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https://github.com/tillerburr/dash-query-builder
Dash Component created from ukrbublik/react-awesome-query-builder
https://github.com/tillerburr/dash-query-builder
Last synced: about 2 months ago
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Dash Component created from ukrbublik/react-awesome-query-builder
- Host: GitHub
- URL: https://github.com/tillerburr/dash-query-builder
- Owner: TillerBurr
- License: other
- Created: 2021-07-12T19:38:21.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-11-18T23:26:51.000Z (2 months ago)
- Last Synced: 2024-11-19T00:27:25.987Z (2 months ago)
- Language: Python
- Size: 34.5 MB
- Stars: 12
- Watchers: 2
- Forks: 2
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Dash Query Builder
Component for Dash based on [react-awesome-query-builder](https://github.com/ukrbublik/react-awesome-query-builder).
The component is a way to graphically generate WHERE clauses for SQL queries.
## Install
```shell
pip install dash_query_builder
```
## Usage
To use Dash Query Builder (DQB), you need to have a Dash app and a dictionary of fields.
The fields property is a dictionary of fields and their properties, following the
[config.fields docs](https://github.com/ukrbublik/react-awesome-query-builder/blob/master/CONFIG.adoc#configfields).
The only caveat is that JavaScript cannot be used as in the example.
For instance the following dictionary is valid:
```python
fields = {
"qty": {
"label": "Qty",
"type": "number",
"fieldSettings": {"min": 0},
"valueSources": ["value"],
"preferWidgets": ["number"],
},
"price": {
"label": "Price",
"type": "number",
"valueSources": ["value"],
"fieldSettings": {"min": 10, "max": 100},
"preferWidgets": ["slider", "rangeslider"],
"operators": ["equal", "between"],
},
"color": {
"label": "Color",
"type": "select",
"valueSources": ["value"],
"fieldSettings": {
"listValues": [
{"value": "yellow", "title": "Yellow"},
{"value": "green", "title": "Green"},
{"value": "orange", "title": "Orange"},
]
},
},
"is_promotion": {
"label": "Promo?",
"type": "boolean",
"operators": ["equal", "is_empty"],
"valueSources": ["value"],
},
}
```
The basic component can be created via:
```python
from dash import Dash, html
import dash_query_builder as dqb
fields =...
app=Dash(__name__)
app.layout=html.Div([dqb.DashQueryBuilder(fields=fields)])
app.run_server()
```
This will run the app similar to this:
https://github.com/TillerBurr/dash-query-builder/assets/49296311/1fdc9663-fde7-4c26-a706-00b5edc9f902
There are other properties available as well, with defaults in parentheses.
- config({}): see [CONFIG.adoc](https://github.com/ukrbublik/react-awesome-query-builder/blob/master/CONFIG.adoc) for full options
- theme("basic"): one of "antd", "mui", "fluent", "bootstrap", "basic"
- loadFormat("tree"): one of "tree", "spelFormat", "jsonLogicFormat"
- alwaysShowActionButtons(True): A boolean whether to always show action buttons, e.g. "Add Rule", "Add Group", etc.
With the above parameters, a query builder will be created with an empty tree. To pre-populate the query builder,
there are several ways to do so:
1. `loadFormat=="tree"`: Set `tree` to a valid tree object.
1. `loadFormat=="spelFormat"`: Set `spelFormat` to a valid SpEL string.
1. `loadFormat=="jsonLogicFormat"`: Set `jsonLogicFormat` to a valid jsonLogic object.
Once `loadFormat` is set, the tree/query builder will update when the query is changed or when the corresponding property is changed.
The `loadFormat` can be changed via a callback, while keeping the same tree.
Here's an example using `usage.py`:
https://github.com/TillerBurr/dash-query-builder/assets/49296311/1191a643-27c0-4a4f-8032-2eb5d4b1d88e
## Where Parser
DQB has a built-in parser for SQL queries. The parser is relatively simple as far as parsers go, but it does what I need it to.
It will parse the query and return a template string and a parameter dictionary. The template string will be in `pyformat` style, as
specified in [PEP 249](https://peps.python.org/pep-0249/#paramstyle).
### Example
```python
from dash_query_builder.where_parser import WhereParser
where_parser = WhereParser()
template, params = where_parser.get_template("qty > 15 and price between 10 and 20")
print(template) # (qty > %(YSaAddDFs27s)s AND price BETWEEN %(W5PRwTGpFqqF)s AND %(N2nGExcGaUSt)s)
print(params) # {'YSaAddDFs27s': 15, 'W5PRwTGpFqqF': 10, 'N2nGExcGaUSt': 20}
```
Currently, only `pyformat` is supported. PRs are welcome!
## Tools Used
- [uv](https://github.com/astral-sh/uv) for Python virtual environment and dependencies.
- [just](https://github.com/casey/just) for common commands
- [mise-en-place](https://mise.jdx.dev) to manage the toolchain.
## Development
### Getting Started
1. Create a Python environment from previous step 1 and install:
```shell
just sync
```
1. Update the requirements and dev requirements
```shell
just compile
```
1. Build
```shell
just build
```
1. Publish
```shell
just publish
```
1. See all commands with `just -l`