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https://github.com/amancevice/flatsplode

Flatten/Explode JSON objects
https://github.com/amancevice/flatsplode

json python

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Flatten/Explode JSON objects

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# Flatsplode

[![pypi](https://img.shields.io/pypi/v/flatsplode?color=yellow&logo=python&logoColor=eee&style=flat-square)](https://pypi.org/project/flatsplode/)
[![python](https://img.shields.io/pypi/pyversions/flatsplode?logo=python&logoColor=eee&style=flat-square)](https://pypi.org/project/flatsplode/)
[![pytest](https://img.shields.io/github/actions/workflow/status/amancevice/flatsplode/pytest.yml?logo=github&style=flat-square)](https://github.com/amancevice/flatsplode/actions/workflows/pytest.yml)
[![coverage](https://img.shields.io/codeclimate/coverage/amancevice/flatsplode?logo=code-climate&style=flat-square)](https://codeclimate.com/github/amancevice/flatsplode/test_coverage)
[![maintainability](https://img.shields.io/codeclimate/maintainability/amancevice/flatsplode?logo=code-climate&style=flat-square)](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
```