# Bubbleio Python API
## Project overview
This python package is a toolset to query Bubble.io API. This package uses [Pandas](https://pandas.pydata.org/)
DataFrame to returns results.
Pandas.DataFrame lets you query the data, process it, save it (ant later on uptate changes directly to Bubble app with
this package).
**⚠ Warning**: This project is quite new (october 2021), and breaking changes may appears until version 1.0
## Installation
```
python -m pip install -U pip
python -m pip install bubbleio
```
## Package documentation
https://vlebert.github.io/bubbleio/
## Bubble.io API documentation
https://manual.bubble.io/core-resources/api/data-api
## Roadmap
* [GET](https://manual.bubble.io/core-resources/api/data-api#getting-a-list-of-things-and-search) function : **80%**
* TODO: Sorting options
* TODO: [PATCH](https://manual.bubble.io/core-resources/api/data-api#modify-a-thing-by-id) function : **0%**
* TODO: Bulk [PATCH](https://manual.bubble.io/core-resources/api/data-api#modify-a-thing-by-id)
* ...
## Example of usage :
```python
>>> from bubbleio import Bubbleio
>>> API_KEY = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
>>> API_ROOT = "https://appname.bubbleapps.io/api/1.1/obj"
>>> bbio = Bubbleio(API_KEY, API_ROOT)
>>> bbio.get("fooType")
{
"cursor": 0,
"results": [
{
"foo_field_1": "value1",
"foo_field_2": "value2",
"_id": "item1_bubble_id"
},
{
"foo_field_1": "value3",
"foo_field_2": "value4",
"_id": "item2_bubble_id"
},
...
],
"remaining": 0,
"count": 31
}
>>> bbio.get("fooType", constraints=[
... {"key": "foo_field_1", "value": "value1", "constraint_type":"equals"}
... ])
{
"cursor": 0,
"results": [
{
"foo_field_1": "value1",
"foo_field_2": "value2",
"_id": "item1_bubble_id"
}
],
"remaining": 0,
"count": 1
}
```
```python
>>> from bubbleio import Bubbleio
>>> bbio = Bubbleio(API_KEY, API_ROOT)
>>> joins_ = [
... {
... "field": "fooBar",
... "typename": "barType",
... }
... ]
>>> bbio.get_results("fooType")
_id fooField1 fooField2 fooBar
idFoo1 value value idBar1
idFoo2 value value idBar2
>>> bbio.get_results("barType")
_id barField1 barField2
idBar1 value value
idBar2 value value
>>> bbio.get_all_results_as_df("fooType", joins=joins_)
_id fooField1 fooField2 fooBar fooBar__id fooBar_barField1 fooBar_barField2
idFoo1 value value idBar1 idBar1 value value
idFoo2 value value idBar2 idBar2 value value
```
