# Sparql Query Demo

## Table Of Contents
- [About](#about)
- [Requirements](#requirements)
- [Before using](#before-using)
- [Usage](#usage)
  * [Python 3.11](#python-311)
  * [Docker](#docker)
  * [Argument list](#argument-list)
    + [General:](#general-)
    + [Queries-related:](#queries-related-)
    + [Requirements-related:](#requirements-related-)
- [Acknowledgement](#acknowledgement)
- [License](#license)

## About
Easy deploy a demo capable of executing your sparql queries to the desired target endpoint in a simple way.

![](./media/usage_example.gif)


## Requirements 
The required python packages are:
```python
gradio==4.16.0
gradio_client==0.8.1
pandas==1.5.3
SPARQLWrapper==2.0.0
```

## Before using
First you need to drag to the ``data`` folder your tabular file (csv, tsv, excel, ...) and to the subfolder ``queries`` the queries. The file structure should look like this:
```
data
├── queries
│   ├── Q1.rq
│   ├── Q2.rq
│   └── Q3.rq
└── requirements.csv
```
It is important that in the requirements file there is a column with the identifier of the competency question/requirement and another column with the text.  **CAUTION:** Query files must have the same name as the requirements file identifier (and end in ``.rq``). In order to read the queries from the ``queries`` folder, the content of the ``requirements.csv`` file should be as follows:
| ID | Question |
| -------- | ------- |
| Q1 | Countries that have a Featured Article on Russian Wikipedia |
| Q2 | List of popes |
| Q3 | US presidents & causes of death |

The column names and separators (```\t``` ```;``` ```,``` ...) can be arbitrary. The application has specific arguments to define them.

*NOTE: The queries used are taken from the examples available on [wikidata](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries/examples).*

## Usage
**IMPORTANT:** [The above requirements must be met](#before-using)

### Python 3.11
To run directly from python you need version 3.11 and install the requirements:
- ``` pip install -r requirements.txt ```

After that, you just need to run the application with the parameters you want. In this case, to run the example you can use the following code ([look at argument list for more options](#argument-list)):
-   ``` python
    python sparql-query-demo.py \
        --demo_title="Demo for wikidata queries" \
        --endpoint="https://query.wikidata.org/sparql" \
        --return_format="JSON" \
        --include_example="True" \
        --requirements_file="data/requirements.csv" \
        --requirements_separator="," \
        --identifier_columname="ID" \
        --requirement_columname="Question" \
        --query_path="data/queries"
    ```

### Docker
The official image of this demo is posted on dockerhub [ibaiguillen/sparql-query-demo](https://hub.docker.com/r/ibaiguillen/sparql-query-demo). To run the example with docker you need the ```data``` folder as [explained before](#before-using). Remember that you can include more arguments or change them, see ([argument list for more options](#argument-list)).

You can run the application with the following docker command:
- ``` bash
    docker run \
    --name sparql-query-demo \
    -p 9900:9900 \
    -v $(pwd)/data:/sparql-query-demo/data \
    ibaiguillen/sparql-query-demo:v1.1 \
    --demo_title="Demo for wikidata queries" \
    --endpoint="https://query.wikidata.org/sparql" \
    --return_format=JSON \
    --include_example=True \
    --requirements_file=requirements.csv \
    --requirements_separator=',' \
    --identifier_columname=ID \
    --requirement_columname=Question \
    --query_path=queries
    ```

Or you can run docker compose to deploy it:
- ```docker-compose up``` or ```docker compose up```


### Argument list
The parameters that exist and their purpose are as follows:
#### General:
- ```--demo_title```: Title of the demo website. Not mandatory, '*Title of the demo website.*' by default.
- ```--port```: Port in which the demo will be available. Not mandatory, '*9900*' by default.
- ```--endpoint``` Endpoint to which queries point. **Mandatory**.
- ```--return_format```: Endpoint return format. Two options: *JSON* or *CSV*. Not mandatory, '*JSON*' by default. 
    - *Some endpoints such as wikidata do not accept CSV format, so it is recommended to use JSON in that cases.*
#### Queries-related:
- ```--query_path```: Path to the folder where all queries are located. **Mandatory**
    - *Remember that the queries have to end in ".rd" and have the name of the identifier it corresponds to (e.g. "Q1.rq").*
- ```--include_example```: Whether or not to include a test query. Not mandatory, '*True*' by default.
#### Requirements-related:
- ```--requirements_file```: Name of the tabular file with identifier and requirements columns. **Mandatory**.
- ```--requirements_encoding```: Encoding of the requirements tabular file. Not mandatory, default '*utf-8*'.
- ```--requirements_separator```: Tabular file separator. Not mandatory, by default '```,```' (csv).
- ```--identifier_columname```: Name of the column (header) of identifiers. Not mandatory, default '*ID*'.
- ```--requirement_columname```: Name of the column (header) of requirements. Not mandatory, default '*Question*'.

## Acknowledgement
This work is supported by the Predoctoral Grant (PIPF-2022/COM-25947) of the Consejería de Educación, Ciencia y Universidades de la Comunidad de Madrid, Spain.

## License
MIT License

Copyright (c) 2024 Ibai Guillén

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