Cara menggunakan python json dumps emoji

A Little Vocabulary

The process of encoding JSON is usually called serialization. This term refers to the transformation of data into a series of bytes (hence serial) to be stored or transmitted across a network. You may also hear the term marshaling, but that’s a whole other discussion. Naturally, deserialization is the reciprocal process of decoding data that has been stored or delivered in the JSON standard.

Yikes! That sounds pretty technical. Definitely. But in reality, all we’re talking about here is reading and writing. Think of it like this: encoding is for writing data to disk, while decoding is for reading data into memory.

Serializing JSON

What happens after a computer processes lots of information? It needs to take a data dump. Accordingly, the

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

Simple Python objects are translated to JSON according to a fairly intuitive conversion.

PythonJSON

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

A Simple Serialization Example

Imagine you’re working with a Python object in memory that looks a little something like this:

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

It is critical that you save this information to disk, so your mission is to write it to a file.

Using Python’s context manager, you can create a file called

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

Note that

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

Or, if you were so inclined as to continue using this serialized JSON data in your program, you could write it to a native Python

json_string = json.dumps(data)

json_string = json.dumps(data)

Notice that the file-like object is absent since you aren’t actually writing to disk. Other than that,

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

Hooray! You’ve birthed some baby JSON, and you’re ready to release it out into the wild to grow big and strong.

Some Useful Keyword Arguments

Remember, JSON is meant to be easily readable by humans, but readable syntax isn’t enough if it’s all squished together. Plus you’ve probably got a different programming style than me, and it might be easier for you to read code when it’s formatted to your liking.

NOTE: Both the

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

3 and

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

4 methods use the same keyword arguments.

The first option most people want to change is whitespace. You can use the

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

>>>

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

Another formatting option is the

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

There are others, like

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

Deserializing JSON

Great, looks like you’ve captured yourself some wild JSON! Now it’s time to whip it into shape. In the

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

Just like serialization, there is a simple conversion table for deserialization, though you can probably guess what it looks like already.

JSONPython

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

json_string = json.dumps(data)

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

Technically, this conversion isn’t a perfect inverse to the serialization table. That basically means that if you encode an object now and then decode it again later, you may not get exactly the same object back. I imagine it’s a bit like teleportation: break my molecules down over here and put them back together over there. Am I still the same person?

In reality, it’s probably more like getting one friend to translate something into Japanese and another friend to translate it back into English. Regardless, the simplest example would be encoding a

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

>>>

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

A Simple Deserialization Example

This time, imagine you’ve got some data stored on disk that you’d like to manipulate in memory. You’ll still use the context manager, but this time you’ll open up the existing

>>> json.dumps(data)
>>> json.dumps(data, indent=4)

with open("data_file.json", "r") as read_file:
    data = json.load(read_file)

Things are pretty straightforward here, but keep in mind that the result of this method could return any of the allowed data types from the conversion table. This is only important if you’re loading in data you haven’t seen before. In most cases, the root object will be a

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

If you’ve pulled JSON data in from another program or have otherwise obtained a string of JSON formatted data in Python, you can easily deserialize that with

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

json_string = """
{
    "researcher": {
        "name": "Ford Prefect",
        "species": "Betelgeusian",
        "relatives": [
            {
                "name": "Zaphod Beeblebrox",
                "species": "Betelgeusian"
            }
        ]
    }
}
"""
data = json.loads(json_string)

Voilà! You’ve tamed the wild JSON, and now it’s under your control. But what you do with that power is up to you. You could feed it, nurture it, and even teach it tricks. It’s not that I don’t trust you…but keep it on a leash, okay?

Simplifying Data Structures

Now, the question is how to deal with more complex data structures. Well, you could try to encode and decode the JSON by hand, but there’s a slightly more clever solution that’ll save you some work. Instead of going straight from the custom data type to JSON, you can throw in an intermediary step.

All you need to do is represent your data in terms of the built-in types

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

To get the hang of this, you’ll need a complex object to play with. You could use any custom class you like, but Python has a built-in type called

import json

import json

>>>

import json

Where do complex numbers come from? You see, when a real number and an imaginary number love each other very much, they add together to produce a number which is (justifiably) called complex.

A good question to ask yourself when working with custom types is What is the minimum amount of information necessary to recreate this object? In the case of complex numbers, you only need to know the real and imaginary parts, both of which you can access as attributes on the

import json

>>>

import json

Passing the same numbers into a

import json

import json

>>>

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

Breaking custom data types down into their essential components is critical to both the serialization and deserialization processes.

Encoding Custom Types

To translate a custom object into JSON, all you need to do is provide an encoding function to the

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

import json

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

Notice that you’re expected to raise a

import json

>>>

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

Why did we encode the complex number as a

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

8? Great question! That certainly wasn’t the only choice, nor is it necessarily the best choice. In fact, this wouldn’t be a very good representation if you ever wanted to decode the object later, as you’ll see shortly.

The other common approach is to subclass the standard

import json

import json

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

Instead of raising the

import json

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

import json

import json

>>>

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

Decoding Custom Types

While the real and imaginary parts of a complex number are absolutely necessary, they are actually not quite sufficient to recreate the object. This is what happens when you try encoding a complex number with the

import json

>>>

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

All you get back is a list, and you’d have to pass the values into a

import json

I suppose the question you really ought ask yourself is What is the minimum amount of information that is both necessary and sufficient to recreate this object?

The

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

import json

import json

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

See the clever bit? That

import json

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

If

import json

Every time the

>>> blackjack_hand = (8, "Q")
>>> encoded_hand = json.dumps(blackjack_hand)
>>> decoded_hand = json.loads(encoded_hand)

>>> blackjack_hand == decoded_hand
False
>>> type(blackjack_hand)
<class 'tuple'>
>>> type(decoded_hand)
<class 'list'>
>>> blackjack_hand == tuple(decoded_hand)
True

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

import json

Now play the same kind of game as before:

>>>

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

While

import json

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

import json

This doesn’t just work with one object either. Try putting this list of complex numbers into

import json

data = {
    "president": {
        "name": "Zaphod Beeblebrox",
        "species": "Betelgeusian"
    }
}

If all goes well, you’ll get a list of

import json

>>>

with open("data_file.json", "w") as write_file:
    json.dump(data, write_file)

You could also try subclassing

import json

import json