How do you modify a json object in python?
try this script: Show
the result is:
Just the arrangement is different, You can solve the problem by converting the "data" type to a list, then arranging it as you wish, then returning it and saving the file, like that:
the result is:
you can add if condition in order not to repeat the key, just change it, like that: Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Working With JSON Data in Python Since its inception, JSON has quickly become the de facto standard for information exchange. Chances are you’re here because you need to transport some data from here to there. Perhaps you’re gathering information through an API or storing your data in a document database. One way or another, you’re up to your neck in JSON, and you’ve got to Python your way out. Luckily, this is a pretty common task, and—as with most common tasks—Python makes it almost disgustingly easy. Have no fear, fellow Pythoneers and Pythonistas. This one’s gonna be a breeze!
A (Very) Brief History of JSONNot so surprisingly, JavaScript Object Notation was inspired by a subset of the JavaScript programming language dealing with object literal syntax. They’ve got a nifty website that explains the whole thing. Don’t worry though: JSON has long since become language agnostic and exists as its own standard, so we can thankfully avoid JavaScript for the sake of this discussion. Ultimately, the community at large adopted JSON because it’s easy for both humans and machines to create and understand. Look, it’s JSON!Get ready. I’m about to show you some real life JSON—just like you’d see out there in the wild. It’s okay: JSON is supposed to be readable by anyone who’s used a C-style language, and Python is a C-style language…so that’s you!
As you can see, JSON supports primitive types, like strings and numbers, as well as nested lists and objects.
Whew! You survived your first encounter with some wild JSON. Now you just need to learn how to tame it. Python Supports JSON Natively!Python comes with
a built-in package called Just throw this little guy up at the top of your file: A Little VocabularyThe 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.
Serializing JSONWhat happens after a computer processes lots of information? It needs to take a data dump. Accordingly, the Simple Python objects are translated to JSON according to a fairly intuitive conversion.
A Simple Serialization ExampleImagine you’re working with a Python object in memory that looks a little something like this:
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
Note that 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
Notice that the
file-like object is absent since you aren’t actually writing to disk. Other than that, 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 ArgumentsRemember, 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.
The first option most people want to change is whitespace. You can use the >>>
Another formatting option is the There are others, like Deserializing JSONGreat, looks like you’ve captured yourself some wild JSON! Now it’s time to whip it into shape. In
the Just like serialization, there is a simple conversion table for deserialization, though you can probably guess what it looks like already.
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 >>>
A Simple Deserialization ExampleThis 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
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 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
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? A Real World Example (sort of)For your introductory example, you’ll use JSONPlaceholder, a great source of fake JSON data for practice purposes. First create a script file called You’ll need to make an API request to the JSONPlaceholder service, so just use the
Now, you’re going to be working with a list of TODOs cuz like…you know, it’s a rite of passage or whatever. Go ahead and make a request to the JSONPlaceholder API for the
You don’t
believe this works? Fine, run the file in interactive mode and test it for yourself. While you’re at it, check the type of >>>
See, I wouldn’t lie to you, but I’m glad you’re a skeptic.
All right, time for some action. You can see the structure of the data by visiting the endpoint in a browser, but here’s a sample TODO:
There are multiple users, each with a unique
Yeah, yeah, your implementation is better, but the point is, you can now manipulate the JSON data as a normal Python object! I don’t know about you, but when I run the script interactively again, I get the following results: >>>
That’s cool and all, but you’re here to learn about JSON. For your final task, you’ll create a JSON file that contains the completed TODOs for each of the users who completed the maximum number of TODOs. All you need to do is filter
Perfect, you’ve gotten rid of all the data you don’t need and saved the good stuff to a brand new file! Run the script again and check out Now that you’ve made it this far, I bet you’re feeling like some pretty hot stuff, right? Don’t get cocky: humility is a virtue. I am inclined to agree with you though. So far, it’s been smooth sailing, but you might want to batten down the hatches for this last leg of the journey. Encoding and Decoding Custom Python ObjectsWhat happens when we try to serialize the
Not so surprisingly, Python complains that
>>>
Although the Simplifying Data StructuresNow, 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 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 >>>
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 >>>
Passing the same numbers into a >>>
Breaking custom data types down into their essential components is critical to both the serialization and deserialization processes. Encoding Custom TypesTo translate a custom object into JSON, all you need to do is provide an encoding function to the
Notice that you’re expected to raise a >>>
The other common approach is to subclass the standard
Instead of raising the >>>
Decoding Custom TypesWhile 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 >>>
All you get back is a list, and you’d have to pass the values into a 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
See the clever bit? That
If Every time the Now play the same kind of game as before: >>>
While This doesn’t just work with one object either. Try putting this list of complex numbers into
If all goes
well, you’ll get a list of >>>
You could also try subclassing All done!Congratulations, you can now wield the mighty power of JSON for any and all of your nefarious Python needs. While the examples you’ve worked with here are certainly contrived and overly simplistic, they illustrate a workflow you can apply to more general tasks:
What you do with your data once it’s been loaded into memory will depend on your use case. Generally, your goal will be gathering data from a source, extracting useful information, and passing that information along or keeping a record of it. Today you took a journey: you captured and tamed some wild JSON, and you made it back in time for supper! As an added bonus, learning the Good luck with all of your future Pythonic endeavors! Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Working With JSON Data in Python What is a JSON object in Python?JSON (JavaScript Object Notation) is a popular data format used for representing structured data. It's common to transmit and receive data between a server and web application in JSON format. In Python, JSON exists as a string. For example: p = '{"name": "Bob", "languages": ["Python", "Java"]}'. It's also common to store a JSON object in a file.
How do I convert JSON data to Python?In the json library, you’ll find load() and loads() for turning JSON encoded data into Python objects. Just like serialization, there is a simple conversion table for deserialization, though you can probably guess what it looks like already.
How to send and receive data in JSON in Python?It's common to transmit and receive data between a server and web application in JSON format. In Python, JSON exists as a string. For example: It's also common to store a JSON object in a file. To work with JSON (string, or file containing JSON object), you can use Python's json module.
What is JSON file and how to open it?JSON (JavaScript Object Notation) is a file that is mainly used to store and transfer data mostly between a server and a web application. It is popularly used for representing structured data.
How do I change the value of a JSON object?Array value of a JSON object can be modified. It can be simply done by modifying the value present at a given index. Note: If value is modified at an index which is out of the array size, then the new modification will not replace anything in the original information but rather will be an add-on.
How do I edit JSON?Procedure. In the Enterprise Explorer view, right-click your . json file or other file type that contains JSON code and select Open With > JSON Editor. You can compress JSON strings so that the strings display on one line with white space removed between JSON elements.
How do you add a field to a JSON object in Python?How to add an element to a JSON object in Python. fruit_json = {"apple" : 1, "orange" : 2}. key = "banana". value = 3.. fruit_json[key] = value.. print(fruit_json). How do I update an existing JSON file?Updating or Merging the Existing JSON File. Create a new. task.. In. Definition. tab, select. Update. as the task operation.. Follow the same procedure of creating a JSON Target file using Insert task operation to update the existing JSON file.. |