README

Relevent Files

I have uploaded the whole project, however, there are many files that are not relevent to grading (since they are libraries or code for running django). As such, this is a list of the relevent files and what each file has. Please note, all revelent files will be in the folder: project-name/resturant/helloworld

Models and Indexes

The models.py file contains the models created for this project as well as the indexes for each model.

Index Report

• States

  • attributes: name, region
  • indexes: region
  • justification of indexes:
    • region: The States are on occations requested based off of the region they exist in. As such, having a indexes on States will allow you to request States based on regions fasters since the regions will be adjacent to each other. Another thing to note, since this is one of the main ways which you would request a list of states, this query happens very often, making an Index helpful and relevent. In file view.py:
      • 92 States.objects.filter(region=region)
      • 97 temp = States.objects.filter(region=i)
      • 240 states_picked = States.objects.filter(region=states_picked_list[0])
      • 403 states_picked = States.objects.filter(region=states_picked_list[0])
      • 534 states_picked = States.objects.filter(region=states_picked_list[0])

• City

  • attribtues: id, state, name
  • indexes: state
  • justification of indexes:
    • state: The Cities that are picked are often chosen based on the State they exist in and indexing based on a State will reduce the overhead of querying based on state, since cities that are being found will ba adjacent to each other. In file view.py
      • 130 city_list = City.objects.filter(state=states_picked[0]);
      • 132 cities = City.objects.filter(state=i)
      • 257 city_list = City.objects.filter(state=states_picked[0]);
      • 259 cities = City.objects.filter(state=i)
      • 421 city_list = City.objects.filter(state=states_picked[0]);
      • 423 cities = City.objects.filter(state=i)
      • 552 city_list = City.objects.filter(state=states_picked[0]);
      • 554 cities = City.objects.filter(state=i)

• Landmark

  • attributes: city, name, type, price, opening_time, closing_time
  • indexes: opening_time, closing_time, type
  • justification of indexes:
    • opening_time: Landmarks can be sorted/filtered in the report based on their opening time, as such having an index will reduce the stress for ranged queries on the opening time
      • 287 start_landmark = Landmark.objects.filter(opening_time__lt=start)
    • closing_time: Landmarks can be sorted/filtered in the report based on their closing time, as such having an index will reduce the stress for ranged queries on the opening time
      • 291 close_landmark = Landmark.objects.filter(closing_time__gt=end)
    • type: Another query which Landmarks can be sorted/filtered is their type. Having types be adjacent to one-another will reudce the stree of querying based on type, and thus, you would not need to make as many page requests as if there was no index.
      • 277 temp1 = Landmark.objects.filter(type="C")
      • 279 temp2 = Landmark.objects.filter(type="H")
      • 281 temp3 = Landmark.objects.filter(type="N")

• Resturant

  • attributes: city, name, cusine, rating, price, opening_time, closing_time
  • indexes: opening_time, closing_time, price, rating
  • justification of indexes:
    • opening_time: Resturant can be sorted/filtered in the report based on their opening time, as such having an index will reduce the stress for ranged queries on the opening time
      • 447 resturants = resturants.filter(opening_time__lt=start)
    • closing_time: Resturant can be sorted/filtered in the report based on their closing time, as such having an index will reduce the stress for ranged queries on the opening time
      • 449 resturants = resturants.filter(closing_time__gt=end)
    • price: Another attriute that you can sort based on is price. Keeping in mind that price is seperated into 4 categorties only and since you can only request one price point, having price points adjacent to each other will reduce the number of page I/O and speed up the querying process
      • 440 resturants = resturants.filter(price=price_range)
    • rating: This is a ranged query which (especially with high ratings), benefits from this index.
      • 444 resturants = resturants.filter(rating__gte=rating)

• Activity

  • attributes: city, name, description, type
  • indexes: none

Queries

The file views.py is where all queries are held: prepared statements, and ORM. The most important functions are:

• Creating new rows:
  • add_edit_activity
  • add_edit_resturant
  • add_edit_landmark
• Request a specific object:
  • edit_activity_edit
  • edit_resturant_edit
  • edit_landmark_edit
• Large queries with multiple filtering/sort/gets:
  • activity_sort
  • resturant_sort
  • landmark_sort
  • state
• Requesting lots of data (little to no filtering):
  • get_name
  • index

Forms

The forms for requesting edits or sorting/filtering queries residents in the fomrs.py file.

HTML website

Within the templates/polls folder is the html files which are used to create the look of the website

URLs and Requesting Form information

urls.py file

These are the files that I have had a hand in editing that make the website work