installed, you can call pydate from the command line with the desired function and flags.

Activity Recommendation: activity(indoor, time)

The activity function has two flags:

1. --indoor specifies if the suggested activity takes place indoors -indoor True or outdoors-indoor False. The indoor default is True.
2. --time specifies when the activity takes place. Options for this flag are morning, afternoon, evening. The time default is evening.

For example, python pydate_cli.py activity --indoor False --time evening will suggest an evening outdoor activity.

Food Recommendation: food(cuisine, price_range, meal)

The food function has three flags:

1. --cuisine specifies the type of cuisine the recommended food will fall under. Options for this flag are French, Chinese, American, Italian. The cuisine default is French.
2. --price_range specifies the price range of the meal. Options for this flag are low, medium, high. The price range default is medium.
3. --meal specifies the time of day the meal will be eaten. Options for this flag are breakfast, lunch, dinner. The meal default is dinner.

For example, python pydate_cli.py food --cuisine French --price_range medium --meal dinner will suggest a moderately priced French meal that can be eaten for dinner.

Dessert Recommendation: dessert(type, price)

The dessert function has two flags:

1. --type specifies the type of dessert that will be suggested. Options for this flag are bakery, candy, frozen. The type default is bakery.
2. --price specifies the price range of the dessert. Options for this flag are low, medium, high. The price default is low.

For example, python pydate_cli.py dessert --type bakery --price medium will suggest a moderately priced bakery as a dessert option.

Pick Up Line Recommendation: pickupline(text, category)

The pick up line function has two flags:

1. --text is a boolean that specifies whether the pick up line generated should be suitable for text usage or not. Most flags with text set to true will have an emoji to accompany the pickup line. The boolean's default value is set to true.
2. --category is a string that can further filter the category of the pick up line. Options for this flag are not case-sensitive, and include: 'Literary', 'Compliment', 'Sweet', 'Cute', 'Romantic', 'Classic', 'Bold', 'Direct', 'Geeky', 'Clever', 'Suggestive', 'Modern', 'Whimsical', 'Edgy', 'Humorous', 'Confident', 'Tech', 'Pun', 'Historical', 'Seasonal', 'Futuristic', 'Nerdy', 'Playful', 'Caring', 'Charming', 'Funny', 'Blessed', 'Science', 'Contemporary'

For example, python pydate_cli.py pickupline --text=True --category=funny will suggest a funny pickup line that is suited for texts.

To import project into your own code

You can access the date generator in your own project by importing the pydate package and using the functions activity(indoor, time), food(cuisine, price_range, meal), dessert(type, price) to get a recommendation from the chosen category.

Example code

PyDate example Interface

• Run Using python example.py

Peer Contributions to PyDate

Here are the steps to contribute to this package if you'd like

1. Clone the repository to your local machine [https://github.com/software-students-fall2023/3-python-package-exercise-threepeat]
2. To set up the virtual environment and dependencies:
   a. If pipenv is not installed, run pip install pipenv
   b. Run pipenv install to install package dependencies
   c. Run pipenv shell to activate virtual environment
3. To run tests, run python3 -m pytest tests/test_file_name.py and replace test_file_name.py with the test you want to run
4. To build package, run python3 -m build

PyPI Link

Contributors

Danica Jin - https://github.com/dj9771
Emma Zheng - https://github.com/emxyz
Gabriel Park - https://github.com/gmp9469
Megan Chen - https://github.com/meganchen99