https://github.com/amancevice/flatsplode
Flatten/Explode JSON objects
https://github.com/amancevice/flatsplode
json python
Last synced: 10 days ago
JSON representation
Flatten/Explode JSON objects
- Host: GitHub
- URL: https://github.com/amancevice/flatsplode
- Owner: amancevice
- License: mit
- Created: 2018-11-13T21:01:03.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2024-06-18T16:29:58.000Z (11 months ago)
- Last Synced: 2025-04-22T22:18:55.041Z (10 days ago)
- Topics: json, python
- Language: Python
- Homepage:
- Size: 146 KB
- Stars: 19
- Watchers: 3
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Flatsplode
[](https://pypi.org/project/flatsplode/)
[](https://pypi.org/project/flatsplode/)
[](https://github.com/amancevice/flatsplode/actions/workflows/pytest.yml)
[](https://codeclimate.com/github/amancevice/flatsplode/test_coverage)
[](https://codeclimate.com/github/amancevice/flatsplode/maintainability)
Flatten/Explode JSON objects.
## Installation
```bash
pip install flatsplode
```
## Usage
Use the `flatsplode()` function to recursively flatten and explode complex JSON objects.
Import the `flatsplode` function:
```python
from flatsplode import flatsplode
```
Create a sample object to flatsplode:
```python
item = {
'id': '78e5b18c',
'keywords': [
'fizz',
'buzz'
],
'attrs': [
{'name': 'color', 'value': 'green'},
{'name': 'size', 'value': 42},
],
'deep': {
'nested': {
'keys': {
'fizz': 'buzz',
'jazz': 'fuzz',
}
}
}
}
```
Calling `flatsplode(item)` will return a generator. Use `list()` to expand:
```python
list(flatsplode(item))
[
{
'id': '78e5b18c',
'keywords': 'fizz',
'attrs.name': 'color',
'attrs.value': 'green',
'deep.nested.keys.fizz': 'buzz',
'deep.nested.keys.jazz': 'fuzz'
},
{
'id': '78e5b18c',
'keywords': 'fizz',
'attrs.name': 'size',
'attrs.value': 42,
'deep.nested.keys.fizz': 'buzz',
'deep.nested.keys.jazz': 'fuzz'
},
{
'id': '78e5b18c',
'keywords': 'buzz',
'attrs.name': 'color',
'attrs.value': 'green',
'deep.nested.keys.fizz': 'buzz',
'deep.nested.keys.jazz': 'fuzz'
},
{
'id': '78e5b18c',
'keywords': 'buzz',
'attrs.name': 'size',
'attrs.value': 42,
'deep.nested.keys.fizz': 'buzz',
'deep.nested.keys.jazz': 'fuzz'
}
]
```
You can also provide your own join-character:
```python
list(flatsplode(item, '/'))
[
{
'id': '78e5b18c',
'keywords': 'fizz',
'attrs/name': 'color',
'attrs/value': 'green',
'deep/nested/keys/fizz': 'buzz',
'deep/nested/keys/jazz': 'fuzz'
},
…
]
```
Flatsploding is useful when converting objects to pandas DataFrame matrices:
```python
import pandas
from flatsplode import flatsplode
pandas.DataFrame(flatsplode(item))
```
Pandas also has a built in normalizer that will flatten (but not explode) your data:
```python
from flatsplode import explode
pandas.json_normalize(explode(item))
```
Result:
```plaintext
id attrs.name attrs.value deep.nested.keys.fizz deep.nested.keys.jazz keywords
0 78e5b18c color green buzz fuzz fizz
1 78e5b18c size 42 buzz fuzz fizz
2 78e5b18c color green buzz fuzz buzz
3 78e5b18c size 42 buzz fuzz buzz
```