Loading JSON data in Python using function `json.load()`
The function in Python is a handy tool for reading and parsing JSON files, converting their content into a corresponding Python object such as a dictionary or a list. Here's a step-by-step guide on how to use this function with an example.
Using json.load() with an example
- First, you need to import the module.
- Next, open the JSON file in read mode ().
- The function will return a Python object representing the JSON data. In this case, it would be a dictionary.
Example Usage
Let's consider a JSON file named with the following content:
By using the function, we can read and convert this JSON file into a Python object:
```python import json
with open('data.json', 'r') as f: data = json.load(f) ```
Now, is a Python dictionary where the key maps to a list of employee dictionaries. You can then manipulate or access this Python object directly in your code.
```python
for emp in data['emp_details']: print(emp) ```
This will output:
Important Notes
- The file must be opened in text mode (), not binary.
- JSON keys are always strings; Python converts JSON objects to dictionaries.
- JSON arrays become Python lists.
- After reading the JSON file, the content can be accessed and manipulated using Python programming.
- The function accepts a file object opened in text mode ('r').
- JSON values can be strings, numbers, booleans, arrays, or other JSON objects.
In summary, the function in Python is a straightforward way to read JSON data from a file into a usable Python data structure. This function converts a JSON file into a Python object, which can be a dictionary or a list, depending on the structure of the JSON file.
In the example usage, the Python list is obtained, which demonstrated the conversion of JSON arrays into Python lists. If we wanted to use a to store our employee data instead, we could implement a Trie data structure, utilizing technology to optimize search and insert operations.
Moreover, since the 'emp_details' key maps to a list of employee dictionaries in the Python data structure, employing arrays for this purpose might also be viable, depending on the specific requirements of your program.
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