import json

# We'll use these two classes to demonstrate encoding and
# decoding of custom types below.
class Response1:
    def __init__(self, page, fruits):
        self.page = page
        self.fruits = fruits

class Response2:
    def __init__(self, page, fruits):
        self.page = page
        self.fruits = fruits

def main():
    # First we'll look at encoding basic data types to
    # JSON strings. Here are some examples for atomic
    # values.
    print(json.dumps(True))
    print(json.dumps(1))
    print(json.dumps(2.34))
    print(json.dumps("gopher"))

    # And here are some for slices and maps, which encode
    # to JSON arrays and objects as you'd expect.
    print(json.dumps(["apple", "peach", "pear"]))
    print(json.dumps({"apple": 5, "lettuce": 7}))

    # The json package can automatically encode your
    # custom data types. It will only include public
    # attributes in the encoded output and will by default
    # use those names as the JSON keys.
    res1 = Response1(page=1, fruits=["apple", "peach", "pear"])
    print(json.dumps(res1.__dict__))

    # You can use a custom encoder to customize the encoding process.
    def custom_encoder(obj):
        if isinstance(obj, Response2):
            return {"page": obj.page, "fruits": obj.fruits}
        return obj.__dict__

    res2 = Response2(page=1, fruits=["apple", "peach", "pear"])
    print(json.dumps(res2, default=custom_encoder))

    # Now let's look at decoding JSON data into Python
    # values. Here's an example for a generic data
    # structure.
    byt = b'{"num":6.13,"strs":["a","b"]}'

    # We need to provide a variable where the JSON
    # package can put the decoded data. This
    # dict will hold a dictionary of strings
    # to arbitrary data types.
    dat = json.loads(byt)
    print(dat)

    # In order to use the values in the decoded map,
    # we can directly access them with the appropriate type.
    num = dat["num"]
    print(num)

    # Accessing nested data is straightforward.
    strs = dat["strs"]
    str1 = strs[0]
    print(str1)

    # We can also decode JSON into custom data types.
    # This has the advantages of adding additional
    # type-safety to our programs and eliminating the
    # need for type assertions when accessing the decoded
    # data.
    str_data = '{"page": 1, "fruits": ["apple", "peach"]}'
    res = json.loads(str_data)
    print(res)
    print(res["fruits"][0])

    # In the examples above we always used strings as intermediates between the data and
    # JSON representation. We can also stream JSON encodings directly to file-like objects.
    import sys
    json.dump({"apple": 5, "lettuce": 7}, sys.stdout)
    print()  # Add a newline for better formatting

if __name__ == "__main__":
    main()