UCLA Parse

Web scrapper built with BeautifulSoup used for parsing UCLA data, including UCLA dining hall data.

This project is used as the backend for my iOS application Bruin Feed (App Store, Github).

NOTE: This project has been only tested for Python 3

Features

• Parse dining hall menus from the UCLA website
• Parse nutrition data for specific entrees (with a specific ID)

Usage

Copy the files parse.py and nutrition.py to your directory.

Menu Parsing

Command Line Interface (CLI)

The CLI for parsing dining hall menus is simple, simply run

$ python3 parse.py [year] [month] [day]

substituting values in the brackets. For example, if we wanted to parse the menus for Aug. 1, 2016, simply run

$ python3 parse.py 2016 8 1

There are other also options you can specify to custominze your parsing:

  -h, --help         shows the help message
  -n, --nutrition    determine whether to download nutrition data
  -b, --breakfast    download breakfast menus
  -l, --lunch        download lunch menus
  -d, --dinner       download dinner menus

The printed result will be a minified JSON string in the format

{
    "b": [...],
    "l": [...],
    "d": [...]
}

Using the MenuParser Class

A full example can be found in the file run-menu.py.

To use the MenuParser class, we would first include the following two lines

from parse import Meal
from parse import MealParser

Then we create a MenuParser object with the arguments date (of type datetime.datetime), and meal (of type Meal). For example, we want to create a MenuParser with today's date for the meal dinner:

import datetime

date = datetime.datetime.today()
meal = Meal.dinner
parser = MenuParser(date, meal)

Now we can parse the menus by calling getMenus(shouldGetNutrition). The only argument is a boolean which specifies whether to download the nutrition data

shouldGetNutrition = True      
menu = parser.getMenus(shouldGetNutrition)

This will return an array of dictionaries, each dictionary of the format

kEntreeName = "e"
kType = "t"
kNutritionData = "n"

{
    kEntreeName: "...",
    kType: "...",
    kNutritionData: [...]
}

Note that kNutritionData consists of an array of nutrition data, elements of which will be explained below in the Nutrition Parsing section.

Nutrition Parsing

Command Line Interface (CLI)

To download the nutrition data for an entree with nutrition data of ID (this ID can be found on the UCLA dining hall website, but you will have to look into the URL to locate it) You would use it like this:

$ python3 nutrition.py [ID]

Suppose you want to download the nutrition data for an entree called Hungarian Beef Goulash (which has an ID=075008), we can use the CLI:

$ python3 nutrition.py 075008

The results will be an array of the format below (comments show which nutrition data each array element represents)

[
  "0",   # total calories
  "0",   # calories from fat

  "0%",  # vitamin A
  "0%",  # vitamin C
  "0%",  # calcium
  "0%",  # iron

  "0g",  # total fat
  "0%",  # total fat percentage
  "0g",  # saturated fat
  "0%",  # saturated fat percentage
  "0g",  # trans fat

  "0mg", # cholesterol
  "0%",  # cholesterol percentage
  "0mg", # sodium
  "0%",  # sodium percentage

  "0g",  # total carbohydrate
  "0%",  # total carbohydrate percentage
  "0g",  # dietary fiber
  "0%",  # dietary fiber percentage
  "0g",  # sugars

  "0g"   # protein
]

Using the NutritionParser Class

A full example can be found in the file run-nutrition.py.

To use the NutritionParser class, we would first include the following line

from nutrition import NutritionParser

Then we create a NutritionParser object with the arguments recipe (of type string). For example, we want to create a NutritionParser with the recipe ID=075008:

recipe = "075008"
parser = NutritionParser(recipe)

Now we can parse the nutrition data by calling downloadNutritionData(shouldSave, filebase). Arguments include a boolean shouldSave which specifies whether to save the downloaded data as a file, and a string filebase, which specifies where to save the downloaded data (default is ./nutrition/). For example, to download the data and not save, we use:

nutrition = parser.downloadNutritionData()

To save the data in the default path, we use:

shouldSave = True
nutrition = parser.downloadNutritionData(shouldSave)

To save to a specified location, such as /home/user/desktop/nutrition/, we use:

shouldSave = True
filebase = "/home/user/desktop/"
nutrition = parser.downloadNutritionData(shouldSave, filebase)

The return value is a JSON object in the format described above.

The MIT License (MIT)

Copyright (c) 2016 Qingwei Lan ([email protected])

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.