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Python JSON to Dictionary

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  • Convert JSON Object to Python Dictionary
  • Convert JSON nested object to Python dictionary

To convert Python JSON string to Dictionary, use json.loads() function. Note that only if the JSON content is a JSON Object, and when parsed using loads() function, we get Python Dictionary object.

JSON content with array of objects will be converted to a Python list by loads() function.

For example, following JSON content will be parsed to a Python Dictionary.

Following JSON content will be parsed to a Python List.

1. Convert JSON Object to Python Dictionary

In this example, we will take a JSON string that contains a JSON object. We will use loads() function to load the JSON string into a Python Dictionary, and access the name:value pairs.

Python Program

2. Convert JSON nested object to Python dictionary

In this example, we will take a JSON string that contains a JSON object nested with another JSON object as value for one of the name:value pair. We will parse the JSON object to Dictionary, and access its values.

In this Python JSON Tutorial , we learned how to convert a JSON Object string to a Python Dictionary, with the help of well detailed example programs.

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Convert JSON to a Python Dictionary

  • May 25, 2022 May 16, 2022

Convert JSON to a Python Dictionary Cover Image

In this tutorial, you’re going to learn how to convert a JSON file or string into a Python dictionary . Being able to work with JSON data is an important skill for a Python developer of any skill level. In most cases, data you access through web APIs will come in the form JSON data. Being able to convert these JSON objects into Python dictionaries will allow you to work with the data in meaningful ways.

By the of this tutorial, you’ll have learned:

  • How to load a JSON file into a Python dictionary
  • How to load a JSON string into a dictionary
  • How to load data from an API into a Python dictionary

Table of Contents

What is JSON?

JSON stands for JavaScript Object Notation and it’s a popular format used to represent data. While originating from JavaScript, the format spread quickly due to its versatility. The format itself is quite similar to that of a Python dictionary. However, in many cases, the data comes in a string representing the object. We need to convert that string into a Python dictionary in order to work with it in Python.

Using JSON with Python

Python comes with a built-in library, json , that lets you work with JSON objects in meaningful ways. In this tutorial, we’ll be looking at two of its functions that allow you to convert JSON objects to Python dictionaries:

  • json.load() , which loads a JSON file into a Python dictionary
  • json.loads() , which loads a string representation of a JSON file into a Python dictionary

In the second function, as you may have guessed, the s suffix refers to string . In the following sections, you’ll learn how to use these functions to convert a JSON object into a Python dictionary.

Load a JSON File into a Python dictionary

In this section, you’ll learn how to use the json.load() function to load a JSON file into a Python dictionary . If you want to follow along, you can download the file here . The file represents data from the internal space station, the API we’ll explore later on in the tutorial.

Let’s see how you can use the load() function to load an external JSON file:

Let’s break down what we did in the code above:

  • We loaded the json library
  • We used a context manager to load our file in “read” mode using the alias file
  • We then used the json.load() function to load our file into a variable, data
  • Finally, we printed our resulting dictionary

While you can do this without using a context manager, the context manager handles closing the file, thereby preserving memory.

We can verify the type of the resulting value by using the type() function. This allows us to make sure that we actually loaded in a dictionary:

In some cases, however, you won’t be working with data in a .json file. In some cases, you’ll simply be presented with a string that represents the JSON object. In the following section, you’ll learn how to work with strings that represent JSON objects.

Load a JSON String into a Python Dictionary

In many cases, you’ll be given JSON data in a string format. Working with this is different than working with a .json file. When working with string representations of a JSON file, you can use the json.loads() function , which is used to “load a string”.

Let’s see how we can do this in Python using the json module:

We can see from the example above that by passing in the string into the json.loads() function, that we were able to easily transform a JSON string into a Pyhon dictionary. In the final section below, you’ll learn how to use the json.loads() function to load a JSON response object from a web API into a Python dictionary.

Load JSON Data from an API into a Python Dictionary

In this section, you’ll learn how to use the json and requests libraries to get data from a web API and load it into a Python dictionary. For this, we’ll be using a NASA API that describes the current status of the International Space Station, which you can find here . The endpoint we’ll use the iss-now endpoint, which provides the current location.

Let’s see how we can use the json library to load the response we get back:

Let’s break down what we did here:

  • We imported the required libraries, json and requests
  • We loaded the response variable using the requests.get() function, passing in our url
  • We then got the text representation from the response object
  • Finally, we passed this into the json.loads() function to convert the string into a dictionary

This is quite a bit of code and thankfully there’s an easier way! The requests library allows us to apply the .json() method to the response object to convert it to a dictionary .

Let’s take a look at how this works:

In the example above, we didn’t need to import the json library to convert the string into a Python dictionary. This works by loading a response object using the .get() function. We then apply the .json() method to the response object to convert it to a Python dictionary.

In this tutorial, you learned how to convert JSON into a Python dictionary. You learned three different ways of accomplishing this: first by loading a .json file into a Python dictionary, then by loading a JSON string into a dictionary, and, finally, working with web APIs.

Being able to work with JSON data is an important skill, given the ubiquity of the file format. Being able to convert this format to a Python dictionary will help you work with both web development and data science.

Additional Resources

To learn more about related topics, check out the tutorials below:

  • Python Dictionaries: A Complete Overview
  • Python: Pretty Print JSON (3 Different Ways!)
  • Python: Pretty Print a Dict (Dictionary) – 4 Ways

Nik Piepenbreier

Nik is the author of datagy.io and has over a decade of experience working with data analytics, data science, and Python. He specializes in teaching developers how to use Python for data science using hands-on tutorials. View Author posts

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Python JSON to Dict: Converting JSON Data into Python Dictionaries

Python JSON to Dict

Python JSON to Dict conversion:

Additional notes.

  • Handling Errors:  Use try-except blocks to catch potential errors like invalid JSON syntax.
  • Nested Data:  Access nested elements using dot notation or bracket notation.
  • Custom Decoders/Encoders:  Create custom decoders and encoders for specific data types or formatting requirements.

Understanding JSON and Python Dictionaries

JSON, standing for JavaScript Object Notation, is a lightweight data format for data interchange. It’s easily readable by humans and parsed by machines. JSON structure closely resembles dictionary objects in Python—it’s a collection of key-value pairs.

A Python dictionary is a mutable, unordered collection that stores data values like a map. Given their structural similarities, Python developers frequently convert JSON to dictionaries for easier manipulation within Python scripts.

Converting JSON to a Dictionary:

  • Read the JSON data.
  • Use the json module’s loads() function.

Here’s what this looks like in action:

Consider the key characteristics of each:

  • Text-based and language-independent.
  • Based on JavaScript’s way of defining objects.

Python Dictionary:

  • Core data type in Python.
  • Consists of keys and values.
  • Keys must be immutable types.

While they share similarities, there are distinctions. For instance, JSON keys are always in double quotes, while dictionary keys in Python do not require quotes. Therefore, when working with these formats, attention to detail is essential.

Moreover, the json library in Python also allows one to serialize Python dictionaries into JSON format, creating a JSON string representation of the dictionary. This process is as simple as using the dumps() function.

Understanding how JSON and Python dictionaries interchange can streamline data handling for developers. It opens up numerous opportunities for data processing and storage, an important aspect of modern programming.

The Basics of Python’s JSON Library

Python’s JSON library is a versatile toolkit, ideal for exchanging and storing data . The library converts data between JSON text and Python objects using four main methods: load() , loads() , dump() , and dumps() .

  • Reading JSON : To read JSON from a file, Python offers the json.load() function. It reads a file containing a JSON document and returns a Python object.
  • Reading JSON String : If you have JSON data as a string, json.loads() serves to convert this string to a Python object.

The conversion process is usually referred to as parsing .

  • Writing JSON : Writing a Python object to a file in JSON format uses the json.dump() method. It outputs JSON data to a writable file-like object.
  • Writing JSON String : To convert a Python object back into a JSON string, the library provides json.dumps() . This is especially handy for sending JSON data over a network.

The JSON library also includes JSONEncoder and JSONDecoder classes for more control over serialization and deserialization. However, for straightforward tasks, using the four primary methods should suffice.

A common mistake can occur if incorrect data types are used, raising a TypeError . Always check the type of the object being processed with the type() function to ensure compatibility with the JSON format.

The Python JSON library, while not overly complex, is a powerful general-purpose tool. It allows developers to work with JSON data in a clear and effective way by translating Python code and the JSON format back and forth seamlessly.

Loading JSON into Python Objects

When working with JSON data in Python, one often needs to transform it into native Python objects. This process is essential for manipulating JSON data within a Python program.

Using load()

The load() function is a vital tool for reading JSON data from a file. One typically uses this function within a context manager to ensure proper handling of the file stream. To use load() , one must have a file object ready, which is typically obtained by opening a JSON file in read mode.

The above code will read JSON data from ‘data.json’ and convert it into a Python dictionary. It’s important to note that using a context manager, like the with statement, helps prevent common file-related errors by managing the file’s opening and closing.

Using loads()

In contrast, the loads() function converts JSON data from a string format into a Python object. It is particularly useful when dealing with JSON data received from an API or similar sources where JSON is transmitted as a string.

Here, the variable json_string contains the JSON data structure, and loads() parses it into a Python dictionary named python_object . It’s crucial to ensure that the JSON string is correctly formatted to avoid a ValueError that occurs if the string is not a valid JSON format.

Converting Python Objects to JSON Strings

When we want to save Python objects like dictionaries or lists as JSON, we use either dump() or dumps() functions from the json module. This act is known as serialization.

Using dump()

The dump() function takes a Python object, usually a dictionary or a list, and writes it to a file. With dump() , you have the option to pretty-print your JSON for better readability by setting the indent parameter. You might also want to sort the keys in alphabetic order, which you can do with sort_keys=True . Here’s how you would typically use it:

Using dumps()

Conversely, dumps() is used to convert a Python object into a JSON string, which you can then save or send over a network. The dumps() function offers parameters like indent , separators , and sort_keys to control the serialization process. For example:

dumps() allows you to use custom encoders through the cls parameter if you need to handle complex objects. And just like with dump() , you can set the default parameter to a function that will take care of those objects that dumps() normally can’t serialize.

Handling Data Types and Serialization

When working with JSON in Python, understanding how data types translate during the serialization process is key. Serialization is the method of converting a data structure, like a list or a dictionary, into a string format that can be easily saved to a file or transmitted over a network. This string format is typically in JSON—JavaScript Object Notation.

The json module in Python seamlessly handles the serialization of basic data types. Here’s a quick conversion table that highlights the process:

When one uses the json.dump() function, Python dictionaries are turned into JSON objects—it’s a straightforward process. This is a typical usage for storing or sending data in a format that other systems and languages can interpret. In the same vein, arrays in Python, which are represented by lists or tuples, become JSON arrays.

Numbers and strings maintain their essence and are represented in JSON as you’d expect—a number as a number, and a string as a string. For those who prefer to see code in action, here is an example:

After the process, data_json holds a string that looks like a Python dictionary but is actually JSON formatted. Deserialization, the reverse of serialization, turns JSON back into a Python dictionary using json.loads() . This duality makes JSON an ideal format for data interchange between different programming environments.

Error Handling and Debugging

When working with JSON in Python, errors can pop up, especially when dealing with user inputs or external data sources. Error handling is crucial to make the code robust and user-friendly. The try-except block is commonly used to catch exceptions that could arise when parsing JSON data.

For instance, the json.loads() function might throw a json.JSONDecodeError if the string being parsed is not properly formatted as JSON. Here’s how one could manage such a scenario:

During debugging , it’s vital to pinpoint the exact issue. A good approach is to examine the JSON data structure and verify the encoding. Always ensure that the object passed to json.loads() or json.load() is what’s expected—usually a string for json.loads() and a file-like object for json.load() .

When an error is caught, a detailed message to the console or log can help in understanding the issue. This may include printing out information about the unexpected data or structure encountered.

In summary:

  • Use try-except blocks to manage potential exceptions like json.JSONDecodeError .
  • Verify the JSON data structure.
  • Validate your JSON data encoding before parsing.
  • Provide informative error messages for easier debugging.

Handling these errors gracefully ensures that your code doesn’t break unexpectedly and can help maintain a smooth user experience.

Advanced JSON Manipulation in Python

Json black and yellow printed paper

Python makes working with JSON data convenient through its built-in json module. To handle more complex tasks, you need to use advanced techniques in manipulating JSON data into Python dictionaries.

When dealing with JSON, you often iterate over data. Python’s for loop and dictionary methods like .items() , .keys() , and .values() become crucial. Let’s take a peek at how you can use these methods with ease.

Iterating through keys and values:

Filtering Data:

Sometimes you want only specific pieces of data. You can filter using dictionary comprehension:

Transforming Data:

Python dictionaries allow you to transform data easily. Here’s an example where we add a new key-value pair:

In tasks where you need to manipulate data on a larger scale, libraries like pandas can be exceptionally useful. They can help you turn JSON into a DataFrame, making it easier to manipulate large datasets with complex structures.

Using these advanced tips in your Python projects will give you the power to handle JSON data with confidence and clarity, ultimately opening the door to more robust data processing and manipulation strategies.

Working with APIs and JSON Data

When a developer needs to exchange data between their program and a web service, they often encounter APIs . APIs, or Application Programming Interfaces, are sets of rules that allow software to communicate. They are used to send and receive data over the internet, often employing the HTTP protocol.

In the world of data exchange, JSON (JavaScript Object Notation) is a popular format. Many APIs send and receive data as JSON because it’s lightweight and easy for both humans and machines to read. In Python, programmers interact with JSON data using built-in libraries.

Here’s how they usually handle this process:

  • Sending a Request : They use the requests library to send an HTTP request to the API. The type of request (GET, POST, PUT, DELETE) depends on the action they want to perform.
  • Receiving JSON Data : If the API sends back a response, it typically comes in the form of a JSON object. This is where Python shines; it can effortlessly interpret JSON.
  • Converting JSON to a Dictionary : They use Python’s json library, specifically the json.loads() function, to turn the JSON object into a Python dictionary. This dictionary is easy to work with because it’s structured just like a regular Python object.
  • Using the Data : Once they have the data in a dictionary, programmers can use it just like any other data in Python.

For example, to fetch and convert data from an API, they might write:

Doing this allows Python developers to interact with web services smoothly, harnessing the power of APIs to extend the capabilities of their programs. The key is understanding how to manipulate these technologies to work together effectively.

Comparison with Other Formats

Python Code: turned on gray laptop computer

When exploring different data formats, JSON (JavaScript Object Notation) is one often lined up against YAML (YAML Ain’t Markup Language), especially in terms of readability and ease of use. Both are text-based formats ideal for transporting and storing structured data. However, they have different approaches and features that cater to various requirements.

JSON is widely known for its compatibility with web applications, primarily because it’s easy to parse in JavaScript. This format represents objects with a simple, clear structure:

On the flip side, YAML presents a more human-readable option, relying on indentation to convey structure:

The encoding and decoding process for each format also varies. JSON is typically more strict, requiring keys to be in double quotes and supporting a narrower set of data types. YAML, however, offers a broader range without strict quoting, which can include complex types like nodes and references that aren’t natively supported by JSON.

Here’s a breakdown of their key differences:

  • JSON’s syntax is more compact, making it more efficient for transmission over networks.
  • YAML offers better readability, which can be a boon for configuration files and data sharing between humans.
  • JSON has many parsers available across various programming languages, ensuring its objects and arrays are easily decoded into in-memory data structures.
  • YAML, while having parsers available, can be more prone to errors in translation due to its complex features.

In conclusion, choosing between JSON or YAML—or any data format, for that matter—depends on the project’s specific needs, whether it’s for configuration management, data serialization, or web communication.

Best Practices and Performance

Python Code a computer screen with a bunch of code on it

When working with JSON and Python dictionaries, performance and best practices should go hand-in-hand to ensure swift and reliable code. It begins with the basics: always employ the json module’s loads() and dumps() methods appropriately. When converting JSON data to a dictionary, json.loads() is the go-to choice because it parses the JSON string into a native Python dictionary efficiently.

Memory Usage and Efficiency: Avoid loading large JSON files into memory all at once. If faced with substantial JSON data, consider using ijson or similar libraries that allow for iterative parsing, which is kinder to your memory footprint.

Maintainable Code: The code should be readable for anyone who might review it later. That means sticking to clear variable names and commenting when necessary. Maintainability often trumps a minor performance gain.

Error Handling: Robust code anticipates what might go wrong. When parsing JSON, using try-except blocks will ensure that unexpected data types or malformed JSON doesn’t break the application.

Lastly, efficiency isn’t just about speed; it’s also about writing code that won’t need constant revisiting. Use consistent methods for converting between JSON and dictionaries to avoid confusion and errors.

By giving thought to these elements, one not only writes code that performs well but also stands the test of time in terms of readability and maintainability.

Tools and Libraries for Enhanced JSON Handling

Working with JSON in Python can be a breeze with the right tools. Python comes equipped with a built-in json library, which provides a straightforward way to encode and decode JSON data. For basic needs, functions like json.load() and json.dumps() are quite handy for converting between JSON strings and Python dictionaries.

However, sometimes developers need more speed or functionality than what the standard library offers. That’s where third-party libraries shine. For instance, orjson is known for being fast and precise. This tool has the upper hand in quickly serializing complex data types like dataclasses, datetime , numpy , and UUID objects. It dramatically speeds up processing, even more so than other JSON libraries.

When handling very large JSON files or a surplus of small ones, performance matters. A library like cysimdjson is a hero in such scenarios. Its main appeal? Blazing speed. It’s significantly faster—some users note 7 to 12 times quicker—than Python’s default JSON parser, making it an excellent tool for performance-critical applications.

Lastly, it’s essential to write and maintain readable and efficient code. A typical improvement is direct dictionary key lookups by avoiding the slower a_dict.keys() approach. Optimizing if conditions and understanding how the underlying library works can help developers handle JSON data both accurately and swiftly.

In summary, developers have a variety of enhanced tools at their disposal to work with JSON data effectively:

  • Standard Library : Good for basic JSON tasks.
  • orjson : Optimized for speed and correctly handles more Python data types natively.
  • cysimdjson : Offers a major speed boost for parsing large quantities of data.

Remember, the key is to pick the tool that best suits the task at hand.

Frequently Asked Questions

Converting JSON to a dictionary in Python is a common and straightforward task. The json module, which is bundled with Python, provides robust methods to handle JSON data. This section will answer some common questions regarding the conversion process.

How can I convert a JSON string into a dictionary in Python?

To transform a JSON string to a dictionary, Python’s json.loads() function comes in handy. It takes a JSON string as input and returns a dictionary.

What is the process for reading a JSON file into a Python dictionary?

For reading a JSON file, open the file for reading and then use json.load() to decode the file content to a dictionary.

Can you give an example of transforming JSON data into a Python dictionary?

Sure! Here’s how to do it:

After running this code, dictionary will be a Python dict with the data from json_data .

How do I parse a JSON file into a list of dictionaries in Python?

If the JSON file contains an array of objects, using the json.load() function will automatically convert it into a list of dictionaries.

What is the best way to convert complex JSON structures into Python dictionaries?

For complex JSON structures, you can still use json.loads() or json.load() , but you might need to perform additional parsing to handle nested objects and arrays appropriately.

How to use Python’s json.loads() function for converting JSON to a dictionary?

Invoke json.loads() with a proper JSON string. It will decode the string and map it to a Python dictionary. Remember that JSON objects convert to dictionaries and JSON arrays to lists .

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PythonForBeginners.com

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Learn By Example

Load JSON into a Python Dictionary

Author: Aditya Raj Last Updated: February 8, 2023

Softwares often use JSON file format to store and transmit data. While writing software in python, we might need to convert a JSON string or file into a python object. This article discusses how to load JSON into a python dictionary.

What is JSON Format?

Convert json string to python dictionary, convert json file to python dictionary, convert json to user-defined python objects.

JSON (JavaScript Object Notation) is a lightweight data-interchange format that is easy for humans to read and write and for machines to parse and generate.

The syntax of JSON consists of keys and values, separated by a colon (:), and surrounded by curly braces ({}). The keys must be strings, and the values can be any data type including strings, numbers, arrays, and objects.

python assign json to dict

For example, the following JSON string contains data of an employee.

  • The name of the employee is “John Doe”.
  • The age of the employee is 35.
  • The job title of the employee is “Software Engineer”.
  • The department the employee works in is “IT”.
  • The employee has 10 years of experience in the field.
  • The employee’s address includes street name “123 Main St.”, city “San Francisco”, state “CA”, and zip code 94102.

You can observe that the JSON format is almost similar to the format of a python dictionary . 

To load a json string into a python dictionary, you can use the loads() method defined in the json module. The loads() method takes the JSON string as its input argument and returns the dictionary as shown below.

While using the loads() method, you should pass a valid JSON string as an input argument. Otherwise, the program will run into an error.

Instead of using the loads() function, you can also use the JSONDecoder class to convert a JSON string to python dictionary. The JSONDecoder class is defined in the json module and has a decode() method.

When the decode() method is invoked on the JSONDecoder object, it takes a json string as its input argument. After execution, it returns a dictionary as shown below.

Suggested Reading: Working with JSON files in Python

If we have a JSON file instead of a json string, we can also convert it to a dictionary. For this, we will use the following steps.

  • First, we will open the JSON file in read mode using the open() function. The open() function takes the file name as its first input argument and the python literal “r” as its second input argument. After execution, it returns a file pointer. 
  • Next, we will pass the file pointer to the load() method defined in the json module. The load() method will return the python dictionary after execution. 

You can observe this in the following example.

Instead of obtaining a dictionary, we can also convert a JSON file or string to a custom python object. For this, you can read this article on custom JSON decoder in python .

In this article, we have discussed how to load a json string or file to a dictionary. To learn more about python programming, you can read this article on how to convert JSON to YAML in Python . You might also like this article on custom json encoders in python .

I hope you enjoyed reading this article. Stay tuned for more informative articles.

Happy Learning!

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How to convert JSON to a dictionary in Python?

Convert JSON String Into Dictionary

Hello folks! In this tutorial, we are going to discuss how we can convert JSON to a dictionary in Python.

What is JSON?

JSON stands for JavaScript Object Notation . It is one of the most popular and widely accepted data formats to represent structured data. It is a lightweight format used to store and exchange textual data written in JavaScript notation. The file containing the JSON data must be saved with the file extension .json .

JSON in Python

The representation of JSON data present inside a JSON file is similar to a Python dictionary. It means that the JSON data is also a collection of name: value pairs just like a Python dictionary.

In Python, we have a built-in module called json . Let’s import the json module in our Python program to work with the JSON data.

Prerequisites to convert JSON to a dictionary

  • Import the Python json module.
  • Provide the full path of the JSON file if it is not present in the same directory
  • All the JSON data (string) should be enclosed in double quotes to avoid the JSONDecodeError.

Create a sample JSON file

Let’s create a sample JSON file that will contain some JSON strings. We will be using this JSON file in our Python program to demonstrate the working of json module to handle the JSON data in Python.

Convert JSON to a dictionary

We have created a sample JSON file containing JSON data (string). Now, let’s convert this JSON data into a Python object .We will follow the steps given below to convert JSON to a dictionary in Python

  • Import the json module in the program.
  • Open the sample JSON file which we created above.
  • Convert the file data into dictionary using json.load() function.
  • Check the type of the value returned by the json.load() function.
  • Print the key: value pairs inside the Python dictionary using a for loop.
  • Close the opened sample JSON file so that it doesn’t get tampered.

Let’s implement all these steps through Python code.

In this tutorial, we have learned how to read a JSON file and then convert it into a Python dictionary using json.load() function . Hope this topic is clear to you and you are ready to perform these operations on your own. Thanks for reading this article and stay tuned with us for more amazing content on Python programming.

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Convert JSON to Dictionary in Python

  • Post author: Gottumukkala Sravan Kumar
  • Post category: Python / Python Tutorial
  • Post last modified: January 11, 2024
  • Reading time: 18 mins read

Let’s discuss how to convert the JSON string object to a Dictionary in python. From JSON string, we can convert it to a dictionary using the json.loads() method. Suppose you have a JSON file, then loads() will not work. In this scenario, we can use json.load() method (load without s at the end).

JSON stands for Javascript object notation which is mostly used to serialize structured data and exchange it over web applications. Python has a built-in package called  json  to work with JSON file or strings. The data in the JSON is made up of the form of key/value pairs and they can be enclosed with  {} . Look wise it is similar to a Python dictionary . But JSON keys must be string-type objects with a double-quoted and values can be any datatype such as string, integer, nested JSON, a list, a tuple, or even another dictionary. 

Please enable JavaScript

1. Quick Examples of Converting JSON to a Dictionary

If you are in a hurry, below are some quick examples of converting JSON to a Dictionary (dict).

2. Use json.loads() to Convert JSON String to Dictionary

To convert JSON string to a Python dictionary object you can use the json.loads() , this method parses the JSON string and converts it into the dictionary. This method is available in the json module, so you need to import it to use this module.

This method accepts the json string as a parameter and converts this json string into a dictionary object, the string has to be in dictionary format otherwise you may get an error.

2.1 Syntax of json.loads()

Following is the syntax of json.loads() method.

Here, input_json is the string object that holds the JSON.

2.2 Convert JSON String to Dictionary Examples

Let’s have a JSON string that holds country details and convert this into a dictionary. First, import the json module as we will be using the loads() function.

Yields below output.

python convert json dictionary

For confirmation, we used the type() function to check whether the json is converted to a dictionary or not. Here, we can see that country_json is converted to the dictionary.

2.3 Convert Nested JSON to Dictionary

In the previous example, the string is similar to the dictionary but in this example, we will consider the json as nested and convert this into a nested dictionary.

Here, ‘ States ‘ holds again a dictionary as value.

3. Using json.load()

The above examples cover when you have a JSON string, but, If you are having a JSON file that you need to convert into a Python dictionary, you can use the json.load() method. It will parse the json string and convert it into the dictionary.

This method accepts JSON objects as a parameter. This JSON object is like a file pointer that will come from the json file. Let’s first see the syntax and them some examples of using this method.

3.1 Syntax of json.load()

Following is the syntax of json.load() method.

3.2 Examples

Example 1: Let’s have a JSON string that holds country details and convert this into a dictionary. By using open() method, we will get the data present in the JSON file.

Example 2: It can also be possible to return a particular value based on the key after converting JSON to the dictionary. Let’s return the ‘Country Name’, ‘States’, and ‘Lakes_Available’ separately.

Example 3: Load ‘country2.json’ and convert it into a dictionary and use the keys to return associated values.

4. Difference between json.load() and json.loads()

Let’s see the difference between json.load() and json.loads().

Frequently Asked Questions on Convert JSON to Dictionary in Python

JSON (JavaScript Object Notation) is a lightweight data interchange format that is easy for humans to read and write, and easy for machines to parse and generate. It is commonly used to transmit data between a server and a web application, as well as to store and exchange data.

You can convert a JSON string to a Python dictionary in Python using the json module. The json.loads() function is specifically designed for this purpose. For example, json_string is the JSON data in string format. The json.loads() function parses the JSON string and converts it into a Python dictionary ( python_dict ).

JSON is often used to represent structured data, and converting it to a dictionary in Python allows you to work with the data in a more convenient and flexible way. Python dictionaries are a native data type that can be easily manipulated, searched, and modified.

If the JSON string is not well-formed, i.e., it contains syntax errors, attempting to load it using json.loads() will raise a json.JSONDecodeError . It’s important to handle such exceptions appropriately in your code.

You can use the json.loads() function from the json module in Python. This function parses a JSON string and returns a Python object, typically a dictionary.

You can convert a Python dictionary back to a JSON string using the json.dumps() function in Python. For example, python_dict is a Python dictionary, and json.dumps() serializes it into a JSON-formatted string ( json_string ). The resulting JSON string can be used for various purposes, such as storing data in a file or sending it over a network.

In this article, you have learned how to convert JSON string to a dictionary and JSON file to a dictionary object using json.loads() and json.load() method respectively. We utilized the type() function to check whether the JSON is converted to a dictionary or not. Finally, we discussed the differences between json.load() and json.loads() .

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Python JSON

JSON ( J ava S cript O bject N otation) 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:

It's also common to store a JSON object in a file.

Import json Module

To work with JSON (string, or file containing JSON object), you can use Python's json module. You need to import the module before you can use it.

Parse JSON in Python

The json module makes it easy to parse JSON strings and files containing JSON object.

Example 1: Python JSON to dict

You can parse a JSON string using json.loads() method. The method returns a dictionary.

Here, person is a JSON string, and person_dict is a dictionary.

Example 2: Python read JSON file

You can use json.load() method to read a file containing JSON object.

Suppose, you have a file named person.json which contains a JSON object.

Here's how you can parse this file:

Here, we have used the open() function to read the json file. Then, the file is parsed using json.load() method which gives us a dictionary named data .

If you do not know how to read and write files in Python, we recommend you to check Python File I/O .

Python Convert to JSON string

You can convert a dictionary to JSON string using json.dumps() method.

Example 3: Convert dict to JSON

Here's a table showing Python objects and their equivalent conversion to JSON.

Writing JSON to a file

To write JSON to a file in Python, we can use json.dump() method.

Example 4: Writing JSON to a file

In the above program, we have opened a file named person.txt in writing mode using 'w' . If the file doesn't already exist, it will be created. Then, json.dump() transforms person_dict to a JSON string which will be saved in the person.txt file.

When you run the program, the person.txt file will be created. The file has following text inside it.

Python pretty print JSON

To analyze and debug JSON data, we may need to print it in a more readable format. This can be done by passing additional parameters indent and sort_keys to json.dumps() and json.dump() method.

Example 5: Python pretty print JSON

When you run the program, the output will be:

In the above program, we have used 4 spaces for indentation. And, the keys are sorted in ascending order.

By the way, the default value of indent is None . And, the default value of sort_keys is False .

Recommended Readings:

  • Python JSON to CSV and vice-versa
  • Python XML to JSON and vice-versa
  • Python simplejson

Table of Contents

  • What is JSON?
  • Using json Module
  • Example: JSON string to dict
  • Example: Python read JSON file
  • dict to JSON string (with Example)
  • Writing JSON to a file (with Example)
  • Pretty print JSON (with Example)

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JSON is a syntax for storing and exchanging data.

JSON is text, written with JavaScript object notation.

JSON in Python

Python has a built-in package called json , which can be used to work with JSON data.

Import the json module:

Parse JSON - Convert from JSON to Python

If you have a JSON string, you can parse it by using the json.loads() method.

The result will be a Python dictionary .

Convert from JSON to Python:

Convert from Python to JSON

If you have a Python object, you can convert it into a JSON string by using the json.dumps() method.

Convert from Python to JSON:

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You can convert Python objects of the following types, into JSON strings:

Convert Python objects into JSON strings, and print the values:

When you convert from Python to JSON, Python objects are converted into the JSON (JavaScript) equivalent:

Convert a Python object containing all the legal data types:

Format the Result

The example above prints a JSON string, but it is not very easy to read, with no indentations and line breaks.

The json.dumps() method has parameters to make it easier to read the result:

Use the indent parameter to define the numbers of indents:

You can also define the separators, default value is (", ", ": "), which means using a comma and a space to separate each object, and a colon and a space to separate keys from values:

Use the separators parameter to change the default separator:

Order the Result

The json.dumps() method has parameters to order the keys in the result:

Use the sort_keys parameter to specify if the result should be sorted or not:

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Python: Write a list of dictionaries to a JSON file

JSON (JavaScript Object Notation) is a lightweight data interchange format that is easy for humans to read and write, and easy for machines to parse and generate. It is based on a subset of the JavaScript language and is commonly used for transmitting data in web applications.

Lists and dictionaries are two of the most commonly used data structures in Python. A list of dictionaries is a common way to represent a collection of records or objects, where each record is a dictionary with a common set of keys.

In this tutorial, you’ll learn how to write a list of dictionaries to a JSON file in Python, enhancing data persistence and exchange in your applications.

Writing to JSON

To write a list of dictionaries to a JSON file in Python, you can use the built-in json module, which provides a simple API for encoding and decoding JSON data.

Example 1: Basic JSON Writing

Here, we define a simple list of dictionaries and write it to a file named data.json . We use the json.dump function, which takes two arguments: the data to be encoded and the file object to write to.

Example 2: Pretty Printing

To make the JSON output more readable, you can use the indent argument to add indentation to the output.

Setting indent to 4 means each level in the JSON will be indented by 4 spaces. Note that this increases file size but makes it easier to read for humans.

Example 3: Working with File Path

When working with file paths, it’s crucial to ensure the path is correct and the correct permissions are in place. The pathlib module can make file handling more intuitive.

This code uses Path to define the file path, offering more flexibility for file manipulation and being compatible with various operating systems.

Handling Exceptions

Error handling with Try-Except blocks can ensure your program doesn’t crash unexpectedly during the file writing process.

By using a Try-Except block, the code catches any IOError that may be raised if the file cannot be opened or written to. This allows the program to handle the error gracefully.

Working with Different Encodings

If you’re dealing with non-standard text encodings, the json module also provides options to accommodate that.

Here we specify 'utf-8' as the encoding and set ensure_ascii to False to allow non-ASCII characters to be written to the file. This is especially important if your data contains special characters, such as accents or symbols from non-English languages.

We’ve explored multiple ways to write a list of dictionaries to a JSON file in Python, from simple dumps to pretty-printed and correctly encoded outputs. Exception handling and working with file paths were also discussed to ensure robust and adaptable coding practices. Whether you’re storing application data or processing data for exchange between services, these techniques establish a strong foundation for working with JSON in Python.

Next Article: Python: How to Convert a List to JSON (2 Approaches)

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5 Best Ways to Convert Python Dict to JSON Format

💡 Problem Formulation: Converting a Python dictionary to JSON format is a common task when working with web data. For instance, if you have a Python dictionary {'name': 'John', 'age': 30, 'city': 'New York'} and you need to send this data to a web server, you would need to convert it to JSON format, which would look like: {"name": "John", "age": 30, "city": "New York"} . This article will explore different methods to perform this conversion effectively.

Method 1: Using the json.dumps() Function

One of the simplest ways to convert a Python dictionary to a JSON string is by using the json.dumps() function from Python’s built-in json module. This function takes the dictionary as an argument and returns a JSON-formatted string.

Here’s an example:

The output of this code snippet:

This code snippet is straightforward: It imports the json module and uses the dumps() function to convert the dictionary into a JSON-formatted string, which is then printed out.

Method 2: Writing to a JSON File Using json.dump()

If you want to write the Python dictionary to a file in JSON format, you can use the json.dump() function. The function writes the dictionary to a file specified by the user, handling all the necessary file operations itself.

The data.json file now contains the JSON:

Here, the json.dump() function is used within a with statement to ensure the file is automatically closed after the operation. The dictionary is written to a new file ‘data.json’ in JSON format.

Method 3: Pretty Printing JSON

For better readability, the json.dumps() function also offers parameters to format the JSON so that it’s more human-readable. Parameters like indent and sort_keys can make the output neat and sorted.

This code snippet converts the dictionary into a well-formatted JSON string with sorted keys and an indentation of 4 spaces, making it much easier to read.

Method 4: Converting Custom Objects to JSON

Sometimes, you may need to convert custom objects to JSON, in which case you’ll use the default parameter in the json.dumps() function to specify a method that tells json how to handle these objects.

The user_converter function checks if the object is an instance of User and returns an appropriate serializable dictionary. If the object can’t be handled, it raises a TypeError .

Bonus One-Liner Method 5: Using Generator Expressions and dict()

For simple flattening and transformation of dictionary data without using the json module, a combination of a dictionary constructor with a generator expression is an elegant one-liner. This is more about transforming data structures than JSON conversion per se.

This one-liner recreates a dictionary from the original and explicitly converts it to a string, mimicking a JSON representation. It’s not true JSON conversion, but it might suffice for simple non-nested dictionaries.

Summary/Discussion

  • Method 1: json.dumps() . Strengths: Easy to use and versatile. Weaknesses: Outputs a string, not directly a file.
  • Method 2: json.dump() . Strengths: Writes JSON directly to a file. Weaknesses: Requires file-handling code.
  • Method 3: Pretty Printing. Strengths: Produces more readable JSON. Weaknesses: Slightly more complex code.
  • Method 4: Converting Custom Objects. Strengths: Handles complex data structures. Weaknesses: Requires extra code for a custom handler.
  • Method 5: Generator Expression. Strengths: Quick and dirty one-liner for simple cases. Weaknesses: Not true JSON serialization; limited to simple data structures.

Emily Rosemary Collins is a tech enthusiast with a strong background in computer science, always staying up-to-date with the latest trends and innovations. Apart from her love for technology, Emily enjoys exploring the great outdoors, participating in local community events, and dedicating her free time to painting and photography. Her interests and passion for personal growth make her an engaging conversationalist and a reliable source of knowledge in the ever-evolving world of technology.

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How To Convert Python Dictionary To JSON?

JSON stands for JavaScript Object Notation. It means that a script (executable) file made of text in a programming language, is used to store and transfer the data. Python supports JSON through a built-in package called JSON. To use this feature, we import the JSON package in Python script. The text in JSON is done through quoted-string which contains a value in key-value mapping within {} . It is similar to the dictionary in Python .

Note: For more information, refer to Read, Write, and Parse JSON using Python

Methods used to Convert Python to JSON and Writing JSON 

  • Using dump() function
  • Using dumps() function

Difference Between Dictionary and JSON

Convert dictionary python to json file using json.dump().

In this program, we are going to convert the Python dictionary to a JSON object and then stored it in a file. Firstly we import the JSON module and then define a dictionary that stored student details. Now, we are going to use json.dump() method to convert and write the JSON object to a file along with open() method of file handling in Python. We open the sample.json file in writing mode and after that, we write the file using json.dump() method of JSON module in Python.

python assign json to dict

Convert Python to JSON object Using dumps() function

In the below code, we are going to convert a Python dictionary to a JSON object using json.dumps() method of JSON module in Python. Firstly, we import the JSON module and then define a dictionary that stores employee details. After that, we convert the ’employee_details’ dictionary to JSON object using json.dumps() method and stored into the variable ‘json_object’.

Converting Nested Dictionary to JSON in Python

In the below code, we will convert the nested dictionary to JSON in Python. Firstly, we import JSON module and then create a nested dictionary. After that we convert the nested dictionary to JSON using json.dumps() method by passing dictionary ‘person’ and ‘indent=4’ as argument in it. Finally, we print the converted JSON.

Convert Dictionary to JSON Quotes

The below code will convert a Python dictionary to a JSON string with double quotes around the keys and values, we can achieve this using the json.dumps() function with the ensure_ascii parameter set to ‘ False’.

Convert Dictionary to JSON Array in Python

In the below code, we will convert the Python dictionary to JSON array. First, we create a sample dictionary ‘data’ and then create a list of dictionary using list comprehension to iterate over the keys of the dictionary and store it in a variable ‘array’. After that convert the array to JSON array using json.dumps() function and then print the JSON array.

Convert Dictionary to JSON using sort_keys in Python

In the below code, we will convert the Python dictionary using while sorting the keys. To convert a Python dictionary to a JSON string with sorted keys we have to specify the ‘ sort_keys’ parameter as ‘True’ in json.dumps() function. We can see in the output that data is sorted based on keys.

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Lampiran Kamus Python: Cara Menambahkan Pasangan Kunci/Nilai

Steve Campbell

Kunci dalam kamus bersifat unik dan dapat berupa string, integer, tuple, dll. Nilai dapat berupa daftar atau daftar di dalam daftar, angka, string, dll.

Berikut ini contoh kamus:

Pembatasan Kamus Utama

Berikut daftar batasan kunci dalam kamus:

  • Jika ada kunci duplikat yang didefinisikan dalam kamus, yang terakhir akan dipertimbangkan. Misalnya pertimbangkan kamus my_dict = {“Name”:”ABC”,”Address”:”Mumbai”,”Age”:30, “Name”: “XYZ”};. Ini memiliki kunci "Nama" yang didefinisikan dua kali dengan nilai sebagai ABC dan XYZ. Preferensi akan diberikan kepada yang terakhir ditentukan, yaitu, “Nama”: “XYZ.”
  • Tipe data untuk kunci Anda bisa berupa angka, string, float, boolean, tupel, objek bawaan seperti kelas dan fungsi. Misalnya my_dict = {bin:”001″, hex:”6″ ,10:”ten”, bool:”1″, float:”12.8″, int:1, False:'0′};Satu-satunya hal yang tidak diperbolehkan adalah, Anda tidak dapat menentukan kunci dalam tanda kurung siku misalnya my_dict = {[“Name”]:”ABC”,”Address”:”Mumbai”,”Age”:30};

Bagaimana cara menambahkan elemen ke kunci dalam kamus dengan Python?

Kita dapat menggunakan fungsi bawaan append() untuk menambahkan elemen ke kunci dalam kamus. Untuk menambahkan elemen menggunakan append() ke kamus, pertama-tama kita harus menemukan kunci yang perlu kita tambahkan.

Anggaplah Anda memiliki kamus sebagai berikut:

Kunci dalam kamus adalah Nama, Alamat dan Umur. Dengan menggunakan metodeappend() kita dapat memperbarui nilai kunci dalam kamus.

Saat kami mencetak kamus setelah memperbarui nilainya, outputnya adalah sebagai berikut:

Mengakses elemen kamus

Data di dalam kamus tersedia dalam pasangan kunci/nilai. Untuk mengakses elemen dari kamus, Anda perlu menggunakan tanda kurung siku (['kunci']) dengan kunci di dalamnya.

Berikut adalah contoh yang menunjukkan akses elemen dari kamus dengan menggunakan kunci dalam tanda kurung siku.

Jika Anda mencoba menggunakan kunci yang tidak ada di kamus, maka akan muncul kesalahan seperti yang ditunjukkan di bawah ini:

Menghapus elemen dalam kamus

Untuk menghapus elemen dari kamus, Anda harus menggunakan itu kata kunci.

Sintaksnya adalah:

Untuk menghapus seluruh kamus, Anda dapat menggunakan kata kunci del lagi seperti yang ditunjukkan di bawah ini:

Untuk sekadar mengosongkan kamus atau menghapus konten di dalam kamus, Anda dapat menggunakan metode clear() pada kamus Anda seperti yang ditunjukkan di bawah ini:

Berikut adalah contoh kerja yang menunjukkan penghapusan elemen, untuk menghapus konten dict dan menghapus seluruh kamus.

Menghapus Elemen dari kamus menggunakan metode pop()

Selain kata kunci del, Anda juga dapat menggunakan metode dict.pop() untuk menghapus elemen dari kamus. Pop() adalah metode bawaan yang tersedia dengan kamus yang membantu menghapus elemen berdasarkan kunci yang diberikan.

Metode pop() mengembalikan elemen yang dihapus untuk kunci yang diberikan, dan jika kunci yang diberikan tidak ada, maka akan mengembalikan nilai default. Jika nilai default tidak diberikan dan kunci tidak ada dalam kamus, maka akan terjadi kesalahan.

Berikut adalah contoh kerja yang menunjukkan penggunaan dict.pop() untuk menghapus sebuah elemen.

Menambahkan elemen ke kamus

Untuk menambahkan elemen ke kamus yang sudah ada, Anda harus menggunakan nama kamus diikuti tanda kurung siku dengan nama kunci dan memberikan nilai padanya.

Berikut adalah contoh yang sama:

Memperbarui elemen yang ada dalam kamus

Untuk memperbarui elemen yang ada di dalam kamus, Anda memerlukan referensi ke kunci yang ingin Anda perbarui nilainya.

Jadi kita memiliki kamus my_dict = {“nama pengguna”: “XYZ”, “email”: “[email protected]”, “lokasi”:”Mumbai”}.

Kami ingin memperbarui nama pengguna dari XYZ ke ABC. Berikut adalah contoh yang menunjukkan bagaimana Anda dapat memperbaruinya.

Masukkan kamus ke kamus lain

Anggaplah Anda memiliki dua kamus seperti yang ditunjukkan di bawah ini:

Sekarang saya ingin kamus my_dict1 dimasukkan ke dalam kamus my_dict. Untuk melakukan itu mari buat kunci bernama "nama" di my_dict dan tetapkan kamus my_dict1 ke dalamnya.

Berikut adalah contoh kerja yang menunjukkan memasukkan kamus my_dict1 ke my_dict.

Sekarang jika Anda melihat kunci “nama”, itu memiliki kamus my_dict1.

  • Kamus adalah salah satu tipe data penting yang tersedia di Python. Data dalam kamus disimpan sebagai pasangan kunci/nilai. Kunci/nilai dipisahkan dengan titik dua(:), dan pasangan kunci/nilai dipisahkan dengan koma(,). Kunci dalam kamus bersifat unik dan dapat berupa string, integer, tuple, dll. Nilai dapat berupa daftar atau daftar di dalam daftar, angka, string, dll. Saat bekerja dengan daftar, Anda mungkin ingin mengurutkannya. Dalam hal ini, Anda dapat mempelajari lebih lanjut Penyortiran daftar Python dalam artikel informatif ini.

Metode bawaan yang penting pada kamus:

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COMMENTS

  1. Convert JSON to dictionary in Python

    In the below code, firstly we open the "data.json" file using file handling in Python and then convert the file to Python object using the json.load () method we have also print the type of data after conversion and print the dictionary. Python3 import json with open('data.json') as json_file: data = json.load (json_file) print("Type:", type(data))

  2. Python JSON to Dictionary

    1. Convert JSON Object to Python Dictionary In this example, we will take a JSON string that contains a JSON object. We will use loads () function to load the JSON string into a Python Dictionary, and access the name:value pairs. Python Program import json jsonString = '{"a":54, "b": 28}'

  3. Convert JSON string to dict using Python

    4 Answers Sorted by: 849 json.loads () import json d = json.loads (j) print d ['glossary'] ['title'] Share Improve this answer Follow edited Jul 24, 2018 at 8:28 David Leon 1,017 8 25 answered Dec 24, 2010 at 19:51

  4. Convert JSON to a Python Dictionary • datagy

    # Loading a JSON File to a Python Dictionary import json with open ( '/Users/nikpi/Desktop/iss-now.json', 'r') as file: data = json.load (file) print (data) # Returns: # {'message': 'success', 'iss_position': {'latitude': '41.8157', 'longitude': '-138.3051'}, 'timestamp': 1652700632} Let's break down what we did in the code above:

  5. Python JSON to Dict: Converting JSON Data into Python Dictionaries

    Here's what this looks like in action: import json # JSON data as a string json_data = ' {"name": "John", "age": 30, "city": "New York"}' # Convert to Python dictionary parsed_data = json.loads (json_data) print (parsed_data) # Output: {'name': 'John', 'age': 30, 'city': 'New York'} Consider the key characteristics of each: JSON:

  6. Load JSON into a Python Dictionary

    While writing software in python, we might need to convert a JSON string or file into a python object. This article discusses how to load JSON into a python dictionary. Table of Contents What is JSON Format? Convert JSON String to Python Dictionary Convert JSON File to Python Dictionary Convert JSON to User-defined Python Objects Conclusion

  7. How to convert JSON to a dictionary in Python?

    Import the json module in the program. Open the sample JSON file which we created above. Convert the file data into dictionary using json.load () function. Check the type of the value returned by the json.load () function. Print the key: value pairs inside the Python dictionary using a for loop. Close the opened sample JSON file so that it ...

  8. Working With JSON Data in Python

    Working With JSON Data in Python by Lucas Lofaro 47 Comments intermediate python Mark as Completed Share Share Table of Contents A (Very) Brief History of JSON Look, it's JSON! Python Supports JSON Natively! A Little Vocabulary Serializing JSON A Simple Serialization Example Some Useful Keyword Arguments Deserializing JSON

  9. Convert JSON to Dictionary in Python

    For confirmation, we used the type() function to check whether the json is converted to a dictionary or not. Here, we can see that country_json is converted to the dictionary.. 2.3 Convert Nested JSON to Dictionary. In the previous example, the string is similar to the dictionary but in this example, we will consider the json as nested and convert this into a nested dictionary.

  10. Python Dictionary and JSON

    The json.load() is used to read the JSON data from a file and The json.loads() is used to convert the JSON String into the Python dictionary. Lets read the file we saved in 2 into a variable data ...

  11. Python JSON: Read, Write, Parse JSON (With Examples)

    In this tutorial, you will learn to parse, read and write JSON in Python with the help of examples. Also, you will learn to convert JSON to dict and pretty print it. Courses Tutorials Examples . ... Example 1: Python JSON to dict. You can parse a JSON string using json.loads() method. The method returns a dictionary.

  12. Python JSON

    Try it Yourself » Convert from Python to JSON If you have a Python object, you can convert it into a JSON string by using the json.dumps () method. Example Convert from Python to JSON: import json # a Python object (dict): x = { "name": "John", "age": 30, "city": "New York" } # convert into JSON: y = json.dumps (x) # the result is a JSON string:

  13. Python JSON load() and loads() for JSON Parsing

    The json.load () is used to read the JSON document from file and The json.loads () is used to convert the JSON String document into the Python dictionary. fp file pointer used to read a text file, binary file or a JSON file that contains a JSON document. object_hook is the optional function that will be called with the result of any object ...

  14. How to read a json file and return as dictionary in Python

    1 Answer Sorted by: 41 Use the json module to decode it. import json def js_r (filename: str): with open (filename) as f_in: return json.load (f_in) if __name__ == "__main__": my_data = js_r ('num.json') print (my_data) Share Improve this answer Follow edited Nov 29, 2020 at 17:55 GeneralCode 874 1 12 29 answered Jan 5, 2017 at 3:08 tdelaney

  15. Python: Write a list of dictionaries to a JSON file

    To write a list of dictionaries to a JSON file in Python, you can use the built-in json module, which provides a simple API for encoding and decoding JSON data. Example 1: Basic JSON Writing

  16. 5 Best Ways to Convert Python Dict to JSON Format

    Method 1: Using the json.dumps () Function. One of the simplest ways to convert a Python dictionary to a JSON string is by using the json.dumps () function from Python's built-in json module. This function takes the dictionary as an argument and returns a JSON-formatted string. Here's an example:

  17. How To Convert Python Dictionary To JSON?

    Python supports JSON through a built-in package called JSON. To use this feature, we import the JSON package in Python script. The text in JSON is done through quoted-string which contains a value in key-value mapping within {}. It is similar to the dictionary in Python. Note: For more information, refer to Read, Write, and Parse JSON using Python

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    Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based. Although the Faust library aims to bring Kafka Streaming ideas into the Python ecosystem, it may pose challenges in terms of ease of use. This document serves as a tutorial and offers best practices ...

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    I am generating a large json file using python. I have many keys and values. I see two ways of populating my python dictionary. Explicitly: my_dict = {} my_dict['key1'] = "value1" my_dict...

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    I am generating a large json file using python. I have many keys and values. I see two ways of populating my python dictionary. Explicitly: my_dict = {} my_dict['key1'] = "value1" my_dict...

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    Dictionary is one of the important data types available in Python. The data in a dictionary is stored as a key/value pair. It is separated by a colon(:), and the key/value pair is separated by comma(,). The keys in a dictionary are unique and can be a string, integer, tuple, etc. The values can be a list or list within a list, numbers, string, etc.

  22. Python Requests: Handling JSON response, storing to list or dict

    r=requests.get (url + id, headers=h, params=p) inbound_dict = {} inbound=json.loads (r.text) for item in inbound ['messages']: inbound_dict [item ['conversationId']] = item ['body'] print (inbound_dict)

  23. python

    6 Answers Sorted by: 802 json.dumps () converts a dictionary to str object, not a json (dict) object! So you have to load your str into a dict to use it by using json.loads () method See json.dumps () as a save method and json.loads () as a retrieve method. This is the code sample which might help you understand it more: import json

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    with open (join (dirname (__file__),'text.json')) as tone_json: python_obj = json.load (tone_json) #read file object into string my_list = python_obj ["data"] #assign list name to string for dictionary in my_list: #loop through dictionaries in list for key,value in dictionary.items (): #loop through key pairs in dictionaries if key == "text...

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    I have created a custom operator which takes some parameters and ultimately triggers a glue job. Here's how it looks -. task = MyCustomOperator ( task_id="my_op", custom_property=False, r_params = { "run_date": " { { ds }}" } ) Inside the custom operator we use json.dumps on r_params and pass it to glue operator, which only accepts strings. The ...