Introduction to Python

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The JSON File Format and Multidimensional Containers

the JSON file format

JavaScript Object Notation is a simple "data interchange" format for sending or storing structured data as text.

• JSON is used by many web APIs and other programs for communcating data
• it is "lightweight", meaning it does not require overhead (as with a database server)
• it is text-based, so it can be easily stored to file or transmitted over a network
• it was originally created for JavaScript, but became popular for use with any language
• it is more flexible than CSV in describing many-to-one relationships
• it uses lists and dictionaries to describe data
• in many ways it resembles Python, because both languages grew out of the same tradition of languages

a sample json file

Fortunately for us, JSON resembles Python in many ways, making it easy to read and understand.

contents of file sample.json

{
   "key1":  ["a", "b", "c"],
   "key2":  {
              "innerkey1": 5,
              "innerkey2": "woah"
            },
   "key3":  false,
   "key4":  null
}

• JSON containers use the same syntax as Python lists and dictionaries
• this makes it easy for Python programmers to read and understand them
• any container may contain other containers (dicts inside dicts, lists inside dicts, etc.)
• this allows for the expression of complex ("many-to-one") data relationships

reading a structure from a json file

The json.load() function decodes the contents of a JSON file.

import json                 # this module is used to read JSON files

fh = open('sample.json')

mys = json.load(fh)         # load data objects from the file,
                            # convert into Python objects

fh.close()

print((type(mys)))            # dict (the outer container of this struct)

print(mys['key2']['innerkey2'])     # woah

Ex. 7.1

reading a structure from a json string

The json.loads() function decodes the contents of a JSON string.

import json                   # we use this module to read JSON
import requests               # use 'pip install' to install


response = requests.get('https://davidbpython.com/mystruct.json')

text = response.text          # str, entire file data

mys = json.loads(text)        # read string, convert into Python container

print((type(mys)))              # dict (the outer container of this struct)

print((mys['key2']['innerkey2']))    # woah

• data retrieved from the internet comes to us as strings
• in order to read it, we use json.loads()
• this function reads from a string rather than a file

About requests:

• like a web browser, your Python program can request and receive data
• requests is a module that helps facilitate web requests
• in order to use it, you may need to install it: at the command line, type (conda install requests or pip install requests)

printing a complex object readably: writing to a string

A nested object can be confusing to read.

If we have an multidimensional object that is squished together and hard to read, we can use .dumps() with indent=4

import json

obj = {'a': {'x': 1, 'y': 2, 'z': 3}, 'b': {'x': 1, 'y': 2, 'z': 3}, 'c': {'x': 1, 'y': 2, 'z': 3} }

print((json.dumps(obj, indent=4)))

this prints:

{
    "a": {
        "x": 1,
        "y": 2,
        "z": 3
    },
    "b": {
        "x": 1,
        "y": 2,
        "z": 3
    }
}

sidebar: writing an object to json file

We can use json.dump() to write to a JSON file.

import json

wfh = open('newfile.json', 'w')    # open file for writing

obj = {'a': 1, 'b': 2}

json.dump(obj, wfh)

wfh.close()

• we must open the file for writing with 'w'
• we must also remember to close the file
• running this program, you should see file newfile.json appear in your project folder
• (keep in mind that if newfile.json already exists, it will be overwritten)