Data Structure: J-Son?

Announcements

• Project ImageShop is due today!
• Guidelines for Personal Project is posted
  • Personal project is 10% of the course grade component
  • Due date is Monday 14 April at 10:00pm
• On a general note, be concrete and creative about the project.
• Next week Monday 14th, Professor Emeritus Eric S Roberts will be our guest.
  • Opportunity to meet the CS151 course designer
  • Engage with Eric in a relax mode
    • I need some volunteers to help organize some light food (Pizza)
• Polling: here

Project guidelines

• Click : here!

Sample projects

• Demo a couple of past personal projects in-class

Review Question

data ={
    "CS151": {
        "Sally": {"A", "B", "B"},
        "Jake": {"B", "A", "B", "C"},
        "Ben": {"A", "B", "A", "B"}
    },
    "DATA152": {
        "James": ["B", "C", "A"],
        "Lily": ["A", "A", "B"]
    }
}
course1 = data["CS151"]
course2 = data["DATA152"]
for std, grade in course1.items():
    if len(grade) == len(course2["Lily"]):
        print(std, grade)

Compound Structure Storage

• Structures representing complicated data can often be large enough that you don’t want to store them within your program itself
• We can put them in their own file, but reading them in with our current tools would be complicated
  • Current methods read in text, so we would need to parse the text to identify what data structures we needed to create and what elements we needed to add
  • This is certainly possible, but potentially more overhead than what we would like for some structures
• Useful then to store the data structure in file in such a format that it can be easily read into Python

File I/O

• A variety of ways this can be done
  • XML, YAML, JSON
• JSON is particularly interesting to us, because its syntax almost exactly matches Python’s (even though it was made for Javascript)
• Python has a built-in library to read and write JSON files, just called json
  • json.load(file_handle)
    • Loads the JSON data structure from the specified file into its Python equivalent
  • json.dump(data_object, file_handle)
    • Writes a JSON text representation of the data object to the given file
  • Both methods are used inside our normal with open() as fhandle: syntax

Using JSON

• To read a JSON file into a variable data:

  import json
  with open('file.json') as fh:
      data = json.load(fh)

• To write a variable with complex structure out to a JSON file:

  import json
  with open('file.json', 'w') as fh:
      json.dump(data, fh)

The Power of JSON

• One very nice aspect of JSON is that it is often the defacto way that information is passed around the internet
• This means it can be easy to find data providers where you can access or download information already in a JSON format
• DND Fireball Spell info here
• We could download this information to a file, which we could then read in and use within our Python program
• It is possible to also process the information straight from the internet as well

JSON Gotchas

• If you are writing JSON files from within Python or using files gotten elsewhere, they should already be properly formatted
• If you need/want to edit a JSON file directly though, you should be aware of a few “gotchas” where the JSON syntax varies slightly from Python’s syntax
  • You can not have trailing commas at the end of a JSON structure
    • Something like [1, 2, 3,] is perfectly fine in Python, but illegal in JSON
  • JSON strings require double quotes
    • In Python you can use either double or single quotes, but JSON requires double
  • Booleans are all lowercase in JSON
    • Vs starting with a capital letter in Python