| Name | jsify JSON |
| Version |
0.9.6
JSON |
| download |
| home_page | https://github.com/citsystems/jsify |
| Summary | Jsify is a Python library designed to bridge the gap between Python's data structures and JSON-like objects, offering seamless integration and manipulation of data in a JavaScript-like manner.With Jsify, you can effortlessly convert Python dictionaries, lists, and tuples into JSON-like objects that support attribute-style access (dot notation), automatic handling of undefined properties, and easy serialization. |
| upload_time | 2024-08-08 12:27:45 |
| maintainer | None |
| docs_url | None |
| author | Zbigniew Rajewski |
| requires_python | >=3.0 |
| license | None |
| keywords |
json
javascript
objects
jsify
dot
notation
attributes
serialization
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Jsify Library
Jsify is a Python library designed to bridge the gap between Python's data structures and JSON-like objects, offering seamless integration and manipulation of data in a JavaScript-like manner. With Jsify, you can effortlessly convert Python dictionaries, lists, and tuples into JSON-like objects that support attribute-style access, automatic handling of undefined properties, and easy serialization.
## Features
- **Jsified Objects**: Convert Python dictionaries, lists, and tuples into `Object`, `Dict`, `List`, and `Tuple` objects that allow attribute-style access.
- **Custom JSON Serialization**: Seamlessly serialize jsified objects to JSON format, with options to handle undefined values.
- **Flexible Data Manipulation**: Access and manipulate data using JavaScript-like syntax in Python.
- **Assertion Utilities**: Validate the structure and contents of JSON-like objects using built-in assertions.
- **Custom Function Decorators**: Automatically convert function arguments to jsified objects and handle results with custom decorators.
## Installation
Install Jsify using pip:
```bash
pip install jsify
```
## Getting Started
Here’s a quick overview of how to use Jsify with some simple examples.
### 1. Creating Jsified Objects
You can easily convert Python data structures into jsified objects using the `jsify` function:
```python
from jsify import jsify
data = {
'name': 'Alice',
'details': {
'age': 30,
'city': 'Wonderland'
}
}
# Convert to a jsified object
json_obj = jsify(data)
# Accessing properties using attribute-style access
print(json_obj.name) # Outputs: Alice
print(json_obj.details.age) # Outputs: 30
```
### 2. Handling Undefined Properties
Jsify allows you to safely access properties that may not exist, returning an `Undefined` object instead of raising an error:
```python
from jsify import Undefined
# Accessing a non-existent property
print(json_obj.details.country) # Outputs: Undefined
# Checking if a property is undefined
if json_obj.details.country is Undefined:
print("Country is not defined.")
```
### 3. Custom JSON Serialization
Jsify provides custom JSON serialization that handles jsified objects and offers the ability to omit undefined values:
```python
import json
from jsify import jsify
data = {
'name': 'Alice',
'details': {
'age': 30,
'nickname': Undefined
}
}
json_obj = jsify(data)
# Serialize with omitting Undefined fields
json_string = json.dumps(json_obj, omit_undefined=True)
print(json_string) # Outputs: {"name": "Alice", "details": {"age": 30}}
# Serialize without omitting Undefined fields
json_string = json.dumps(json_obj, omit_undefined=False)
print(json_string) # Outputs: {"name": "Alice", "details": {"age": 30, "nickname": null}}
```
### 4. Using Assertions to Validate Data
Jsify includes an `assertions` module to help you validate the structure and contents of JSON-like objects:
```python
from jsify import jsify, Assert
data = {
'name': 'Alice',
'details': {
'age': 30,
'city': 'Wonderland'
}
}
json_obj = jsify(data)
# Assert that a key exists
assert_key_present = Assert.IsIn()
assert_key_present.assertion(json_obj, 'name', 'root') # No error
# Assert that a key does not exist
assert_key_absent = Assert.NotIn()
assert_key_absent.assertion(json_obj, 'nonexistent', 'root') # No error
```
### 5. Creating Jsified Functions
You can create functions that automatically handle jsified objects using decorators:
```python
from jsify import jsified_function
@jsified_function(result_original=True)
def process_data(data):
# Accessing properties with attribute-style access
return data.details.age + 10
data = {
'details': {
'age': 30
}
}
# Call the decorated function
result = process_data(data)
print(result) # Outputs: 40
```
## Documentation
For detailed documentation and more advanced usage, please refer to the [official documentation](https://citsystems.github.io/jsify/).
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Conclusion
Jsify simplifies the process of working with JSON-like data in Python by providing a set of tools that emulate JavaScript's flexibility while maintaining Pythonic design principles. Whether you're building APIs, working with configuration files, or manipulating complex data structures, Jsify offers a clean and intuitive approach.
Feel free to explore the library further and see how it can fit into your projects!
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