Python Read JSON File – How to Load JSON from a File and Parse Dumps

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Welcome! If you need to learn the way to work with JSON information in Python, then this text is for you.

You will study:

  • Why the JSON format is so vital.
  • Its primary construction and knowledge varieties.
  • How JSON and Python Dictionaries work collectively in Python.
  • How to work with the Python built-in Β json module.
  • How to convert JSON strings to Python objects and vice versa.
  • How to use masses() and dumps()
  • How to indent JSON strings robotically.
  • How to learn JSON information in Python utilizing load()
  • How to write to JSON information in Python utilizing dump()
  • And extra!

Are you prepared? Let’s start! πŸ”…

πŸ”Ή Introduction: What is JSON?

The JSON format was initially impressed by the syntax of JavaScript (a programming language used for net improvement). But since then it has grow to be a language-independent knowledge format and many of the programming languages that we use at this time can generate and learn JSON.

Importance and Use Cases of JSON

JSON is principally a format used to retailer or symbolize knowledge. Its frequent use instances embrace net improvement and configuration information.

Let’s see why:

  • Web Development: JSON is often used to ship knowledge from the server to the shopper and vice versa in net purposes.

  • Configuration information: JSON can be used to retailer configurations and settings. For instance, to create a Google Chrome App, you want to embrace a JSON file known as manifest.json to specify the identify of the app, its description, present model, and different properties and settings. Β 

πŸ”Έ JSON Structure and Format

Now that you recognize what the JSON format is used for, let’s have a look at its primary construction with an instance that represents the information of a pizza order:

{ 
	"size": "medium",
	"price": 15.67,
	"toppings": ["mushrooms", "pepperoni", "basil"],
	"extra_cheese": false,
	"delivery": true,
	"client": {
		"name": "Jane Doe",
		"phone": null,
		"email": "janedoe@email.com"
	}
}
Sample .json file

These are the principle traits of the JSON format:

  • There is a sequence of key-value pairs surrounded by curly brackets {}.
  • Each key’s mapped to a specific worth utilizing this format:

"key": <worth> 

πŸ’‘ Tip: The values that require quotes have to be surrounded by double quotes.

  • Key-value pairs are separated by a comma. Only the final pair isn’t adopted by a comma.

{
	"size": "medium", # Comma!
	"price": 15.67
}

πŸ’‘ Tip: We usually format JSON with totally different ranges of indentation to make the information simpler to learn. In this text, you’ll learn the way to add the indentation robotically with Python.

JSON Data Types: Keys and Values

JSON information have particular guidelines that decide which knowledge varieties are legitimate for keys and values.

  • Keys have to be strings.
  • Values may be both a string, a quantity, an array, a boolean worth (true/ false), null, or a JSON object.

According to the Python Documentation:

Keys in key/worth pairs of JSON are all the time of the kind str. When a dictionary is transformed into JSON, all of the keys of the dictionary are coerced to strings.

Style Guide

According to the Google JSON Style Guide:

  • Always select significant names.
  • Array varieties ought to have plural key names. All different key names must be singular. For instance: use "orders" as an alternative of "order" if the corresponding worth is an array.
  • There must be no feedback in JSON objects.

πŸ”Ή JSON vs. Python Dictionaries

JSON and Dictionaries would possibly look very related at first (visually), however they’re fairly totally different. Let’s see how they’re “connected” and how they complement one another to make Python a highly effective instrument to work with JSON information.

JSON is a file format used to symbolize and retailer knowledge whereas a Python Dictionary is the precise knowledge construction (object) that’s stored in reminiscence whereas a Python program runs.

How JSON and Python Dictionaries Work Together

When we work with JSON information in Python, we will not simply learn them and use the information in our program immediately. This is as a result of the whole file could be represented as a single string and we might not give you the option to entry the key-value pairs individually.

Unless…

We use the key-value pairs of the JSON file to create a Python dictionary that we are able to use in our program to learn the information, use it, and modify it (if wanted).

This is the principle connection between JSON and Python Dictionaries. JSON is the string illustration of the information and dictionaries are the precise knowledge buildings in reminiscence which might be created when this system runs.

Great. Now that you recognize extra about JSON, let’s begin diving into the sensible facets of how one can work with JSON in Python.

πŸ”Έ The JSON Module

Luckily for us, Python comes with a built-in module known as json. It is put in robotically while you set up Python and it consists of capabilities to aid you work with JSON information and strings.

We will use this module within the coming examples.

How to Import the JSON Module

To use json in our program, we simply want to write an import assertion on the prime of the file.

Like this:

With this line, you should have entry to the capabilities outlined within the module. We will use a number of of them within the examples.

πŸ’‘ Tip: If you write this import assertion, you have to to use this syntax to name a operate outlined within the json module:

πŸ”Ή Python and JSON Strings

To illustrate how a number of the most vital capabilities of the json module work, we’ll use a multi-line string with JSON format.

JSON String

Particularly, we’ll use this string within the examples. It is simply a common multi-line Python string that follows the JSON format.

data_JSON =  """
{
	"size": "Medium",
	"price": 15.67,
	"toppings": ["Mushrooms", "Extra Cheese", "Pepperoni", "Basil"],
	"client": {
		"name": "Jane Doe",
		"phone": "455-344-234",
		"email": "janedoe@email.com"
	}
}
"""
JSON String

  • To define a multi-line string in Python, we use triple quotes. Β 
  • Then, we assign the string to the variable data_JSON.

πŸ’‘ Tip: The Python Style Guide recommends using double quote characters for triple-quoted strings. Β 

JSON String to Python Dictionary

We will use the string with JSON format to create a Python dictionary that we can access, work with, and modify.

To do this, we will use the loads() function of the json module, passing the string as the argument.

This is the basic syntax:

Here is the code:

# Import the module
import json

# String with JSON format
data_JSON =  """
{
	"size": "Medium",
	"price": 15.67,
	"toppings": ["Mushrooms", "Extra Cheese", "Pepperoni", "Basil"],
	"client": {
		"name": "Jane Doe",
		"phone": "455-344-234",
		"email": "janedoe@email.com"
	}
}
"""

# Convert JSON string to dictionary
data_dict = json.masses(data_JSON)

Let’s give attention to this line:

data_dict = json.masses(data_JSON)

  • json.masses(data_JSON) creates a new dictionary with the key-value pairs of the JSON string and it returns this new dictionary.
  • Then, the dictionary returned is assigned to the variable data_dict.

Awesome! If we print this dictionary, we see this output:

{'dimension': 'Medium', 'value': 15.67, 'toppings': ['Mushrooms', 'Extra Cheese', 'Pepperoni', 'Basil'], 'shopper': {'identify': 'Jane Doe', 'cellphone': '455-344-234', 'electronic mail': 'janedoe@electronic mail.com'}}

The dictionary has been populated with the information of the JSON string. Each key-value pair was added efficiently.

Now let’s have a look at what occurs after we attempt to entry the values of the key-value pairs with the identical syntax that we might use to entry the values of a common Python dictionary:

print(data_dict["size"])
print(data_dict["price"])
print(data_dict["toppings"])
print(data_dict["client"])

The output is:

Medium
15.67
['Mushrooms', 'Extra Cheese', 'Pepperoni', 'Basil']
{'identify': 'Jane Doe', 'cellphone': '455-344-234', 'electronic mail': 'janedoe@electronic mail.com'}

Exactly what we anticipated. Each key can be utilized to entry its corresponding worth.

πŸ’‘ Tip: We can use this dictionary identical to another Python dictionary. For instance, we are able to name dictionary strategies, add, replace, and take away key-value pairs, and extra. We may even use it in a for loop.

JSON to Python: Type Conversion

When you employ masses() to create a Python dictionary from a JSON string, you’ll discover that some values might be transformed into their corresponding Python values and knowledge varieties.

This desk introduced within the Python Documentation for the json module summarizes the correspondence from JSON knowledge varieties and values to Python knowledge varieties and values:

Table introduced within the official documentation of the json moduleΒ 

πŸ’‘ Tip: The identical conversion desk applies after we work with JSON information.

Python Dictionary to JSON String

Now you understand how to create a Python dictionary from a string with JSON format.

But generally we’d want to do precisely the alternative, creating a string with JSON format from an object (for instance, a dictionary) to print it, show it, retailer it, or work with it as a string.

To do this, we are able to use the dumps operate of the json module, passing the article as argument:

πŸ’‘ Tip: This operate will return a string.

This is an instance the place we convert the Python dictionary shopper into a string with JSON format and retailer it in a variable:

# Python Dictionary
shopper = {
    "name": "Nora",
    "age": 56,
    "id": "45355",
    "eye_color": "green",
    "wears_glasses": False
}

# Get a JSON formatted string
client_JSON = json.dumps(shopper)

Let’s give attention to this line:

client_JSON = json.dumps(shopper)

  • json.dumps(shopper) creates and returns a string with all of the key-value pairs of the dictionary in JSON format.
  • Then, this string is assigned to the client_JSON variable.

If we print this string, we see this output:

{"name": "Nora", "age": 56, "id": "45355", "eye_color": "green", "wears_glasses": false}

πŸ’‘ Tip: Notice that the final worth (false) was modified. In the Python dictionary, this worth was False however in JSON, the equal worth is false. This helps us affirm that, certainly, the unique dictionary is now represented as a string with JSON format.

If we examine the information sort of this variable, we see:

<class 'str'>

So the return worth of this operate was positively a string.

Python to JSON: Type Conversion

A strategy of sort conversion happens as properly after we convert a dictionary into a JSON string. This desk from the Python Documentation illustrates the corresponding values:

Table from the official documentation of the json module.

How to Print JSON With Indentation

If we use the dumps operate and we print the string that we acquired within the earlier instance, we see:

{"name": "Nora", "age": 56, "id": "45355", "eye_color": "green", "wears_glasses": false}

But this isn’t very readable, proper?

We can enhance the readability of the JSON string by including indentation.

To do that robotically, we simply want to cross a second argument to specify the variety of areas that we wish to use to indent the JSON string:

πŸ’‘ Tip: the second argument has to be a non-negative integer (variety of areas) or a string. If indent is a string (akin to "t"), that string is used to indent every stage (supply).

Now, if we name dumps with this second argument:

client_JSON = json.dumps(shopper, indent=4)

The results of printing client_JSON is:

{
    "name": "Nora",
    "age": 56,
    "id": "45355",
    "eye_color": "green",
    "wears_glasses": false
}

That’s nice, proper? Now our string is properly formatted. This might be very useful after we begin working with information to retailer the information in a human-readable format.

How to Sort the Keys

You may also type the keys in alphabetical order if you happen to want to. To do that, you simply want to write the identify of the parameter sort_keys and cross the worth True:

πŸ’‘ Tip: The worth of sort_keys is False by default if you happen to do not cross a worth.

For instance:

client_JSON = json.dumps(shopper, sort_keys=True)

Returns this string with the keys sorted in alphabetical order:

{"age": 56, "eye_color": "green", "id": "45355", "name": "Nora", "wears_glasses": false}

How to Sort Alphabetically and Indent (on the identical time)

To generate a JSON string that’s sorted alphabetically and indented, you simply want to cross the 2 arguments:

In this case, the output is:

{
    "age": 56,
    "eye_color": "green",
    "id": "45355",
    "name": "Nora",
    "wears_glasses": false
}

πŸ’‘ Tip: You can cross these arguments in any order (relative to one another), however the object has to be the primary argument within the checklist.

Great. Now you understand how to work with JSON strings, so let’s have a look at how one can work with JSON information in your Python packages.

πŸ”Έ JSON and Files

Typically, JSON is used to retailer knowledge in information, so Python provides us the instruments we’d like to learn these kinds of file in our program, work with their knowledge, and write new knowledge.

πŸ’‘ Tip: a JSON file has a .json extension:

Let’s see how we are able to work with .json information in Python.

How to Read a JSON File in Python

Let’s say that we created an orders.json file with this knowledge that represents two orders in a pizza store:

{
	"orders": [ 
		{
			"size": "medium",
			"price": 15.67,
			"toppings": ["mushrooms", "pepperoni", "basil"],
			"extra_cheese": false,
			"delivery": true,
			"client": {
				"name": "Jane Doe",
				"phone": null,
				"email": "janedoe@email.com"
			}
		},
		{
			"size": "small",
			"price": 6.54,
			"toppings": null,
			"extra_cheese": true,
			"delivery": false,
			"client": {
				"name": "Foo Jones",
				"phone": "556-342-452",
				"email": null
			}
		}
	]
}
orders.json

Please take a second to analyze the construction of this JSON file.

Here are some fast ideas:

  • Notice the information kinds of the values, the indentation, and the general construction of the file.
  • The worth of the principle key "orders" is an array of JSON objects (this array might be represented as checklist in Python). Each JSON object holds the information of a pizza order.

If we wish to learn this file in Python, we simply want to use a with assertion:

πŸ’‘ Tip: In the syntax above, we are able to assign any identify to file (inexperienced field). This is a variable that we are able to use throughout the with assertion to refer to the file object.

The key line of code on this syntax is:

knowledge = json.load(file)

  • json.load(file) creates and returns a new Python dictionary with the key-value pairs within the JSON file.
  • Then, this dictionary is assigned to the knowledge variable.

πŸ’‘ Tip: Notice that we’re utilizing load() as an alternative of masses(). This is a totally different operate within the json module. You will study extra about their variations on the finish of this text.

Once we have now the content material of the JSON file saved within the knowledge variable as a dictionary, we are able to use it to do principally something we wish.

Examples

For instance, if we write:

print(len(knowledge["orders"]))

The output is 2 as a result of the worth of the principle key "orders" is a checklist with two parts.

We may also use the keys to entry their corresponding values. This is what we usually do after we work with JSON information.

For instance, to entry the toppings of the primary order, we might write:

knowledge["orders"][0]["toppings"]

  • First, we choose the principle key "orders"
  • Then, we choose the primary ingredient within the checklist (index 0).
  • Finally, we choose the worth that corresponds to the important thing "toppings"

You can see this “path” graphically within the diagram:

If we print this worth, the output is:

['mushrooms', 'pepperoni', 'basil']

Exactly what we anticipated. You simply want to “dive deeper” into the construction of the dictionary by utilizing the mandatory keys and indices. You can use the unique JSON file/string as a visible reference. This manner, you possibly can entry, modify, or delete any worth.

πŸ’‘ Tip: Remember that we’re working with the brand new dictionary. The modifications made to this dictionary won’t have an effect on the JSON file. To replace the content material of the file, we’d like to write to the file.

How to Write to a JSON File

Let’s see how one can write to a JSON file.

The first line of the with assertion could be very related. The solely change is that you just want to open the file in 'w' (write) mode to give you the option to modify the file.

πŸ’‘ Tip: If the file does not exist already within the present working listing (folder), it is going to be created robotically. By utilizing the 'w' mode, we might be changing the whole content material of the file if it already exists.

There are two other ways to write to a JSON file within the physique of the with assertion:

Let’s see them intimately.

First Approach: dump

This is a operate that takes two arguments:

  • The object that might be saved in JSON format (for instance, a dictionary).
  • The file the place it is going to be saved (a file object).

Let’s say that the pizza store needs to take away the purchasers’ knowledge from the JSON file and create a new JSON file known as orders_new.json with this new model.

We can do that with this code:

# Open the orders.json file
with open("orders.json") as file:
    # Load its content material and make a new dictionary
    knowledge = json.load(file)

    # Delete the "client" key-value pair from every order
    for order in knowledge["orders"]:
        del order["client"]

# Open (or create) an orders_new.json file 
# and retailer the brand new model of the information.
with open("orders_new.json", 'w') as file:
    json.dump(knowledge, file)

This was the unique model of the information within the orders.json file. Notice that the "client" key-value pair exists.

{
	"orders": [ 
		{
			"size": "medium",
			"price": 15.67,
			"toppings": ["mushrooms", "pepperoni", "basil"],
			"extra_cheese": false,
			"delivery": true,
			"client": {
				"name": "Jane Doe",
				"phone": null,
				"email": "janedoe@email.com"
			}
		},
		{
			"size": "small",
			"price": 6.54,
			"toppings": null,
			"extra_cheese": true,
			"delivery": false,
			"client": {
				"name": "Foo Jones",
				"phone": "556-342-452",
				"email": null
			}
		}
	]
}
orders.json

This is the brand new model within the orders_new.json file:

{"orders": [{"size": "medium", "price": 15.67, "toppings": ["mushrooms", "pepperoni", "basil"], "extra_cheese": false, "delivery": true}, {"size": "small", "price": 6.54, "toppings": null, "extra_cheese": true, "delivery": false}]}
orders_new.json

If you analyze this fastidiously, you will note that the "clients" key-value pair was eliminated from all of the orders.

However, there’s something lacking on this file, proper?

Please take a second to take into consideration this… What may or not it’s?

Indentation, in fact!

The file does not actually appear to be a JSON file, however we are able to simply repair this by passing the argument indentation=4 to dump()

Now the content material of the file seems like this:

{
    "orders": [
        {
            "size": "medium",
            "price": 15.67,
            "toppings": [
                "mushrooms",
                "pepperoni",
                "basil"
            ],
            "extra_cheese": false,
            "delivery": true
        },
        {
            "size": "small",
            "price": 6.54,
            "toppings": null,
            "extra_cheese": true,
            "delivery": false
        }
    ]
}
orders_new.json

What a distinction! This is precisely what we might count on a JSON file to appear to be.

Now you understand how to learn and write to JSON information utilizing load() and dump(). Let’s see the variations between these capabilities and the capabilities that we used to work with JSON strings. Β 

πŸ”Ή load() vs. masses()

This desk summarizes the important thing variations between these two capabilities:

πŸ’‘ Tip: Think of masses() as “load string” and that may aid you keep in mind which operate is used for which function.

πŸ”Έ dump() vs. dumps()

Here we have now a desk that summarizes the important thing variations between these two capabilities:

πŸ’‘ Tip: Think of dumps() as a “dump string” and that may aid you keep in mind which operate is used for which function.

πŸ”Ή Important Terminology in JSON

Finally, there are two vital phrases that you just want to know to work with JSON:

  • Serialization: changing an object into a JSON string.
  • Deserialization: changing a JSON string into an object.

πŸ”Έ In Summary

  • JSON (JavaScript Object Notation) is a format used to symbolize and retailer knowledge.
  • It is often used to switch knowledge on the net and to retailer configuration settings.
  • JSON information have a .json extension.
  • You can convert JSON strings into Python objects and vice versa.
  • You can learn JSON information and create Python objects from their key-value pairs.
  • You can write to JSON information to retailer the content material of Python objects in JSON format.

I actually hope you favored my article and discovered it useful. Now you understand how to work with JSON in Python. Follow me on Twitter @EstefaniaCassN and try my on-line programs.



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